Spatial temporal clustering for hotspot using kulldorff scan statistic method (KSS): A case in Riau Province

NASA Astrophysics Data System (ADS)

Hudjimartsu, S. A.; Djatna, T.; Ambarwari, A.; Apriliantono

2017-01-01

The forest fires in Indonesia occurs frequently in the dry season. Almost all the causes of forest fires are caused by the human activity itself. The impact of forest fires is the loss of biodiversity, pollution hazard and harm the economy of surrounding communities. To prevent fires required the method, one of them with spatial temporal clustering. Spatial temporal clustering formed grouping data so that the results of these groupings can be used as initial information on fire prevention. To analyze the fires, used hotspot data as early indicator of fire spot. Hotspot data consists of spatial and temporal dimensions can be processed using the Spatial Temporal Clustering with Kulldorff Scan Statistic (KSS). The result of this research is to the effectiveness of KSS method to cluster spatial hotspot in a case within Riau Province and produces two types of clusters, most cluster and secondary cluster. This cluster can be used as an early fire warning information.

Spatio-temporal source cluster analysis reveals fronto-temporal auditory change processing differences within a shared autistic and schizotypal trait phenotype.

PubMed

Ford, Talitha C; Woods, Will; Crewther, David P

2017-01-01

Social Disorganisation (SD) is a shared autistic and schizotypal phenotype that is present in the subclinical population. Auditory processing deficits, particularly in mismatch negativity/field (MMN/F) have been reported across both spectrum disorders. This study investigates differences in MMN/F cortical spatio-temporal source activity between higher and lower quintiles of the SD spectrum. Sixteen low (9 female) and 19 high (9 female) SD subclinical adults (18-40years) underwent magnetoencephalography (MEG) during an MMF paradigm where standard tones (50ms) were interrupted by infrequent duration deviants (100ms). Spatio-temporal source cluster analysis with permutation testing revealed no difference between the groups in source activation to the standard tone. To the deviant tone however, there was significantly reduced right hemisphere fronto-temporal and insular cortex activation for the high SD group ( p = 0.038). The MMF, as a product of the cortical response to the deviant minus that to the standard, did not differ significantly between the high and low Social Disorganisation groups. These data demonstrate a deficit in right fronto-temporal processing of an auditory change for those with more of the shared SD phenotype, indicating that right fronto-temporal auditory processing may be associated with psychosocial functioning.

Shifting Patterns of Aedes aegypti Fine Scale Spatial Clustering in Iquitos, Peru

PubMed Central

LaCon, Genevieve; Morrison, Amy C.; Astete, Helvio; Stoddard, Steven T.; Paz-Soldan, Valerie A.; Elder, John P.; Halsey, Eric S.; Scott, Thomas W.; Kitron, Uriel; Vazquez-Prokopec, Gonzalo M.

2014-01-01

Background Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels. Methodologies/Principal Findings Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance) were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study. Conclusions/Significance Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots. PMID:25102062

Epicardial mapping of ventricular fibrillation over the posterior descending artery and left posterior papillary muscle of the swine heart.

PubMed

Nielsen, Thomas D; Huang, Jian; Rogers, Jack M; Killingsworth, Cheryl R; Ideker, Raymond E

2009-01-01

Recent studies suggest that during ventricular fibrillation (VF) epicardial vessels may be a site of conduction block and the posterior papillary muscle (PPM) in the left ventricle (LV) may be the location of a "mother rotor." The goal of this study was to obtain evidence to support or refute these possibilities. Epicardial activation over the posterior LV and right ventricle (RV) was mapped during the first 20 s of electrically induced VF in six open-chest pigs with a 504 electrode plaque covering a 20 cm(2) area centered over the posterior descending artery (PDA). The locations of epicardial breakthrough as well as reentry clustered in time and space during VF. Spatially, reentry occurred significantly more frequently over the LV than the RV in all 48 episodes, and breakthrough clustered near the PPM (p < 0.001). Significant temporal clustering occurred in 79% of breakthrough episodes and 100% of reentry episodes. These temporal clusters occurred at different times so that there was significantly less breakthrough when reentry was present (p < 0.0001). Conduction block occurred significantly more frequently near the PDA than elsewhere. The PDA is a site of epicardial block which may contribute to VF maintenance. Epicardial breakthrough clusters near the PPM. Reentry also clusters in space but at a separate site. The fact that breakthrough and reentry cluster at different locations and at different times supports the possibility of a drifting filament at the PPM so that at times reentry is present on the surface but at other times the reentrant wavefront breaks through to the epicardium.

Event Networks and the Identification of Crime Pattern Motifs

PubMed Central

2015-01-01

In this paper we demonstrate the use of network analysis to characterise patterns of clustering in spatio-temporal events. Such clustering is of both theoretical and practical importance in the study of crime, and forms the basis for a number of preventative strategies. However, existing analytical methods show only that clustering is present in data, while offering little insight into the nature of the patterns present. Here, we show how the classification of pairs of events as close in space and time can be used to define a network, thereby generalising previous approaches. The application of graph-theoretic techniques to these networks can then offer significantly deeper insight into the structure of the data than previously possible. In particular, we focus on the identification of network motifs, which have clear interpretation in terms of spatio-temporal behaviour. Statistical analysis is complicated by the nature of the underlying data, and we provide a method by which appropriate randomised graphs can be generated. Two datasets are used as case studies: maritime piracy at the global scale, and residential burglary in an urban area. In both cases, the same significant 3-vertex motif is found; this result suggests that incidents tend to occur not just in pairs, but in fact in larger groups within a restricted spatio-temporal domain. In the 4-vertex case, different motifs are found to be significant in each case, suggesting that this technique is capable of discriminating between clustering patterns at a finer granularity than previously possible. PMID:26605544

First Description of a Cluster of Acute/Subacute Paracoccidioidomycosis Cases and Its Association with a Climatic Anomaly

PubMed Central

Silva, Maria Elisa Siqueira; Bagagli, Eduardo; Marques, Silvio Alencar; Mendes, Rinaldo Poncio

2010-01-01

Background Identifying clusters of acute paracoccidioidomycosis cases could potentially help in identifying the environmental factors that influence the incidence of this mycosis. However, unlike other endemic mycoses, there are no published reports of clusters of paracoccidioidomycosis. Methodology/Principal Findings A retrospective cluster detection test was applied to verify if an excess of acute form (AF) paracoccidioidomycosis cases in time and/or space occurred in Botucatu, an endemic area in São Paulo State. The scan-test SaTScan v7.0.3 was set to find clusters for the maximum temporal period of 1 year. The temporal test indicated a significant cluster in 1985 (P<0.005). This cluster comprised 10 cases, although 2.19 were expected for this year in this area. Age and clinical presentation of these cases were typical of AF paracccidioidomycosis. The space-time test confirmed the temporal cluster in 1985 and showed the localities where the risk was higher in that year. The cluster suggests that some particularities took place in the antecedent years in those localities. Analysis of climate variables showed that soil water storage was atypically high in 1982/83 (∼2.11/2.5 SD above mean), and the absolute air humidity in 1984, the year preceding the cluster, was much higher than normal (∼1.6 SD above mean), conditions that may have favored, respectively, antecedent fungal growth in the soil and conidia liberation in 1984, the probable year of exposure. These climatic anomalies in this area was due to the 1982/83 El Niño event, the strongest in the last 50 years. Conclusions/Significance We describe the first cluster of AF paracoccidioidomycosis, which was potentially linked to a climatic anomaly caused by the 1982/83 El Niño Southern Oscillation. This finding is important because it may help to clarify the conditions that favor Paracoccidioides brasiliensis survival and growth in the environment and that enhance human exposure, thus allowing the development of preventive measures. PMID:20361032

Temporal indiscriminateness: the case of cluster bombs.

PubMed

Cavanaugh, T A

2010-03-01

This paper argues that the current stock of anti-personnel cluster bombs are temporally indiscriminate, and, therefore, unjust weapons. The paper introduces and explains the idea of temporal indiscriminateness. It argues that to honor non-combatant immunity-in addition to not targeting civilians-one must adequately target combatants. Due to their high dud rate, cluster submunitions fail to target combatants with sufficient temporal accuracy, and, thereby, result in avoidable serious harm to non-combatants. The paper concludes that non-combatant immunity and the principle of discrimination require a moratorium on the use of current cluster munitions.

Using scan statistics for congenital anomalies surveillance: the EUROCAT methodology.

PubMed

Teljeur, Conor; Kelly, Alan; Loane, Maria; Densem, James; Dolk, Helen

2015-11-01

Scan statistics have been used extensively to identify temporal clusters of health events. We describe the temporal cluster detection methodology adopted by the EUROCAT (European Surveillance of Congenital Anomalies) monitoring system. Since 2001, EUROCAT has implemented variable window width scan statistic for detecting unusual temporal aggregations of congenital anomaly cases. The scan windows are based on numbers of cases rather than being defined by time. The methodology is imbedded in the EUROCAT Central Database for annual application to centrally held registry data. The methodology was incrementally adapted to improve the utility and to address statistical issues. Simulation exercises were used to determine the power of the methodology to identify periods of raised risk (of 1-18 months). In order to operationalize the scan methodology, a number of adaptations were needed, including: estimating date of conception as unit of time; deciding the maximum length (in time) and recency of clusters of interest; reporting of multiple and overlapping significant clusters; replacing the Monte Carlo simulation with a lookup table to reduce computation time; and placing a threshold on underlying population change and estimating the false positive rate by simulation. Exploration of power found that raised risk periods lasting 1 month are unlikely to be detected except when the relative risk and case counts are high. The variable window width scan statistic is a useful tool for the surveillance of congenital anomalies. Numerous adaptations have improved the utility of the original methodology in the context of temporal cluster detection in congenital anomalies.

Local Spatial and Temporal Processes of Influenza in Pennsylvania, USA: 2003–2009

PubMed Central

Stark, James H.; Sharma, Ravi; Ostroff, Stephen; Cummings, Derek A. T.; Ermentrout, Bard; Stebbins, Samuel; Burke, Donald S.; Wisniewski, Stephen R.

2012-01-01

Background Influenza is a contagious respiratory disease responsible for annual seasonal epidemics in temperate climates. An understanding of how influenza spreads geographically and temporally within regions could result in improved public health prevention programs. The purpose of this study was to summarize the spatial and temporal spread of influenza using data obtained from the Pennsylvania Department of Health's influenza surveillance system. Methodology and Findings We evaluated the spatial and temporal patterns of laboratory-confirmed influenza cases in Pennsylvania, United States from six influenza seasons (2003–2009). Using a test of spatial autocorrelation, local clusters of elevated risk were identified in the South Central region of the state. Multivariable logistic regression indicated that lower monthly precipitation levels during the influenza season (OR = 0.52, 95% CI: 0.28, 0.94), fewer residents over age 64 (OR = 0.27, 95% CI: 0.10, 0.73) and fewer residents with more than a high school education (OR = 0.76, 95% CI: 0.61, 0.95) were significantly associated with membership in this cluster. In addition, time series analysis revealed a temporal lag in the peak timing of the influenza B epidemic compared to the influenza A epidemic. Conclusions These findings illustrate a distinct spatial cluster of cases in the South Central region of Pennsylvania. Further examination of the regional transmission dynamics within these clusters may be useful in planning public health influenza prevention programs. PMID:22470544

Spatio-temporal patterns of Campylobacter colonization in Danish broilers.

PubMed

Chowdhury, S; Themudo, G E; Sandberg, M; Ersbøll, A K

2013-05-01

Despite a number of risk-factor studies in different countries, the epidemiology of Campylobacter colonization in broilers, particularly spatial dependencies, is still not well understood. A series of analyses (visualization and exploratory) were therefore conducted in order to obtain a better understanding of the spatial and temporal distribution of Campylobacter in the Danish broiler population. In this study, we observed a non-random temporal occurrence of Campylobacter, with high prevalence during summer and low during winter. Significant spatio-temporal clusters were identified in the same areas in the summer months from 2007 to 2009. Range of influence between broiler farms were estimated at distances of 9.6 km and 13.5 km in different years. Identification of areas and time with greater risk indicates variable presence of risk factors with space and time. Implementation of safety measures on farms within high-risk clusters during summer could have an impact in reducing prevalence.

Epicardial mapping of ventricular fibrillation over the posterior descending artery and left posterior papillary muscle of the swine heart

PubMed Central

Nielsen, Thomas D.; Huang, Jian; Rogers, Jack M.; Killingsworth, Cheryl R.

2008-01-01

Background Recent studies suggest that during ventricular fibrillation (VF) epicardial vessels may be a site of conduction block and the posterior papillary muscle (PPM) in the left ventricle (LV) may be the location of a “mother rotor.” The goal of this study was to obtain evidence to support or refute these possibilities. Methods Epicardial activation over the posterior LV and right ventricle (RV) was mapped during the first 20 s of electrically induced VF in six open-chest pigs with a 504 electrode plaque covering a 20 cm2 area centered over the posterior descending artery (PDA). Results The locations of epicardial breakthrough as well as reentry clustered in time and space during VF. Spatially, reentry occurred significantly more frequently over the LV than the RV in all 48 episodes, and breakthrough clustered near the PPM (p<0.001). Significant temporal clustering occurred in 79% of breakthrough episodes and 100% of reentry episodes. These temporal clusters occurred at different times so that there was significantly less breakthrough when reentry was present (p<0.0001). Conduction block occurred significantly more frequently near the PDA than elsewhere. Conclusions The PDA is a site of epicardial block which may contribute to VF maintenance. Epicardial breakthrough clusters near the PPM. Reentry also clusters in space but at a separate site. The fact that breakthrough and reentry cluster at different locations and at different times supports the possibility of a drifting filament at the PPM so that at times reentry is present on the surface but at other times the reentrant wavefront breaks through to the epicardium. PMID:18839296

Temporal information entropy of the Blood-Oxygenation Level-Dependent signals increases in the activated human primary visual cortex

NASA Astrophysics Data System (ADS)

DiNuzzo, Mauro; Mascali, Daniele; Moraschi, Marta; Bussu, Giorgia; Maraviglia, Bruno; Mangia, Silvia; Giove, Federico

2017-02-01

Time-domain analysis of blood-oxygenation level-dependent (BOLD) signals allows the identification of clusters of voxels responding to photic stimulation in primary visual cortex (V1). However, the characterization of information encoding into temporal properties of the BOLD signals of an activated cluster is poorly investigated. Here, we used Shannon entropy to determine spatial and temporal information encoding in the BOLD signal within the most strongly activated area of the human visual cortex during a hemifield photic stimulation. We determined the distribution profile of BOLD signals during epochs at rest and under stimulation within small (19-121 voxels) clusters designed to include only voxels driven by the stimulus as highly and uniformly as possible. We found consistent and significant increases (2-4% on average) in temporal information entropy during activation in contralateral but not ipsilateral V1, which was mirrored by an expected loss of spatial information entropy. These opposite changes coexisted with increases in both spatial and temporal mutual information (i.e. dependence) in contralateral V1. Thus, we showed that the first cortical stage of visual processing is characterized by a specific spatiotemporal rearrangement of intracluster BOLD responses. Our results indicate that while in the space domain BOLD maps may be incapable of capturing the functional specialization of small neuronal populations due to relatively low spatial resolution, some information encoding may still be revealed in the temporal domain by an increase of temporal information entropy.

Spatio-temporal cluster detection of chickenpox in Valencia, Spain in the period 2008-2012.

PubMed

Iftimi, Adina; Martínez-Ruiz, Francisco; Míguez Santiyán, Ana; Montes, Francisco

2015-05-18

Chickenpox is a highly contagious airborne disease caused by Varicella zoster, which affects nearly all non-immune children worldwide with an annual incidence estimated at 80-90 million cases. To analyze the spatiotemporal pattern of the chickenpox incidence in the city of Valencia, Spain two complementary statistical approaches were used. First, we evaluated the existence of clusters and spatio-temporal interaction; secondly, we used this information to find the locations of the spatio-temporal clusters via the space-time permutation model. The first method used detects any aggregation in our data but does not provide the spatial and temporal information. The second method gives the locations, areas and time-frame for the spatio-temporal clusters. An overall decreasing time trend, a pronounced 12-monthly periodicity and two complementary periods were observed. Several areas with high incidence, surrounding the center of the city were identified. The existence of aggregation in time and space was observed, and a number of spatio-temporal clusters were located.

Age Differences in Recall and Information Processing in Verbal and Spatial Learning.

ERIC Educational Resources Information Center

Mungas, Dan; And Others

1991-01-01

Three age groups of 24 people each completed verbal word list tasks and spatial learning tasks 5 times each. Significant age differences were found for total recall and type of task. Younger subjects showed increased levels of clustering--organizing information according to semantic or spatial clusters. Age was not related to temporal order of…

Temporal Data-Driven Sleep Scheduling and Spatial Data-Driven Anomaly Detection for Clustered Wireless Sensor Networks

PubMed Central

Li, Gang; He, Bin; Huang, Hongwei; Tang, Limin

2016-01-01

The spatial–temporal correlation is an important feature of sensor data in wireless sensor networks (WSNs). Most of the existing works based on the spatial–temporal correlation can be divided into two parts: redundancy reduction and anomaly detection. These two parts are pursued separately in existing works. In this work, the combination of temporal data-driven sleep scheduling (TDSS) and spatial data-driven anomaly detection is proposed, where TDSS can reduce data redundancy. The TDSS model is inspired by transmission control protocol (TCP) congestion control. Based on long and linear cluster structure in the tunnel monitoring system, cooperative TDSS and spatial data-driven anomaly detection are then proposed. To realize synchronous acquisition in the same ring for analyzing the situation of every ring, TDSS is implemented in a cooperative way in the cluster. To keep the precision of sensor data, spatial data-driven anomaly detection based on the spatial correlation and Kriging method is realized to generate an anomaly indicator. The experiment results show that cooperative TDSS can realize non-uniform sensing effectively to reduce the energy consumption. In addition, spatial data-driven anomaly detection is quite significant for maintaining and improving the precision of sensor data. PMID:27690035

Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks.

PubMed

Arunraja, Muruganantham; Malathi, Veluchamy; Sakthivel, Erulappan

2015-11-01

Wireless sensor networks are engaged in various data gathering applications. The major bottleneck in wireless data gathering systems is the finite energy of sensor nodes. By conserving the on board energy, the life span of wireless sensor network can be well extended. Data communication being the dominant energy consuming activity of wireless sensor network, data reduction can serve better in conserving the nodal energy. Spatial and temporal correlation among the sensor data is exploited to reduce the data communications. Data similar cluster formation is an effective way to exploit spatial correlation among the neighboring sensors. By sending only a subset of data and estimate the rest using this subset is the contemporary way of exploiting temporal correlation. In Distributed Similarity based Clustering and Compressed Forwarding for wireless sensor networks, we construct data similar iso-clusters with minimal communication overhead. The intra-cluster communication is reduced using adaptive-normalized least mean squares based dual prediction framework. The cluster head reduces the inter-cluster data payload using a lossless compressive forwarding technique. The proposed work achieves significant data reduction in both the intra-cluster and the inter-cluster communications, with the optimal data accuracy of collected data. Copyright © 2015 ISA. Published by Elsevier Ltd. All rights reserved.

Characterization of spatial and temporal variability in hydrochemistry of Johor Straits, Malaysia.

PubMed

Abdullah, Pauzi; Abdullah, Sharifah Mastura Syed; Jaafar, Othman; Mahmud, Mastura; Khalik, Wan Mohd Afiq Wan Mohd

2015-12-15

Characterization of hydrochemistry changes in Johor Straits within 5 years of monitoring works was successfully carried out. Water quality data sets (27 stations and 19 parameters) collected in this area were interpreted subject to multivariate statistical analysis. Cluster analysis grouped all the stations into four clusters ((Dlink/Dmax) × 100<90) and two clusters ((Dlink/Dmax) × 100<80) for site and period similarities. Principal component analysis rendered six significant components (eigenvalue>1) that explained 82.6% of the total variance of the data set. Classification matrix of discriminant analysis assigned 88.9-92.6% and 83.3-100% correctness in spatial and temporal variability, respectively. Times series analysis then confirmed that only four parameters were not significant over time change. Therefore, it is imperative that the environmental impact of reclamation and dredging works, municipal or industrial discharge, marine aquaculture and shipping activities in this area be effectively controlled and managed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Shifting patterns of Aedes aegypti fine scale spatial clustering in Iquitos, Peru.

PubMed

LaCon, Genevieve; Morrison, Amy C; Astete, Helvio; Stoddard, Steven T; Paz-Soldan, Valerie A; Elder, John P; Halsey, Eric S; Scott, Thomas W; Kitron, Uriel; Vazquez-Prokopec, Gonzalo M

2014-08-01

Empiric evidence shows that Aedes aegypti abundance is spatially heterogeneous and that some areas and larval habitats produce more mosquitoes than others. There is a knowledge gap, however, with regards to the temporal persistence of such Ae. aegypti abundance hotspots. In this study, we used a longitudinal entomologic dataset from the city of Iquitos, Peru, to (1) quantify the spatial clustering patterns of adult Ae. aegypti and pupae counts per house, (2) determine overlap between clusters, (3) quantify the temporal stability of clusters over nine entomologic surveys spaced four months apart, and (4) quantify the extent of clustering at the household and neighborhood levels. Data from 13,662 household entomological visits performed in two Iquitos neighborhoods differing in Ae. aegypti abundance and dengue virus transmission was analyzed using global and local spatial statistics. The location and extent of Ae. aegypti pupae and adult hotspots (i.e., small groups of houses with significantly [p<0.05] high mosquito abundance) were calculated for each of the 9 entomologic surveys. The extent of clustering was used to quantify the probability of finding spatially correlated populations. Our analyses indicate that Ae. aegypti distribution was highly focal (most clusters do not extend beyond 30 meters) and that hotspots of high vector abundance were common on every survey date, but they were temporally unstable over the period of study. Our findings have implications for understanding Ae. aegypti distribution and for the design of surveillance and control activities relying on household-level data. In settings like Iquitos, where there is a relatively low percentage of Ae. aegypti in permanent water-holding containers, identifying and targeting key premises will be significantly challenged by shifting hotspots of Ae. aegypti infestation. Focusing efforts in large geographic areas with historically high levels of transmission may be more effective than targeting Ae. aegypti hotspots.

Groundwater Quality: Analysis of Its Temporal and Spatial Variability in a Karst Aquifer.

PubMed

Pacheco Castro, Roger; Pacheco Ávila, Julia; Ye, Ming; Cabrera Sansores, Armando

2018-01-01

This study develops an approach based on hierarchical cluster analysis for investigating the spatial and temporal variation of water quality governing processes. The water quality data used in this study were collected in the karst aquifer of Yucatan, Mexico, the only source of drinking water for a population of nearly two million people. Hierarchical cluster analysis was applied to the quality data of all the sampling periods lumped together. This was motivated by the observation that, if water quality does not vary significantly in time, two samples from the same sampling site will belong to the same cluster. The resulting distribution maps of clusters and box-plots of the major chemical components reveal the spatial and temporal variability of groundwater quality. Principal component analysis was used to verify the results of cluster analysis and to derive the variables that explained most of the variation of the groundwater quality data. Results of this work increase the knowledge about how precipitation and human contamination impact groundwater quality in Yucatan. Spatial variability of groundwater quality in the study area is caused by: a) seawater intrusion and groundwater rich in sulfates at the west and in the coast, b) water rock interactions and the average annual precipitation at the middle and east zones respectively, and c) human contamination present in two localized zones. Changes in the amount and distribution of precipitation cause temporal variation by diluting groundwater in the aquifer. This approach allows to analyze the variation of groundwater quality controlling processes efficiently and simultaneously. © 2017, National Ground Water Association.

Hierarchical Aligned Cluster Analysis for Temporal Clustering of Human Motion.

PubMed

Zhou, Feng; De la Torre, Fernando; Hodgins, Jessica K

2013-03-01

Temporal segmentation of human motion into plausible motion primitives is central to understanding and building computational models of human motion. Several issues contribute to the challenge of discovering motion primitives: the exponential nature of all possible movement combinations, the variability in the temporal scale of human actions, and the complexity of representing articulated motion. We pose the problem of learning motion primitives as one of temporal clustering, and derive an unsupervised hierarchical bottom-up framework called hierarchical aligned cluster analysis (HACA). HACA finds a partition of a given multidimensional time series into m disjoint segments such that each segment belongs to one of k clusters. HACA combines kernel k-means with the generalized dynamic time alignment kernel to cluster time series data. Moreover, it provides a natural framework to find a low-dimensional embedding for time series. HACA is efficiently optimized with a coordinate descent strategy and dynamic programming. Experimental results on motion capture and video data demonstrate the effectiveness of HACA for segmenting complex motions and as a visualization tool. We also compare the performance of HACA to state-of-the-art algorithms for temporal clustering on data of a honey bee dance. The HACA code is available online.

Classification of childhood asthma phenotypes and long-term clinical responses to inhaled anti-inflammatory medications.

PubMed

Howrylak, Judie A; Fuhlbrigge, Anne L; Strunk, Robert C; Zeiger, Robert S; Weiss, Scott T; Raby, Benjamin A

2014-05-01

Although recent studies have identified the presence of phenotypic clusters in asthmatic patients, the clinical significance and temporal stability of these clusters have not been explored. Our aim was to examine the clinical relevance and temporal stability of phenotypic clusters in children with asthma. We applied spectral clustering to clinical data from 1041 children with asthma participating in the Childhood Asthma Management Program. Posttreatment randomization follow-up data collected over 48 months were used to determine the effect of these clusters on pulmonary function and treatment response to inhaled anti-inflammatory medication. We found 5 reproducible patient clusters that could be differentiated on the basis of 3 groups of features: atopic burden, degree of airway obstruction, and history of exacerbation. Cluster grouping predicted long-term asthma control, as measured by the need for oral prednisone (P < .0001) or additional controller medications (P = .001), as well as longitudinal differences in pulmonary function (P < .0001). We also found that the 2 clusters with the highest rates of exacerbation had different responses to inhaled corticosteroids when compared with the other clusters. One cluster demonstrated a positive response to both budesonide (P = .02) and nedocromil (P = .01) compared with placebo, whereas the other cluster demonstrated minimal responses to both budesonide (P = .12) and nedocromil (P = .56) compared with placebo. Phenotypic clustering can be used to identify longitudinally consistent and clinically relevant patient subgroups, with implications for targeted therapeutic strategies and clinical trials design.

Measuring temporal liking simultaneously to Temporal Dominance of Sensations in several intakes. An application to Gouda cheeses in 6 Europeans countries.

PubMed

Thomas, A; Chambault, M; Dreyfuss, L; Gilbert, C C; Hegyi, A; Henneberg, S; Knippertz, A; Kostyra, E; Kremer, S; Silva, A P; Schlich, P

2017-09-01

The idea of having untrained consumers performing Temporal Dominance of Sensations (TDS) and dynamic liking in the same session was recently introduced (Thomas, van der Stelt, Prokop, Lawlor, & Schlich, 2016). In the present study, a variation of the data acquisition protocol was done, aiming to record TDS and liking simultaneously on the same screen in a single session during multiple product intakes. This method, called Simultaneous Temporal Drivers of Liking (S-TDL), was used to describe samples of Gouda cheese in an international experiment. To test this idea, consumers from six European countries (n=667) assessed 4 Gouda cheeses with different ages and fat contents during one sensory evaluation session. Ten sensory attributes and a 9-point hedonic scale were presented simultaneously on the computer screen. While performing TDS, consumers could reassess their liking score as often as they wanted. This new type of sensory data was coded by individual average liking scores while a given attribute was perceived as dominant (Liking While Dominant; LWD). Although significant differences in preference were observed among countries, there were global preferences for a longer dominance of melting, fatty and tender textures. The cheese flavour attribute was the best positive TDL, whereas bitter was a strong negative TDL. A cluster analysis of the 667 consumers identified three significant liking clusters, each with different most and least preferred samples. For the TDL computation by cluster, significant specific TDL were observed. These results showed the importance of overall liking segmentation before TDL analysis to determine which attributes should have a longer dominance duration in order to please specific consumer targets. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial, temporal and spatio-temporal clusters of measles incidence at the county level in Guangxi, China during 2004-2014: flexibly shaped scan statistics.

PubMed

Tang, Xianyan; Geater, Alan; McNeil, Edward; Deng, Qiuyun; Dong, Aihu; Zhong, Ge

2017-04-04

Outbreaks of measles re-emerged in Guangxi province during 2013-2014, where measles again became a major public health concern. A better understanding of the patterns of measles cases would help in identifying high-risk areas and periods for optimizing preventive strategies, yet these patterns remain largely unknown. Thus, this study aimed to determine the patterns of measles clusters in space, time and space-time at the county level over the period 2004-2014 in Guangxi. Annual data on measles cases and population sizes for each county were obtained from Guangxi CDC and Guangxi Bureau of Statistics, respectively. Epidemic curves and Kulldorff's temporal scan statistics were used to identify seasonal peaks and high-risk periods. Tango's flexible scan statistics were implemented to determine irregular spatial clusters. Spatio-temporal clusters in elliptical cylinder shapes were detected by Kulldorff's scan statistics. Population attributable risk percent (PAR%) of children aged ≤24 months was used to identify regions with a heavy burden of measles. Seasonal peaks occurred between April and June, and a temporal measles cluster was detected in 2014. Spatial clusters were identified in West, Southwest and North Central Guangxi. Three phases of spatio-temporal clusters with high relative risk were detected: Central Guangxi during 2004-2005, Midwest Guangxi in 2007, and West and Southwest Guangxi during 2013-2014. Regions with high PAR% were mainly clustered in West, Southwest, North and Central Guangxi. A temporal uptrend of measles incidence existed in Guangxi between 2010 and 2014, while downtrend during 2004-2009. The hotspots shifted from Central to West and Southwest Guangxi, regions overburdened with measles. Thus, intensifying surveillance of timeliness and completeness of routine vaccination and implementing supplementary immunization activities for measles should prioritized in these regions.

Evidence for a global seismic-moment release sequence

USGS Publications Warehouse

Bufe, C.G.; Perkins, D.M.

2005-01-01

Temporal clustering of the larger earthquakes (foreshock-mainshock-aftershock) followed by relative quiescence (stress shadow) are characteristic of seismic cycles along plate boundaries. A global seismic-moment release history, based on a little more than 100 years of instrumental earthquake data in an extended version of the catalog of Pacheco and Sykes (1992), illustrates similar behavior for Earth as a whole. Although the largest earthquakes have occurred in the circum-Pacific region, an analysis of moment release in the hemisphere antipodal to the Pacific plate shows a very similar pattern. Monte Carlo simulations confirm that the global temporal clustering of great shallow earthquakes during 1952-1964 at M ??? 9.0 is highly significant (4% random probability) as is the clustering of the events of M ??? 8.6 (0.2% random probability) during 1950-1965. We have extended the Pacheco and Sykes (1992) catalog from 1989 through 2001 using Harvard moment centroid data. Immediately after the 1950-1965 cluster, significant quiescence at and above M 8.4 begins and continues until 2001 (0.5% random probability). In alternative catalogs derived by correcting for possible random errors in magnitude estimates in the extended Pacheco-Sykes catalog, the clustering of M ??? 9 persists at a significant level. These observations indicate that, for great earthquakes, Earth behaves as a coherent seismotectonic system. A very-large-scale mechanism for global earthquake triggering and/or stress transfer is implied. There are several candidates, but so far only viscoelastic relaxation has been modeled on a global scale.

Wildfire cluster detection using space-time scan statistics

NASA Astrophysics Data System (ADS)

Tonini, M.; Tuia, D.; Ratle, F.; Kanevski, M.

2009-04-01

The aim of the present study is to identify spatio-temporal clusters of fires sequences using space-time scan statistics. These statistical methods are specifically designed to detect clusters and assess their significance. Basically, scan statistics work by comparing a set of events occurring inside a scanning window (or a space-time cylinder for spatio-temporal data) with those that lie outside. Windows of increasing size scan the zone across space and time: the likelihood ratio is calculated for each window (comparing the ratio "observed cases over expected" inside and outside): the window with the maximum value is assumed to be the most probable cluster, and so on. Under the null hypothesis of spatial and temporal randomness, these events are distributed according to a known discrete-state random process (Poisson or Bernoulli), which parameters can be estimated. Given this assumption, it is possible to test whether or not the null hypothesis holds in a specific area. In order to deal with fires data, the space-time permutation scan statistic has been applied since it does not require the explicit specification of the population-at risk in each cylinder. The case study is represented by Florida daily fire detection using the Moderate Resolution Imaging Spectroradiometer (MODIS) active fire product during the period 2003-2006. As result, statistically significant clusters have been identified. Performing the analyses over the entire frame period, three out of the five most likely clusters have been identified in the forest areas, on the North of the country; the other two clusters cover a large zone in the South, corresponding to agricultural land and the prairies in the Everglades. Furthermore, the analyses have been performed separately for the four years to analyze if the wildfires recur each year during the same period. It emerges that clusters of forest fires are more frequent in hot seasons (spring and summer), while in the South areas they are widely present along the whole year. The analysis of fires distribution to evaluate if they are statistically more frequent in some area or/and in some period of the year, can be useful to support fire management and to focus on prevention measures.

Cluster Analysis in Sociometric Research: A Pattern-Oriented Approach to Identifying Temporally Stable Peer Status Groups of Girls

ERIC Educational Resources Information Center

Zettergren, Peter

2007-01-01

A modern clustering technique was applied to age-10 and age-13 sociometric data with the purpose of identifying longitudinally stable peer status clusters. The study included 445 girls from a Swedish longitudinal study. The identified temporally stable clusters of rejected, popular, and average girls were essentially larger than corresponding…

A new approach for the assessment of temporal clustering of extratropical wind storms

NASA Astrophysics Data System (ADS)

Schuster, Mareike; Eddounia, Fadoua; Kuhnel, Ivan; Ulbrich, Uwe

2017-04-01

A widely-used methodology to assess the clustering of storms in a region is based on dispersion statistics of a simple homogeneous Poisson process. This clustering measure is determined by the ratio of the variance and the mean of the local storm statistics per grid point. Resulting values larger than 1, i.e. when the variance is larger than the mean, indicate clustering; while values lower than 1 indicate a sequencing of storms that is more regular than a random process. However, a disadvantage of this methodology is that the characteristics are valid for a pre-defined climatological time period, and it is not possible to identify a temporal variability of clustering. Also, the absolute value of the dispersion statistics is not particularly intuitive. We have developed an approach to describe temporal clustering of storms which offers a more intuitive comprehension, and at the same time allows to assess temporal variations. The approach is based on the local distribution of waiting times between the occurrence of two individual storm events, the former being computed through the post-processing of individual windstorm tracks which in turn are obtained by an objective tracking algorithm. Based on this distribution a threshold can be set, either by the waiting time expected from a random process or by a quantile of the observed distribution. Thus, it can be determined if two consecutive wind storm events count as part of a (temporal) cluster. We analyze extratropical wind storms in a reanalysis dataset and compare the results of the traditional clustering measure with our new methodology. We assess what range of clustering events (in terms of duration and frequency) is covered and identify if the historically known clustered seasons are detectable by the new clustering measure in the reanalysis.

Which catchment characteristics control the temporal dependence structure of daily river flows?

NASA Astrophysics Data System (ADS)

Chiverton, Andrew; Hannaford, Jamie; Holman, Ian; Corstanje, Ron; Prudhomme, Christel; Bloomfield, John; Hess, Tim

2014-05-01

A hydrological classification system would provide information about the dominant processes in the catchment enabling information to be transferred between catchments. Currently there is no widely-agreed upon system for classifying river catchments. This paper developed a novel approach to assess the influence that catchment characteristics have on the precipitation-to-flow relationship, using a catchment classification based on the average temporal dependence structure in daily river flow data over the period 1980 to 2010. Temporal dependence in river flow data is driven by the flow pathways, connectivity and storage within the catchment. Temporal dependence was analysed by creating temporally averaged semi-variograms for a set of 116 near-natural catchments (in order to prevent direct anthropogenic disturbances influencing the results) distributed throughout the UK. Cluster analysis, using the variogram, classified the catchments into four well defined clusters driven by the interaction of catchment characteristics, predominantly characteristics which influence the precipitation-to-flow relationship. Geology, depth to gleyed layer in soils, slope of the catchment and the percentage of arable land were significantly different between the clusters. These characteristics drive the temporal dependence structure by influencing the rate at which water moves through the catchment and / or the storage in the catchment. Arable land is correlated with several other variables, hence is a proxy indicating the residence time of the water in the catchment. Finally, quadratic discriminant analysis was used to show that a model with five catchment characteristics is able to predict the temporal dependence structure for un-gauged catchments. This work demonstrates that a variogram-based approach is a powerful and flexible methodology for grouping catchments based on the precipitation-to-flow relationship which could be applied to any set of catchments with a relatively complete daily river flow record.

[Temporal analysis of mortality due to intimate partner violence in Spain].

PubMed

Vives, Carmen; Caballero, Pablo; Álvarez-Dardet, Carlos

2004-01-01

To analyze the temporal distribution of mortality due to violence by intimate partners (VIP) and to identify possible temporal clusters in women deaths by VIP in Spain. We performed a descriptive epidemiological study based on the VIP deaths included in the database of the Federation of Divorced and Separated Women (1998-2003). The epidemic index (EI) was calculated as the ratio between the actual number of VIP deaths in a given month from January to July 2003 and the median number in the same month in the five preceding years. A Poisson model was used to analyze the distribution by years (1998-2002), seasons, months, and days. Simple regression analysis was performed with three-monthly means. A temporal cluster analysis was also carried out. In 2003, the EI of VIP mortality was high in January (EI = 1.6), March (EI = 1.2), May (EI = 1.5), June (EI = 2), and July (EI = 2.5). Compared with 1998 and Sundays, respectively, mortality due to VIP was significantly increased in 2001 (relative risk, RR = 1.52; 95% confidence interval [CI], 1.05-2.20) and on Mondays (RR = 1.77; 95%CI, 1.13-2.76). The regression analyses confirmed an increase between the first three-month period of 1998 and the last three-month period of 2001. There were no differences between seasons and months. No temporal clusters of deaths were detected. VIP is currently an increasing epidemic in Spain with no clear temporal pattern. Political and legal efforts to reduce this problem do not seem to be successful.

Spatiotemporal clusters of malaria cases at village level, northwest Ethiopia.

PubMed

Alemu, Kassahun; Worku, Alemayehu; Berhane, Yemane; Kumie, Abera

2014-06-06

Malaria attacks are not evenly distributed in space and time. In highland areas with low endemicity, malaria transmission is highly variable and malaria acquisition risk for individuals is unevenly distributed even within a neighbourhood. Characterizing the spatiotemporal distribution of malaria cases in high-altitude villages is necessary to prioritize the risk areas and facilitate interventions. Spatial scan statistics using the Bernoulli method were employed to identify spatial and temporal clusters of malaria in high-altitude villages. Daily malaria data were collected, using a passive surveillance system, from patients visiting local health facilities. Georeference data were collected at villages using hand-held global positioning system devices and linked to patient data. Bernoulli model using Bayesian approaches and Marcov Chain Monte Carlo (MCMC) methods were used to identify the effects of factors on spatial clusters of malaria cases. The deviance information criterion (DIC) was used to assess the goodness-of-fit of the different models. The smaller the DIC, the better the model fit. Malaria cases were clustered in both space and time in high-altitude villages. Spatial scan statistics identified a total of 56 spatial clusters of malaria in high-altitude villages. Of these, 39 were the most likely clusters (LLR = 15.62, p < 0.00001) and 17 were secondary clusters (LLR = 7.05, p < 0.03). The significant most likely temporal malaria clusters were detected between August and December (LLR = 17.87, p < 0.001). Travel away home, males and age above 15 years had statistically significant effect on malaria clusters at high-altitude villages. The study identified spatial clusters of malaria cases occurring at high elevation villages within the district. A patient who travelled away from home to a malaria-endemic area might be the most probable source of malaria infection in a high-altitude village. Malaria interventions in high altitude villages should address factors associated with malaria clustering.

Spatial-Temporal Heterogeneity in Regional Watershed Phosphorus Cycles Driven by Changes in Human Activity over the Past Century

NASA Astrophysics Data System (ADS)

Hale, R. L.; Grimm, N. B.; Vorosmarty, C. J.

2014-12-01

An ongoing challenge for society is to harness the benefits of phosphorus (P) while minimizing negative effects on downstream ecosystems. To meet this challenge we must understand the controls on the delivery of anthropogenic P from landscapes to downstream ecosystems. We used a model that incorporates P inputs to watersheds, hydrology, and infrastructure (sewers, waste-water treatment plants, and reservoirs) to reconstruct historic P yields for the northeastern U.S. from 1930 to 2002. At the regional scale, increases in P inputs were paralleled by increased fractional retention, thus P loading to the coast did not increase significantly. We found that temporal variation in regional P yield was correlated with P inputs. Spatial patterns of watershed P yields were best predicted by inputs, but the correlation between inputs and yields in space weakened over time, due to infrastructure development. Although the magnitude of infrastructure effect was small, its role changed over time and was important in creating spatial and temporal heterogeneity in input-yield relationships. We then conducted a hierarchical cluster analysis to identify a typology of anthropogenic P cycling, using data on P inputs (fertilizer, livestock feed, and human food), infrastructure (dams, wastewater treatment plants, sewers), and hydrology (runoff coefficient). We identified 6 key types of watersheds that varied significantly in climate, infrastructure, and the types and amounts of P inputs. Annual watershed P yields and retention varied significantly across watershed types. Although land cover varied significantly across typologies, clusters based on land cover alone did not explain P budget patterns, suggesting that this variable is insufficient to understand patterns of P cycling across large spatial scales. Furthermore, clusters varied over time as patterns of climate, P use, and infrastructure changed. Our results demonstrate that the drivers of P cycles are spatially and temporally heterogeneous, yet they also suggest that a relatively simple typology of watersheds can be useful for understanding regional P cycles and may help inform P management approaches.

The functional neuroanatomy of verbal memory in Alzheimer's disease: [18F]-Fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET) correlates of recency and recognition memory.

PubMed

Staffaroni, Adam M; Melrose, Rebecca J; Leskin, Lorraine P; Riskin-Jones, Hannah; Harwood, Dylan; Mandelkern, Mark; Sultzer, David L

2017-09-01

The objective of this study was to distinguish the functional neuroanatomy of verbal learning and recognition in Alzheimer's disease (AD) using the Consortium to Establish a Registry for Alzheimer's Disease (CERAD) Word Learning task. In 81 Veterans diagnosed with dementia due to AD, we conducted a cluster-based correlation analysis to assess the relationships between recency and recognition memory scores from the CERAD Word Learning Task and cortical metabolic activity measured using [ 18 F]-fluoro-2-deoxy-D-glucose positron emission tomography (FDG-PET). AD patients (Mini-Mental State Examination, MMSE mean = 20.2) performed significantly better on the recall of recency items during learning trials than of primacy and middle items. Recency memory was associated with cerebral metabolism in the left middle and inferior temporal gyri and left fusiform gyrus (p < .05 at the corrected cluster level). In contrast, recognition memory was correlated with metabolic activity in two clusters: (a) a large cluster that included the left hippocampus, parahippocampal gyrus, entorhinal cortex, anterior temporal lobe, and inferior and middle temporal gyri; (b) the bilateral orbitofrontal cortices (OFC). The present study further informs our understanding of the disparate functional neuroanatomy of recency memory and recognition memory in AD. We anticipated that the recency effect would be relatively preserved and associated with temporoparietal brain regions implicated in short-term verbal memory, while recognition memory would be associated with the medial temporal lobe and possibly the OFC. Consistent with our a priori hypotheses, list learning in our AD sample was characterized by a reduced primacy effect and a relatively spared recency effect; however, recency memory was associated with cerebral metabolism in inferior and lateral temporal regions associated with the semantic memory network, rather than regions associated with short-term verbal memory. The correlates of recognition memory included the medial temporal lobe and OFC, replicating prior studies.

Spatio-Temporal Clustering of Monitoring Network

NASA Astrophysics Data System (ADS)

Hussain, I.; Pilz, J.

2009-04-01

Pakistan has much diversity in seasonal variation of different locations. Some areas are in desserts and remain very hot and waterless, for example coastal areas are situated along the Arabian Sea and have very warm season and a little rainfall. Some areas are covered with mountains, have very low temperature and heavy rainfall; for instance Karakoram ranges. The most important variables that have an impact on the climate are temperature, precipitation, humidity, wind speed and elevation. Furthermore, it is hard to find homogeneous regions in Pakistan with respect to climate variation. Identification of homogeneous regions in Pakistan can be useful in many aspects. It can be helpful for prediction of the climate in the sub-regions and for optimizing the number of monitoring sites. In the earlier literature no one tried to identify homogeneous regions of Pakistan with respect to climate variation. There are only a few papers about spatio-temporal clustering of monitoring network. Steinhaus (1956) presented the well-known K-means clustering method. It can identify a predefined number of clusters by iteratively assigning centriods to clusters based. Castro et al. (1997) developed a genetic heuristic algorithm to solve medoids based clustering. Their method is based on genetic recombination upon random assorting recombination. The suggested method is appropriate for clustering the attributes which have genetic characteristics. Sap and Awan (2005) presented a robust weighted kernel K-means algorithm incorporating spatial constraints for clustering climate data. The proposed algorithm can effectively handle noise, outliers and auto-correlation in the spatial data, for effective and efficient data analysis by exploring patterns and structures in the data. Soltani and Modarres (2006) used hierarchical and divisive cluster analysis to categorize patterns of rainfall in Iran. They only considered rainfall at twenty-eight monitoring sites and concluded that eight clusters existed. Soltani and Modarres (2006) classified the sites by using only average rainfall of sites, they did not consider time replications and spatial coordinates. Kerby et.al (2007) purposed spatial clustering method based on likelihood. They took account of the geographic locations through the variance covariance matrix. Their purposed method works like hierarchical clustering methods. Moreovere, it is inappropiriate for time replication data and could not perform well for large number of sites. Tuia.et.al (2008) used scan statistics for identifying spatio-temporal clusters for fire sequences in the Tuscany region in Italy. The scan statistics clustering method was developed by Kulldorff et al. (1997) to detect spatio-temporal clusters in epidemiology and assessing their significance. The purposed scan statistics method is used only for univariate discrete stochastic random variables. In this paper we make use of a very simple approach for spatio-temporal clustering which can create separable and homogeneous clusters. Most of the clustering methods are based on Euclidean distances. It is well known that geographic coordinates are spherical coordinates and estimating Euclidean distances from spherical coordinates is inappropriate. As a transformation from geographic coordinates to rectangular (D-plane) coordinates we use the Lambert projection method. The partition around medoids clustering method is incorporated on the data including D-plane coordinates. Ordinary kriging is taken as validity measure for the precipitation data. The kriging results for clusters are more accurate and have less variation compared to complete monitoring network precipitation data. References Casto.V.E and Murray.A.T (1997). Spatial Clustering with Data Mining with Genetic Algorithms. http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.56.8573 Kaufman.L and Rousseeuw.P.J (1990). Finding Groups in Data: An Introduction to Cluster Analysis. Wiley series of Probability and Mathematical Statistics, New York. Kulldorf.M (1997). A spatial scan statistic. Commun. Stat.-Theor. Math. 26(6), 1481-1496 Kerby. A , Marx. D, Samal. A and Adamchuck. V. (2007). Spatial Clustering Using the Likelihood Function. Seventh IEEE International Conference on Data Mining - Workshops Steinhaus.H (1956). Sur la division des corp materiels en parties. Bull. Acad. Polon. Sci., C1. III vol IV:801- 804 Snyder, J. P. (1987). Map Projection: A Working Manual. U. S. Geological Survey Professional Paper 1395. Washington, DC: U. S. Government Printing Office, pp. 104-110 Sap.M.N and Awan. A.M (2005). Finding Spatio-Temporal Patterns in Climate Data Using Clustering. Proceedings of the International Conference on Cyberworlds (CW'05) Soltani.S and Modarres.R (2006). Classification of Spatio -Temporal Pattern of Rainfall in Iran: Using Hierarchical and Divisive Cluster Analysis. Journal of Spatial Hydrology Vol.6, No.2 Tuia.D, Ratle.F, Lasaponara.R, Telesca.L and Kanevski.M (2008). Scan Statistics Analysis for Forest Fire Clusters. Commun. in Nonlinear science and numerical simulation 13,1689-1694.

Structure-function relationship between the octopus perimeter cluster mean sensitivity and sector retinal nerve fiber layer thickness measured with the RTVue optical coherence tomography and scanning laser polarimetry.

PubMed

Naghizadeh, Farzaneh; Garas, Anita; Vargha, Péter; Holló, Gábor

2014-01-01

To determine structure-function relationship between each of 16 Octopus perimeter G2 program clusters and the corresponding 16 peripapillary sector retinal nerve fiber layer thickness (RNFLT) values measured with the RTVue-100 Fourier-domain optical coherence tomography (RTVue OCT) and scanning laser polarimetry with variable corneal compensation (GDx-VCC) and enhanced corneal compensation (GDx-ECC) corneal compensation. One eye of 110 white patients (15 healthy, 20 ocular hypertensive, and 75 glaucoma eyes) were investigated. The Akaike information criterion and the F test were used to identify the best fitting model. Parabolic relationship with logarithmic cluster mean sensitivity and linear sector RNFLT values provided the best fit. For RTVue OCT, significant (P<0.0001) coefficients of determination (R) were found for all 16 RNFLT sectors. The R values were highest for the temporal, superotemporal, and inferotemporal RNFLT sectors (0.4483 to 0.5186). For GDx-VCC/ECC, significant (P<0.01) parabolic relationship was seen for all but the temporal and nasal RNFLT sectors. The overall highest R value (0.6943) was found for a superotemporal RNFLT sector with GDx-ECC. For some RNFLT sectors, the goodness of fit differed significantly between the imaging methods. Structure-function relationship was similar for the total population and the glaucoma subgroup, whereas no relationship (P>0.05) was found for the control eyes. Mean sensitivity of the Octopus visual field clusters showed significant parabolic relationship with the corresponding peripapillary RNFLT sectors. The relationship was more general with the RTVue OCT than GDx-VCC or GDx-ECC. The results show that visual field clusters of the Octopus G program can be applied for detailed structure-function research.

Stability of Synchronization Clusters and Seizurability in Temporal Lobe Epilepsy

PubMed Central

Palmigiano, Agostina; Pastor, Jesús; García de Sola, Rafael; Ortega, Guillermo J.

2012-01-01

Purpose Identification of critical areas in presurgical evaluations of patients with temporal lobe epilepsy is the most important step prior to resection. According to the “epileptic focus model”, localization of seizure onset zones is the main task to be accomplished. Nevertheless, a significant minority of epileptic patients continue to experience seizures after surgery (even when the focus is correctly located), an observation that is difficult to explain under this approach. However, if attention is shifted from a specific cortical location toward the network properties themselves, then the epileptic network model does allow us to explain unsuccessful surgical outcomes. Methods The intraoperative electrocorticography records of 20 patients with temporal lobe epilepsy were analyzed in search of interictal synchronization clusters. Synchronization was analyzed, and the stability of highly synchronized areas was quantified. Surrogate data were constructed and used to statistically validate the results. Our results show the existence of highly localized and stable synchronization areas in both the lateral and the mesial areas of the temporal lobe ipsilateral to the clinical seizures. Synchronization areas seem to play a central role in the capacity of the epileptic network to generate clinical seizures. Resection of stable synchronization areas is associated with elimination of seizures; nonresection of synchronization clusters is associated with the persistence of seizures after surgery. Discussion We suggest that synchronization clusters and their stability play a central role in the epileptic network, favoring seizure onset and propagation. We further speculate that the stability distribution of these synchronization areas would differentiate normal from pathologic cases. PMID:22844524

Hierarchical Spatio-temporal Visual Analysis of Cluster Evolution in Electrocorticography Data

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2016-10-02

Here, we present ECoG ClusterFlow, a novel interactive visual analysis tool for the exploration of high-resolution Electrocorticography (ECoG) data. Our system detects and visualizes dynamic high-level structures, such as communities, using the time-varying spatial connectivity network derived from the high-resolution ECoG data. ECoG ClusterFlow provides a multi-scale visualization of the spatio-temporal patterns underlying the time-varying communities using two views: 1) an overview summarizing the evolution of clusters over time and 2) a hierarchical glyph-based technique that uses data aggregation and small multiples techniques to visualize the propagation of clusters in their spatial domain. ECoG ClusterFlow makes it possible 1) tomore » compare the spatio-temporal evolution patterns across various time intervals, 2) to compare the temporal information at varying levels of granularity, and 3) to investigate the evolution of spatial patterns without occluding the spatial context information. Lastly, we present case studies done in collaboration with neuroscientists on our team for both simulated and real epileptic seizure data aimed at evaluating the effectiveness of our approach.« less

Bayesian Modeling of Temporal Coherence in Videos for Entity Discovery and Summarization.

PubMed

Mitra, Adway; Biswas, Soma; Bhattacharyya, Chiranjib

2017-03-01

A video is understood by users in terms of entities present in it. Entity Discovery is the task of building appearance model for each entity (e.g., a person), and finding all its occurrences in the video. We represent a video as a sequence of tracklets, each spanning 10-20 frames, and associated with one entity. We pose Entity Discovery as tracklet clustering, and approach it by leveraging Temporal Coherence (TC): the property that temporally neighboring tracklets are likely to be associated with the same entity. Our major contributions are the first Bayesian nonparametric models for TC at tracklet-level. We extend Chinese Restaurant Process (CRP) to TC-CRP, and further to Temporally Coherent Chinese Restaurant Franchise (TC-CRF) to jointly model entities and temporal segments using mixture components and sparse distributions. For discovering persons in TV serial videos without meta-data like scripts, these methods show considerable improvement over state-of-the-art approaches to tracklet clustering in terms of clustering accuracy, cluster purity and entity coverage. The proposed methods can perform online tracklet clustering on streaming videos unlike existing approaches, and can automatically reject false tracklets. Finally we discuss entity-driven video summarization- where temporal segments of the video are selected based on the discovered entities, to create a semantically meaningful summary.

The smart cluster method. Adaptive earthquake cluster identification and analysis in strong seismic regions

NASA Astrophysics Data System (ADS)

Schaefer, Andreas M.; Daniell, James E.; Wenzel, Friedemann

2017-07-01

Earthquake clustering is an essential part of almost any statistical analysis of spatial and temporal properties of seismic activity. The nature of earthquake clusters and subsequent declustering of earthquake catalogues plays a crucial role in determining the magnitude-dependent earthquake return period and its respective spatial variation for probabilistic seismic hazard assessment. This study introduces the Smart Cluster Method (SCM), a new methodology to identify earthquake clusters, which uses an adaptive point process for spatio-temporal cluster identification. It utilises the magnitude-dependent spatio-temporal earthquake density to adjust the search properties, subsequently analyses the identified clusters to determine directional variation and adjusts its search space with respect to directional properties. In the case of rapid subsequent ruptures like the 1992 Landers sequence or the 2010-2011 Darfield-Christchurch sequence, a reclassification procedure is applied to disassemble subsequent ruptures using near-field searches, nearest neighbour classification and temporal splitting. The method is capable of identifying and classifying earthquake clusters in space and time. It has been tested and validated using earthquake data from California and New Zealand. A total of more than 1500 clusters have been found in both regions since 1980 with M m i n = 2.0. Utilising the knowledge of cluster classification, the method has been adjusted to provide an earthquake declustering algorithm, which has been compared to existing methods. Its performance is comparable to established methodologies. The analysis of earthquake clustering statistics lead to various new and updated correlation functions, e.g. for ratios between mainshock and strongest aftershock and general aftershock activity metrics.

Temporal Clustering and Sequencing in Short-Term Memory and Episodic Memory

ERIC Educational Resources Information Center

Farrell, Simon

2012-01-01

A model of short-term memory and episodic memory is presented, with the core assumptions that (a) people parse their continuous experience into episodic clusters and (b) items are clustered together in memory as episodes by binding information within an episode to a common temporal context. Along with the additional assumption that information…

Termination of seizure clusters is related to the duration of focal seizures.

PubMed

Ferastraoaru, Victor; Schulze-Bonhage, Andreas; Lipton, Richard B; Dümpelmann, Matthias; Legatt, Alan D; Blumberg, Julie; Haut, Sheryl R

2016-06-01

Clustered seizures are characterized by shorter than usual interseizure intervals and pose increased morbidity risk. This study examines the characteristics of seizures that cluster, with special attention to the final seizure in a cluster. This is a retrospective analysis of long-term inpatient monitoring data from the EPILEPSIAE project. Patients underwent presurgical evaluation from 2002 to 2009. Seizure clusters were defined by the occurrence of at least two consecutive seizures with interseizure intervals of <4 h. Other definitions of seizure clustering were examined in a sensitivity analysis. Seizures were classified into three contextually defined groups: isolated seizures (not meeting clustering criteria), terminal seizure (last seizure in a cluster), and intracluster seizures (any other seizures within a cluster). Seizure characteristics were compared among the three groups in terms of duration, type (focal seizures remaining restricted to one hemisphere vs. evolving bilaterally), seizure origin, and localization concordance among pairs of consecutive seizures. Among 92 subjects, 77 (83%) had at least one seizure cluster. The intracluster seizures were significantly shorter than the last seizure in a cluster (p = 0.011), whereas the last seizure in a cluster resembled the isolated seizures in terms of duration. Although focal only (unilateral), seizures were shorter than seizures that evolved bilaterally and there was no correlation between the seizure type and the seizure position in relation to a cluster (p = 0.762). Frontal and temporal lobe seizures were more likely to cluster compared with other localizations (p = 0.009). Seizure pairs that are part of a cluster were more likely to have a concordant origin than were isolated seizures. Results were similar for the 2 h definition of clustering, but not for the 8 h definition of clustering. We demonstrated that intracluster seizures are short relative to isolated seizures and terminal seizures. Frontal and temporal lobe seizures are more likely to cluster. Wiley Periodicals, Inc. © 2016 International League Against Epilepsy.

Network-constrained spatio-temporal clustering analysis of traffic collisions in Jianghan District of Wuhan, China

PubMed Central

Fan, Yaxin; Zhu, Xinyan; Guo, Wei; Guo, Tao

2018-01-01

The analysis of traffic collisions is essential for urban safety and the sustainable development of the urban environment. Reducing the road traffic injuries and the financial losses caused by collisions is the most important goal of traffic management. In addition, traffic collisions are a major cause of traffic congestion, which is a serious issue that affects everyone in the society. Therefore, traffic collision analysis is essential for all parties, including drivers, pedestrians, and traffic officers, to understand the road risks at a finer spatio-temporal scale. However, traffic collisions in the urban context are dynamic and complex. Thus, it is important to detect how the collision hotspots evolve over time through spatio-temporal clustering analysis. In addition, traffic collisions are not isolated events in space. The characteristics of the traffic collisions and their surrounding locations also present an influence of the clusters. This work tries to explore the spatio-temporal clustering patterns of traffic collisions by combining a set of network-constrained methods. These methods were tested using the traffic collision data in Jianghan District of Wuhan, China. The results demonstrated that these methods offer different perspectives of the spatio-temporal clustering patterns. The weighted network kernel density estimation provides an intuitive way to incorporate attribute information. The network cross K-function shows that there are varying clustering tendencies between traffic collisions and different types of POIs. The proposed network differential Local Moran’s I and network local indicators of mobility association provide straightforward and quantitative measures of the hotspot changes. This case study shows that these methods could help researchers, practitioners, and policy-makers to better understand the spatio-temporal clustering patterns of traffic collisions. PMID:29672551

Epidemic characteristics and spatio-temporal patterns of scrub typhus during 2006-2013 in Tai'an, Northern China.

PubMed

Zheng, L; Yang, H-L; Bi, Z-W; Kou, Z-Q; Zhang, L-Y; Zhang, A-H; Yang, L; Zhao, Z-T

2015-08-01

Tai'an, a famous cultural tourist district, is a new endemic foci of scrub typhus in northern China. Frequent reports of travel-acquired cases and absence of effective vaccine indicated a significant health problem of scrub typhus in Tai'an. Thus, descriptive epidemiological methods and spatial-temporal scan statistics were used to describe the epidemic characteristics and detect the significant clusters of the high incidence of scrub typhus at the town level in Tai'an. Results of descriptive epidemiological analysis showed a total of 490 cases were reported in Tai'an with the annual average incidence ranging from 0·48 to 2·27/100 000 during 2006-2013. Females, the elderly and farmers are the high-risk groups. Monthly changes of scrub typhus cases indicated an obvious epidemic period in autumn. Spatial-temporal distribution analysis, showed significant clusters of high incidence mainly located in eastern and northern Tai'an. Our study suggests that more effective, targeted measures for local residents should be implemented in the eastern and northern areas of Tai'an in autumn. Meanwhile, it may prove beneficial for health policy makers to advise travellers to take preventive measures in order to minimize the risk of infection of scrub typhus in Tai'an.

Dopamine D2 receptor levels in striatum, thalamus, substantia nigra, limbic regions, and cortex in schizophrenic subjects.

PubMed

Kessler, Robert M; Woodward, Neil D; Riccardi, Patrizia; Li, Rui; Ansari, M Sib; Anderson, Sharlett; Dawant, Benoit; Zald, David; Meltzer, Herbert Y

2009-06-15

Studies in schizophrenic patients have reported dopaminergic abnormalities in striatum, substantia nigra, thalamus, anterior cingulate, hippocampus, and cortex that have been related to positive symptoms and cognitive impairments. [(18)F]fallypride positron emission tomography studies were performed in off-medication or never-medicated schizophrenic subjects (n = 11, 6 men, 5 women; mean age of 30.5 +/- 8.0 [SD] years; 4 drug-naive) and age-matched healthy subjects (n = 11, 5 men, 6 women, mean age of 31.6 +/- 9.2 [SD]) to examine dopamine D(2) receptor (DA D(2)r) levels in the caudate, putamen, ventral striatum, medial thalamus, posterior thalamus, substantia nigra, amygdala, temporal cortex, anterior cingulate, and hippocampus. In schizophrenic subjects, increased DA D(2)r levels were seen in the substantia nigra bilaterally; decreased levels were seen in the left medial thalamus. Correlations of symptoms with ROI data demonstrated a significant correlation of disorganized thinking/nonparanoid delusions with the right temporal cortex ROI (r = .94, p = .0001), which remained significant after correction for multiple comparisons (p < .03). Correlations of symptoms with parametric images of DA D(2)r levels revealed no significant clusters of correlations with negative symptoms but significant clusters of positive correlations of total positive symptoms, delusions and bizarre behavior with the lateral and anterior temporal cortex, and hallucinations with the left ventral striatum. The results of this study demonstrate abnormal DA D(2)r-mediated neurotransmission in the substantia nigra consistent with nigral dysfunction in schizophrenia and suggest that both temporal cortical and ventral striatal DA D(2)r mediate positive symptoms.

Spatial clustering and local risk of leprosy in São Paulo, Brazil.

PubMed

Ramos, Antônio Carlos Vieira; Yamamura, Mellina; Arroyo, Luiz Henrique; Popolin, Marcela Paschoal; Chiaravalloti Neto, Francisco; Palha, Pedro Fredemir; Uchoa, Severina Alice da Costa; Pieri, Flávia Meneguetti; Pinto, Ione Carvalho; Fiorati, Regina Célia; Queiroz, Ana Angélica Rêgo de; Belchior, Aylana de Souza; Dos Santos, Danielle Talita; Garcia, Maria Concebida da Cunha; Crispim, Juliane de Almeida; Alves, Luana Seles; Berra, Thaís Zamboni; Arcêncio, Ricardo Alexandre

2017-02-01

Although the detection rate is decreasing, the proportion of new cases with WHO grade 2 disability (G2D) is increasing, creating concern among policy makers and the Brazilian government. This study aimed to identify spatial clustering of leprosy and classify high-risk areas in a major leprosy cluster using the SatScan method. Data were obtained including all leprosy cases diagnosed between January 2006 and December 2013. In addition to the clinical variable, information was also gathered regarding the G2D of the patient at diagnosis and after treatment. The Scan Spatial statistic test, developed by Kulldorff e Nagarwalla, was used to identify spatial clustering and to measure the local risk (Relative Risk-RR) of leprosy. Maps considering these risks and their confidence intervals were constructed. A total of 434 cases were identified, including 188 (43.31%) borderline leprosy and 101 (23.28%) lepromatous leprosy cases. There was a predominance of males, with ages ranging from 15 to 59 years, and 51 patients (11.75%) presented G2D. Two significant spatial clusters and three significant spatial-temporal clusters were also observed. The main spatial cluster (p = 0.000) contained 90 census tracts, a population of approximately 58,438 inhabitants, detection rate of 22.6 cases per 100,000 people and RR of approximately 3.41 (95%CI = 2.721-4.267). Regarding the spatial-temporal clusters, two clusters were observed, with RR ranging between 24.35 (95%CI = 11.133-52.984) and 15.24 (95%CI = 10.114-22.919). These findings could contribute to improvements in policies and programming, aiming for the eradication of leprosy in Brazil. The Spatial Scan statistic test was found to be an interesting resource for health managers and healthcare professionals to map the vulnerability of areas in terms of leprosy transmission risk and areas of underreporting.

Grey matter correlates of susceptibility to scams in community-dwelling older adults.

PubMed

Duke Han, S; Boyle, Patricia A; Yu, Lei; Arfanakis, Konstantinos; James, Bryan D; Fleischman, Debra A; Bennett, David A

2016-06-01

Susceptibility to scams is a significant issue among older adults, even among those with intact cognition. Age-related changes in brain macrostructure may be associated with susceptibility to scams; however, this has yet to be explored. Based on previous work implicating frontal and temporal lobe functioning as important in decision making, we tested the hypothesis that susceptibility to scams is associated with smaller grey matter volume in frontal and temporal lobe regions in a large community-dwelling cohort of non-demented older adults. Participants (N = 327, mean age = 81.55, mean education = 15.30, 78.9 % female) completed a self-report measure used to assess susceptibility to scams and an MRI brain scan. Results indicated an inverse association between overall grey matter and susceptibility to scams in models adjusted for age, education, and sex; and in models further adjusted for cognitive function. No significant associations were observed for white matter, cerebrospinal fluid, or total brain volume. Models adjusted for age, education, and sex revealed seven clusters showing smaller grey matter in the right parahippocampal/hippocampal/fusiform, left middle temporal, left orbitofrontal, right ventromedial prefrontal, right middle temporal, right precuneus, and right dorsolateral prefrontal regions. In models further adjusted for cognitive function, results revealed three significant clusters showing smaller grey matter in the right parahippocampal/hippocampal/fusiform, right hippocampal, and right middle temporal regions. Lower grey matter concentration in specific brain regions may be associated with susceptibility to scams, even after adjusting for cognitive ability. Future research is needed to determine whether grey matter reductions in these regions may be a biomarker for susceptibility to scams in old age.

Spatial and temporal characterizations of water quality in Kuwait Bay.

PubMed

Al-Mutairi, N; Abahussain, A; El-Battay, A

2014-06-15

The spatial and temporal patterns of water quality in Kuwait Bay have been investigated using data from six stations between 2009 and 2011. The results showed that most of water quality parameters such as phosphorus (PO4), nitrate (NO3), dissolved oxygen (DO), and Total Suspended Solids (TSS) fluctuated over time and space. Based on Water Quality Index (WQI) data, six stations were significantly clustered into two main classes using cluster analysis, one group located in western side of the Bay, and other in eastern side. Three principal components are responsible for water quality variations in the Bay. The first component included DO and pH. The second included PO4, TSS and NO3, and the last component contained seawater temperature and turbidity. The spatial and temporal patterns of water quality in Kuwait Bay are mainly controlled by seasonal variations and discharges from point sources of pollution along Kuwait Bay's coast as well as from Shatt Al-Arab River. Copyright © 2014 Elsevier Ltd. All rights reserved.

Clustering approaches to feature change detection

NASA Astrophysics Data System (ADS)

G-Michael, Tesfaye; Gunzburger, Max; Peterson, Janet

2018-05-01

The automated detection of changes occurring between multi-temporal images is of significant importance in a wide range of medical, environmental, safety, as well as many other settings. The usage of k-means clustering is explored as a means for detecting objects added to a scene. The silhouette score for the clustering is used to define the optimal number of clusters that should be used. For simple images having a limited number of colors, new objects can be detected by examining the change between the optimal number of clusters for the original and modified images. For more complex images, new objects may need to be identified by examining the relative areas covered by corresponding clusters in the original and modified images. Which method is preferable depends on the composition and range of colors present in the images. In addition to describing the clustering and change detection methodology of our proposed approach, we provide some simple illustrations of its application.

Spatio-Temporal Analysis of Smear-Positive Tuberculosis in the Sidama Zone, Southern Ethiopia

PubMed Central

Dangisso, Mesay Hailu; Datiko, Daniel Gemechu; Lindtjørn, Bernt

2015-01-01

Background Tuberculosis (TB) is a disease of public health concern, with a varying distribution across settings depending on socio-economic status, HIV burden, availability and performance of the health system. Ethiopia is a country with a high burden of TB, with regional variations in TB case notification rates (CNRs). However, TB program reports are often compiled and reported at higher administrative units that do not show the burden at lower units, so there is limited information about the spatial distribution of the disease. We therefore aim to assess the spatial distribution and presence of the spatio-temporal clustering of the disease in different geographic settings over 10 years in the Sidama Zone in southern Ethiopia. Methods A retrospective space–time and spatial analysis were carried out at the kebele level (the lowest administrative unit within a district) to identify spatial and space-time clusters of smear-positive pulmonary TB (PTB). Scan statistics, Global Moran’s I, and Getis and Ordi (Gi*) statistics were all used to help analyze the spatial distribution and clusters of the disease across settings. Results A total of 22,545 smear-positive PTB cases notified over 10 years were used for spatial analysis. In a purely spatial analysis, we identified the most likely cluster of smear-positive PTB in 192 kebeles in eight districts (RR= 2, p<0.001), with 12,155 observed and 8,668 expected cases. The Gi* statistic also identified the clusters in the same areas, and the spatial clusters showed stability in most areas in each year during the study period. The space-time analysis also detected the most likely cluster in 193 kebeles in the same eight districts (RR= 1.92, p<0.001), with 7,584 observed and 4,738 expected cases in 2003-2012. Conclusion The study found variations in CNRs and significant spatio-temporal clusters of smear-positive PTB in the Sidama Zone. The findings can be used to guide TB control programs to devise effective TB control strategies for the geographic areas characterized by the highest CNRs. Further studies are required to understand the factors associated with clustering based on individual level locations and investigation of cases. PMID:26030162

A geo-computational algorithm for exploring the structure of diffusion progression in time and space.

PubMed

Chin, Wei-Chien-Benny; Wen, Tzai-Hung; Sabel, Clive E; Wang, I-Hsiang

2017-10-03

A diffusion process can be considered as the movement of linked events through space and time. Therefore, space-time locations of events are key to identify any diffusion process. However, previous clustering analysis methods have focused only on space-time proximity characteristics, neglecting the temporal lag of the movement of events. We argue that the temporal lag between events is a key to understand the process of diffusion movement. Using the temporal lag could help to clarify the types of close relationships. This study aims to develop a data exploration algorithm, namely the TrAcking Progression In Time And Space (TaPiTaS) algorithm, for understanding diffusion processes. Based on the spatial distance and temporal interval between cases, TaPiTaS detects sub-clusters, a group of events that have high probability of having common sources, identifies progression links, the relationships between sub-clusters, and tracks progression chains, the connected components of sub-clusters. Dengue Fever cases data was used as an illustrative case study. The location and temporal range of sub-clusters are presented, along with the progression links. TaPiTaS algorithm contributes a more detailed and in-depth understanding of the development of progression chains, namely the geographic diffusion process.

Conditional clustering of temporal expression profiles

PubMed Central

Wang, Ling; Montano, Monty; Rarick, Matt; Sebastiani, Paola

2008-01-01

Background Many microarray experiments produce temporal profiles in different biological conditions but common cluster techniques are not able to analyze the data conditional on the biological conditions. Results This article presents a novel technique to cluster data from time course microarray experiments performed across several experimental conditions. Our algorithm uses polynomial models to describe the gene expression patterns over time, a full Bayesian approach with proper conjugate priors to make the algorithm invariant to linear transformations, and an iterative procedure to identify genes that have a common temporal expression profile across two or more experimental conditions, and genes that have a unique temporal profile in a specific condition. Conclusion We use simulated data to evaluate the effectiveness of this new algorithm in finding the correct number of clusters and in identifying genes with common and unique profiles. We also use the algorithm to characterize the response of human T cells to stimulations of antigen-receptor signaling gene expression temporal profiles measured in six different biological conditions and we identify common and unique genes. These studies suggest that the methodology proposed here is useful in identifying and distinguishing uniquely stimulated genes from commonly stimulated genes in response to variable stimuli. Software for using this clustering method is available from the project home page. PMID:18334028

Temporal genetic population structure and interannual variation in migration behavior of Pacific Lamprey Entosphenus tridentatus

USGS Publications Warehouse

Clemens, Benjamin J.; Wyss, Lance A.; McCoun, Rebecca; Courter, Ian; Schwabe, Lawrence; Peery, Christopher; Schreck, Carl B.; Spice, Erin K.; Docker, Margaret F.

2017-01-01

Studies using neutral loci suggest that Pacific lamprey, Entosphenus tridentatus, lack strong spatial genetic population structure. However, it is unknown whether temporal genetic population structure exists. We tested whether adult Pacific lamprey: (1) show temporal genetic population structure; and (2) migrate different distances between years. We non-lethally sampled lamprey for DNA in 2009 and 2010 and used eight microsatellite loci to test for genetic population structure. We used telemetry to record the migration behaviors of these fish. Lamprey were assignable to three moderately differentiated genetic clusters (FST = 0.16–0.24 for all pairwise comparisons): one cluster was composed of individuals from 2009, and the other two contained individuals from 2010. The FST value between years was 0.13 and between genetic clusters within 2010 was 0.20. A total of 372 (72.5%) fish were detected multiple times during their migrations. Most fish (69.9%) remained in the mainstem Willamette River; the remaining 30.1% migrated into tributaries. Eighty-two lamprey exhibited multiple back-and-forth movements among tributaries and the mainstem, which may indicate searching behaviors. All migration distances were significantly greater in 2010, when the amplitude of river discharge was greater. Our data suggest genetic structuring between and within years that may reflect different cohorts.

Dopamine D2 Receptor Levels in Striatum, Thalamus, Substantia Nigra, Limbic Regions, and Cortex in Schizophrenic Subjects

PubMed Central

Kessler, Robert M; Woodward, Neil D; Riccardi, Patrizia; Li, Rui; Ansari, M Sib; Anderson, Sharlett; Dawant, Benoit; Zald, David; Meltzer, Herbert Y

2009-01-01

Background Studies in schizophrenics have reported dopaminergic abnormalities in striatum, substantia nigra, thalamus, anterior cingulate, hippocampus and cortex which have been related to positive symptoms and cognitive impairments. Methods [18F]fallypride PET studies were performed in off medication or never medicated schizophrenic subjects [N = 11, 6 M, 5 F; mean age of 30.5 ± 8.0 (S.D.); 4 drug naive] and age matched healthy subjects [N = 11, 5M, 6F, mean age of 31.6 ± 9.2 (S.D.)] to examine dopamine D2 receptor (DA D2r) levels in the caudate, putamen, ventral striatum, medial thalamus, posterior thalamus, substantia nigra, amygdala, temporal cortex, anterior cingulate, and hippocampus. Results In schizophrenic subjects increased DA D2r levels were seen in the substantia nigra bilaterally; decreased levels were seen in the left medial thalamus. Correlations of symptoms with region of interest data demonstrated a significant correlation of disorganized thinking/nonparanoid delusions with the right temporal cortex region of interest (r = 0.94, P = 0.0001) which remained significant after correction for multiple comparisons (P<0.03). Correlations of symptoms with parametric images of DA D2r levels revealed no significant clusters of correlations with negative symptoms, but significant clusters of positive correlations of total positive symptoms, delusions and bizarre behavior with the lateral and anterior temporal cortex, and hallucinations with the left ventral striatum. Conclusions The results of this study demonstrate abnormal DA D2r mediated neurotransmission in the substantia nigra consistent with nigral dysfunction in schizophrenia and suggest that both temporal cortical and ventral striatal DA D2r mediate positive symptoms. PMID:19251247

A study of the tolerance block approach to special stratification. [winter wheat in Kansas

NASA Technical Reports Server (NTRS)

Richardson, W. (Principal Investigator)

1979-01-01

The author has identified the following significant results. Twelve winter wheat LACIE segments in Kansas were used to compare the performance of three clustering methods: (1) BCLUST, which uses a spectral distance function to accumulate clusters; (2) blocks-alone, which divides spectral space into equally populated blocks; and (3) block-seeds, which uses spectral means of blocks-alone as seeds for accumulating distance-type clusters. Both BCLUST and block-seeds performed equally well and outperformed blocks-alone significantly. Their average variance ratio of about 0.5 showed imperfect separation of wheat from non-wheat. This result points to the need to explore the achievable crop separability in the spectral/temporal domain, and suggest evaluating derived features rather than data channels as a means to achieve purer spectral strata.

[Spatial and temporal clustering characteristics of typhoid and paratyphoid fever and its change pattern in 3 provinces in southwestern China, 2001-2012].

PubMed

Wang, L X; Yang, B; Yan, M Y; Tang, Y Q; Liu, Z C; Wang, R Q; Li, S; Ma, L; Kan, B

2017-11-10

Objective: To analyze the spatial and temporal clustering characteristics of typhoid and paratyphoid fever and its change pattern in Yunnan, Guizhou and Guangxi provinces in southwestern China in recent years. Methods: The incidence data of typhoid and paratyphoid fever cases at county level in 3 provinces during 2001-2012 were collected from China Information System for Diseases Control and Prevention and analyzed by the methods of descriptive epidemiology and geographic informatics. And the map showing the spatial and temporal clustering characters of typhoid and paratyphoid fever cases in three provinces was drawn. SaTScan statistics was used to identify the typhoid and paratyphoid fever clustering areas of three provinces in each year from 2001 to 2012. Results: During the study period, the reported cases of typhoid and paratyphoid fever declined with year. The reported incidence decreased from 30.15 per 100 000 in 2001 to 10.83 per 100 000 in 2006(annual incidence 21.12 per 100 000); while during 2007-2012, the incidence became stable, ranging from 4.75 per 100 000 to 6.83 per 100 000 (annual incidence 5.73 per 100 000). The seasonal variation of the incidence was consistent in three provinces, with majority of cases occurred in summer and autumn. The spatial and temporal clustering of typhoid and paratyphoid fever was demonstrated by the incidence map. Most high-incidence counties were located in a zonal area extending from Yuxi of Yunnan to Guiyang of Guizhou, but were concentrated in Guilin in Guangxi. Temporal and spatial scan statistics identified the positional shifting of class Ⅰ clustering area from Guizhou to Yunnan. Class Ⅰ clustering area was located around the central and western areas (Zunyi and Anshun) of Guizhou during 2001-2003, and moved to the central area of Yunnan during 2004-2012. Conclusion: Spatial and temporal clustering of typhoid and paratyphoid fever existed in the endemic areas of southwestern China, and the clustering area covered a zone connecting the central areas of Guizhou and Yunnan. From 2004 to 2012, the most important clustering area shifted from Guizhou to Yunnan. Findings from this study provided evidence for the identifying key areas for typhoid and paratyphoid fever control and prevention and allocate health resources.

Locality-Aware CTA Clustering For Modern GPUs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Ang; Song, Shuaiwen; Liu, Weifeng

2017-04-08

In this paper, we proposed a novel clustering technique for tapping into the performance potential of a largely ignored type of locality: inter-CTA locality. We first demonstrated the capability of the existing GPU hardware to exploit such locality, both spatially and temporally, on L1 or L1/Tex unified cache. To verify the potential of this locality, we quantified its existence in a broad spectrum of applications and discussed its sources of origin. Based on these insights, we proposed the concept of CTA-Clustering and its associated software techniques. Finally, We evaluated these techniques on all modern generations of NVIDIA GPU architectures. Themore » experimental results showed that our proposed clustering techniques could significantly improve on-chip cache performance.« less

Identification of an intact ParaHox cluster with temporal colinearity but altered spatial colinearity in the hemichordate Ptychodera flava

PubMed Central

2013-01-01

Background ParaHox and Hox genes are thought to have evolved from a common ancestral ProtoHox cluster or from tandem duplication prior to the divergence of cnidarians and bilaterians. Similar to Hox clusters, chordate ParaHox genes including Gsx, Xlox, and Cdx, are clustered and their expression exhibits temporal and spatial colinearity. In non-chordate animals, however, studies on the genomic organization of ParaHox genes are limited to only a few animal taxa. Hemichordates, such as the Enteropneust acorn worms, have been used to gain insights into the origins of chordate characters. In this study, we investigated the genomic organization and expression of ParaHox genes in the indirect developing hemichordate acorn worm Ptychodera flava. Results We found that P. flava contains an intact ParaHox cluster with a similar arrangement to that of chordates. The temporal expression order of the P. flava ParaHox genes is the same as that of the chordate ParaHox genes. During embryogenesis, the spatial expression pattern of PfCdx in the posterior endoderm represents a conserved feature similar to the expression of its orthologs in other animals. On the other hand, PfXlox and PfGsx show a novel expression pattern in the blastopore. Nevertheless, during metamorphosis, PfXlox and PfCdx are expressed in the endoderm in a spatially staggered pattern similar to the situation in chordates. Conclusions Our study shows that P. flava ParaHox genes, despite forming an intact cluster, exhibit temporal colinearity but lose spatial colinearity during embryogenesis. During metamorphosis, partial spatial colinearity is retained in the transforming larva. These results strongly suggest that intact ParaHox gene clustering was retained in the deuterostome ancestor and is correlated with temporal colinearity. PMID:23802544

Patterned biofilm formation reveals a mechanism for structural heterogeneity in bacterial biofilms.

PubMed

Gu, Huan; Hou, Shuyu; Yongyat, Chanokpon; De Tore, Suzanne; Ren, Dacheng

2013-09-03

Bacterial biofilms are ubiquitous and are the major cause of chronic infections in humans and persistent biofouling in industry. Despite the significance of bacterial biofilms, the mechanism of biofilm formation and associated drug tolerance is still not fully understood. A major challenge in biofilm research is the intrinsic heterogeneity in the biofilm structure, which leads to temporal and spatial variation in cell density and gene expression. To understand and control such structural heterogeneity, surfaces with patterned functional alkanthiols were used in this study to obtain Escherichia coli cell clusters with systematically varied cluster size and distance between clusters. The results from quantitative imaging analysis revealed an interesting phenomenon in which multicellular connections can be formed between cell clusters depending on the size of interacting clusters and the distance between them. In addition, significant differences in patterned biofilm formation were observed between wild-type E. coli RP437 and some of its isogenic mutants, indicating that certain cellular and genetic factors are involved in interactions among cell clusters. In particular, autoinducer-2-mediated quorum sensing was found to be important. Collectively, these results provide missing information that links cell-to-cell signaling and interaction among cell clusters to the structural organization of bacterial biofilms.

Spatial and Temporal Distribution of Tuberculosis in the State of Mexico, Mexico

PubMed Central

Zaragoza Bastida, Adrian; Hernández Tellez, Marivel; Bustamante Montes, Lilia P.; Medina Torres, Imelda; Jaramillo Paniagua, Jaime Nicolás; Mendoza Martínez, Germán David; Ramírez Durán, Ninfa

2012-01-01

Tuberculosis (TB) is one of the oldest human diseases that still affects large population groups. According to the World Health Organization (WHO), there were approximately 9.4 million new cases worldwide in the year 2010. In Mexico, there were 18,848 new cases of TB of all clinical variants in 2010. The identification of clusters in space-time is of great interest in epidemiological studies. The objective of this research was to identify the spatial and temporal distribution of TB during the period 2006–2010 in the State of Mexico, using geographic information system (GIS) and SCAN statistics program. Nine significant clusters (P < 0.05) were identified using spatial and space-time analysis. The conclusion is that TB in the State of Mexico is not randomly distributed but is concentrated in areas close to Mexico City. PMID:22919337

Canine parvovirus in Australia: the role of socio-economic factors in disease clusters.

PubMed

Brady, S; Norris, J M; Kelman, M; Ward, M P

2012-08-01

To identify clusters of canine parvoviral related disease occurring in Australia during 2010 and investigate the role of socio-economic factors contributing to these clusters, reported cases of canine parvovirus were extracted from an on-line disease surveillance system. Reported residential postcode was used to locate cases, and clusters were identified using a scan statistic. Cases included in clusters were compared to those not included in such clusters with respect to human socioeconomic factors (postcode area relative socioeconomic disadvantage, economic resources, education and occupation) and dog factors (neuter status, breed, age, gender, vaccination status). During 2010, there were 1187 cases of canine parvovirus reported. Nineteen significant (P<0.05) disease clusters were identified, most commonly located in New South Wales. Eleven (58%) clusters occurred between April and July, and the average cluster length was 5.7 days. All clusters occurred in postcodes with a significantly (P<0.05) greater level of relative socioeconomic disadvantage and a lower rank in education and occupation, and it was noted that clustered cases were less likely to have been neutered (P=0.004). No significant difference (P>0.05) was found between cases reported from cluster postcodes and those not within clusters for dog age, gender, breed or vaccination status (although the latter needs to be interpreted with caution, since vaccination was absent in most of the cases). Further research is required to investigate the apparent association between indicators of poor socioeconomic status and clusters of reported canine parvovirus diseases; however these initial findings may be useful for developing geographically- and temporally-targeted prevention and disease control programs. Copyright © 2012 Elsevier Ltd. All rights reserved.

Identifying sighting clusters of endangered taxa with historical records.

PubMed

Duffy, Karl J

2011-04-01

The probability and time of extinction of taxa is often inferred from statistical analyses of historical records. Many of these analyses require the exclusion of multiple records within a unit of time (i.e., a month or a year). Nevertheless, spatially explicit, temporally aggregated data may be useful for identifying clusters of sightings (i.e., sighting clusters) in space and time. Identification of sighting clusters highlights changes in the historical recording of endangered taxa. I used two methods to identify sighting clusters in historical records: the Ederer-Myers-Mantel (EMM) test and the space-time permutation scan (STPS). I applied these methods to the spatially explicit sighting records of three species of orchids that are listed as endangered in the Republic of Ireland under the Wildlife Act (1976): Cephalanthera longifolia, Hammarbya paludosa, and Pseudorchis albida. Results with the EMM test were strongly affected by the choice of the time interval, and thus the number of temporal samples, used to examine the records. For example, sightings of P. albida clustered when the records were partitioned into 20-year temporal samples, but not when they were partitioned into 22-year temporal samples. Because the statistical power of EMM was low, it will not be useful when data are sparse. Nevertheless, the STPS identified regions that contained sighting clusters because it uses a flexible scanning window (defined by cylinders of varying size that move over the study area and evaluate the likelihood of clustering) to detect them, and it identified regions with high and regions with low rates of orchid sightings. The STPS analyses can be used to detect sighting clusters of endangered species that may be related to regions of extirpation and may assist in the categorization of threat status. ©2010 Society for Conservation Biology.

a Web-Based Interactive Platform for Co-Clustering Spatio-Temporal Data

NASA Astrophysics Data System (ADS)

Wu, X.; Poorthuis, A.; Zurita-Milla, R.; Kraak, M.-J.

2017-09-01

Since current studies on clustering analysis mainly focus on exploring spatial or temporal patterns separately, a co-clustering algorithm is utilized in this study to enable the concurrent analysis of spatio-temporal patterns. To allow users to adopt and adapt the algorithm for their own analysis, it is integrated within the server side of an interactive web-based platform. The client side of the platform, running within any modern browser, is a graphical user interface (GUI) with multiple linked visualizations that facilitates the understanding, exploration and interpretation of the raw dataset and co-clustering results. Users can also upload their own datasets and adjust clustering parameters within the platform. To illustrate the use of this platform, an annual temperature dataset from 28 weather stations over 20 years in the Netherlands is used. After the dataset is loaded, it is visualized in a set of linked visualizations: a geographical map, a timeline and a heatmap. This aids the user in understanding the nature of their dataset and the appropriate selection of co-clustering parameters. Once the dataset is processed by the co-clustering algorithm, the results are visualized in the small multiples, a heatmap and a timeline to provide various views for better understanding and also further interpretation. Since the visualization and analysis are integrated in a seamless platform, the user can explore different sets of co-clustering parameters and instantly view the results in order to do iterative, exploratory data analysis. As such, this interactive web-based platform allows users to analyze spatio-temporal data using the co-clustering method and also helps the understanding of the results using multiple linked visualizations.

Multi-temporal clustering of continental floods and associated atmospheric circulations

NASA Astrophysics Data System (ADS)

Liu, Jianyu; Zhang, Yongqiang

2017-12-01

Investigating clustering of floods has important social, economic and ecological implications. This study examines the clustering of Australian floods at different temporal scales and its possible physical mechanisms. Flood series with different severities are obtained by peaks-over-threshold (POT) sampling in four flood thresholds. At intra-annual scale, Cox regression and monthly frequency methods are used to examine whether and when the flood clustering exists, respectively. At inter-annual scale, dispersion indices with four-time variation windows are applied to investigate the inter-annual flood clustering and its variation. Furthermore, the Kernel occurrence rate estimate and bootstrap resampling methods are used to identify flood-rich/flood-poor periods. Finally, seasonal variation of horizontal wind at 850 hPa and vertical wind velocity at 500 hPa are used to investigate the possible mechanisms causing the temporal flood clustering. Our results show that: (1) flood occurrences exhibit clustering at intra-annual scale, which are regulated by climate indices representing the impacts of the Pacific and Indian Oceans; (2) the flood-rich months occur from January to March over northern Australia, and from July to September over southwestern and southeastern Australia; (3) stronger inter-annual clustering takes place across southern Australia than northern Australia; and (4) Australian floods are characterised by regional flood-rich and flood-poor periods, with 1987-1992 identified as the flood-rich period across southern Australia, but the flood-poor period across northern Australia, and 2001-2006 being the flood-poor period across most regions of Australia. The intra-annual and inter-annual clustering and temporal variation of flood occurrences are in accordance with the variation of atmospheric circulation. These results provide relevant information for flood management under the influence of climate variability, and, therefore, are helpful for developing flood hazard mitigation schemes.

ClueNet: Clustering a temporal network based on topological similarity rather than denseness.

PubMed

Crawford, Joseph; Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of "topologically related" nodes, where the resulting topology-based clusters are expected to "correlate" well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data-their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance.

Patterning of functional human astrocytes onto parylene-C/SiO2 substrates for the study of Ca2+ dynamics in astrocytic networks

NASA Astrophysics Data System (ADS)

Raos, B. J.; Simpson, M. C.; Doyle, C. S.; Murray, A. F.; Graham, E. S.; Unsworth, C. P.

2018-06-01

Objective. Recent literature suggests that astrocytes form organized functional networks and communicate through transient changes in cytosolic Ca2+. Traditional techniques to investigate network activity, such as pharmacological blocking or genetic knockout, are difficult to restrict to individual cells. The objective of this work is to develop cell-patterning techniques to physically manipulate astrocytic interactions to enable the study of Ca2+ in astrocytic networks. Approach. We investigate how an in vitro cell-patterning platform that utilizes geometric patterns of parylene-C on SiO2 can be used to physically isolate single astrocytes and small astrocytic networks. Main results. We report that single astrocytes are effectively isolated on 75  ×  75 µm square parylene nodes, whereas multi-cellular astrocytic networks are isolated on larger nodes, with the mean number of astrocytes per cluster increasing as a function of node size. Additionally, we report that astrocytes in small multi-cellular clusters exhibit spatio-temporal clustering of Ca2+ transients. Finally, we report that the frequency and regularity of Ca2+ transients was positively correlated with astrocyte connectivity. Significance. The significance of this work is to demonstrate how patterning hNT astrocytes replicates spatio-temporal clustering of Ca2+ signalling that is observed in vivo but not in dissociated in vitro cultures. We therefore highlight the importance of the structure of astrocytic networks in determining ensemble Ca2+ behaviour.

Spatial and temporal patterns in preterm birth in the United States.

PubMed

Byrnes, John; Mahoney, Richard; Quaintance, Cele; Gould, Jeffrey B; Carmichael, Suzan; Shaw, Gary M; Showen, Amy; Phibbs, Ciaran; Stevenson, David K; Wise, Paul H

2015-06-01

Despite years of research, the etiologies of preterm birth remain unclear. In order to help generate new research hypotheses, this study explored spatial and temporal patterns of preterm birth in a large, total-population dataset. Data on 145 million US births in 3,000 counties from the Natality Files of the National Center for Health Statistics for 1971-2011 were examined. State trends in early (<34 wk) and late (34-36 wk) preterm birth rates were compared. K-means cluster analyses were conducted to identify gestational age distribution patterns for all US counties over time. A weak association was observed between state trends in <34 wk birth rates and the initial absolute <34 wk birth rate. Significant associations were observed between trends in <34 wk and 34-36 wk birth rates and between white and African American <34 wk births. Periodicity was observed in county-level trends in <34 wk birth rates. Cluster analyses identified periods of significant heterogeneity and homogeneity in gestational age distributional trends for US counties. The observed geographic and temporal patterns suggest periodicity and complex, shared influences among preterm birth rates in the United States. These patterns could provide insight into promising hypotheses for further research.

Temporal features of word-initial /s/+stop clusters in bilingual Mandarin-English children and monolingual English children and adults.

PubMed

Yang, Jing

2018-03-01

This study investigated the durational features of English word-initial /s/+stop clusters produced by bilingual Mandarin (L1)-English (L2) children and monolingual English children and adults. The participants included two groups of five- to six-year-old bilingual children: low proficiency in the L2 (Bi-low) and high proficiency in the L2 (Bi-high), one group of age-matched English children, and one group of English adults. Each participant produced a list of English words containing /sp, st, sk/ at the word-initial position followed by /a, i, u/, respectively. The absolute durations of the clusters and cluster elements and the durational proportions of elements to the overall cluster were measured. The results revealed that Bi-high children behaved similarly to the English monolinguals whereas Bi-low children used a different strategy of temporal organization to coordinate the cluster components in comparison to the English monolinguals and Bi-high children. The influence of language experience and continuing development of temporal features in children were discussed.

Hierarchical organization in the temporal structure of infant-direct speech and song.

PubMed

Falk, Simone; Kello, Christopher T

2017-06-01

Caregivers alter the temporal structure of their utterances when talking and singing to infants compared with adult communication. The present study tested whether temporal variability in infant-directed registers serves to emphasize the hierarchical temporal structure of speech. Fifteen German-speaking mothers sang a play song and told a story to their 6-months-old infants, or to an adult. Recordings were analyzed using a recently developed method that determines the degree of nested clustering of temporal events in speech. Events were defined as peaks in the amplitude envelope, and clusters of various sizes related to periods of acoustic speech energy at varying timescales. Infant-directed speech and song clearly showed greater event clustering compared with adult-directed registers, at multiple timescales of hundreds of milliseconds to tens of seconds. We discuss the relation of this newly discovered acoustic property to temporal variability in linguistic units and its potential implications for parent-infant communication and infants learning the hierarchical structures of speech and language. Copyright © 2017 Elsevier B.V. All rights reserved.

Wavelet-based clustering of resting state MRI data in the rat.

PubMed

Medda, Alessio; Hoffmann, Lukas; Magnuson, Matthew; Thompson, Garth; Pan, Wen-Ju; Keilholz, Shella

2016-01-01

While functional connectivity has typically been calculated over the entire length of the scan (5-10min), interest has been growing in dynamic analysis methods that can detect changes in connectivity on the order of cognitive processes (seconds). Previous work with sliding window correlation has shown that changes in functional connectivity can be observed on these time scales in the awake human and in anesthetized animals. This exciting advance creates a need for improved approaches to characterize dynamic functional networks in the brain. Previous studies were performed using sliding window analysis on regions of interest defined based on anatomy or obtained from traditional steady-state analysis methods. The parcellation of the brain may therefore be suboptimal, and the characteristics of the time-varying connectivity between regions are dependent upon the length of the sliding window chosen. This manuscript describes an algorithm based on wavelet decomposition that allows data-driven clustering of voxels into functional regions based on temporal and spectral properties. Previous work has shown that different networks have characteristic frequency fingerprints, and the use of wavelets ensures that both the frequency and the timing of the BOLD fluctuations are considered during the clustering process. The method was applied to resting state data acquired from anesthetized rats, and the resulting clusters agreed well with known anatomical areas. Clusters were highly reproducible across subjects. Wavelet cross-correlation values between clusters from a single scan were significantly higher than the values from randomly matched clusters that shared no temporal information, indicating that wavelet-based analysis is sensitive to the relationship between areas. Copyright © 2015 Elsevier Inc. All rights reserved.

Modeling the Movement of Homicide by Type to Inform Public Health Prevention Efforts.

PubMed

Zeoli, April M; Grady, Sue; Pizarro, Jesenia M; Melde, Chris

2015-10-01

We modeled the spatiotemporal movement of hotspot clusters of homicide by motive in Newark, New Jersey, to investigate whether different homicide types have different patterns of clustering and movement. We obtained homicide data from the Newark Police Department Homicide Unit's investigative files from 1997 through 2007 (n = 560). We geocoded the address at which each homicide victim was found and recorded the date of and the motive for the homicide. We used cluster detection software to model the spatiotemporal movement of statistically significant homicide clusters by motive, using census tract and month of occurrence as the spatial and temporal units of analysis. Gang-motivated homicides showed evidence of clustering and diffusion through Newark. Additionally, gang-motivated homicide clusters overlapped to a degree with revenge and drug-motivated homicide clusters. Escalating dispute and nonintimate familial homicides clustered; however, there was no evidence of diffusion. Intimate partner and robbery homicides did not cluster. By tracking how homicide types diffuse through communities and determining which places have ongoing or emerging homicide problems by type, we can better inform the deployment of prevention and intervention efforts.

Impaired cerebral blood flow networks in temporal lobe epilepsy with hippocampal sclerosis: A graph theoretical approach.

PubMed

Sone, Daichi; Matsuda, Hiroshi; Ota, Miho; Maikusa, Norihide; Kimura, Yukio; Sumida, Kaoru; Yokoyama, Kota; Imabayashi, Etsuko; Watanabe, Masako; Watanabe, Yutaka; Okazaki, Mitsutoshi; Sato, Noriko

2016-09-01

Graph theory is an emerging method to investigate brain networks. Altered cerebral blood flow (CBF) has frequently been reported in temporal lobe epilepsy (TLE), but graph theoretical findings of CBF are poorly understood. Here, we explored graph theoretical networks of CBF in TLE using arterial spin labeling imaging. We recruited patients with TLE and unilateral hippocampal sclerosis (HS) (19 patients with left TLE, and 21 with right TLE) and 20 gender- and age-matched healthy control subjects. We obtained all participants' CBF maps using pseudo-continuous arterial spin labeling and analyzed them using the Graph Analysis Toolbox (GAT) software program. As a result, compared to the controls, the patients with left TLE showed a significantly low clustering coefficient (p=0.024), local efficiency (p=0.001), global efficiency (p=0.010), and high transitivity (p=0.015), whereas the patients with right TLE showed significantly high assortativity (p=0.046) and transitivity (p=0.011). The group with right TLE also had high characteristic path length values (p=0.085), low global efficiency (p=0.078), and low resilience to targeted attack (p=0.101) at a trend level. Lower normalized clustering coefficient (p=0.081) in the left TLE and higher normalized characteristic path length (p=0.089) in the right TLE were found also at a trend level. Both the patients with left and right TLE showed significantly decreased clustering in similar areas, i.e., the cingulate gyri, precuneus, and occipital lobe. Our findings revealed differing left-right network metrics in which an inefficient CBF network in left TLE and vulnerability to irritation in right TLE are suggested. The left-right common finding of regional decreased clustering might reflect impaired default-mode networks in TLE. Copyright © 2016 Elsevier Inc. All rights reserved.

Spatiotemporal analysis of the agricultural drought risk in Heilongjiang Province, China

NASA Astrophysics Data System (ADS)

Pei, Wei; Fu, Qiang; Liu, Dong; Li, Tian-xiao; Cheng, Kun; Cui, Song

2017-06-01

Droughts are natural disasters that pose significant threats to agricultural production as well as living conditions, and a spatial-temporal difference analysis of agricultural drought risk can help determine the spatial distribution and temporal variation of the drought risk within a region. Moreover, this type of analysis can provide a theoretical basis for the identification, prevention, and mitigation of drought disasters. In this study, the overall dispersion and local aggregation of projection points were based on research by Friedman and Tukey (IEEE Trans on Computer 23:881-890, 1974). In this work, high-dimensional samples were clustered by cluster analysis. The clustering results were represented by the clustering matrix, which determined the local density in the projection index. This method avoids the problem of determining a cutoff radius. An improved projection pursuit model is proposed that combines cluster analysis and the projection pursuit model, which offer advantages for classification and assessment, respectively. The improved model was applied to analyze the agricultural drought risk of 13 cities in Heilongjiang Province over 6 years (2004, 2006, 2008, 2010, 2012, and 2014). The risk of an agricultural drought disaster was characterized by 14 indicators and the following four aspects: hazard, exposure, sensitivity, and resistance capacity. The spatial distribution and temporal variation characteristics of the agricultural drought risk in Heilongjiang Province were analyzed. The spatial distribution results indicated that Suihua, Qigihar, Daqing, Harbin, and Jiamusi are located in high-risk areas, Daxing'anling and Yichun are located in low-risk areas, and the differences among the regions were primarily caused by the aspects exposure and resistance capacity. The temporal variation results indicated that the risk of agricultural drought in most areas presented an initially increasing and then decreasing trend. A higher value for the exposure aspect increased the risk of drought, whereas a higher value for the resistance capacity aspect reduced the risk of drought. Over the long term, the exposure level of the region presented limited increases, whereas the resistance capacity presented considerable increases. Therefore, the risk of agricultural drought in Heilongjiang Province will continue to exhibit a decreasing trend.

Temporal and spatial distribution characteristics in the natural plague foci of Chinese Mongolian gerbils based on spatial autocorrelation.

PubMed

Du, Hai-Wen; Wang, Yong; Zhuang, Da-Fang; Jiang, Xiao-San

2017-08-07

The nest flea index of Meriones unguiculatus is a critical indicator for the prevention and control of plague, which can be used not only to detect the spatial and temporal distributions of Meriones unguiculatus, but also to reveal its cluster rule. This research detected the temporal and spatial distribution characteristics of the plague natural foci of Mongolian gerbils by body flea index from 2005 to 2014, in order to predict plague outbreaks. Global spatial autocorrelation was used to describe the entire spatial distribution pattern of the body flea index in the natural plague foci of typical Chinese Mongolian gerbils. Cluster and outlier analysis and hot spot analysis were also used to detect the intensity of clusters based on geographic information system methods. The quantity of M. unguiculatus nest fleas in the sentinel surveillance sites from 2005 to 2014 and host density data of the study area from 2005 to 2010 used in this study were provided by Chinese Center for Disease Control and Prevention. The epidemic focus regions of the Mongolian gerbils remain the same as the hot spot regions relating to the body flea index. High clustering areas possess a similar pattern as the distribution pattern of the body flea index indicating that the transmission risk of plague is relatively high. In terms of time series, the area of the epidemic focus gradually increased from 2005 to 2007, declined rapidly in 2008 and 2009, and then decreased slowly and began trending towards stability from 2009 to 2014. For the spatial change, the epidemic focus regions began moving northward from the southwest epidemic focus of the Mongolian gerbils from 2005 to 2007, and then moved from north to south in 2007 and 2008. The body flea index of Chinese gerbil foci reveals significant spatial and temporal aggregation characteristics through the employing of spatial autocorrelation. The diversity of temporary and spatial distribution is mainly affected by seasonal variation, the human activity and natural factors.

Spatio-temporal Analysis of African Swine Fever in Sardinia (2012-2014): Trends in Domestic Pigs and Wild Boar.

PubMed

Iglesias, I; Rodríguez, A; Feliziani, F; Rolesu, S; de la Torre, A

2017-04-01

African swine fever (ASF) is a notifiable viral disease affecting domestic pigs and wild boars that has been endemic in Sardinia since 1978. Several risk factors complicate the control of ASF in Sardinia: generally poor level of biosecurity, traditional breeding practices, illegal behaviour in movements and feeding of pigs, and sporadic occurrence of long-term carriers. A previous study describes the disease in Sardinia during 1978-2013. The aim of this study was to gain more in-depth knowledge of the spatio-temporal pattern of ASF in Sardinia during 2012 to May 2014, comparing patterns of occurrence in domestic pigs and wild boar and identifying areas of local transmission. African swine fever notifications were studied considering seasonality, spatial autocorrelation, spatial point pattern and spatio-temporal clusters. Results showed differences in temporal and spatial pattern of wild boar and domestic pig notifications. The peak in wild boar notifications (October 2013 to February 2014) occurred six months after than in domestic pig (May to early summer 2013). Notifications of cases in both host species tended to be clustered, with a maximum significant distance of spatial association of 15 and 25 km in domestic pigs and wild boars, respectively. Five clusters for local ASF transmission were identified for domestic pigs, with a mean radius and duration of 4 km (3-9 km) and 38 days (6-55 days), respectively. Any wild boar clusters were found. The apparently secondary role of wild boar in ASF spread in Sardinia could be explained by certain socio-economic factors (illegal free-range pig breeding or the mingling of herds. The lack of effectiveness of previous surveillance and control programmes reveals the necessity of employing a new approach). Results present here provide better knowledge of the dynamics of ASF in Sardinia, which could be used in a more comprehensive risk analysis necessary to introduce a new approach in the eradication strategy. © 2015 Blackwell Verlag GmbH.

Spatial and temporal clustering of dengue virus transmission in Thai villages.

PubMed

Mammen, Mammen P; Pimgate, Chusak; Koenraadt, Constantianus J M; Rothman, Alan L; Aldstadt, Jared; Nisalak, Ananda; Jarman, Richard G; Jones, James W; Srikiatkhachorn, Anon; Ypil-Butac, Charity Ann; Getis, Arthur; Thammapalo, Suwich; Morrison, Amy C; Libraty, Daniel H; Green, Sharone; Scott, Thomas W

2008-11-04

Transmission of dengue viruses (DENV), the leading cause of arboviral disease worldwide, is known to vary through time and space, likely owing to a combination of factors related to the human host, virus, mosquito vector, and environment. An improved understanding of variation in transmission patterns is fundamental to conducting surveillance and implementing disease prevention strategies. To test the hypothesis that DENV transmission is spatially and temporally focal, we compared geographic and temporal characteristics within Thai villages where DENV are and are not being actively transmitted. Cluster investigations were conducted within 100 m of homes where febrile index children with (positive clusters) and without (negative clusters) acute dengue lived during two seasons of peak DENV transmission. Data on human infection and mosquito infection/density were examined to precisely (1) define the spatial and temporal dimensions of DENV transmission, (2) correlate these factors with variation in DENV transmission, and (3) determine the burden of inapparent and symptomatic infections. Among 556 village children enrolled as neighbors of 12 dengue-positive and 22 dengue-negative index cases, all 27 DENV infections (4.9% of enrollees) occurred in positive clusters (p < 0.01; attributable risk [AR] = 10.4 per 100; 95% confidence interval 1-19.8 per 100]. In positive clusters, 12.4% of enrollees became infected in a 15-d period and DENV infections were aggregated centrally near homes of index cases. As only 1 of 217 pairs of serologic specimens tested in positive clusters revealed a recent DENV infection that occurred prior to cluster initiation, we attribute the observed DENV transmission subsequent to cluster investigation to recent DENV transmission activity. Of the 1,022 female adult Ae. aegypti collected, all eight (0.8%) dengue-infected mosquitoes came from houses in positive clusters; none from control clusters or schools. Distinguishing features between positive and negative clusters were greater availability of piped water in negative clusters (p < 0.01) and greater number of Ae. aegypti pupae per person in positive clusters (p = 0.04). During primarily DENV-4 transmission seasons, the ratio of inapparent to symptomatic infections was nearly 1:1 among child enrollees. Study limitations included inability to sample all children and mosquitoes within each cluster and our reliance on serologic rather than virologic evidence of interval infections in enrollees given restrictions on the frequency of blood collections in children. Our data reveal the remarkably focal nature of DENV transmission within a hyperendemic rural area of Thailand. These data suggest that active school-based dengue case detection prompting local spraying could contain recent virus introductions and reduce the longitudinal risk of virus spread within rural areas. Our results should prompt future cluster studies to explore how host immune and behavioral aspects may impact DENV transmission and prevention strategies. Cluster methodology could serve as a useful research tool for investigation of other temporally and spatially clustered infectious diseases.

Spatial and Temporal Clustering of Dengue Virus Transmission in Thai Villages

PubMed Central

Mammen, Mammen P; Pimgate, Chusak; Koenraadt, Constantianus J. M; Rothman, Alan L; Aldstadt, Jared; Nisalak, Ananda; Jarman, Richard G; Jones, James W; Srikiatkhachorn, Anon; Ypil-Butac, Charity Ann; Getis, Arthur; Thammapalo, Suwich; Morrison, Amy C; Libraty, Daniel H; Green, Sharone; Scott, Thomas W

2008-01-01

Background Transmission of dengue viruses (DENV), the leading cause of arboviral disease worldwide, is known to vary through time and space, likely owing to a combination of factors related to the human host, virus, mosquito vector, and environment. An improved understanding of variation in transmission patterns is fundamental to conducting surveillance and implementing disease prevention strategies. To test the hypothesis that DENV transmission is spatially and temporally focal, we compared geographic and temporal characteristics within Thai villages where DENV are and are not being actively transmitted. Methods and Findings Cluster investigations were conducted within 100 m of homes where febrile index children with (positive clusters) and without (negative clusters) acute dengue lived during two seasons of peak DENV transmission. Data on human infection and mosquito infection/density were examined to precisely (1) define the spatial and temporal dimensions of DENV transmission, (2) correlate these factors with variation in DENV transmission, and (3) determine the burden of inapparent and symptomatic infections. Among 556 village children enrolled as neighbors of 12 dengue-positive and 22 dengue-negative index cases, all 27 DENV infections (4.9% of enrollees) occurred in positive clusters (p < 0.01; attributable risk [AR] = 10.4 per 100; 95% confidence interval 1–19.8 per 100]. In positive clusters, 12.4% of enrollees became infected in a 15-d period and DENV infections were aggregated centrally near homes of index cases. As only 1 of 217 pairs of serologic specimens tested in positive clusters revealed a recent DENV infection that occurred prior to cluster initiation, we attribute the observed DENV transmission subsequent to cluster investigation to recent DENV transmission activity. Of the 1,022 female adult Ae. aegypti collected, all eight (0.8%) dengue-infected mosquitoes came from houses in positive clusters; none from control clusters or schools. Distinguishing features between positive and negative clusters were greater availability of piped water in negative clusters (p < 0.01) and greater number of Ae. aegypti pupae per person in positive clusters (p = 0.04). During primarily DENV-4 transmission seasons, the ratio of inapparent to symptomatic infections was nearly 1:1 among child enrollees. Study limitations included inability to sample all children and mosquitoes within each cluster and our reliance on serologic rather than virologic evidence of interval infections in enrollees given restrictions on the frequency of blood collections in children. Conclusions Our data reveal the remarkably focal nature of DENV transmission within a hyperendemic rural area of Thailand. These data suggest that active school-based dengue case detection prompting local spraying could contain recent virus introductions and reduce the longitudinal risk of virus spread within rural areas. Our results should prompt future cluster studies to explore how host immune and behavioral aspects may impact DENV transmission and prevention strategies. Cluster methodology could serve as a useful research tool for investigation of other temporally and spatially clustered infectious diseases. PMID:18986209

A Model-Based Analysis of Chemical and Temporal Patterns of Cuticular Hydrocarbons in Male Drosophila melanogaster

PubMed Central

Kent, Clement; Azanchi, Reza; Smith, Ben; Chu, Adrienne; Levine, Joel

2007-01-01

Drosophila Cuticular Hydrocarbons (CH) influence courtship behaviour, mating, aggregation, oviposition, and resistance to desiccation. We measured levels of 24 different CH compounds of individual male D. melanogaster hourly under a variety of environmental (LD/DD) conditions. Using a model-based analysis of CH variation, we developed an improved normalization method for CH data, and show that CH compounds have reproducible cyclic within-day temporal patterns of expression which differ between LD and DD conditions. Multivariate clustering of expression patterns identified 5 clusters of co-expressed compounds with common chemical characteristics. Turnover rate estimates suggest CH production may be a significant metabolic cost. Male cuticular hydrocarbon expression is a dynamic trait influenced by light and time of day; since abundant hydrocarbons affect male sexual behavior, males may present different pheromonal profiles at different times and under different conditions. PMID:17896002

Characterizing the Temporal and Spatial Distribution of Earthquake Swarms in the Puerto Rico - Virgin Island Block

NASA Astrophysics Data System (ADS)

Hernandez, F. J.; Lopez, A. M.; Vanacore, E. A.

2017-12-01

The presence of earthquake swarms and clusters in the north and northeast of the island of Puerto Rico in the northeastern Caribbean have been recorded by the Puerto Rico Seismic Network (PRSN) since it started operations in 1974. Although clusters in the Puerto Rico-Virgin Island (PRVI) block have been observed for over forty years, the nature of their enigmatic occurrence is still poorly understood. In this study, the entire seismic catalog of the PRSN, of approximately 31,000 seismic events, has been limited to a sub-set of 18,000 events located all along north of Puerto Rico in an effort to characterize and understand the underlying mechanism of these clusters. This research uses two de-clustering methods to identify cluster events in the PRVI block. The first method, known as Model Independent Stochastic Declustering (MISD), filters the catalog sub-set into cluster and background seismic events, while the second method uses a spatio-temporal algorithm applied to the catalog in order to link the separate seismic events into clusters. After using these two methods, identified clusters were classified into either earthquake swarms or seismic sequences. Once identified, each cluster was analyzed to identify correlations against other clusters in their geographic region. Results from this research seek to : (1) unravel their earthquake clustering behavior through the use of different statistical methods and (2) better understand the mechanism for these clustering of earthquakes. Preliminary results have allowed to identify and classify 128 clusters categorized in 11 distinctive regions based on their centers, and their spatio-temporal distribution have been used to determine intra- and interplate dynamics.

Changes of the time-varying percentiles of daily extreme temperature in China

NASA Astrophysics Data System (ADS)

Li, Bin; Chen, Fang; Xu, Feng; Wang, Xinrui

2017-11-01

Identifying the air temperature frequency distributions and evaluating the trends in time-varying percentiles are very important for climate change studies. In order to get a better understanding of the recent temporal and spatial pattern of the temperature changes in China, we have calculated the trends in temporal-varying percentiles of the daily extreme air temperature firstly. Then we divide all the stations to get the spatial patterns for the percentile trends using the average linkage cluster analysis method. To make a comparison, the shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 are also examined. Important results in three aspects have been achieved: (1) In terms of the trends in temporal-varying percentiles of the daily extreme air temperature, the most intense warming for daily maximum air temperature (Tmax) was detected in the upper percentiles with a significant increasing tendency magnitude (>2.5 °C/50year), and the greatest warming for daily minimum air temperature (Tmin) occurred with very strong trends exceeding 4 °C/50year. (2) The relative coherent spatial patterns for the percentile trends were found, and stations for the whole country had been divided into three clusters. The three primary clusters were distributed regularly to some extent from north to south, indicating the possible large influence of the latitude. (3) The most significant shifts of trends percentile frequency distribution from 1961-1985 to 1986-2010 was found in Tmax. More than half part of the frequency distribution show negative trends less than -0.5 °C/50year in 1961-1985, while showing trends less than 2.5 °C/50year in 1986-2010.

Suicide Clusters: A Review of Risk Factors and Mechanisms

ERIC Educational Resources Information Center

Haw, Camilla; Hawton, Keith; Niedzwiedz, Claire; Platt, Steve

2013-01-01

Suicide clusters, although uncommon, cause great concern in the communities in which they occur. We searched the world literature on suicide clusters and describe the risk factors and proposed psychological mechanisms underlying the spatio-temporal clustering of suicides (point clusters). Potential risk factors include male gender, being an…

Comparison of Salmonella enteritidis phage types isolated from layers and humans in Belgium in 2005.

PubMed

Welby, Sarah; Imberechts, Hein; Riocreux, Flavien; Bertrand, Sophie; Dierick, Katelijne; Wildemauwe, Christa; Hooyberghs, Jozef; Van der Stede, Yves

2011-08-01

The aim of this study was to investigate the available results for Belgium of the European Union coordinated monitoring program (2004/665 EC) on Salmonella in layers in 2005, as well as the results of the monthly outbreak reports of Salmonella Enteritidis in humans in 2005 to identify a possible statistical significant trend in both populations. Separate descriptive statistics and univariate analysis were carried out and the parametric and/or non-parametric hypothesis tests were conducted. A time cluster analysis was performed for all Salmonella Enteritidis phage types (PTs) isolated. The proportions of each Salmonella Enteritidis PT in layers and in humans were compared and the monthly distribution of the most common PT, isolated in both populations, was evaluated. The time cluster analysis revealed significant clusters during the months May and June for layers and May, July, August, and September for humans. PT21, the most frequently isolated PT in both populations in 2005, seemed to be responsible of these significant clusters. PT4 was the second most frequently isolated PT. No significant difference was found for the monthly trend evolution of both PT in both populations based on parametric and non-parametric methods. A similar monthly trend of PT distribution in humans and layers during the year 2005 was observed. The time cluster analysis and the statistical significance testing confirmed these results. Moreover, the time cluster analysis showed significant clusters during the summer time and slightly delayed in time (humans after layers). These results suggest a common link between the prevalence of Salmonella Enteritidis in layers and the occurrence of the pathogen in humans. Phage typing was confirmed to be a useful tool for identifying temporal trends.

Retrospective space-time cluster analysis of whooping cough, re-emergence in Barcelona, Spain, 2000-2011.

PubMed

Solano, Rubén; Gómez-Barroso, Diana; Simón, Fernando; Lafuente, Sarah; Simón, Pere; Rius, Cristina; Gorrindo, Pilar; Toledo, Diana; Caylà, Joan A

2014-05-01

A retrospective, space-time study of whooping cough cases reported to the Public Health Agency of Barcelona, Spain between the years 2000 and 2011 is presented. It is based on 633 individual whooping cough cases and the 2006 population census from the Spanish National Statistics Institute, stratified by age and sex at the census tract level. Cluster identification was attempted using space-time scan statistic assuming a Poisson distribution and restricting temporal extent to 7 days and spatial distance to 500 m. Statistical calculations were performed with Stata 11 and SatScan and mapping was performed with ArcGis 10.0. Only clusters showing statistical significance (P <0.05) were mapped. The most likely cluster identified included five census tracts located in three neighbourhoods in central Barcelona during the week from 17 to 23 August 2011. This cluster included five cases compared with the expected level of 0.0021 (relative risk = 2436, P <0.001). In addition, 11 secondary significant space-time clusters were detected with secondary clusters occurring at different times and localizations. Spatial statistics is felt to be useful by complementing epidemiological surveillance systems through visualizing excess in the number of cases in space and time and thus increase the possibility of identifying outbreaks not reported by the surveillance system.

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance

PubMed Central

Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy. PMID:29795600

Incremental fuzzy C medoids clustering of time series data using dynamic time warping distance.

PubMed

Liu, Yongli; Chen, Jingli; Wu, Shuai; Liu, Zhizhong; Chao, Hao

2018-01-01

Clustering time series data is of great significance since it could extract meaningful statistics and other characteristics. Especially in biomedical engineering, outstanding clustering algorithms for time series may help improve the health level of people. Considering data scale and time shifts of time series, in this paper, we introduce two incremental fuzzy clustering algorithms based on a Dynamic Time Warping (DTW) distance. For recruiting Single-Pass and Online patterns, our algorithms could handle large-scale time series data by splitting it into a set of chunks which are processed sequentially. Besides, our algorithms select DTW to measure distance of pair-wise time series and encourage higher clustering accuracy because DTW could determine an optimal match between any two time series by stretching or compressing segments of temporal data. Our new algorithms are compared to some existing prominent incremental fuzzy clustering algorithms on 12 benchmark time series datasets. The experimental results show that the proposed approaches could yield high quality clusters and were better than all the competitors in terms of clustering accuracy.

Application of Geostatistical Methods and Machine Learning for spatio-temporal Earthquake Cluster Analysis

NASA Astrophysics Data System (ADS)

Schaefer, A. M.; Daniell, J. E.; Wenzel, F.

2014-12-01

Earthquake clustering tends to be an increasingly important part of general earthquake research especially in terms of seismic hazard assessment and earthquake forecasting and prediction approaches. The distinct identification and definition of foreshocks, aftershocks, mainshocks and secondary mainshocks is taken into account using a point based spatio-temporal clustering algorithm originating from the field of classic machine learning. This can be further applied for declustering purposes to separate background seismicity from triggered seismicity. The results are interpreted and processed to assemble 3D-(x,y,t) earthquake clustering maps which are based on smoothed seismicity records in space and time. In addition, multi-dimensional Gaussian functions are used to capture clustering parameters for spatial distribution and dominant orientations. Clusters are further processed using methodologies originating from geostatistics, which have been mostly applied and developed in mining projects during the last decades. A 2.5D variogram analysis is applied to identify spatio-temporal homogeneity in terms of earthquake density and energy output. The results are mitigated using Kriging to provide an accurate mapping solution for clustering features. As a case study, seismic data of New Zealand and the United States is used, covering events since the 1950s, from which an earthquake cluster catalogue is assembled for most of the major events, including a detailed analysis of the Landers and Christchurch sequences.

Pattern recognition approach to the subsequent event of damaging earthquakes in Italy

NASA Astrophysics Data System (ADS)

Gentili, S.; Di Giovambattista, R.

2017-05-01

In this study, we investigate the occurrence of large aftershocks following the most significant earthquakes that occurred in Italy after 1980. In accordance with previous studies (Vorobieva and Panza, 1993; Vorobieva, 1999), we group clusters associated with mainshocks into two categories: ;type A; if, given a main shock of magnitude M, the subsequent strongest earthquake in the cluster has magnitude ≥M - 1 or type B otherwise. In this paper, we apply a pattern recognition approach using statistical features to foresee the class of the analysed clusters. The classification of the two categories is based on some features of the time, space, and magnitude distribution of the aftershocks. Specifically, we analyse the temporal evolution of the radiated energy at different elapsed times after the mainshock, the spatio-temporal evolution of the aftershocks occurring within a few days, and the probability of a strong earthquake. An attempt is made to classify the studied region into smaller seismic zones with a prevalence of type A and B clusters. We demonstrate that the two types of clusters have distinct preferred geographic locations inside the Italian territory that likely reflected key properties of the deforming regions, different crustal domains and faulting style. We use decision trees as classifiers of single features to characterize the features depending on the cluster type. The performance of the classification is tested by the Leave-One-Out method. The analysis is performed on different time-spans after the mainshock to simulate the dependence of the accuracy on the information available as data increased over a longer period with increasing time after the mainshock.

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015.

PubMed

Larsen, David A; Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009-2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted.

Spatio-temporal patterns of gun violence in Syracuse, New York 2009-2015

PubMed Central

Lane, Sandra; Jennings-Bey, Timothy; Haygood-El, Arnett; Brundage, Kim; Rubinstein, Robert A.

2017-01-01

Gun violence in the United States of America is a large public health problem that disproportionately affects urban areas. The epidemiology of gun violence reflects various aspects of an infectious disease including spatial and temporal clustering. We examined the spatial and temporal trends of gun violence in Syracuse, New York, a city of 145,000. We used a spatial scan statistic to reveal spatio-temporal clusters of gunshots investigated and corroborated by Syracuse City Police Department for the years 2009–2015. We also examined predictors of areas with increased gun violence using a multi-level zero-inflated Poisson regression with data from the 2010 census. Two space-time clusters of gun violence were revealed in the city. Higher rates of segregation, poverty and the summer months were all associated with increased risk of gun violence. Previous gunshots in the area were associated with a 26.8% increase in the risk of gun violence. Gun violence in Syracuse, NY is both spatially and temporally stable, with some neighborhoods of the city greatly afflicted. PMID:28319125

ClueNet: Clustering a temporal network based on topological similarity rather than denseness

PubMed Central

Milenković, Tijana

2018-01-01

Network clustering is a very popular topic in the network science field. Its goal is to divide (partition) the network into groups (clusters or communities) of “topologically related” nodes, where the resulting topology-based clusters are expected to “correlate” well with node label information, i.e., metadata, such as cellular functions of genes/proteins in biological networks, or age or gender of people in social networks. Even for static data, the problem of network clustering is complex. For dynamic data, the problem is even more complex, due to an additional dimension of the data—their temporal (evolving) nature. Since the problem is computationally intractable, heuristic approaches need to be sought. Existing approaches for dynamic network clustering (DNC) have drawbacks. First, they assume that nodes should be in the same cluster if they are densely interconnected within the network. We hypothesize that in some applications, it might be of interest to cluster nodes that are topologically similar to each other instead of or in addition to requiring the nodes to be densely interconnected. Second, they ignore temporal information in their early steps, and when they do consider this information later on, they do so implicitly. We hypothesize that capturing temporal information earlier in the clustering process and doing so explicitly will improve results. We test these two hypotheses via our new approach called ClueNet. We evaluate ClueNet against six existing DNC methods on both social networks capturing evolving interactions between individuals (such as interactions between students in a high school) and biological networks capturing interactions between biomolecules in the cell at different ages. We find that ClueNet is superior in over 83% of all evaluation tests. As more real-world dynamic data are becoming available, DNC and thus ClueNet will only continue to gain importance. PMID:29738568

Evaluating and implementing temporal, spatial, and spatio-temporal methods for outbreak detection in a local syndromic surveillance system

PubMed Central

Lall, Ramona; Levin-Rector, Alison; Sell, Jessica; Paladini, Marc; Konty, Kevin J.; Olson, Don; Weiss, Don

2017-01-01

The New York City Department of Health and Mental Hygiene has operated an emergency department syndromic surveillance system since 2001, using temporal and spatial scan statistics run on a daily basis for cluster detection. Since the system was originally implemented, a number of new methods have been proposed for use in cluster detection. We evaluated six temporal and four spatial/spatio-temporal detection methods using syndromic surveillance data spiked with simulated injections. The algorithms were compared on several metrics, including sensitivity, specificity, positive predictive value, coherence, and timeliness. We also evaluated each method’s implementation, programming time, run time, and the ease of use. Among the temporal methods, at a set specificity of 95%, a Holt-Winters exponential smoother performed the best, detecting 19% of the simulated injects across all shapes and sizes, followed by an autoregressive moving average model (16%), a generalized linear model (15%), a modified version of the Early Aberration Reporting System’s C2 algorithm (13%), a temporal scan statistic (11%), and a cumulative sum control chart (<2%). Of the spatial/spatio-temporal methods we tested, a spatial scan statistic detected 3% of all injects, a Bayes regression found 2%, and a generalized linear mixed model and a space-time permutation scan statistic detected none at a specificity of 95%. Positive predictive value was low (<7%) for all methods. Overall, the detection methods we tested did not perform well in identifying the temporal and spatial clusters of cases in the inject dataset. The spatial scan statistic, our current method for spatial cluster detection, performed slightly better than the other tested methods across different inject magnitudes and types. Furthermore, we found the scan statistics, as applied in the SaTScan software package, to be the easiest to program and implement for daily data analysis. PMID:28886112

Evaluating and implementing temporal, spatial, and spatio-temporal methods for outbreak detection in a local syndromic surveillance system.

PubMed

Mathes, Robert W; Lall, Ramona; Levin-Rector, Alison; Sell, Jessica; Paladini, Marc; Konty, Kevin J; Olson, Don; Weiss, Don

2017-01-01

The New York City Department of Health and Mental Hygiene has operated an emergency department syndromic surveillance system since 2001, using temporal and spatial scan statistics run on a daily basis for cluster detection. Since the system was originally implemented, a number of new methods have been proposed for use in cluster detection. We evaluated six temporal and four spatial/spatio-temporal detection methods using syndromic surveillance data spiked with simulated injections. The algorithms were compared on several metrics, including sensitivity, specificity, positive predictive value, coherence, and timeliness. We also evaluated each method's implementation, programming time, run time, and the ease of use. Among the temporal methods, at a set specificity of 95%, a Holt-Winters exponential smoother performed the best, detecting 19% of the simulated injects across all shapes and sizes, followed by an autoregressive moving average model (16%), a generalized linear model (15%), a modified version of the Early Aberration Reporting System's C2 algorithm (13%), a temporal scan statistic (11%), and a cumulative sum control chart (<2%). Of the spatial/spatio-temporal methods we tested, a spatial scan statistic detected 3% of all injects, a Bayes regression found 2%, and a generalized linear mixed model and a space-time permutation scan statistic detected none at a specificity of 95%. Positive predictive value was low (<7%) for all methods. Overall, the detection methods we tested did not perform well in identifying the temporal and spatial clusters of cases in the inject dataset. The spatial scan statistic, our current method for spatial cluster detection, performed slightly better than the other tested methods across different inject magnitudes and types. Furthermore, we found the scan statistics, as applied in the SaTScan software package, to be the easiest to program and implement for daily data analysis.

Spatio-temporal analysis of wildfire ignitions in the St. Johns River Water Management District, Florida

Treesearch

Marc G. Genton; David T. Butry; Marcia L. Gumpertz; Jeffrey P. Prestemon

2006-01-01

We analyse the spatio-temporal structure of wildfire ignitions in the St. Johns River Water Management District in north-eastern Florida. We show, using tools to analyse point patterns (e.g. the L-function), that wildfire events occur in clusters. Clustering of these events correlates with irregular distribution of fire ignitions, including lightning...

Association of GSK3beta polymorphisms with brain structural changes in major depressive disorder.

PubMed

Inkster, Becky; Nichols, Thomas E; Saemann, Philipp G; Auer, Dorothee P; Holsboer, Florian; Muglia, Pierandrea; Matthews, Paul M

2009-07-01

Indirect evidence suggests that the glycogen synthase kinase-3beta (GSK3beta) gene might be implicated in major depressive disorder (MDD). We evaluated 15 GSK3beta single-nucleotide polymorphisms (SNPs) to test for associations with regional gray matter (GM) volume differences in patients with recurrent MDD. We then used the defined regions of interest based on significant associations to test for MDD x genotype interactions by including a matched control group without any psychiatric disorder, including MDD. General linear model with nonstationary cluster-based inference. Munich, Germany. Patients with recurrent MDD (n = 134) and age-, sex-, and ethnicity-matched healthy controls (n = 143). Associations between GSK3beta polymorphisms and regional GM volume differences. Variation in GM volume was associated with GSK3beta polymorphisms; the most significant associations were found for rs6438552, a putative functional intronic SNP that showed 3 significant GM clusters in the right and left superior temporal gyri and the right hippocampus (P < .001, P = .02, and P = .02, respectively, corrected for multiple comparisons across the whole brain). Similar results were obtained with rs12630592, an SNP in high linkage disequilibrium. A significant SNP x MDD status interaction was observed for the effect on GM volumes in the right hippocampus and superior temporal gyri (P < .001 and P = .01, corrected, respectively). The GSK3beta gene may have a role in determining regional GM volume differences of the right hippocampus and bilateral superior temporal gyri. The association between genotype and brain structure was specific to the patients with MDD, suggesting that GSK3beta genotypes might interact with MDD status. We speculate that this is a consequence of regional neocortical, glial, or neuronal growth or survival. In considering core cognitive features of MDD, the association of GSK3beta polymorphisms with structural variation in the temporal lobe and hippocampus is of particular interest in the context of other evidence for structural and functional abnormalities in the hippocampi of patients with MDD.

VizieR Online Data Catalog: Star clusters distances and extinctions. II. (Buckner+, 2014)

NASA Astrophysics Data System (ADS)

Buckner, A. S. M.; Froebrich, D.

2015-04-01

Until now, it has been impossible to observationally measure how star cluster scaleheight evolves beyond 1Gyr as only small samples have been available. Here, we establish a novel method to determine the scaleheight of a cluster sample using modelled distributions and Kolmogorov-Smirnov tests. This allows us to determine the scaleheight with a 25% accuracy for samples of 38 clusters or more. We apply our method to investigate the temporal evolution of cluster scaleheight, using homogeneously selected sub-samples of Kharchenko et al. (MWSC, 2012, Cat. J/A+A/543/A156, 2013, J/A+A/558/A53 ), Dias et al. (DAML02, 2002A&A...389..871D, Cat. B/ocl), WEBDA, and Froebrich et al. (FSR, 2007MNRAS.374..399F, Cat. J/MNRAS/374/399). We identify a linear relationship between scaleheight and log(age/yr) of clusters, considerably different from field stars. The scaleheight increases from about 40pc at 1Myr to 75pc at 1Gyr, most likely due to internal evolution and external scattering events. After 1Gyr, there is a marked change of the behaviour, with the scaleheight linearly increasing with log(age/yr) to about 550pc at 3.5Gyr. The most likely interpretation is that the surviving clusters are only observable because they have been scattered away from the mid-plane in their past. A detailed understanding of this observational evidence can only be achieved with numerical simulations of the evolution of cluster samples in the Galactic disc. Furthermore, we find a weak trend of an age-independent increase in scaleheight with Galactocentric distance. There are no significant temporal or spatial variations of the cluster distribution zero-point. We determine the Sun's vertical displacement from the Galactic plane as Z⊙=18.5+/-1.2pc. (1 data file).

Modeling the Movement of Homicide by Type to Inform Public Health Prevention Efforts

PubMed Central

Grady, Sue; Pizarro, Jesenia M.; Melde, Chris

2015-01-01

Objectives. We modeled the spatiotemporal movement of hotspot clusters of homicide by motive in Newark, New Jersey, to investigate whether different homicide types have different patterns of clustering and movement. Methods. We obtained homicide data from the Newark Police Department Homicide Unit’s investigative files from 1997 through 2007 (n = 560). We geocoded the address at which each homicide victim was found and recorded the date of and the motive for the homicide. We used cluster detection software to model the spatiotemporal movement of statistically significant homicide clusters by motive, using census tract and month of occurrence as the spatial and temporal units of analysis. Results. Gang-motivated homicides showed evidence of clustering and diffusion through Newark. Additionally, gang-motivated homicide clusters overlapped to a degree with revenge and drug-motivated homicide clusters. Escalating dispute and nonintimate familial homicides clustered; however, there was no evidence of diffusion. Intimate partner and robbery homicides did not cluster. Conclusions. By tracking how homicide types diffuse through communities and determining which places have ongoing or emerging homicide problems by type, we can better inform the deployment of prevention and intervention efforts. PMID:26270315

Including foreshocks and aftershocks in time-independent probabilistic seismic hazard analyses

USGS Publications Warehouse

Boyd, Oliver S.

2012-01-01

Time‐independent probabilistic seismic‐hazard analysis treats each source as being temporally and spatially independent; hence foreshocks and aftershocks, which are both spatially and temporally dependent on the mainshock, are removed from earthquake catalogs. Yet, intuitively, these earthquakes should be considered part of the seismic hazard, capable of producing damaging ground motions. In this study, I consider the mainshock and its dependents as a time‐independent cluster, each cluster being temporally and spatially independent from any other. The cluster has a recurrence time of the mainshock; and, by considering the earthquakes in the cluster as a union of events, dependent events have an opportunity to contribute to seismic ground motions and hazard. Based on the methods of the U.S. Geological Survey for a high‐hazard site, the inclusion of dependent events causes ground motions that are exceeded at probability levels of engineering interest to increase by about 10% but could be as high as 20% if variations in aftershock productivity can be accounted for reliably.

Discovering shared segments on the migration route of the bar-headed goose by time-based plane-sweeping trajectory clustering

USGS Publications Warehouse

Luo, Ze; Baoping, Yan; Takekawa, John Y.; Prosser, Diann J.

2012-01-01

We propose a new method to help ornithologists and ecologists discover shared segments on the migratory pathway of the bar-headed geese by time-based plane-sweeping trajectory clustering. We present a density-based time parameterized line segment clustering algorithm, which extends traditional comparable clustering algorithms from temporal and spatial dimensions. We present a time-based plane-sweeping trajectory clustering algorithm to reveal the dynamic evolution of spatial-temporal object clusters and discover common motion patterns of bar-headed geese in the process of migration. Experiments are performed on GPS-based satellite telemetry data from bar-headed geese and results demonstrate our algorithms can correctly discover shared segments of the bar-headed geese migratory pathway. We also present findings on the migratory behavior of bar-headed geese determined from this new analytical approach.

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

Spatial-temporal clustering of tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2016-12-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Spatial-Temporal Clustering of Tornadoes

NASA Astrophysics Data System (ADS)

Malamud, Bruce D.; Turcotte, Donald L.; Brooks, Harold E.

2017-04-01

The standard measure of the intensity of a tornado is the Enhanced Fujita scale, which is based qualitatively on the damage caused by a tornado. An alternative measure of tornado intensity is the tornado path length, L. Here we examine the spatial-temporal clustering of severe tornadoes, which we define as having path lengths L ≥ 10 km. Of particular concern are tornado outbreaks, when a large number of severe tornadoes occur in a day in a restricted region. We apply a spatial-temporal clustering analysis developed for earthquakes. We take all pairs of severe tornadoes in observed and modelled outbreaks, and for each pair plot the spatial lag (distance between touchdown points) against the temporal lag (time between touchdown points). We apply our spatial-temporal lag methodology to the intense tornado outbreaks in the central United States on 26 and 27 April 2011, which resulted in over 300 fatalities and produced 109 severe (L ≥ 10 km) tornadoes. The patterns of spatial-temporal lag correlations that we obtain for the 2 days are strikingly different. On 26 April 2011, there were 45 severe tornadoes and our clustering analysis is dominated by a complex sequence of linear features. We associate the linear patterns with the tornadoes generated in either a single cell thunderstorm or a closely spaced cluster of single cell thunderstorms moving at a near-constant velocity. Our study of a derecho tornado outbreak of six severe tornadoes on 4 April 2011 along with modelled outbreak scenarios confirms this association. On 27 April 2011, there were 64 severe tornadoes and our clustering analysis is predominantly random with virtually no embedded linear patterns. We associate this pattern with a large number of interacting supercell thunderstorms generating tornadoes randomly in space and time. In order to better understand these associations, we also applied our approach to the Great Plains tornado outbreak of 3 May 1999. Careful studies by others have associated individual tornadoes with specified supercell thunderstorms. Our analysis of the 3 May 1999 tornado outbreak directly associated linear features in the largely random spatial-temporal analysis with several supercell thunderstorms, which we then confirmed using model scenarios of synthetic tornado outbreaks. We suggest that it may be possible to develop a semi-automated modelling of tornado touchdowns to match the type of observations made on the 3 May 1999 outbreak.

Frontal and temporal lobe involvement on verbal fluency measures in amyotrophic lateral sclerosis.

PubMed

Lepow, Lauren; Van Sweringen, James; Strutt, Adriana M; Jawaid, Ali; MacAdam, Claire; Harati, Yadollah; Schulz, Paul E; York, Michele K

2010-11-01

Amyotrophic lateral sclerosis (ALS) has been associated with changes in frontal and temporal lobe-mediated cognitive and behavioral functions. Verbal fluency, a sensitive measure to these changes, was utilized to investigate phonemic and semantic abilities in 49 ALS patients and 25 healthy controls (HCs). A subset of the ALS patients was classified as ALS-intact, ALS with mild cognitive impairments (ALS-mild), and ALS with fronto-temporal dementia (ALS-FTD) based on a comprehensive neuropsychological evaluation. Clustering and switching, the underlying component processes of verbal fluency, were analyzed using Troyer's (Troyer, Moscovitch, & Winocur, 1997) and Abwender's (Abwender, Swan, Bowerman, & Connolly, 2001) scoring systems. ALS patients exhibited decreased fluency versus HCs. For phonemic fluency, the intact ALS sample generated fewer clusters and more switches than the ALS-mild and ALS-FTD patients using both scoring systems. This suggests temporal involvement in ALS patients, with increasing frontal lobe involvement in patients with greater cognitive dysfunction. For semantic fluency, similar results were obtained with a greater emphasis on declines in clustering or increased temporal lobe dysfunction. These results suggest that verbal fluency measures identify frontal and temporal lobe involvement in the cognitive decline associated with ALS, particularly when the component processes are evaluated. The clinical utility of these scoring systems with ALS patients is also discussed.

Distinct anatomical subtypes of the behavioural variant of frontotemporal dementia: a cluster analysis study.

PubMed

Whitwell, Jennifer L; Przybelski, Scott A; Weigand, Stephen D; Ivnik, Robert J; Vemuri, Prashanthi; Gunter, Jeffrey L; Senjem, Matthew L; Shiung, Maria M; Boeve, Bradley F; Knopman, David S; Parisi, Joseph E; Dickson, Dennis W; Petersen, Ronald C; Jack, Clifford R; Josephs, Keith A

2009-11-01

The behavioural variant of frontotemporal dementia is a progressive neurodegenerative syndrome characterized by changes in personality and behaviour. It is typically associated with frontal lobe atrophy, although patterns of atrophy are heterogeneous. The objective of this study was to examine case-by-case variability in patterns of grey matter atrophy in subjects with the behavioural variant of frontotemporal dementia and to investigate whether behavioural variant of frontotemporal dementia can be divided into distinct anatomical subtypes. Sixty-six subjects that fulfilled clinical criteria for a diagnosis of the behavioural variant of frontotemporal dementia with a volumetric magnetic resonance imaging scan were identified. Grey matter volumes were obtained for 26 regions of interest, covering frontal, temporal and parietal lobes, striatum, insula and supplemental motor area, using the automated anatomical labelling atlas. Regional volumes were divided by total grey matter volume. A hierarchical agglomerative cluster analysis using Ward's clustering linkage method was performed to cluster the behavioural variant of frontotemporal dementia subjects into different anatomical clusters. Voxel-based morphometry was used to assess patterns of grey matter loss in each identified cluster of subjects compared to an age and gender-matched control group at P < 0.05 (family-wise error corrected). We identified four potentially useful clusters with distinct patterns of grey matter loss, which we posit represent anatomical subtypes of the behavioural variant of frontotemporal dementia. Two of these subtypes were associated with temporal lobe volume loss, with one subtype showing loss restricted to temporal lobe regions (temporal-dominant subtype) and the other showing grey matter loss in the temporal lobes as well as frontal and parietal lobes (temporofrontoparietal subtype). Another two subtypes were characterized by a large amount of frontal lobe volume loss, with one subtype showing grey matter loss in the frontal lobes as well as loss of the temporal lobes (frontotemporal subtype) and the other subtype showing loss relatively restricted to the frontal lobes (frontal-dominant subtype). These four subtypes differed on clinical measures of executive function, episodic memory and confrontation naming. There were also associations between the four subtypes and genetic or pathological diagnoses which were obtained in 48% of the cohort. The clusters did not differ in behavioural severity as measured by the Neuropsychiatric Inventory; supporting the original classification of the behavioural variant of frontotemporal dementia in these subjects. Our findings suggest behavioural variant of frontotemporal dementia can therefore be subdivided into four different anatomical subtypes.

Order of onset of drug use and criminal activities in a sample of drug-abusing women convicted of violent crimes.

PubMed

Baltieri, Danilo Antonio

2014-03-01

This study aims to explore the temporal relationship between age of onset of substance use and criminal activity in women convicted of violent crimes as well as to subdivide them into clinically significant groups to which tailored treatment can be guided. Of the 353 female inmates randomised for this study, 38 (10.8%) refused to participate and 182 (51.6%) met inclusion criteria. Data were obtained only from substance-abusing female inmates serving a sentence for robbery or homicide in a female penitentiary in Brazil. Participant information was gathered through face-to-face interviews during which alcohol and drug abuse, impulsiveness levels, depressive symptoms, and criminological aspects were investigated. . Age of first alcohol and drug use significantly preceded the age of onset of criminal activities in the overall sample. Onset ages of alcohol and drug use problems significantly preceded the beginning of criminal activities in women convicted of homicide only. Latent Class Analysis resulted in two groups: cluster 1 (n = 122; 67%), early-onset alcohol and drug users; and cluster 2 (n = 60; 33%), late-onset alcohol and drug users. Higher depression levels, higher incidence of committing robbery and less official history of recidivism were associated with cluster 1 inmates. The temporal relationship between the onset age of alcohol/drug use problems and age of the beginning of criminal activities can set apart women convicted of robbery from those convicted of homicide. Further, a distinctive therapeutic approach to early- and late-onset offenders may be valuable. © 2014 Australasian Professional Society on Alcohol and other Drugs.

Spatio-temporal clustering of wildfires in Portugal

NASA Astrophysics Data System (ADS)

Costa, R.; Pereira, M. G.; Caramelo, L.; Vega Orozco, C.; Kanevski, M.

2012-04-01

Several studies have shown that wildfires in Portugal presenthigh temporal as well as high spatial variability (Pereira et al., 2005, 2011). The identification and characterization of spatio-temporal clusters contributes to a comprehensivecharacterization of the fire regime and to improve the efficiency of fire prevention and combat activities. The main goalsin this studyare: (i) to detect the spatio-temporal clusters of burned area; and, (ii) to characterize these clusters along with the role of human and environmental factors. The data were supplied by the National Forest Authority(AFN, 2011) and comprises: (a)the Portuguese Rural Fire Database, PRFD, (Pereira et al., 2011) for the 1980-2007period; and, (b) the national mapping burned areas between 1990 and 2009. In this work, in order to complement the more common cluster analysis algorithms, an alternative approach based onscan statistics and on the permutation modelwas used. This statistical methodallows the detection of local excess events and to test if such an excess can reasonably have occurred by chance.Results obtained for different simulations performed for different spatial and temporal windows are presented, compared and interpreted.The influence of several fire factors such as (climate, vegetation type, etc.) is also assessed. Pereira, M.G., Trigo, R.M., DaCamara, C.C., Pereira, J.M.C., Leite, S.M., 2005:"Synoptic patterns associated with large summer forest fires in Portugal".Agricultural and Forest Meteorology. 129, 11-25. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 AFN, 2011: AutoridadeFlorestalNacional (National Forest Authority). Available at http://www.afn.min-agricultura.pt/portal.

Dynamics of Surfactant Clustering at Interfaces and Its Influence on the Interfacial Tension: Atomistic Simulation of a Sodium Hexadecane-Benzene Sulfonate-Tetradecane-Water System.

PubMed

Paredes, Ricardo; Fariñas-Sánchez, Ana Isabel; Medina-Rodrı Guez, Bryan; Samaniego, Samantha; Aray, Yosslen; Álvarez, Luis Javier

2018-03-06

The process of equilibration of the tetradecane-water interface in the presence of sodium hexadecane-benzene sulfonate is studied using intensive atomistic molecular dynamics simulations. Starting as an initial point with all of the surfactants at the interface, it is obtained that the equilibration time of the interface (several microseconds) is orders of magnitude higher than previously reported simulated times. There is strong evidence that this slow equilibration process is due to the aggregation of surfactants molecules on the interface. To determine this fact, temporal evolution of interfacial tension and interfacial formation energy are studied and their temporal variations are correlated with cluster formation. To study cluster evolution, the mean cluster size and the probability that a molecule of surfactant chosen at random is free are obtained as a function of time. Cluster size distribution is estimated, and it is observed that some of the molecules remain free, whereas the rest agglomerate. Additionally, the temporal evolution of the interfacial thickness and the structure of the surfactant molecules on the interface are studied. It is observed how this structure depends on whether the molecules agglomerate or not.

Deforestation, agriculture and farm jobs: a good recipe for Plasmodium vivax in French Guiana.

PubMed

Basurko, Célia; Demattei, Christophe; Han-Sze, René; Grenier, Claire; Joubert, Michel; Nacher, Mathieu; Carme, Bernard

2013-03-11

In a malaria-endemic area the distribution of patients is neither constant in time nor homogeneous in space. The WHO recommends the stratification of malaria risk on a fine geographical scale. In the village of Cacao in French Guiana, the study of the spatial and temporal distribution of malaria cases, during an epidemic, allowed a better understanding of the environmental factors promoting malaria transmission. A dynamic cohort of 839 persons living in 176 households (only people residing permanently in the village) was constituted between January 1st, 2002 and December 31st, 2007.The information about the number of inhabitants per household, the number of confirmed cases of Plasmodium vivax and house GPS coordinates were collected to search for spatial or temporal clustering using Kurlldorff's statistical method. Of the 839 persons living permanently in the village of Cacao, 359 persons presented at least one vivax malaria episode between 2002 and 2007. Five temporal clusters and four spatial clusters were identified during the study period. In all temporal clusters, April was included. Two spatial clusters were localized at the north of the village near the Comté River and two others localized close to orchards. The spatial heterogeneity of malaria in the village may have been influenced by environmental disturbances due to local agricultural policies: deforestation, cultures of fresh produce, or drainage of water for agriculture. This study allowed generating behavioural, entomological, or environmental hypotheses that could be useful to improve prevention campaigns.

Differential patterns of contextual organization of memory in first-episode psychosis.

PubMed

Murty, Vishnu P; McKinney, Rachel A; DuBrow, Sarah; Jalbrzikowski, Maria; Haas, Gretchen L; Luna, Beatriz

2018-02-15

Contextual information is used to support and organize episodic memory. Prior research has reliably shown memory deficits in psychosis; however, little research has characterized how this population uses contextual information during memory recall. We employed an approach founded in a computational framework of free recall to quantify how individuals with first episode of psychosis (FEP, N = 97) and controls (CON, N = 55) use temporal and semantic context to organize memory recall. Free recall was characterized using the Hopkins Verbal Learning Test-Revised (HVLT-R). We compared FEP and CON on three measures of free recall: proportion recalled, temporal clustering, and semantic clustering. Measures of temporal/semantic clustering quantified how individuals use contextual information to organize memory recall. We also assessed to what extent these measures relate to antipsychotic use and differentiated between different types of psychosis. We also explored the relationship between these measures and intelligence. In comparison to CON, FEP had reduced recall and less temporal clustering during free recall (p < 0.05, Bonferroni-corrected), and showed a trend towards greater semantic clustering (p = 0.10, Bonferroni-corrected). Within FEP, antipsychotic use and diagnoses did not differentiate between free recall accuracy or contextual organization of memory. IQ was related to free recall accuracy, but not the use of contextual information during recall in either group (p < 0.05, Bonferroni-corrected). These results show that in addition to deficits in memory recall, FEP differed in how they organize memories compared to CON.

Spatio-Temporal Variation of Longevity Clusters and the Influence of Social Development Level on Lifespan in a Chinese Longevous Area (1982–2010)

PubMed Central

Qin, Jian; Xia, Tianlong; Li, You; Liang, Xue; Wei, Peng; Long, Bingshuang; Lei, Mingzhi; Wei, Xiao; Tang, Xianyan; Zhang, Zhiyong

2017-01-01

The study aims to determine the spatial and temporal variation of a longevous region and explore the correlation between longevity and socioeconomic development. Population data at the township level were obtained from the last four population censuses (1982–2010). Five main lifespan indicators and the Human Development Index (HDI) were calculated. Getis-Ord G*, Gravity modeling, and Pearson’s r between lifespan indicators and HDI were applied. In this study, a stable longevous gathering area was discovered in Hechi during different periods. Under the influence of social and economic development, more longevous areas appeared. However, the effects of genetic and natural environmental factors on longevity were always dominant in this remote and mountainous city. Furthermore, longevity indicators lacked any significant correlation with life expectancy. No significant positive correlation was detected between lifespan indicators and HDI. Thus, we conclude that lifespan indicators can determine the spatial distribution and variation pattern of longevity from multiple dimensions. The geographical scope of longevity in Hechi City is gradually expanding, and significant spatial clustering was detected in southwestern, southern, and eastern parts of Hechi. This study also found that social economic development is likely to have a certain impact on new longevous areas, but their role on extreme longevity is not significant. PMID:28753971

Temporal and spatial analysis of psittacosis in association with poultry farming in the Netherlands, 2000-2015.

PubMed

Hogerwerf, Lenny; Holstege, Manon M C; Benincà, Elisa; Dijkstra, Frederika; van der Hoek, Wim

2017-07-26

Human psittacosis is a highly under diagnosed zoonotic disease, commonly linked to psittacine birds. Psittacosis in birds, also known as avian chlamydiosis, is endemic in poultry, but the risk for people living close to poultry farms is unknown. Therefore, our study aimed to explore the temporal and spatial patterns of human psittacosis infections and identify possible associations with poultry farming in the Netherlands. We analysed data on 700 human cases of psittacosis notified between 01-01-2000 and 01-09-2015. First, we studied the temporal behaviour of psittacosis notifications by applying wavelet analysis. Then, to identify possible spatial patterns, we applied spatial cluster analysis. Finally, we investigated the possible spatial association between psittacosis notifications and data on the Dutch poultry sector at municipality level using a multivariable model. We found a large spatial cluster that covered a highly poultry-dense area but additional clusters were found in areas that had a low poultry density. There were marked geographical differences in the awareness of psittacosis and the amount and the type of laboratory diagnostics used for psittacosis, making it difficult to draw conclusions about the correlation between the large cluster and poultry density. The multivariable model showed that the presence of chicken processing plants and slaughter duck farms in a municipality was associated with a higher rate of human psittacosis notifications. The significance of the associations was influenced by the inclusion or exclusion of farm density in the model. Our temporal and spatial analyses showed weak associations between poultry-related variables and psittacosis notifications. Because of the low number of psittacosis notifications available for analysis, the power of our analysis was relative low. Because of the exploratory nature of this research, the associations found cannot be interpreted as evidence for airborne transmission of psittacosis from poultry to the general population. Further research is needed to determine the prevalence of C. psittaci in Dutch poultry. Also, efforts to promote PCR-based testing for C. psittaci and genotyping for source tracing are important to reduce the diagnostic deficit, and to provide better estimates of the human psittacosis burden, and the possible role of poultry.

Correlation between magnetoencephalography-based "clusterectomy" and postoperative seizure freedom.

PubMed

Vadera, Sumeet; Jehi, Lara; Burgess, Richard C; Shea, Katherine; Alexopoulos, Andreas V; Mosher, John; Gonzalez-Martinez, Jorge; Bingaman, William

2013-06-01

During the presurgical evaluation of patients with medically intractable focal epilepsy, a variety of noninvasive studies are performed to localize the hypothetical epileptogenic zone and guide the resection. Magnetoencephalography (MEG) is becoming increasingly used in the clinical realm for this purpose. No investigators have previously reported on coregisteration of MEG clusters with postoperative resection cavities to evaluate whether complete "clusterectomy" (resection of the area associated with MEG clusters) was performed or to compare these findings with postoperative seizure-free outcomes. The authors retrospectively reviewed the charts and imaging studies of 65 patients undergoing MEG followed by resective epilepsy surgery from 2009 until 2012 at the Cleveland Clinic. Preoperative MEG studies were fused with postoperative MRI studies to evaluate whether clusters were within the resected area. These data were then correlated with postoperative seizure freedom. Sixty-five patients were included in this study. The average duration of follow-up was 13.9 months, the mean age at surgery was 23.1 years, and the mean duration of epilepsy was 13.7 years. In 30 patients, the main cluster was located completely within the resection cavity, in 28 it was completely outside the resection cavity, and in 7 it was partially within the resection cavity. Seventy-four percent of patients were seizure free at 12 months after surgery, and this rate decreased to 60% at 24 months. Improved likelihood of seizure freedom was seen with complete clusterectomy in patients with localization outside the temporal lobe (extra-temporal lobe epilepsy) (p = 0.04). In patients with preoperative MEG studies that show clusters in surgically accessible areas outside the temporal lobe, we suggest aggressive resection to improve the chances for seizure freedom. When the cluster is found within the temporal lobe, further diagnostic testing may be required to better localize the epileptogenic zone.

[Spatial analysis of autumn-winter type scrub typhus in Shandong province, 2006-2014].

PubMed

Yang, H; Bi, Z W; Kou, Z Q; Zheng, L; Zhao, Z T

2016-05-01

To discuss the spatial-temporal distribution and epidemic trends of autumn-winter type scrub typhus in Shandong province, and provide scientific evidence for further study for the prevention and control of the disease. The scrub typhus surveillance data during 2006-2014 were collected from Shandong Disease Reporting Information System. The data was analyzed by using software ArcGIS 9.3(ESRI Inc., Redlands, CA, USA), GeoDa 0.9.5-i and SatScan 9.1.1. The Moran' s I, log-likelihood ratio(LLR), relative risk(RR)were calculated and the incidence choropleth maps, local indicators of spatial autocorrelation cluster maps and space scaning cluster maps were drawn. A total of 4 453 scrub typhus cases were reported during 2006-2014, and the annual incidence increased with year. Among the 17 prefectures(municipality)in Shandong, 13 were affected by scrub typhus. The global Moran's I index was 0.501 5(P<0.01). The differences in local Moran' s I index among 16 prefectures were significant(P<0.01). The " high-high" clustering areas were mainly Wulian county, Lanshan district and Juxian county of Rizhao, Xintai county of Tai' an, Gangcheng and Laicheng districts of Laiwu, Yiyuan county of Zibo and Mengyin county of Linyi. Spatial scan analysis showed that an eastward moving trend of high-risk clusters and two new high-risk clusters were found in Zaozhuang in 2014. The centers of the most likely clusters were in the south central mountainous areas during 2006-2010 and in 2012, eastern hilly areas in 2011, 2013 and 2014, and the size of the clusters expanded in 2008, 2011, 2013 and 2014. One spatial-temporal cluster was detected from October 1, 2014 to November 30, 2014, the center of the cluster was in Rizhao and the radius was 222.34 kilometers. A positive spatial correlation and spatial agglomerations were found in the distribution of autumn-winter type scrub typhus in Shandong. Since 2006, the epidemic area of the disease has expanded and the number of high-risk areas has increased. Moreover, the eastward moving and periodically expanding trends of high-risk clusters were detected.

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906–1909: evaluating local clustering with the Gi* statistic

PubMed Central

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-01-01

Background To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May – 31 October 1906 – 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. Results The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. Conclusion The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century. PMID:16566830

Spatial and temporal structure of typhoid outbreaks in Washington, D.C., 1906-1909: evaluating local clustering with the Gi* statistic.

PubMed

Hinman, Sarah E; Blackburn, Jason K; Curtis, Andrew

2006-03-27

To better understand the distribution of typhoid outbreaks in Washington, D.C., the U.S. Public Health Service (PHS) conducted four investigations of typhoid fever. These studies included maps of cases reported between 1 May - 31 October 1906 - 1909. These data were entered into a GIS database and analyzed using Ripley's K-function followed by the Gi* statistic in yearly intervals to evaluate spatial clustering, the scale of clustering, and the temporal stability of these clusters. The Ripley's K-function indicated no global spatial autocorrelation. The Gi* statistic indicated clustering of typhoid at multiple scales across the four year time period, refuting the conclusions drawn in all four PHS reports concerning the distribution of cases. While the PHS reports suggested an even distribution of the disease, this study quantified both areas of localized disease clustering, as well as mobile larger regions of clustering. Thus, indicating both highly localized and periodic generalized sources of infection within the city. The methodology applied in this study was useful for evaluating the spatial distribution and annual-level temporal patterns of typhoid outbreaks in Washington, D.C. from 1906 to 1909. While advanced spatial analyses of historical data sets must be interpreted with caution, this study does suggest that there is utility in these types of analyses and that they provide new insights into the urban patterns of typhoid outbreaks during the early part of the twentieth century.

Earthquake Clustering in Noisy Viscoelastic Systems

NASA Astrophysics Data System (ADS)

Dicaprio, C. J.; Simons, M.; Williams, C. A.; Kenner, S. J.

2006-12-01

Geologic studies show evidence for temporal clustering of earthquakes on certain fault systems. Since post- seismic deformation may result in a variable loading rate on a fault throughout the inter-seismic period, it is reasonable to expect that the rheology of the non-seismogenic lower crust and mantle lithosphere may play a role in controlling earthquake recurrence times. Previously, the role of rheology of the lithosphere on the seismic cycle had been studied with a one-dimensional spring-dashpot-slider model (Kenner and Simons [2005]). In this study we use the finite element code PyLith to construct a two-dimensional continuum model a strike-slip fault in an elastic medium overlying one or more linear Maxwell viscoelastic layers loaded in the far field by a constant velocity boundary condition. Taking advantage of the linear properties of the model, we use the finite element solution to one earthquake as a spatio-temporal Green's function. Multiple Green's function solutions, scaled by the size of each earthquake, are then summed to form an earthquake sequence. When the shear stress on the fault reaches a predefined yield stress it is allowed to slip, relieving all accumulated shear stress. Random variation in the fault yield stress from one earthquake to the next results in a temporally clustered earthquake sequence. The amount of clustering depends on a non-dimensional number, W, called the Wallace number. For models with one viscoelastic layer, W is equal to the standard deviation of the earthquake stress drop divided by the viscosity times the tectonic loading rate. This definition of W is modified from the original one used in Kenner and Simons [2005] by using the standard deviation of the stress drop instead of the mean stress drop. We also use a new, more appropriate, metric to measure the amount of temporal clustering of the system. W is the ratio of the viscoelastic relaxation rate of the system to the tectonic loading rate of the system. For values of W greater than the critical value of about 10, the clustered earthquake behavior is due to the rapid reloading of the fault due to viscoelastic recycling of stress. A model with multiple viscoelastic layers has more complex clustering behavior than a system with only one viscosity. In this case, multiple clustering modes exist; the size and mean period of which are influenced by the viscosities and relative thicknesses of the viscoelastic layers. Kenner, S.J. and Simons, M., (2005), Temporal cluster of major earthquakes along individual faults due to post-seismic reloading, Geophysical Journal International, 160, 179-194.

Patterning in time and space: HoxB cluster gene expression in the developing chick embryo.

PubMed

Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P

2015-01-01

The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space.

Patterning in time and space: HoxB cluster gene expression in the developing chick embryo

PubMed Central

Gouveia, Analuce; Marcelino, Hugo M; Gonçalves, Lisa; Palmeirim, Isabel; Andrade, Raquel P

2015-01-01

The developing embryo is a paradigmatic model to study molecular mechanisms of time control in Biology. Hox genes are key players in the specification of tissue identity during embryo development and their expression is under strict temporal regulation. However, the molecular mechanisms underlying timely Hox activation in the early embryo remain unknown. This is hindered by the lack of a rigorous temporal framework of sequential Hox expression within a single cluster. Herein, a thorough characterization of HoxB cluster gene expression was performed over time and space in the early chick embryo. Clear temporal collinearity of HoxB cluster gene expression activation was observed. Spatial collinearity of HoxB expression was evidenced in different stages of development and in multiple tissues. Using embryo explant cultures we showed that HoxB2 is cyclically expressed in the rostral presomitic mesoderm with the same periodicity as somite formation, suggesting a link between timely tissue specification and somite formation. We foresee that the molecular framework herein provided will facilitate experimental approaches aimed at identifying the regulatory mechanisms underlying Hox expression in Time and Space. PMID:25602523

Epidemiological characteristics of reported sporadic and outbreak cases of E. coli O157 in people from Alberta, Canada (2000-2002): methodological challenges of comparing clustered to unclustered data.

PubMed

Pearl, D L; Louie, M; Chui, L; Doré, K; Grimsrud, K M; Martin, S W; Michel, P; Svenson, L W; McEwen, S A

2008-04-01

Using multivariable models, we compared whether there were significant differences between reported outbreak and sporadic cases in terms of their sex, age, and mode and site of disease transmission. We also determined the potential role of administrative, temporal, and spatial factors within these models. We compared a variety of approaches to account for clustering of cases in outbreaks including weighted logistic regression, random effects models, general estimating equations, robust variance estimates, and the random selection of one case from each outbreak. Age and mode of transmission were the only epidemiologically and statistically significant covariates in our final models using the above approaches. Weighing observations in a logistic regression model by the inverse of their outbreak size appeared to be a relatively robust and valid means for modelling these data. Some analytical techniques, designed to account for clustering, had difficulty converging or producing realistic measures of association.

Characterization of the temporal and spatial distribution and reproductive ratio of vesicular stomatitis outbreaks in Mexico in 2008.

PubMed

Arroyo, Montserrat; Perez, Andres M; Rodriguez, Luis L

2011-02-01

To characterize the temporal and spatial distribution and reproductive ratio of vesicular stomatitis (VS) outbreaks reported in Mexico in 2008. Bovine herds in Mexico in which VS outbreaks were officially reported and confirmed from January 1 through December 31, 2008. The Poisson model of the space-time scan statistic was used to identify periods and geographical locations at highest risk for VS in Mexico in 2008. The herd reproductive ratio (R(h)) of the epidemic was computed by use of the doubling-time method. 1 significant space-time cluster of VS was detected in the state of Michoacan from September 4 through December 10, 2008. The temporal extent of the VS outbreaks and the value and pattern of decrease of the R(h) were different in the endemic zone of Tabasco and Chiapas, compared with findings in the region included in the space-time cluster. The large number of VS outbreaks reported in Mexico in 2008 was associated with the spread of the disease from the endemic zone in southern Mexico to areas sporadically affected by the disease. Results suggested that implementation of a surveillance system in the endemic zone of Mexico aimed at early detection of changes in the value of R(h) and space-time clustering of the disease could help predict occurrence of future VS outbreaks originating from this endemic zone. This information will help prevent VS spread into regions of Mexico and neighboring countries that are only sporadically affected by the disease.

A multi-criteria evaluation system for marine litter pollution based on statistical analyses of OSPAR beach litter monitoring time series.

PubMed

Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael

2013-12-01

During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.

Predictors of temporal patterns of psychiatric distress during 10 years following the nuclear accident at Three Mile Island.

PubMed

Dew, M A; Bromet, E J

1993-04-01

The present study examines psychiatric symptom levels during a 10-year period in a community sample of mothers of young children. All were identified in the early aftermath of the 1979 Three Mile Island nuclear accident, and followed through the accident's 1989 anniversary. Cluster analysis was used to identify long-term distress profiles during the study period; women's temporal profiles were found to be either (a) stable and at low, clinically nonsignificant levels of distress across all measurement points or (b) at consistently elevated, clinically significant levels that varied with the timing of postaccident events such as the restart of the undamaged reactor and the 10th anniversary. Subsequent multivariate analyses indicated that preaccident characteristics, as well as parameters reflecting respondents' initial involvement with, and reactions to the accident, were important for distinguishing between women within the two temporal profile groups. Implications of the results for both policy formulation and continued research on significant environmental stressors is discussed.

Dengue Fever Occurrence and Vector Detection by Larval Survey, Ovitrap and MosquiTRAP: A Space-Time Clusters Analysis

PubMed Central

de Melo, Diogo Portella Ornelas; Scherrer, Luciano Rios; Eiras, Álvaro Eduardo

2012-01-01

The use of vector surveillance tools for preventing dengue disease requires fine assessment of risk, in order to improve vector control activities. Nevertheless, the thresholds between vector detection and dengue fever occurrence are currently not well established. In Belo Horizonte (Minas Gerais, Brazil), dengue has been endemic for several years. From January 2007 to June 2008, the dengue vector Aedes (Stegomyia) aegypti was monitored by ovitrap, the sticky-trap MosquiTRAP™ and larval surveys in an study area in Belo Horizonte. Using a space-time scan for clusters detection implemented in SaTScan software, the vector presence recorded by the different monitoring methods was evaluated. Clusters of vectors and dengue fever were detected. It was verified that ovitrap and MosquiTRAP vector detection methods predicted dengue occurrence better than larval survey, both spatially and temporally. MosquiTRAP and ovitrap presented similar results of space-time intersections to dengue fever clusters. Nevertheless ovitrap clusters presented longer duration periods than MosquiTRAP ones, less acuratelly signalizing the dengue risk areas, since the detection of vector clusters during most of the study period was not necessarily correlated to dengue fever occurrence. It was verified that ovitrap clusters occurred more than 200 days (values ranged from 97.0±35.35 to 283.0±168.4 days) before dengue fever clusters, whereas MosquiTRAP clusters preceded dengue fever clusters by approximately 80 days (values ranged from 65.5±58.7 to 94.0±14. 3 days), the former showing to be more temporally precise. Thus, in the present cluster analysis study MosquiTRAP presented superior results for signaling dengue transmission risks both geographically and temporally. Since early detection is crucial for planning and deploying effective preventions, MosquiTRAP showed to be a reliable tool and this method provides groundwork for the development of even more precise tools. PMID:22848729

Visual Field Map Clusters in High-Order Visual Processing: Organization of V3A/V3B and a New Cloverleaf Cluster in the Posterior Superior Temporal Sulcus

PubMed Central

Barton, Brian; Brewer, Alyssa A.

2017-01-01

The cortical hierarchy of the human visual system has been shown to be organized around retinal spatial coordinates throughout much of low- and mid-level visual processing. These regions contain visual field maps (VFMs) that each follows the organization of the retina, with neighboring aspects of the visual field processed in neighboring cortical locations. On a larger, macrostructural scale, groups of such sensory cortical field maps (CFMs) in both the visual and auditory systems are organized into roughly circular cloverleaf clusters. CFMs within clusters tend to share properties such as receptive field distribution, cortical magnification, and processing specialization. Here we use fMRI and population receptive field (pRF) modeling to investigate the extent of VFM and cluster organization with an examination of higher-level visual processing in temporal cortex and compare these measurements to mid-level visual processing in dorsal occipital cortex. In human temporal cortex, the posterior superior temporal sulcus (pSTS) has been implicated in various neuroimaging studies as subserving higher-order vision, including face processing, biological motion perception, and multimodal audiovisual integration. In human dorsal occipital cortex, the transverse occipital sulcus (TOS) contains the V3A/B cluster, which comprises two VFMs subserving mid-level motion perception and visuospatial attention. For the first time, we present the organization of VFMs in pSTS in a cloverleaf cluster. This pSTS cluster contains four VFMs bilaterally: pSTS-1:4. We characterize these pSTS VFMs as relatively small at ∼125 mm2 with relatively large pRF sizes of ∼2–8° of visual angle across the central 10° of the visual field. V3A and V3B are ∼230 mm2 in surface area, with pRF sizes here similarly ∼1–8° of visual angle across the same region. In addition, cortical magnification measurements show that a larger extent of the pSTS VFM surface areas are devoted to the peripheral visual field than those in the V3A/B cluster. Reliability measurements of VFMs in pSTS and V3A/B reveal that these cloverleaf clusters are remarkably consistent and functionally differentiable. Our findings add to the growing number of measurements of widespread sensory CFMs organized into cloverleaf clusters, indicating that CFMs and cloverleaf clusters may both be fundamental organizing principles in cortical sensory processing. PMID:28293182

A K-means multivariate approach for clustering independent components from magnetoencephalographic data.

PubMed

Spadone, Sara; de Pasquale, Francesco; Mantini, Dante; Della Penna, Stefania

2012-09-01

Independent component analysis (ICA) is typically applied on functional magnetic resonance imaging, electroencephalographic and magnetoencephalographic (MEG) data due to its data-driven nature. In these applications, ICA needs to be extended from single to multi-session and multi-subject studies for interpreting and assigning a statistical significance at the group level. Here a novel strategy for analyzing MEG independent components (ICs) is presented, Multivariate Algorithm for Grouping MEG Independent Components K-means based (MAGMICK). The proposed approach is able to capture spatio-temporal dynamics of brain activity in MEG studies by running ICA at subject level and then clustering the ICs across sessions and subjects. Distinctive features of MAGMICK are: i) the implementation of an efficient set of "MEG fingerprints" designed to summarize properties of MEG ICs as they are built on spatial, temporal and spectral parameters; ii) the implementation of a modified version of the standard K-means procedure to improve its data-driven character. This algorithm groups the obtained ICs automatically estimating the number of clusters through an adaptive weighting of the parameters and a constraint on the ICs independence, i.e. components coming from the same session (at subject level) or subject (at group level) cannot be grouped together. The performances of MAGMICK are illustrated by analyzing two sets of MEG data obtained during a finger tapping task and median nerve stimulation. The results demonstrate that the method can extract consistent patterns of spatial topography and spectral properties across sessions and subjects that are in good agreement with the literature. In addition, these results are compared to those from a modified version of affinity propagation clustering method. The comparison, evaluated in terms of different clustering validity indices, shows that our methodology often outperforms the clustering algorithm. Eventually, these results are confirmed by a comparison with a MEG tailored version of the self-organizing group ICA, which is largely used for fMRI IC clustering. Copyright © 2012 Elsevier Inc. All rights reserved.

Modulation of task demands suggests that semantic processing interferes with the formation of episodic associations

PubMed Central

Long, Nicole M.; Kahana, Michael J.

2016-01-01

Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of responses. We asked whether orienting participants toward semantic associations interferes with or facilitates the formation of episodic associations. We compared electroencephalographic (EEG) activity recorded during the encoding of subsequently recalled words that were either temporally or semantically clustered. Participants studied words with or without a concurrent semantic orienting task. We identified a neural signature of successful episodic association formation whereby high frequency EEG activity (HFA, 44 – 100 Hz) overlying left prefrontal regions increased for subsequently temporally clustered words, but only for those words studied without a concurrent semantic orienting task. To confirm that this disruption in the formation of episodic associations was driven by increased semantic processing, we measured the neural correlates of subsequent semantic clustering. We found that HFA increased for subsequently semantically clustered words only for lists with a concurrent semantic orienting task. This dissociation suggests that increased semantic processing of studied items interferes with the neural processes that support the formation of novel episodic associations. PMID:27617775

Modulation of task demands suggests that semantic processing interferes with the formation of episodic associations.

PubMed

Long, Nicole M; Kahana, Michael J

2017-02-01

Although episodic and semantic memory share overlapping neural mechanisms, it remains unclear how our pre-existing semantic associations modulate the formation of new, episodic associations. When freely recalling recently studied words, people rely on both episodic and semantic associations, shown through temporal and semantic clustering of responses. We asked whether orienting participants toward semantic associations interferes with or facilitates the formation of episodic associations. We compared electroencephalographic (EEG) activity recorded during the encoding of subsequently recalled words that were either temporally or semantically clustered. Participants studied words with or without a concurrent semantic orienting task. We identified a neural signature of successful episodic association formation whereby high-frequency EEG activity (HFA, 44-100 Hz) overlying left prefrontal regions increased for subsequently temporally clustered words, but only for those words studied without a concurrent semantic orienting task. To confirm that this disruption in the formation of episodic associations was driven by increased semantic processing, we measured the neural correlates of subsequent semantic clustering. We found that HFA increased for subsequently semantically clustered words only for lists with a concurrent semantic orienting task. This dissociation suggests that increased semantic processing of studied items interferes with the neural processes that support the formation of novel episodic associations. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Imbalance of community structures in epilepsy

NASA Astrophysics Data System (ADS)

Ortega, G. J.; Herrera Peco, I.; García de Sola, R.; Pastor, J.

2010-09-01

Epilepsy is commonly associated with synchronous activity in the form of spikes and also in developed seizures. Desynchronised activity seems to play an important role also in the seizure process, favouring the initiation of seizures. The aim of the present work is to explore synchronization activity in the inner areas in the temporal lobe of epileptic patients by a novel approach. Two temporal lobe epilepsy (TLE) patients' records have been analyzed through a cluster analysis. Electrical activity in the inner part of the temporal has been recorded by using Foramen Ovale Electrodes (FOE), a semi-invasive technique frequently used in drug resistant epileptic patients. Instead of tracking synchronized activity, we give here special attention to desynchronized activity, mainly those areas which are not included in synchronization clusters. Our results show that electrical activity in the epileptic side behaves in a less cohesive fashion than the contra-lateral side. There exists a clear tendency in the epileptic side to be organized as isolated clusters of electrical activity as compared with the contra-lateral side, which is organized in the form of large clusters of synchronous activity. In particular, we shall give special attention to the cluster desynchronization during the seizures. As we shall show, our results can help in understand several characteristics of the seizures dynamics.

Hemisphere- and gender-related differences in small-world brain networks: a resting-state functional MRI study.

PubMed

Tian, Lixia; Wang, Jinhui; Yan, Chaogan; He, Yong

2011-01-01

We employed resting-state functional MRI (R-fMRI) to investigate hemisphere- and gender-related differences in the topological organization of human brain functional networks. Brain networks were first constructed by measuring inter-regional temporal correlations of R-fMRI data within each hemisphere in 86 young, healthy, right-handed adults (38 males and 48 females) followed by a graph-theory analysis. The hemispheric networks exhibit small-world attributes (high clustering and short paths) that are compatible with previous results in the whole-brain functional networks. Furthermore, we found that compared with females, males have a higher normalized clustering coefficient in the right hemispheric network but a lower clustering coefficient in the left hemispheric network, suggesting a gender-hemisphere interaction. Moreover, we observed significant hemisphere-related differences in the regional nodal characteristics in various brain regions, such as the frontal and occipital regions (leftward asymmetry) and the temporal regions (rightward asymmetry), findings that are consistent with previous studies of brain structural and functional asymmetries. Together, our results suggest that the topological organization of human brain functional networks is associated with gender and hemispheres, and they provide insights into the understanding of functional substrates underlying individual differences in behaviors and cognition. Copyright © 2010 Elsevier Inc. All rights reserved.

Spatial-temporal travel pattern mining using massive taxi trajectory data

NASA Astrophysics Data System (ADS)

Zheng, Linjiang; Xia, Dong; Zhao, Xin; Tan, Longyou; Li, Hang; Chen, Li; Liu, Weining

2018-07-01

Deep understanding of residents' travel patterns would provide helpful insights into the mechanisms of many socioeconomic phenomena. With the rapid development of location-aware computing technologies, researchers have easy access to large quantities of travel data. As an important data source, taxi trajectory data are featured by their high quality, good continuity and wide distribution, making it suitable for travel pattern mining. In this paper, we use taxi trajectory data to study spatial-temporal characterization of urban residents' travel patterns from two aspects: attractive areas and hot paths. Firstly, a framework of trajectory preprocessing, including data cleaning and extracting the taxi passenger pick-up/drop-off points, is presented to reduce the noise and redundancy in raw trajectory data. Then, a grid density based clustering algorithm is proposed to discover travel attractive areas in different periods of a day. On this basis, we put forward a spatial-temporal trajectory clustering method to discover hot paths among travel attractive areas. Compared with previous algorithms, which only consider the spatial constraint between trajectories, temporal constraint is also considered in our method. Through the experiments, we discuss how to determine the optimal parameters of the two clustering algorithms and verify the effectiveness of the algorithms using real data. Furthermore, we analyze spatial-temporal characterization of Chongqing residents' travel pattern.

A genome-wide supported psychiatric risk variant in NCAN influences brain function and cognitive performance in healthy subjects.

PubMed

Raum, Heidelore; Dietsche, Bruno; Nagels, Arne; Witt, Stephanie H; Rietschel, Marcella; Kircher, Tilo; Krug, Axel

2015-01-01

The A allele of the single nucleotide polymorphism (SNP) rs1064395 in the NCAN gene has recently been identified as a susceptibility factor for bipolar disorder and schizophrenia. NCAN encodes neurocan, a brain-specific chondroitin sulfate proteoglycan that is thought to influence neuronal adhesion and migration. Several lines of research suggest an impact of NCAN on neurocognitive functioning. In the present study, we investigated the effects of rs1064395 genotype on neural processing and cognitive performance in healthy subjects. Brain activity was measured with functional magnetic resonance imaging (fMRI) during an overt semantic verbal fluency task in 110 healthy subjects who were genotyped for the NCAN SNP rs1064395. Participants additionally underwent comprehensive neuropsychological testing. Whole brain analyses revealed that NCAN risk status, defined as AA or AG genotype, was associated with a lack of task-related deactivation in a large left lateral temporal cluster extending from the middle temporal gyrus to the temporal pole. Regarding neuropsychological measures, risk allele carriers demonstrated poorer immediate and delayed verbal memory performance when compared to subjects with GG genotype. Better verbal memory performance was significantly associated with greater deactivation of the left temporal cluster during the fMRI task in subjects with GG genotype. The current data demonstrate that common genetic variation in NCAN influences both neural processing and cognitive performance in healthy subjects. Our study provides new evidence for a specific genetic influence on human brain function. © 2014 Wiley Periodicals, Inc.

Local bladder cancer clusters in southeastern Michigan accounting for risk factors, covariates and residential mobility.

PubMed

Jacquez, Geoffrey M; Shi, Chen; Meliker, Jaymie R

2015-01-01

In case control studies disease risk not explained by the significant risk factors is the unexplained risk. Considering unexplained risk for specific populations, places and times can reveal the signature of unidentified risk factors and risk factors not fully accounted for in the case-control study. This potentially can lead to new hypotheses regarding disease causation. Global, local and focused Q-statistics are applied to data from a population-based case-control study of 11 southeast Michigan counties. Analyses were conducted using both year- and age-based measures of time. The analyses were adjusted for arsenic exposure, education, smoking, family history of bladder cancer, occupational exposure to bladder cancer carcinogens, age, gender, and race. Significant global clustering of cases was not found. Such a finding would indicate large-scale clustering of cases relative to controls through time. However, highly significant local clusters were found in Ingham County near Lansing, in Oakland County, and in the City of Jackson, Michigan. The Jackson City cluster was observed in working-ages and is thus consistent with occupational causes. The Ingham County cluster persists over time, suggesting a broad-based geographically defined exposure. Focused clusters were found for 20 industrial sites engaged in manufacturing activities associated with known or suspected bladder cancer carcinogens. Set-based tests that adjusted for multiple testing were not significant, although local clusters persisted through time and temporal trends in probability of local tests were observed. Q analyses provide a powerful tool for unpacking unexplained disease risk from case-control studies. This is particularly useful when the effect of risk factors varies spatially, through time, or through both space and time. For bladder cancer in Michigan, the next step is to investigate causal hypotheses that may explain the excess bladder cancer risk localized to areas of Oakland and Ingham counties, and to the City of Jackson.

Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing

NASA Astrophysics Data System (ADS)

Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.

2017-09-01

Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.

Mapping the cortical representation of speech sounds in a syllable repetition task.

PubMed

Markiewicz, Christopher J; Bohland, Jason W

2016-11-01

Speech repetition relies on a series of distributed cortical representations and functional pathways. A speaker must map auditory representations of incoming sounds onto learned speech items, maintain an accurate representation of those items in short-term memory, interface that representation with the motor output system, and fluently articulate the target sequence. A "dorsal stream" consisting of posterior temporal, inferior parietal and premotor regions is thought to mediate auditory-motor representations and transformations, but the nature and activation of these representations for different portions of speech repetition tasks remains unclear. Here we mapped the correlates of phonetic and/or phonological information related to the specific phonemes and syllables that were heard, remembered, and produced using a series of cortical searchlight multi-voxel pattern analyses trained on estimates of BOLD responses from individual trials. Based on responses linked to input events (auditory syllable presentation), predictive vowel-level information was found in the left inferior frontal sulcus, while syllable prediction revealed significant clusters in the left ventral premotor cortex and central sulcus and the left mid superior temporal sulcus. Responses linked to output events (the GO signal cueing overt production) revealed strong clusters of vowel-related information bilaterally in the mid to posterior superior temporal sulcus. For the prediction of onset and coda consonants, input-linked responses yielded distributed clusters in the superior temporal cortices, which were further informative for classifiers trained on output-linked responses. Output-linked responses in the Rolandic cortex made strong predictions for the syllables and consonants produced, but their predictive power was reduced for vowels. The results of this study provide a systematic survey of how cortical response patterns covary with the identity of speech sounds, which will help to constrain and guide theoretical models of speech perception, speech production, and phonological working memory. Copyright © 2016 Elsevier Inc. All rights reserved.

Attempting to physically explain space-time correlation of extremes

NASA Astrophysics Data System (ADS)

Bernardara, Pietro; Gailhard, Joel

2010-05-01

Spatial and temporal clustering of hydro-meteorological extreme events is scientific evidence. Moreover, the statistical parameters characterizing their local frequencies of occurrence show clear spatial patterns. Thus, in order to robustly assess the hydro-meteorological hazard, statistical models need to be able to take into account spatial and temporal dependencies. Statistical models considering long term correlation for quantifying and qualifying temporal and spatial dependencies are available, such as multifractal approach. Furthermore, the development of regional frequency analysis techniques allows estimating the frequency of occurrence of extreme events taking into account spatial patterns on the extreme quantiles behaviour. However, in order to understand the origin of spatio-temporal clustering, an attempt to find physical explanation should be done. Here, some statistical evidences of spatio-temporal correlation and spatial patterns of extreme behaviour are given on a large database of more than 400 rainfall and discharge series in France. In particular, the spatial distribution of multifractal and Generalized Pareto distribution parameters shows evident correlation patterns in the behaviour of frequency of occurrence of extremes. It is then shown that the identification of atmospheric circulation pattern (weather types) can physically explain the temporal clustering of extreme rainfall events (seasonality) and the spatial pattern of the frequency of occurrence. Moreover, coupling this information with the hydrological modelization of a watershed (as in the Schadex approach) an explanation of spatio-temporal distribution of extreme discharge can also be provided. We finally show that a hydro-meteorological approach (as the Schadex approach) can explain and take into account space and time dependencies of hydro-meteorological extreme events.

Proper Motions and Structural Parameters of the Galactic Globular Cluster M71

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cadelano, M.; Dalessandro, E.; Ferraro, F. R.

2017-02-20

By exploiting two ACS/ HST data sets separated by a temporal baseline of ∼7 years, we have determined the relative stellar proper motions (PMs; providing membership) and the absolute PM of the Galactic globular cluster M71. The absolute PM has been used to reconstruct the cluster orbit within a Galactic, three-component, axisymmetric potential. M71 turns out to be in a low-latitude disk-like orbit inside the Galactic disk, further supporting the scenario in which it lost a significant fraction of its initial mass. Since large differential reddening is known to affect this system, we took advantage of near-infrared, ground-based observations tomore » re-determine the cluster center and density profile from direct star counts. The new structural parameters turn out to be significantly different from the ones quoted in the literature. In particular, M71 has a core and a half-mass radii almost 50% larger than previously thought. Finally, we estimate that the initial mass of M71 was likely one order of magnitude larger than its current value, thus helping to solve the discrepancy with the observed number of X-ray sources.« less

Time fluctuation analysis of forest fire sequences

NASA Astrophysics Data System (ADS)

Vega Orozco, Carmen D.; Kanevski, Mikhaïl; Tonini, Marj; Golay, Jean; Pereira, Mário J. G.

2013-04-01

Forest fires are complex events involving both space and time fluctuations. Understanding of their dynamics and pattern distribution is of great importance in order to improve the resource allocation and support fire management actions at local and global levels. This study aims at characterizing the temporal fluctuations of forest fire sequences observed in Portugal, which is the country that holds the largest wildfire land dataset in Europe. This research applies several exploratory data analysis measures to 302,000 forest fires occurred from 1980 to 2007. The applied clustering measures are: Morisita clustering index, fractal and multifractal dimensions (box-counting), Ripley's K-function, Allan Factor, and variography. These algorithms enable a global time structural analysis describing the degree of clustering of a point pattern and defining whether the observed events occur randomly, in clusters or in a regular pattern. The considered methods are of general importance and can be used for other spatio-temporal events (i.e. crime, epidemiology, biodiversity, geomarketing, etc.). An important contribution of this research deals with the analysis and estimation of local measures of clustering that helps understanding their temporal structure. Each measure is described and executed for the raw data (forest fires geo-database) and results are compared to reference patterns generated under the null hypothesis of randomness (Poisson processes) embedded in the same time period of the raw data. This comparison enables estimating the degree of the deviation of the real data from a Poisson process. Generalizations to functional measures of these clustering methods, taking into account the phenomena, were also applied and adapted to detect time dependences in a measured variable (i.e. burned area). The time clustering of the raw data is compared several times with the Poisson processes at different thresholds of the measured function. Then, the clustering measure value depends on the threshold which helps to understand the time pattern of the studied events. Our findings detected the presence of overdensity of events in particular time periods and showed that the forest fire sequences in Portugal can be considered as a multifractal process with a degree of time-clustering of the events. Key words: time sequences, Morisita index, fractals, multifractals, box-counting, Ripley's K-function, Allan Factor, variography, forest fires, point process. Acknowledgements This work was partly supported by the SNFS Project No. 200021-140658, "Analysis and Modelling of Space-Time Patterns in Complex Regions". References - Kanevski M. (Editor). 2008. Advanced Mapping of Environmental Data: Geostatistics, Machine Learning and Bayesian Maximum Entropy. London / Hoboken: iSTE / Wiley. - Telesca L. and Pereira M.G. 2010. Time-clustering investigation of fire temporal fluctuations in Portugal, Nat. Hazards Earth Syst. Sci., vol. 10(4): 661-666. - Vega Orozco C., Tonini M., Conedera M., Kanevski M. (2012) Cluster recognition in spatial-temporal sequences: the case of forest fires, Geoinformatica, vol. 16(4): 653-673.

Tempo-spatial analysis of Fennoscandian intraplate seismicity

NASA Astrophysics Data System (ADS)

Roberts, Roland; Lund, Björn

2017-04-01

Coupled spatial-temporal patterns of the occurrence of earthquakes in Fennoscandia are analysed using non-parametric methods. The occurrence of larger events is unambiguously and very strongly temporally clustered, with major implications for the assessment of seismic hazard in areas such as Fennoscandia. In addition, there is a clear pattern of geographical migration of activity. Data from the Swedish National Seismic Network and a collated international catalogue are analysed. Results show consistent patterns on different spatial and temporal scales. We are currently investigating these patterns in order to assess the statistical significance of the tempo-spatial patterns, and to what extent these may be consistent with stress transfer mechanism such as coulomb stress and pore fluid migration. Indications are that some further mechanism is necessary in order to explain the data, perhaps related to post-glacial uplift, which is up to 1cm/year.

Spatial-temporal epidemiology of human Salmonella Enteritidis infections with major phage types (PTs 1, 4, 5b, 8, 13, and 13a) in Ontario, Canada, 2008-2009.

PubMed

Varga, Csaba; Pearl, David L; McEwen, Scott A; Sargeant, Jan M; Pollari, Frank; Guerin, Michele T

2015-12-17

In Ontario and Canada, the incidence of human Salmonella enterica serotype Enteritidis (S. Enteritidis) infections have increased steadily during the last decade. Our study evaluated the spatial and temporal epidemiology of the major phage types (PTs) of S. Enteritidis infections to aid public health practitioners design effective prevention and control programs. Data on S. Enteritidis infections between January 1, 2008 and December 31, 2009 were obtained from Ontario's disease surveillance system. Salmonella Enteritidis infections with major phage types were classified by their annual health region-level incidence rates (IRs), monthly IRs, clinical symptoms, and exposure settings. A scan statistic was employed to detect retrospective phage type-specific spatial, temporal, and space-time clusters of S. Enteritidis infections. Space-time cluster cases' exposure settings were evaluated to identify common exposures. 1,336 cases were available for analysis. The six most frequently reported S. Enteritidis PTs were 8 (n = 398), 13a (n = 218), 13 (n = 198), 1 (n = 132), 5b (n = 83), and 4 (n = 76). Reported rates of S. Enteritidis infections with major phage types varied by health region and month. International travel and unknown exposure settings were the most frequently reported settings for PT 5b, 4, and 1 cases, whereas unknown exposure setting, private home, food premise, and international travel were the most frequently reported settings for PT 8, 13, and 13a cases. Diarrhea, abdominal pain, and fever were the most commonly reported clinical symptoms. A number of phage type-specific spatial, temporal, and space-time clusters were identified. Space-time clusters of PTs 1, 4, and 5b occurred mainly during the winter and spring months in the North West, North East, Eastern, Central East, and Central West regions. Space-time clusters of PTs 13 and 13a occurred at different times of the year in the Toronto region. Space-time clusters of PT 8 occurred at different times of the year in the North West and South West regions. Phage type-specific differences in exposure settings, and spatial-temporal clustering of S. Enteritidis infections were demonstrated that might guide public health surveillance of disease outbreaks. Our study methodology could be applied to other foodborne disease surveillance data to detect retrospective high disease rate clusters, which could aid public health authorities in developing effective prevention and control programs.

Disentangling the multigenic and pleiotropic nature of molecular function

PubMed Central

2015-01-01

Background Biological processes at the molecular level are usually represented by molecular interaction networks. Function is organised and modularity identified based on network topology, however, this approach often fails to account for the dynamic and multifunctional nature of molecular components. For example, a molecule engaging in spatially or temporally independent functions may be inappropriately clustered into a single functional module. To capture biologically meaningful sets of interacting molecules, we use experimentally defined pathways as spatial/temporal units of molecular activity. Results We defined functional profiles of Saccharomyces cerevisiae based on a minimal set of Gene Ontology terms sufficient to represent each pathway's genes. The Gene Ontology terms were used to annotate 271 pathways, accounting for pathway multi-functionality and gene pleiotropy. Pathways were then arranged into a network, linked by shared functionality. Of the genes in our data set, 44% appeared in multiple pathways performing a diverse set of functions. Linking pathways by overlapping functionality revealed a modular network with energy metabolism forming a sparse centre, surrounded by several denser clusters comprised of regulatory and metabolic pathways. Signalling pathways formed a relatively discrete cluster connected to the centre of the network. Genetic interactions were enriched within the clusters of pathways by a factor of 5.5, confirming the organisation of our pathway network is biologically significant. Conclusions Our representation of molecular function according to pathway relationships enables analysis of gene/protein activity in the context of specific functional roles, as an alternative to typical molecule-centric graph-based methods. The pathway network demonstrates the cooperation of multiple pathways to perform biological processes and organises pathways into functionally related clusters with interdependent outcomes. PMID:26678917

Cortical substrates and functional correlates of auditory deviance processing deficits in schizophrenia

PubMed Central

Rissling, Anthony J.; Miyakoshi, Makoto; Sugar, Catherine A.; Braff, David L.; Makeig, Scott; Light, Gregory A.

2014-01-01

Although sensory processing abnormalities contribute to widespread cognitive and psychosocial impairments in schizophrenia (SZ) patients, scalp-channel measures of averaged event-related potentials (ERPs) mix contributions from distinct cortical source-area generators, diluting the functional relevance of channel-based ERP measures. SZ patients (n = 42) and non-psychiatric comparison subjects (n = 47) participated in a passive auditory duration oddball paradigm, eliciting a triphasic (Deviant−Standard) tone ERP difference complex, here termed the auditory deviance response (ADR), comprised of a mid-frontal mismatch negativity (MMN), P3a positivity, and re-orienting negativity (RON) peak sequence. To identify its cortical sources and to assess possible relationships between their response contributions and clinical SZ measures, we applied independent component analysis to the continuous 68-channel EEG data and clustered the resulting independent components (ICs) across subjects on spectral, ERP, and topographic similarities. Six IC clusters centered in right superior temporal, right inferior frontal, ventral mid-cingulate, anterior cingulate, medial orbitofrontal, and dorsal mid-cingulate cortex each made triphasic response contributions. Although correlations between measures of SZ clinical, cognitive, and psychosocial functioning and standard (Fz) scalp-channel ADR peak measures were weak or absent, for at least four IC clusters one or more significant correlations emerged. In particular, differences in MMN peak amplitude in the right superior temporal IC cluster accounted for 48% of the variance in SZ-subject performance on tasks necessary for real-world functioning and medial orbitofrontal cluster P3a amplitude accounted for 40%/54% of SZ-subject variance in positive/negative symptoms. Thus, source-resolved auditory deviance response measures including MMN may be highly sensitive to SZ clinical, cognitive, and functional characteristics. PMID:25379456

Significance of flow clustering and sequencing on sediment transport: 1D sediment transport modelling

NASA Astrophysics Data System (ADS)

Hassan, Kazi; Allen, Deonie; Haynes, Heather

2016-04-01

This paper considers 1D hydraulic model data on the effect of high flow clusters and sequencing on sediment transport. Using observed flow gauge data from the River Caldew, England, a novel stochastic modelling approach was developed in order to create alternative 50 year flow sequences. Whilst the observed probability density of gauge data was preserved in all sequences, the order in which those flows occurred was varied using the output from a Hidden Markov Model (HMM) with generalised Pareto distribution (GP). In total, one hundred 50 year synthetic flow series were generated and used as the inflow boundary conditions for individual flow series model runs using the 1D sediment transport model HEC-RAS. The model routed graded sediment through the case study river reach to define the long-term morphological changes. Comparison of individual simulations provided a detailed understanding of the sensitivity of channel capacity to flow sequence. Specifically, each 50 year synthetic flow sequence was analysed using a 3-month, 6-month or 12-month rolling window approach and classified for clusters in peak discharge. As a cluster is described as a temporal grouping of flow events above a specified threshold, the threshold condition used herein is considered as a morphologically active channel forming discharge event. Thus, clusters were identified for peak discharges in excess of 10%, 20%, 50%, 100% and 150% of the 1 year Return Period (RP) event. The window of above-peak flows also required cluster definition and was tested for timeframes 1, 2, 10 and 30 days. Subsequently, clusters could be described in terms of the number of events, maximum peak flow discharge, cumulative flow discharge and skewness (i.e. a description of the flow sequence). The model output for each cluster was analysed for the cumulative flow volume and cumulative sediment transport (mass). This was then compared to the total sediment transport of a single flow event of equivalent flow volume. Results illustrate that clustered flood events generated sediment loads up to an order of magnitude greater than that of individual events of the same flood volume. Correlations were significant for sediment volume compared to both maximum flow discharge (R2<0.8) and number of events (R2 -0.5 to -0.7) within the cluster. The strongest correlations occurred for clusters with a greater number of flow events only slightly above-threshold. This illustrates that the numerical model can capture a degree of the non-linear morphological response to flow magnitude. Analysis of the relationship between morphological change and the skewness of flow events within each cluster was also determined, illustrating only minor sensitivity to cluster peak distribution skewness. This is surprising and discussion is presented on model limitations, including the capability of sediment transport formulae to effectively account for temporal processes of antecedent flow, hysteresis, local supply etc.

Solar Wind/Magnetosphere/Ionosphere Coupling and the Temporal and Spatial Evolution of Boundary Layers using Cluster, Polar and other ISTP Satellites

NASA Technical Reports Server (NTRS)

Maynard, Nelson C.

2004-01-01

Our analysis concerns macro and meso-scale aspects of coupling between the IMF and the magnetosphere-ionosphere system, as opposed to the microphysics of determining how electron gyrotropy is broken and merging actually occurs. We correlate observed behaviors at Cluster and at Polar with temporal variations in other regions, such as in the ionosphere as measured by SuperDARN. Addressing problems with simultaneous observations from diverse locations properly constrains our interpretations.

A spatial approach for the epidemiology of antibiotic use and resistance in community-based studies: the emergence of urban clusters of Escherichia coli quinolone resistance in Sao Paulo, Brasil

PubMed Central

2011-01-01

Background Population antimicrobial use may influence resistance emergence. Resistance is an ecological phenomenon due to potential transmissibility. We investigated spatial and temporal patterns of ciprofloxacin (CIP) population consumption related to E. coli resistance emergence and dissemination in a major Brazilian city. A total of 4,372 urinary tract infection E. coli cases, with 723 CIP resistant, were identified in 2002 from two outpatient centres. Cases were address geocoded in a digital map. Raw CIP consumption data was transformed into usage density in DDDs by CIP selling points influence zones determination. A stochastic model coupled with a Geographical Information System was applied for relating resistance and usage density and for detecting city areas of high/low resistance risk. Results E. coli CIP resistant cluster emergence was detected and significantly related to usage density at a level of 5 to 9 CIP DDDs. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. Conclusions There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. The usage density of 5-9 CIP DDDs per 1,000 inhabitants within the same influence zone was the resistance triggering level. This level led to E. coli resistance clustering, proving that individual resistance emergence and dissemination was affected by antimicrobial population consumption. PMID:21356088

Exploring hotspots of pneumococcal pneumonia and potential impacts of ejecta dust exposure following the Christchurch earthquakes.

PubMed

Pearson, Amber L; Kingham, Simon; Mitchell, Peter; Apparicio, Philippe

2013-12-01

The etiology of pneumococcal pneumonia (PP) is well-known. Yet, some events may increase its incidence. Natural disasters may worsen air quality, a risk factor for PP. We investigated spatial/spatio-temporal clustering of PP pre- and post-earthquakes in Christchurch, New Zealand. The earthquakes resulted in deaths, widespread damage and liquefaction ejecta (a source of air-borne dust). We tested for clusters and associations with ejecta, using 97 cases (diagnosed 10/2008-12/2011), adjusted for age and area-level deprivation. The strongest evidence to support the potential role of ejecta in clusters of PP cases was the: (1) geographic shift in the spatio-temporal cluster after deprivation adjustment to match the post-earthquake clusters and; (2) increased relative risk in the fully-adjusted post-earthquake compared to the pre-earthquake cluster. The application of spatial statistics to study PP and ejecta are novel. Further studies to assess the long-term impacts of ejecta inhalation are recommended particularly in Christchurch, where seismic activity continues. Copyright © 2013 Elsevier Ltd. All rights reserved.

Analysis of temporal gene expression profiles: clustering by simulated annealing and determining the optimal number of clusters.

PubMed

Lukashin, A V; Fuchs, R

2001-05-01

Cluster analysis of genome-wide expression data from DNA microarray hybridization studies has proved to be a useful tool for identifying biologically relevant groupings of genes and samples. In the present paper, we focus on several important issues related to clustering algorithms that have not yet been fully studied. We describe a simple and robust algorithm for the clustering of temporal gene expression profiles that is based on the simulated annealing procedure. In general, this algorithm guarantees to eventually find the globally optimal distribution of genes over clusters. We introduce an iterative scheme that serves to evaluate quantitatively the optimal number of clusters for each specific data set. The scheme is based on standard approaches used in regular statistical tests. The basic idea is to organize the search of the optimal number of clusters simultaneously with the optimization of the distribution of genes over clusters. The efficiency of the proposed algorithm has been evaluated by means of a reverse engineering experiment, that is, a situation in which the correct distribution of genes over clusters is known a priori. The employment of this statistically rigorous test has shown that our algorithm places greater than 90% genes into correct clusters. Finally, the algorithm has been tested on real gene expression data (expression changes during yeast cell cycle) for which the fundamental patterns of gene expression and the assignment of genes to clusters are well understood from numerous previous studies.

Investigation of Spatial and Temporal Trends in Water Quality in Daya Bay, South China Sea

PubMed Central

Wu, Mei-Lin; Wang, You-Shao; Dong, Jun-De; Sun, Cui-Ci; Wang, Yu-Tu; Sun, Fu-Lin; Cheng, Hao

2011-01-01

The objective is to identify the spatial and temporal variability of the hydrochemical quality of the water column in a subtropical coastal system, Daya Bay, China. Water samples were collected in four seasons at 12 monitoring sites. The Southeast Asian monsoons, northeasterly from October to the next April and southwesterly from May to September have also an important influence on water quality in Daya Bay. In the spatial pattern, two groups have been identified, with the help of multidimensional scaling analysis and cluster analysis. Cluster I consisted of the sites S3, S8, S10 and S11 in the west and north coastal parts of Daya Bay. Cluster I is mainly related to anthropogenic activities such as fish-farming. Cluster II consisted of the rest of the stations in the center, east and south parts of Daya Bay. Cluster II is mainly related to seawater exchange from South China Sea. PMID:21776234

Time-Hierarchical Clustering and Visualization of Weather Forecast Ensembles.

PubMed

Ferstl, Florian; Kanzler, Mathias; Rautenhaus, Marc; Westermann, Rudiger

2017-01-01

We propose a new approach for analyzing the temporal growth of the uncertainty in ensembles of weather forecasts which are started from perturbed but similar initial conditions. As an alternative to traditional approaches in meteorology, which use juxtaposition and animation of spaghetti plots of iso-contours, we make use of contour clustering and provide means to encode forecast dynamics and spread in one single visualization. Based on a given ensemble clustering in a specified time window, we merge clusters in time-reversed order to indicate when and where forecast trajectories start to diverge. We present and compare different visualizations of the resulting time-hierarchical grouping, including space-time surfaces built by connecting cluster representatives over time, and stacked contour variability plots. We demonstrate the effectiveness of our visual encodings with forecast examples of the European Centre for Medium-Range Weather Forecasts, which convey the evolution of specific features in the data as well as the temporally increasing spatial variability.

Spatiotemporal earthquake clusters along the North Anatolian fault zone offshore Istanbul

USGS Publications Warehouse

Bulut, Fatih; Ellsworth, William L.; Bohnhoff, Marco; Aktar, Mustafa; Dresen, Georg

2011-01-01

We investigate earthquakes with similar waveforms in order to characterize spatiotemporal microseismicity clusters within the North Anatolian fault zone (NAFZ) in northwest Turkey along the transition between the 1999 ??zmit rupture zone and the Marmara Sea seismic gap. Earthquakes within distinct activity clusters are relocated with cross-correlation derived relative travel times using the double difference method. The spatiotemporal distribution of micro earthquakes within individual clusters is resolved with relative location accuracy comparable to or better than the source size. High-precision relative hypocenters define the geometry of individual fault patches, permitting a better understanding of fault kinematics and their role in local-scale seismotectonics along the region of interest. Temporal seismic sequences observed in the eastern Sea of Marmara region suggest progressive failure of mostly nonoverlapping areas on adjacent fault patches and systematic migration of microearthquakes within clusters during the progressive failure of neighboring fault patches. The temporal distributions of magnitudes as well as the number of events follow swarmlike behavior rather than a mainshock/aftershock pattern.

Cluster Adjusted Regression for Displaced Subject Data (CARDS): Marginal Inference under Potentially Informative Temporal Cluster Size Profiles

PubMed Central

Bible, Joe; Beck, James D.; Datta, Somnath

2016-01-01

Summary Ignorance of the mechanisms responsible for the availability of information presents an unusual problem for analysts. It is often the case that the availability of information is dependent on the outcome. In the analysis of cluster data we say that a condition for informative cluster size (ICS) exists when the inference drawn from analysis of hypothetical balanced data varies from that of inference drawn on observed data. Much work has been done in order to address the analysis of clustered data with informative cluster size; examples include Inverse Probability Weighting (IPW), Cluster Weighted Generalized Estimating Equations (CWGEE), and Doubly Weighted Generalized Estimating Equations (DWGEE). When cluster size changes with time, i.e., the data set possess temporally varying cluster sizes (TVCS), these methods may produce biased inference for the underlying marginal distribution of interest. We propose a new marginalization that may be appropriate for addressing clustered longitudinal data with TVCS. The principal motivation for our present work is to analyze the periodontal data collected by Beck et al. (1997, Journal of Periodontal Research 6, 497–505). Longitudinal periodontal data often exhibits both ICS and TVCS as the number of teeth possessed by participants at the onset of study is not constant and teeth as well as individuals may be displaced throughout the study. PMID:26682911

Clustering the lexicon in the brain: a meta-analysis of the neurofunctional evidence on noun and verb processing

PubMed Central

Crepaldi, Davide; Berlingeri, Manuela; Cattinelli, Isabella; Borghese, Nunzio A.; Luzzatti, Claudio; Paulesu, Eraldo

2013-01-01

Although it is widely accepted that nouns and verbs are functionally independent linguistic entities, it is less clear whether their processing recruits different brain areas. This issue is particularly relevant for those theories of lexical semantics (and, more in general, of cognition) that suggest the embodiment of abstract concepts, i.e., based strongly on perceptual and motoric representations. This paper presents a formal meta-analysis of the neuroimaging evidence on noun and verb processing in order to address this dichotomy more effectively at the anatomical level. We used a hierarchical clustering algorithm that grouped fMRI/PET activation peaks solely on the basis of spatial proximity. Cluster specificity for grammatical class was then tested on the basis of the noun-verb distribution of the activation peaks included in each cluster. Thirty-two clusters were identified: three were associated with nouns across different tasks (in the right inferior temporal gyrus, the left angular gyrus, and the left inferior parietal gyrus); one with verbs across different tasks (in the posterior part of the right middle temporal gyrus); and three showed verb specificity in some tasks and noun specificity in others (in the left and right inferior frontal gyrus and the left insula). These results do not support the popular tenets that verb processing is predominantly based in the left frontal cortex and noun processing relies specifically on temporal regions; nor do they support the idea that verb lexical-semantic representations are heavily based on embodied motoric information. Our findings suggest instead that the cerebral circuits deputed to noun and verb processing lie in close spatial proximity in a wide network including frontal, parietal, and temporal regions. The data also indicate a predominant—but not exclusive—left lateralization of the network. PMID:23825451

Identification of repeating earthquakes and spatio-temporal variations of fault zone properties around the Parkfield section of the San Andreas fault and the central Calaveras fault

NASA Astrophysics Data System (ADS)

Zhao, P.; Peng, Z.

2008-12-01

We systemically identify repeating earthquakes and investigate spatio-temporal variations of fault zone properties associated with the 2004 Mw6.0 Parkfield earthquake along the Parkfield section of the San Andreas fault, and the 1984 Mw6.2 Morgan Hill earthquake along the central Calaveras fault. The procedure for identifying repeating earthquakes is based on overlapping of the source regions and the waveform similarity, and is briefly described as follows. First, we estimate the source radius of each event based on a circular crack model and a normal stress drop of 3 MPa. Next, we compute inter-hypocentral distance for events listed in the relocated catalog of Thurber et al. (2006) around Parkfield, and Schaff et al. (2002) along the Calaveras fault. Then, we group all events into 'initial' clusters by requiring the separation distance between each event pair to be less than the source radius of larger event, and their magnitude difference to be less than 1. Next, we calculate the correlation coefficients between every event pair within each 'initial' cluster using a 3-s time window around the direct P waves for all available stations. The median value of the correlation coefficients is used as a measure of similarity between each event pair. We drop an event if the median similarity to the rest events in that cluster is less than 0.9. After identifying repeating clusters in both regions, our next step is to apply a sliding window waveform cross-correlation technique (Niu et al., 2003; Peng and Ben-Zion, 2006) to calculate the delay time and decorrelation index for each repeating cluster. By measuring temporal changes in waveforms of repeating clusters at different locations and depth, we hope to obtain a better constraint on spatio-temporal variations of fault zone properties and near-surface layers associated with the occurrence of major earthquakes.

Historic changes in fish assemblage structure in midwestern nonwadeable rivers

USGS Publications Warehouse

Parks, Timothy P.; Quist, Michael C.; Pierce, Clay L.

2014-01-01

Historical change in fish assemblage structure was evaluated in the mainstems of the Des Moines, Iowa, Cedar, Wapsipinicon, and Maquoketa rivers, in Iowa. Fish occurrence data were compared in each river between historical and recent time periods to characterize temporal changes among 126 species distributions and assess spatiotemporal patterns in faunal similarity. A resampling procedure was used to estimate species occurrences in rivers during each assessment period and changes in species occurrence were summarized. Spatiotemporal shifts in species composition were analyzed at the river and river section scale using cluster analysis, pairwise Jaccard's dissimilarities, and analysis of multivariate beta dispersion. The majority of species exhibited either increases or declines in distribution in all rivers with the exception of several “unknown” or inconclusive trends exhibited by species in the Maquoketa River. Cluster analysis identified temporal patterns of similarity among fish assemblages in the Des Moines, Cedar, and Iowa rivers within the historical and recent assessment period indicating a significant change in species composition. Prominent declines of backwater species with phytophilic spawning strategies contributed to assemblage changes occurring across river systems.

The absoluteness of semantic processing: lessons from the analysis of temporal clusters in phonemic verbal fluency.

PubMed

Vonberg, Isabelle; Ehlen, Felicitas; Fromm, Ortwin; Klostermann, Fabian

2014-01-01

For word production, we may consciously pursue semantic or phonological search strategies, but it is uncertain whether we can retrieve the different aspects of lexical information independently from each other. We therefore studied the spread of semantic information into words produced under exclusively phonemic task demands. 42 subjects participated in a letter verbal fluency task, demanding the production of as many s-words as possible in two minutes. Based on curve fittings for the time courses of word production, output spurts (temporal clusters) considered to reflect rapid lexical retrieval based on automatic activation spread, were identified. Semantic and phonemic word relatedness within versus between these clusters was assessed by respective scores (0 meaning no relation, 4 maximum relation). Subjects produced 27.5 (±9.4) words belonging to 6.7 (±2.4) clusters. Both phonemically and semantically words were more related within clusters than between clusters (phon: 0.33±0.22 vs. 0.19±0.17, p<.01; sem: 0.65±0.29 vs. 0.37±0.29, p<.01). Whereas the extent of phonemic relatedness correlated with high task performance, the contrary was the case for the extent of semantic relatedness. The results indicate that semantic information spread occurs, even if the consciously pursued word search strategy is purely phonological. This, together with the negative correlation between semantic relatedness and verbal output suits the idea of a semantic default mode of lexical search, acting against rapid task performance in the given scenario of phonemic verbal fluency. The simultaneity of enhanced semantic and phonemic word relatedness within the same temporal cluster boundaries suggests an interaction between content and sound-related information whenever a new semantic field has been opened.

Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques

NASA Astrophysics Data System (ADS)

Gulgundi, Mohammad Shahid; Shetty, Amba

2018-03-01

Groundwater quality deterioration due to anthropogenic activities has become a subject of prime concern. The objective of the study was to assess the spatial and temporal variations in groundwater quality and to identify the sources in the western half of the Bengaluru city using multivariate statistical techniques. Water quality index rating was calculated for pre and post monsoon seasons to quantify overall water quality for human consumption. The post-monsoon samples show signs of poor quality in drinking purpose compared to pre-monsoon. Cluster analysis (CA), principal component analysis (PCA) and discriminant analysis (DA) were applied to the groundwater quality data measured on 14 parameters from 67 sites distributed across the city. Hierarchical cluster analysis (CA) grouped the 67 sampling stations into two groups, cluster 1 having high pollution and cluster 2 having lesser pollution. Discriminant analysis (DA) was applied to delineate the most meaningful parameters accounting for temporal and spatial variations in groundwater quality of the study area. Temporal DA identified pH as the most important parameter, which discriminates between water quality in the pre-monsoon and post-monsoon seasons and accounts for 72% seasonal assignation of cases. Spatial DA identified Mg, Cl and NO3 as the three most important parameters discriminating between two clusters and accounting for 89% spatial assignation of cases. Principal component analysis was applied to the dataset obtained from the two clusters, which evolved three factors in each cluster, explaining 85.4 and 84% of the total variance, respectively. Varifactors obtained from principal component analysis showed that groundwater quality variation is mainly explained by dissolution of minerals from rock water interactions in the aquifer, effect of anthropogenic activities and ion exchange processes in water.

Genetic effect of interleukin-1 beta (C-511T) polymorphism on the structural covariance network and white matter integrity in Alzheimer's disease.

PubMed

Huang, Chi-Wei; Hsu, Shih-Wei; Tsai, Shih-Jen; Chen, Nai-Ching; Liu, Mu-En; Lee, Chen-Chang; Huang, Shu-Hua; Chang, Weng-Neng; Chang, Ya-Ting; Tsai, Wan-Chen; Chang, Chiung-Chih

2017-01-18

Inflammatory processes play a pivotal role in the degenerative process of Alzheimer's disease. In humans, a biallelic (C/T) polymorphism in the promoter region (position-511) (rs16944) of the interleukin-1 beta gene has been significantly associated with differences in the secretory capacity of interleukin-1 beta. In this study, we investigated whether this functional polymorphism mediates the brain networks in patients with Alzheimer's disease. We enrolled a total of 135 patients with Alzheimer's disease (65 males, 70 females), and investigated their gray matter structural covariance networks using 3D T1 magnetic resonance imaging and their white matter macro-structural integrities using fractional anisotropy. The patients were classified into two genotype groups: C-carriers (n = 108) and TT-carriers (n = 27), and the structural covariance networks were constructed using seed-based analysis focusing on the default mode network medial temporal or dorsal medial subsystem, salience network and executive control network. Neurobehavioral scores were used as the major outcome factors for clinical correlations. There were no differences between the two genotype groups in the cognitive test scores, seed, or peak cluster volumes and white matter fractional anisotropy. The covariance strength showing C-carriers > TT-carriers was the entorhinal-cingulum axis. There were two peak clusters (Brodmann 6 and 10) in the salience network and four peak clusters (superior prefrontal, precentral, fusiform, and temporal) in the executive control network that showed C-carriers < TT-carriers in covariance strength. The salience network and executive control network peak clusters in the TT group and the default mode network peak clusters in the C-carriers strongly predicted the cognitive test scores. Interleukin-1 beta C-511 T polymorphism modulates the structural covariance strength on the anterior brain network and entorhinal-interconnected network which were independent of the white matter tract integrity. Depending on the specific C-511 T genotype, different network clusters could predict the cognitive tests.

Cluster of atypical adult Guillain-Barré syndrome temporally associated with neurological illness due to EV-D68 in children, South Wales, United Kingdom, October 2015 to January 2016.

PubMed

Williams, Christopher J; Thomas, Rhys H; Pickersgill, Trevor P; Lyons, Marion; Lowe, Gwen; Stiff, Rhianwen E; Moore, Catherine; Jones, Rachel; Howe, Robin; Brunt, Huw; Ashman, Anna; Mason, Brendan W

2016-01-01

We report a cluster of atypical Guillain-Barré syndrome in 10 adults temporally related to a cluster of four children with acute flaccid paralysis, over a 3-month period in South Wales, United Kingdom. All adult cases were male, aged between 24 and 77 years. Seven had prominent facial diplegia at onset. Available electrophysiological studies showed axonal involvement in five adults. Seven reported various forms of respiratory disease before onset of neurological symptoms. The ages of children ranged from one to 13 years, three of the four were two years old or younger. Enterovirus testing is available for three children; two had evidence of enterovirus D68 infection in stool or respiratory samples. We describe the clinical features, epidemiology and state of current investigations for these unusual clusters of illness.

Big Data GPU-Driven Parallel Processing Spatial and Spatio-Temporal Clustering Algorithms

NASA Astrophysics Data System (ADS)

Konstantaras, Antonios; Skounakis, Emmanouil; Kilty, James-Alexander; Frantzeskakis, Theofanis; Maravelakis, Emmanuel

2016-04-01

Advances in graphics processing units' technology towards encompassing parallel architectures [1], comprised of thousands of cores and multiples of parallel threads, provide the foundation in terms of hardware for the rapid processing of various parallel applications regarding seismic big data analysis. Seismic data are normally stored as collections of vectors in massive matrices, growing rapidly in size as wider areas are covered, denser recording networks are being established and decades of data are being compiled together [2]. Yet, many processes regarding seismic data analysis are performed on each seismic event independently or as distinct tiles [3] of specific grouped seismic events within a much larger data set. Such processes, independent of one another can be performed in parallel narrowing down processing times drastically [1,3]. This research work presents the development and implementation of three parallel processing algorithms using Cuda C [4] for the investigation of potentially distinct seismic regions [5,6] present in the vicinity of the southern Hellenic seismic arc. The algorithms, programmed and executed in parallel comparatively, are the: fuzzy k-means clustering with expert knowledge [7] in assigning overall clusters' number; density-based clustering [8]; and a selves-developed spatio-temporal clustering algorithm encompassing expert [9] and empirical knowledge [10] for the specific area under investigation. Indexing terms: GPU parallel programming, Cuda C, heterogeneous processing, distinct seismic regions, parallel clustering algorithms, spatio-temporal clustering References [1] Kirk, D. and Hwu, W.: 'Programming massively parallel processors - A hands-on approach', 2nd Edition, Morgan Kaufman Publisher, 2013 [2] Konstantaras, A., Valianatos, F., Varley, M.R. and Makris, J.P.: 'Soft-Computing Modelling of Seismicity in the Southern Hellenic Arc', Geoscience and Remote Sensing Letters, vol. 5 (3), pp. 323-327, 2008 [3] Papadakis, S. and Diamantaras, K.: 'Programming and architecture of parallel processing systems', 1st Edition, Eds. Kleidarithmos, 2011 [4] NVIDIA.: 'NVidia CUDA C Programming Guide', version 5.0, NVidia (reference book) [5] Konstantaras, A.: 'Classification of Distinct Seismic Regions and Regional Temporal Modelling of Seismicity in the Vicinity of the Hellenic Seismic Arc', IEEE Selected Topics in Applied Earth Observations and Remote Sensing, vol. 6 (4), pp. 1857-1863, 2013 [6] Konstantaras, A. Varley, M.R.,. Valianatos, F., Collins, G. and Holifield, P.: 'Recognition of electric earthquake precursors using neuro-fuzzy models: methodology and simulation results', Proc. IASTED International Conference on Signal Processing Pattern Recognition and Applications (SPPRA 2002), Crete, Greece, 2002, pp 303-308, 2002 [7] Konstantaras, A., Katsifarakis, E., Maravelakis, E., Skounakis, E., Kokkinos, E. and Karapidakis, E.: 'Intelligent Spatial-Clustering of Seismicity in the Vicinity of the Hellenic Seismic Arc', Earth Science Research, vol. 1 (2), pp. 1-10, 2012 [8] Georgoulas, G., Konstantaras, A., Katsifarakis, E., Stylios, C.D., Maravelakis, E. and Vachtsevanos, G.: '"Seismic-Mass" Density-based Algorithm for Spatio-Temporal Clustering', Expert Systems with Applications, vol. 40 (10), pp. 4183-4189, 2013 [9] Konstantaras, A. J.: 'Expert knowledge-based algorithm for the dynamic discrimination of interactive natural clusters', Earth Science Informatics, 2015 (In Press, see: www.scopus.com) [10] Drakatos, G. and Latoussakis, J.: 'A catalog of aftershock sequences in Greece (1971-1997): Their spatial and temporal characteristics', Journal of Seismology, vol. 5, pp. 137-145, 2001

Toeplitz Inverse Covariance-Based Clustering of Multivariate Time Series Data

PubMed Central

Hallac, David; Vare, Sagar; Boyd, Stephen; Leskovec, Jure

2018-01-01

Subsequence clustering of multivariate time series is a useful tool for discovering repeated patterns in temporal data. Once these patterns have been discovered, seemingly complicated datasets can be interpreted as a temporal sequence of only a small number of states, or clusters. For example, raw sensor data from a fitness-tracking application can be expressed as a timeline of a select few actions (i.e., walking, sitting, running). However, discovering these patterns is challenging because it requires simultaneous segmentation and clustering of the time series. Furthermore, interpreting the resulting clusters is difficult, especially when the data is high-dimensional. Here we propose a new method of model-based clustering, which we call Toeplitz Inverse Covariance-based Clustering (TICC). Each cluster in the TICC method is defined by a correlation network, or Markov random field (MRF), characterizing the interdependencies between different observations in a typical subsequence of that cluster. Based on this graphical representation, TICC simultaneously segments and clusters the time series data. We solve the TICC problem through alternating minimization, using a variation of the expectation maximization (EM) algorithm. We derive closed-form solutions to efficiently solve the two resulting subproblems in a scalable way, through dynamic programming and the alternating direction method of multipliers (ADMM), respectively. We validate our approach by comparing TICC to several state-of-the-art baselines in a series of synthetic experiments, and we then demonstrate on an automobile sensor dataset how TICC can be used to learn interpretable clusters in real-world scenarios. PMID:29770257

Clustering Timber Harvests and the Effects of Dynamic Forest Management Policy on Forest Fragmentation

Treesearch

Eric J. Gustafson

1998-01-01

To integrate multiple uses (mature forest and commodity production) better on forested lands, timber management strategies that cluster harvests have been proposed. One such approach clusters harvest activity in space and time, and rotates timber production zones across the landscape with a long temporal period (dynamic zoning). Dynamic zoning has...

Quantitative and qualitative analysis of semantic verbal fluency in patients with temporal lobe epilepsy.

PubMed

Jaimes-Bautista, A G; Rodríguez-Camacho, M; Martínez-Juárez, I E; Rodríguez-Agudelo, Y

2017-08-29

Patients with temporal lobe epilepsy (TLE) perform poorly on semantic verbal fluency (SVF) tasks. Completing these tasks successfully involves multiple cognitive processes simultaneously. Therefore, quantitative analysis of SVF (number of correct words in one minute), conducted in most studies, has been found to be insufficient to identify cognitive dysfunction underlying SVF difficulties in TLE. To determine whether a sample of patients with TLE had SVF difficulties compared with a control group (CG), and to identify the cognitive components associated with SVF difficulties using quantitative and qualitative analysis. SVF was evaluated in 25 patients with TLE and 24 healthy controls; the semantic verbal fluency test included 5 semantic categories: animals, fruits, occupations, countries, and verbs. All 5 categories were analysed quantitatively (number of correct words per minute and interval of execution: 0-15, 16-30, 31-45, and 46-60seconds); the categories animals and fruits were also analysed qualitatively (clusters, cluster size, switches, perseverations, and intrusions). Patients generated fewer words for all categories and intervals and fewer clusters and switches for animals and fruits than the CG (P<.01). Differences between groups were not significant in terms of cluster size and number of intrusions and perseverations (P>.05). Our results suggest an association between SVF difficulties in TLE and difficulty activating semantic networks, impaired strategic search, and poor cognitive flexibility. Attention, inhibition, and working memory are preserved in these patients. Copyright © 2017 Sociedad Española de Neurología. Publicado por Elsevier España, S.L.U. All rights reserved.

Temporal Changes in Gene Expression after Injury in the Rat Retina

PubMed Central

Vázquez-Chona, Félix; Song, Bong K.; Geisert, Eldon E.

2010-01-01

Purpose The goal of this study was to define the temporal changes in gene expression after retinal injury and to relate these changes to the inflammatory and reactive response. A specific emphasis was placed on the tetraspanin family of proteins and their relationship with markers of reactive gliosis. Methods Retinal tears were induced in adult rats by scraping the retina with a needle. After different survival times (4 hours, and 1, 3, 7, and 30 days), the retinas were removed, and mRNA was isolated, prepared, and hybridized to the Affymatrix RGU34A microarray (Santa Clara, CA). Microarray results were confirmed by using RT-PCR and correlation to protein levels was determined. Results Of the 8750 genes analyzed, approximately 393 (4.5%) were differentially expressed. Clustering analysis revealed three major profiles: (1) The early response was characterized by the upregulation of transcription factors; (2) the delayed response included a high percentage of genes related to cell cycle and cell death; and (3) the late, sustained profile clustered a significant number of genes involved in retinal gliosis. The late, sustained cluster also contained the upregulated crystallin genes. The tetraspanins Cd9, Cd81, and Cd82 were also associated with the late, sustained response. Conclusions The use of microarray technology enables definition of complex genetic changes underlying distinct phases of the cellular response to retinal injury. The early response clusters genes associate with the transcriptional regulation of the wound-healing process and cell death. Most of the genes in the late, sustained response appear to be associated with reactive gliosis. PMID:15277499

Meteor tracking via local pattern clustering in spatio-temporal domain

NASA Astrophysics Data System (ADS)

Kukal, Jaromír.; Klimt, Martin; Švihlík, Jan; Fliegel, Karel

2016-09-01

Reliable meteor detection is one of the crucial disciplines in astronomy. A variety of imaging systems is used for meteor path reconstruction. The traditional approach is based on analysis of 2D image sequences obtained from a double station video observation system. Precise localization of meteor path is difficult due to atmospheric turbulence and other factors causing spatio-temporal fluctuations of the image background. The proposed technique performs non-linear preprocessing of image intensity using Box-Cox transform as recommended in our previous work. Both symmetric and asymmetric spatio-temporal differences are designed to be robust in the statistical sense. Resulting local patterns are processed by data whitening technique and obtained vectors are classified via cluster analysis and Self-Organized Map (SOM).

Spatio-temporal pattern of viral meningitis in Michigan, 1993-2001

NASA Astrophysics Data System (ADS)

Greene, Sharon K.; Schmidt, Mark A.; Stobierski, Mary Grace; Wilson, Mark L.

2005-05-01

To characterize Michigan's high viral meningitis incidence rates, 8,803 cases from 1993-2001 were analyzed for standard epidemiological indices, geographic distribution, and spatio-temporal clusters. Blacks and infants were found to be high-risk groups. Annual seasonality and interannual variability in epidemic magnitude were apparent. Cases were concentrated in southern Michigan, and cumulative incidence was correlated with population density at the county level (r=0.45, p<0.001). Kulldorff's Scan test identified the occurrence of spatio-temporal clusters in Lower Michigan during July-October 1998 and 2001 (p=0.01). More extensive data on cases, laboratory isolates, sociodemographics, and environmental exposures should improve detection and enhance the effectiveness of a Space-Time Information System aimed at prevention.

Functional and structural brain correlates of theory of mind and empathy deficits in schizophrenia.

PubMed

Benedetti, Francesco; Bernasconi, Alessandro; Bosia, Marta; Cavallaro, Roberto; Dallaspezia, Sara; Falini, Andrea; Poletti, Sara; Radaelli, Daniele; Riccaboni, Roberta; Scotti, Giuseppe; Smeraldi, Enrico

2009-10-01

Patients affected by schizophrenia show deficits in social cognition, with abnormal performance on tasks targeting theory of mind (ToM) and empathy (Emp). Brain imaging studies suggested that ToM and Emp depend on the activation of brain networks mainly localized at the superior temporal lobe and temporo-parietal junction. Participants included 24 schizophrenia patients and 20 control subjects. We used brain blood oxygen level dependent fMRI to study the neural responses to tasks targeting ToM and Emp. We then studied voxel-based morphometry of grey matter in areas where diagnosis influenced functional activation to both tasks. Outcomes were analyzed in the context of the general linear model, with global grey matter volume as nuisance covariate for structural MRI. Patients showed worse performance on both tasks. We found significant effects of diagnosis on neural responses to the tasks in a wide cluster in right posterior superior temporal lobe (encompassing BA 22-42), in smaller clusters in left temporo-parietal junction and temporal pole (BA 38 and 39), and in a white matter region adjacent to medial prefrontal cortex (BA 10). A pattern of double dissociation of the effects of diagnosis and task on neural responses emerged. Among these areas, grey matter volume was found to be reduced in right superior temporal lobe regions of patients. Functional and structural abnormalities were observed in areas affected by the schizophrenic process early in the illness course, and known to be crucial for social cognition, suggesting a biological basis for social cognition deficits in schizophrenia.

A temporal study of Salmonella serovars in animals in Alberta between 1990 and 2001

PubMed Central

2005-01-01

Abstract Passive laboratory-based surveillance data from Alberta Agriculture Food and Rural Development were analyzed for common Salmonella serovars, prevalences, trends, and for the presence of temporal clusters. There were 1767 isolates between October 1990 and December 2001 comprising 63 different serovars, including 961 isolates from chickens, 418 from cattle, 108 from pigs, 102 from turkeys, and 178 from all other species combined. Salmonella Typhimurium, Heidelberg, Hadar, Kentucky, and Thompson were the 5 most frequently isolated serovars. Approximately 60% of the S. Typhimurium were isolated from cattle, whereas over 90% of the S. Heidelberg, Hadar, Kentucky, and Thompson were isolated from chickens. Salmonella Enteritidis was rarely isolated. There was an increasing trend in isolates from chickens, cattle, and pigs, and a decreasing trend in isolates from turkeys. Temporal clusters were observed in 11 of 15 serovars examined in chickens (S. Anatum, Heidelberg, Infantis, Kentucky, Mbandaka, Montevideo, Nienstedten, Oranienburg, Thompson, Typhimurium, and Typhimurium var. Copenhagen), 5 of 5 serovars in cattle (S. Dublin, Montevideo, Muenster, Typhimurium, and Typhimurium var. Copenhagen), and 1 of 3 serovars in pigs (S. Typhimurium). Short-duration clusters may imply point source infections, whereas long-duration clusters may indicate an increase in the prevalence of the serovar, farm-to-farm transmission, or a wide-spread common source. A higher concentration of clusters in the winter months may reflect greater confinement, reduced ventilation, stressors, or increased exposure to wildlife vectors that are sharing housing during the winter. Detection of large clusters of Salmonella may have public health implications in addition to animal health concerns. PMID:15971672

Spatial and temporal patterns of locally-acquired dengue transmission in northern Queensland, Australia, 1993-2012.

PubMed

Naish, Suchithra; Dale, Pat; Mackenzie, John S; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992-1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993-2012. Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ(2) = 15.17, d.f.  = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas.

Spatial and Temporal Patterns of Locally-Acquired Dengue Transmission in Northern Queensland, Australia, 1993–2012

PubMed Central

Naish, Suchithra; Dale, Pat; Mackenzie, John S.; McBride, John; Mengersen, Kerrie; Tong, Shilu

2014-01-01

Background Dengue has been a major public health concern in Australia since it re-emerged in Queensland in 1992–1993. We explored spatio-temporal characteristics of locally-acquired dengue cases in northern tropical Queensland, Australia during the period 1993–2012. Methods Locally-acquired notified cases of dengue were collected for northern tropical Queensland from 1993 to 2012. Descriptive spatial and temporal analyses were conducted using geographic information system tools and geostatistical techniques. Results 2,398 locally-acquired dengue cases were recorded in northern tropical Queensland during the study period. The areas affected by the dengue cases exhibited spatial and temporal variation over the study period. Notified cases of dengue occurred more frequently in autumn. Mapping of dengue by statistical local areas (census units) reveals the presence of substantial spatio-temporal variation over time and place. Statistically significant differences in dengue incidence rates among males and females (with more cases in females) (χ2 = 15.17, d.f. = 1, p<0.01). Differences were observed among age groups, but these were not statistically significant. There was a significant positive spatial autocorrelation of dengue incidence for the four sub-periods, with the Moran's I statistic ranging from 0.011 to 0.463 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the northern Queensland. Conclusions Tropical areas are potential high-risk areas for mosquito-borne diseases such as dengue. This study demonstrated that the locally-acquired dengue cases have exhibited a spatial and temporal variation over the past twenty years in northern tropical Queensland, Australia. Therefore, this study provides an impetus for further investigation of clusters and risk factors in these high-risk areas. PMID:24691549

GPI-anchored proteins are confined in subdiffraction clusters at the apical surface of polarized epithelial cells

PubMed Central

Paladino, Simona; Lebreton, Stéphanie; Lelek, Mickaël; Riccio, Patrizia; De Nicola, Sergio; Zimmer, Christophe

2017-01-01

Spatio-temporal compartmentalization of membrane proteins is critical for the regulation of diverse vital functions in eukaryotic cells. It was previously shown that, at the apical surface of polarized MDCK cells, glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are organized in small cholesterol-independent clusters of single GPI-AP species (homoclusters), which are required for the formation of larger cholesterol-dependent clusters formed by multiple GPI-AP species (heteroclusters). This clustered organization is crucial for the biological activities of GPI-APs; hence, understanding the spatio-temporal properties of their membrane organization is of fundamental importance. Here, by using direct stochastic optical reconstruction microscopy coupled to pair correlation analysis (pc-STORM), we were able to visualize and measure the size of these clusters. Specifically, we show that they are non-randomly distributed and have an average size of 67 nm. We also demonstrated that polarized MDCK and non-polarized CHO cells have similar cluster distribution and size, but different sensitivity to cholesterol depletion. Finally, we derived a model that allowed a quantitative characterization of the cluster organization of GPI-APs at the apical surface of polarized MDCK cells for the first time. Experimental FRET (fluorescence resonance energy transfer)/FLIM (fluorescence-lifetime imaging microscopy) data were correlated to the theoretical predictions of the model. PMID:29046391

Earthquake Clusters and Spatio-temporal Migration of earthquakes in Northeastern Tibetan Plateau: a Finite Element Modeling

NASA Astrophysics Data System (ADS)

Sun, Y.; Luo, G.

2017-12-01

Seismicity in a region is usually characterized by earthquake clusters and earthquake migration along its major fault zones. However, we do not fully understand why and how earthquake clusters and spatio-temporal migration of earthquakes occur. The northeastern Tibetan Plateau is a good example for us to investigate these problems. In this study, we construct and use a three-dimensional viscoelastoplastic finite-element model to simulate earthquake cycles and spatio-temporal migration of earthquakes along major fault zones in northeastern Tibetan Plateau. We calculate stress evolution and fault interactions, and explore effects of topographic loading and viscosity of middle-lower crust and upper mantle on model results. Model results show that earthquakes and fault interactions increase Coulomb stress on the neighboring faults or segments, accelerating the future earthquakes in this region. Thus, earthquakes occur sequentially in a short time, leading to regional earthquake clusters. Through long-term evolution, stresses on some seismogenic faults, which are far apart, may almost simultaneously reach the critical state of fault failure, probably also leading to regional earthquake clusters and earthquake migration. Based on our model synthetic seismic catalog and paleoseismic data, we analyze probability of earthquake migration between major faults in northeastern Tibetan Plateau. We find that following the 1920 M 8.5 Haiyuan earthquake and the 1927 M 8.0 Gulang earthquake, the next big event (M≥7) in northeastern Tibetan Plateau would be most likely to occur on the Haiyuan fault.

Exploring Lightning Jump Characteristics

NASA Technical Reports Server (NTRS)

Chronis, Themis; Carey, Larry D.; Schultz, Christopher J.; Schultz, Elise; Calhoun, Kristin; Goodman, Steven J.

2014-01-01

This study is concerned with the characteristics of storms exhibiting an abrupt temporal increase in the total lightning flash rate (i.e., lightning jump, LJ). An automated storm tracking method is used to identify storm "clusters" and total lightning activity from three different lightning detection systems over Oklahoma, northern Alabama and Washington, D.C. On average and for different employed thresholds, the clusters that encompass at least one LJ (LJ1) last longer, relate to higher Maximum Expected Size of Hail, Vertical Integrated Liquid and lightning flash rates (area-normalized) than the clusters that did not exhibit any LJ (LJ0). The respective mean values for LJ1 (LJ0) clusters are 80 min (35 min), 14 mm (8 mm), 25 kg per square meter (18 kg per square meter) and 0.05 flash per min per square kilometer (0.01 flash per min per square kilometer). Furthermore, the LJ1 clusters are also characterized by slower decaying autocorrelation functions, a result that implies a less "random" behavior in the temporal flash rate evolution. In addition, the temporal occurrence of the last LJ provides an estimate of the time remaining to the storm's dissipation. Depending of the LJ strength (i.e., varying thresholds), these values typically range between 20-60 min, with stronger jumps indicating more time until storm decay. This study's results support the hypothesis that the LJ is a proxy for the storm's kinematic and microphysical state rather than a coincidental value.

Quantile regression and clustering analysis of standardized precipitation index in the Tarim River Basin, Xinjiang, China

NASA Astrophysics Data System (ADS)

Yang, Peng; Xia, Jun; Zhang, Yongyong; Han, Jian; Wu, Xia

2017-11-01

Because drought is a very common and widespread natural disaster, it has attracted a great deal of academic interest. Based on 12-month time scale standardized precipitation indices (SPI12) calculated from precipitation data recorded between 1960 and 2015 at 22 weather stations in the Tarim River Basin (TRB), this study aims to identify the trends of SPI and drought duration, severity, and frequency at various quantiles and to perform cluster analysis of drought events in the TRB. The results indicated that (1) both precipitation and temperature at most stations in the TRB exhibited significant positive trends during 1960-2015; (2) multiple scales of SPIs changed significantly around 1986; (3) based on quantile regression analysis of temporal drought changes, the positive SPI slopes indicated less severe and less frequent droughts at lower quantiles, but clear variation was detected in the drought frequency; and (4) significantly different trends were found in drought frequency probably between severe droughts and drought frequency.

Experimentally induced thyrotoxicosis leads to increased connectivity in temporal lobe structures: a resting state fMRI study.

PubMed

Göttlich, Martin; Heldmann, Marcus; Göbel, Anna; Dirk, Anna-Luise; Brabant, Georg; Münte, Thomas F

2015-06-01

Adult onset hyperthyroidism may impact on different cognitive domains, including attention and concentration, memory, perceptual function, language and executive function. Previous PET studies implicated changed functionality of limbic regions, the temporal and frontal lobes in hyperthyroidism, whereas it is unknown whether cognitive effects of hyperthyroidism may be due to changed brain connectivity. This study aimed to investigate the effect of experimentally induced short-term hyperthyroidism thyrotoxicosis on resting-state functional connectivity using functional magnetic resonance imaging. Twenty-nine healthy male right-handed subjects were examined twice, once prior and once after 8 weeks of oral administration of 250 μg levothyroxine per day. Resting-state fMRI was subjected to graph-theory based analysis methods to investigate whole-brain intrinsic functional connectivity. Despite a lack of subjective changes noticed by the subjects significant thyrotoxicosis was confirmed in all subjects. This induced a significant increase in resting-state functional connectivity specifically in the rostral temporal lobes (0.05 FDR corrected at the cluster level), which is caused by an increased connectivity to the cognitive control network. The increased connectivity between temporal poles and the cognitive control network shown here under experimental conditions supports an important function of thyroid hormones in the regulation of paralimbic structures. Copyright © 2015 Elsevier Ltd. All rights reserved.

Impact basins in Southern Daedalia, Mars: Evidence for clustered impactors?

NASA Technical Reports Server (NTRS)

Frey, Herbert; Roark, James H.

1994-01-01

The distribution of ancient massifs and old cratered terrain in the southern Daedalia region indicate the presence of at least two and probably three impact basins of large size. One of these is located near where Craddock et al. placed their center for the Daedalia Basin, but it has very different ring diameters. These basins have rings exceeding 1000 km diameter and overlap significantly with centers separated by 500 to 600 km at nearly identical latitudes of -26 to -29 deg. The smaller westernmost basin appears slightly better preserved, but there is little evidence for obvious superposition that might imply a temporal sequence. Recognizing the improbability of random impacts producing aligned, nearly contemporaneous features, we suggest these basins may have resulted from clustered impactors.

Multiple-class antimicrobial resistance surveillance in swine Escherichia coli F4, Pasteurella multocida and Streptococcus suis isolates from Ontario and the impact of the 2004-2006 Porcine Circovirus type-2 Associated Disease outbreak.

PubMed

Glass-Kaastra, Shiona K; Pearl, David L; Reid-Smith, Richard; McEwen, Beverly; Slavic, Durda; Fairles, Jim; McEwen, Scott A

2014-02-01

The objective of this work was to describe trends in multiple-class antimicrobial resistance present in clinical isolates of Escherichia coli F4, Pasteurella multocida and Streptococcus suis from Ontario swine 1998-2010. Temporal changes in multiple-class resistance varied by the pathogens examined; significant yearly changes were apparent for the E. coli and P. multocida data. Although not present in the E. coli data, significant increases in multiple-class resistance within P. multocida isolates occurred from 2003 to 2005, coinciding with the expected increase in antimicrobials used to treat clinical signs of Porcine Circovirus Associated Disease (PCVAD) before it was confirmed. Prospective temporal scan statistics for multiple-class resistance suggest that significant clusters of increased resistance may have been found in the spring of 2004; months before the identification of the PCVAD outbreak in the fall of 2004. Copyright © 2013 Elsevier B.V. All rights reserved.

Statistical Features of the 2010 Beni-Ilmane, Algeria, Aftershock Sequence

NASA Astrophysics Data System (ADS)

Hamdache, M.; Peláez, J. A.; Gospodinov, D.; Henares, J.

2018-03-01

The aftershock sequence of the 2010 Beni-Ilmane ( M W 5.5) earthquake is studied in depth to analyze the spatial and temporal variability of seismicity parameters of the relationships modeling the sequence. The b value of the frequency-magnitude distribution is examined rigorously. A threshold magnitude of completeness equal to 2.1, using the maximum curvature procedure or the changing point algorithm, and a b value equal to 0.96 ± 0.03 have been obtained for the entire sequence. Two clusters have been identified and characterized by their faulting type, exhibiting b values equal to 0.99 ± 0.05 and 1.04 ± 0.05. Additionally, the temporal decay of the aftershock sequence was examined using a stochastic point process. The analysis was done through the restricted epidemic-type aftershock sequence (RETAS) stochastic model, which allows the possibility to recognize the prevailing clustering pattern of the relaxation process in the examined area. The analysis selected the epidemic-type aftershock sequence (ETAS) model to offer the most appropriate description of the temporal distribution, which presumes that all events in the sequence can cause secondary aftershocks. Finally, the fractal dimensions are estimated using the integral correlation. The obtained D 2 values are 2.15 ± 0.01, 2.23 ± 0.01 and 2.17 ± 0.02 for the entire sequence, and for the first and second cluster, respectively. An analysis of the temporal evolution of the fractal dimensions D -2, D 0, D 2 and the spectral slope has been also performed to derive and characterize the different clusters included in the sequence.

[Space-time suicide clustering in the community of Antequera (Spain)].

PubMed

Pérez-Costillas, Lucía; Blasco-Fontecilla, Hilario; Benítez, Nicolás; Comino, Raquel; Antón, José Miguel; Ramos-Medina, Valentín; Lopez, Amalia; Palomo, José Luis; Madrigal, Lucía; Alcalde, Javier; Perea-Millá, Emilio; Artieda-Urrutia, Paula; de León-Martínez, Victoria; de Diego Otero, Yolanda

2015-01-01

Approximately 3,500 people commit suicide every year in Spain. The main aim of this study is to explore if a spatial and temporal clustering of suicide exists in the region of Antequera (Málaga, España). Sample and procedure: All suicides from January 1, 2004 to December 31, 2008 were identified using data from the Forensic Pathology Department of the Institute of Legal Medicine, Málaga (España). Geolocalisation. Google Earth was used to calculate the coordinates for each suicide decedent's address. Statistical analysis. A spatiotemporal permutation scan statistic and the Ripley's K function were used to explore spatiotemporal clustering. Pearson's chi-squared was used to determine whether there were differences between suicides inside and outside the spatiotemporal clusters. A total of 120 individuals committed suicide within the region of Antequera, of which 96 (80%) were included in our analyses. Statistically significant evidence for 7 spatiotemporal suicide clusters emerged within critical limits for the 0-2.5 km distance and for the first and second semanas (P<.05 in both cases) after suicide. There was not a single subject diagnosed with a current psychotic disorder, among suicides within clusters, whereas outside clusters, 20% had this diagnosis (X2=4.13; df=1; P<.05). There are spatiotemporal suicide clusters in the area surrounding Antequera. Patients diagnosed with current psychotic disorder are less likely to be influenced by the factors explaining suicide clustering. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Mapping similarities in temporal parking occupancy behavior based on city-wide parking meter data

NASA Astrophysics Data System (ADS)

Bock, Fabian; Xia, Karen; Sester, Monika

2018-05-01

The search for a parking space is a severe and stressful problem for drivers in many cities. The provision of maps with parking space occupancy information assists drivers in avoiding the most crowded roads at certain times. Since parking occupancy reveals a repetitive pattern per day and per week, typical parking occupancy patterns can be extracted from historical data. In this paper, we analyze city-wide parking meter data from Hannover, Germany, for a full year. We describe an approach of clustering these parking meters to reduce the complexity of this parking occupancy information and to reveal areas with similar parking behavior. The parking occupancy at every parking meter is derived from a timestamp of ticket payment and the validity period of the parking tickets. The similarity of the parking meters is computed as the mean-squared deviation of the average daily patterns in parking occupancy at the parking meters. Based on this similarity measure, a hierarchical clustering is applied. The number of clusters is determined with the Davies-Bouldin Index and the Silhouette Index. Results show that, after extensive data cleansing, the clustering leads to three clusters representing typical parking occupancy day patterns. Those clusters differ mainly in the hour of the maximum occupancy. In addition, the lo-cations of parking meter clusters, computed only based on temporal similarity, also show clear spatial distinctions from other clusters.

Clustering ENTLN sferics to improve TGF temporal analysis

NASA Astrophysics Data System (ADS)

Pradhan, E.; Briggs, M. S.; Stanbro, M.; Cramer, E.; Heckman, S.; Roberts, O.

2017-12-01

Using TGFs detected with Fermi Gamma-ray Burst Monitor (GBM) and simultaneous radio sferics detected by Earth Network Total Lightning Network (ENTLN), we establish a temporal co-relation between them. The first step is to find ENTLN strokes that that are closely associated to GBM TGFs. We then identify all the related strokes in the lightning flash that the TGF-associated-stroke belongs to. After trying several algorithms, we found out that the DBSCAN clustering algorithm was best for clustering related ENTLN strokes into flashes. The operation of DBSCAN was optimized using a single seperation measure that combined time and distance seperation. Previous analysis found that these strokes show three timescales with respect to the gamma-ray time. We will use the improved identification of flashes to research this.

Spatial-temporal clustering of companion animal enteric syndrome: detection and investigation through the use of electronic medical records from participating private practices.

PubMed

Anholt, R M; Berezowski, J; Robertson, C; Stephen, C

2015-09-01

There is interest in the potential of companion animal surveillance to provide data to improve pet health and to provide early warning of environmental hazards to people. We implemented a companion animal surveillance system in Calgary, Alberta and the surrounding communities. Informatics technologies automatically extracted electronic medical records from participating veterinary practices and identified cases of enteric syndrome in the warehoused records. The data were analysed using time-series analyses and a retrospective space-time permutation scan statistic. We identified a seasonal pattern of reports of occurrences of enteric syndromes in companion animals and four statistically significant clusters of enteric syndrome cases. The cases within each cluster were examined and information about the animals involved (species, age, sex), their vaccination history, possible exposure or risk behaviour history, information about disease severity, and the aetiological diagnosis was collected. We then assessed whether the cases within the cluster were unusual and if they represented an animal or public health threat. There was often insufficient information recorded in the medical record to characterize the clusters by aetiology or exposures. Space-time analysis of companion animal enteric syndrome cases found evidence of clustering. Collection of more epidemiologically relevant data would enhance the utility of practice-based companion animal surveillance.

A Catalog of Galaxy Clusters Observed by XMM-Newton

NASA Technical Reports Server (NTRS)

Snowden, S. L.; Mushotzky, R. M.; Kuntz, K. D.; Davis, David S.

2007-01-01

Images and the radial profiles of the temperature, abundance, and brightness for 70 clusters of galaxies observed by XMM-Newton are presented along with a detailed discussion of the data reduction and analysis methods, including background modeling, which were used in the processing. Proper consideration of the various background components is vital to extend the reliable determination of cluster parameters to the largest possible cluster radii. The various components of the background including the quiescent particle background, cosmic diffuse emission, soft proton contamination, and solar wind charge exchange emission are discussed along with suggested means of their identification, filtering, and/or their modeling and subtraction. Every component is spectrally variable, sometimes significantly so, and all components except the cosmic background are temporally variable as well. The distributions of the events over the FOV vary between the components, and some distributions vary with energy. The scientific results from observations of low surface brightness objects and the diffuse background itself can be strongly affected by these background components and therefore great care should be taken in their consideration.

Lung cancer mortality clusters in Shandong Province, China: how do they change over 40 years?

PubMed Central

Fu, Zhentao; Li, Yingmei; Lu, Zilong; Chu, Jie; Sun, Jiandong; Zhang, Jiyu; Zhang, Gaohui; Xue, Fuzhong; Guo, Xiaolei; Xu, Aiqiang

2017-01-01

Lung cancer has long been a major health problem in China. This study aimed to examine the temporal trend and spatial pattern of lung cancer mortality in Shandong Province from 1970 to 2013. Lung cancer mortality data were obtained from Shandong Death Registration System and three nationwide retrospective cause-of-death surveys. A Purely Spatial Scan Statistics method with Discrete Poisson models was used to detect possible high-risk spatial clusters. The results show that lung cancer mortality rate in Shandong Province increased markedly from 1970-1974 (7.22 per 100,000 person-years) to 2011-2013 (56.37/100, 000). This increase was associated with both demographic and non-demographic factors. Several significant spatial clusters with high lung cancer mortality were identified. The most likely cluster was located in the northern region of Shandong Province during both 1970-1974 and 2011-2013. It appears the spatial pattern remained largely consistent over the last 40 years despite the absolute increase in the mortality rates. These findings will help develop intervention strategies to reduce lung cancer mortality in this large Chinese population. PMID:29179474

A particle swarm optimized kernel-based clustering method for crop mapping from multi-temporal polarimetric L-band SAR observations

NASA Astrophysics Data System (ADS)

Tamiminia, Haifa; Homayouni, Saeid; McNairn, Heather; Safari, Abdoreza

2017-06-01

Polarimetric Synthetic Aperture Radar (PolSAR) data, thanks to their specific characteristics such as high resolution, weather and daylight independence, have become a valuable source of information for environment monitoring and management. The discrimination capability of observations acquired by these sensors can be used for land cover classification and mapping. The aim of this paper is to propose an optimized kernel-based C-means clustering algorithm for agriculture crop mapping from multi-temporal PolSAR data. Firstly, several polarimetric features are extracted from preprocessed data. These features are linear polarization intensities, and several statistical and physical based decompositions such as Cloude-Pottier, Freeman-Durden and Yamaguchi techniques. Then, the kernelized version of hard and fuzzy C-means clustering algorithms are applied to these polarimetric features in order to identify crop types. The kernel function, unlike the conventional partitioning clustering algorithms, simplifies the non-spherical and non-linearly patterns of data structure, to be clustered easily. In addition, in order to enhance the results, Particle Swarm Optimization (PSO) algorithm is used to tune the kernel parameters, cluster centers and to optimize features selection. The efficiency of this method was evaluated by using multi-temporal UAVSAR L-band images acquired over an agricultural area near Winnipeg, Manitoba, Canada, during June and July in 2012. The results demonstrate more accurate crop maps using the proposed method when compared to the classical approaches, (e.g. 12% improvement in general). In addition, when the optimization technique is used, greater improvement is observed in crop classification, e.g. 5% in overall. Furthermore, a strong relationship between Freeman-Durden volume scattering component, which is related to canopy structure, and phenological growth stages is observed.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Community detection using Kernel Spectral Clustering with memory

NASA Astrophysics Data System (ADS)

Langone, Rocco; Suykens, Johan A. K.

2013-02-01

This work is related to the problem of community detection in dynamic scenarios, which for instance arises in the segmentation of moving objects, clustering of telephone traffic data, time-series micro-array data etc. A desirable feature of a clustering model which has to capture the evolution of communities over time is the temporal smoothness between clusters in successive time-steps. In this way the model is able to track the long-term trend and in the same time it smooths out short-term variation due to noise. We use the Kernel Spectral Clustering with Memory effect (MKSC) which allows to predict cluster memberships of new nodes via out-of-sample extension and has a proper model selection scheme. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness as a valid prior knowledge. The latter, in fact, allows the model to cluster the current data well and to be consistent with the recent history. Here we propose a generalization of the MKSC model with an arbitrary memory, not only one time-step in the past. The experiments conducted on toy problems confirm our expectations: the more memory we add to the model, the smoother over time are the clustering results. We also compare with the Evolutionary Spectral Clustering (ESC) algorithm which is a state-of-the art method, and we obtain comparable or better results.

fMR-adaptation indicates selectivity to audiovisual content congruency in distributed clusters in human superior temporal cortex.

PubMed

van Atteveldt, Nienke M; Blau, Vera C; Blomert, Leo; Goebel, Rainer

2010-02-02

Efficient multisensory integration is of vital importance for adequate interaction with the environment. In addition to basic binding cues like temporal and spatial coherence, meaningful multisensory information is also bound together by content-based associations. Many functional Magnetic Resonance Imaging (fMRI) studies propose the (posterior) superior temporal cortex (STC) as the key structure for integrating meaningful multisensory information. However, a still unanswered question is how superior temporal cortex encodes content-based associations, especially in light of inconsistent results from studies comparing brain activation to semantically matching (congruent) versus nonmatching (incongruent) multisensory inputs. Here, we used fMR-adaptation (fMR-A) in order to circumvent potential problems with standard fMRI approaches, including spatial averaging and amplitude saturation confounds. We presented repetitions of audiovisual stimuli (letter-speech sound pairs) and manipulated the associative relation between the auditory and visual inputs (congruent/incongruent pairs). We predicted that if multisensory neuronal populations exist in STC and encode audiovisual content relatedness, adaptation should be affected by the manipulated audiovisual relation. The results revealed an occipital-temporal network that adapted independently of the audiovisual relation. Interestingly, several smaller clusters distributed over superior temporal cortex within that network, adapted stronger to congruent than to incongruent audiovisual repetitions, indicating sensitivity to content congruency. These results suggest that the revealed clusters contain multisensory neuronal populations that encode content relatedness by selectively responding to congruent audiovisual inputs, since unisensory neuronal populations are assumed to be insensitive to the audiovisual relation. These findings extend our previously revealed mechanism for the integration of letters and speech sounds and demonstrate that fMR-A is sensitive to multisensory congruency effects that may not be revealed in BOLD amplitude per se.

Prostate cancer incidence and tumor severity in Georgia: descriptive epidemiology, racial disparity, and geographic trends.

PubMed

Wagner, Sara E; Bauer, Sarah E; Bayakly, A Rana; Vena, John E

2013-01-01

Limited research has been conducted to describe the geographical clustering and distribution of prostate cancer (PrCA) incidence in Georgia (GA). This study describes and compares the temporal and geographic trends of PrCA incidence in GA with a specific focus on racial disparities. GA Comprehensive Cancer Registry PrCA incidence data were obtained for 1998-2008. Directly standardized age-adjusted PrCA incidence rates per 100,000 were analyzed by race, stage, grade, and county. County-level hotspots of PrCA incidence were analyzed with the Getis-Ord Gi* statistic in a geographic information system; a census tract-level cluster analysis was performed with a Discrete Poisson model and implemented in SaTScan(®) software. Significant (p < 0.05) hotspots of PrCA incidence were observed in nine southwestern counties and six centrally located counties among men of both races. Six significant (p < 0.1) clusters of PrCA incidence rates were detected for men of both races in north and northwest central Georgia. When stratified by race, clusters among white and black men were similar, although centroids were slightly shifted. Most notably, a large (122 km radius) cluster in northwest central Georgia was detected only in whites, and two smaller clusters (0-32 km radii) were detected in Southwest Georgia only in black men. Clusters of high-grade and late-stage tumors were identified primarily in the northern portion of the state among men of both races. This study revealed a pattern of higher incidence and more advanced disease in northern and northwest central Georgia, highlighting geographic patterns that need more research and investigation of possible environmental determinants.

Effects of Educational Music Therapy on State Hope for Recovery in Acute Care Mental Health Inpatients: A Cluster-Randomized Effectiveness Study.

PubMed

Silverman, Michael J

2016-01-01

Background: There has been an increasing emphasis on recovery as the expectation for people with mental health disorders. Purpose: The purpose of this effectiveness study is to determine if group-based educational music therapy can immediately impact state hope for recovery in acute care mental health patients. Research questions included: will acute care mental health inpatients who participate in a single music therapy session have higher agency and pathway aspects of state hope for recovery than patients in a control condition? Will there be differences in state hope for recovery as a result of hope-oriented songwriting or lyric analysis interventions? Method: Participants ( N = 169) were cluster randomized to one of three single-session conditions: lyric analysis, songwriting, or wait-list control. Results: There was no significant between-group difference. However, both music therapy conditions tended to have slightly higher mean pathway, agency, and total state hope scores than the control condition even within the temporal parameters of a single music therapy session. There was no between-group difference in the songwriting and lyric analysis interventions. Conclusion: Although not significant, results support that educational music therapy may impact state hope for recovery within the temporal parameters of a single session. The specific type of educational music therapy intervention did not affect results. Implications for practice, limitations, and suggestions for future research are provided.

Effects of Educational Music Therapy on State Hope for Recovery in Acute Care Mental Health Inpatients: A Cluster-Randomized Effectiveness Study

PubMed Central

Silverman, Michael J.

2016-01-01

Background: There has been an increasing emphasis on recovery as the expectation for people with mental health disorders. Purpose: The purpose of this effectiveness study is to determine if group-based educational music therapy can immediately impact state hope for recovery in acute care mental health patients. Research questions included: will acute care mental health inpatients who participate in a single music therapy session have higher agency and pathway aspects of state hope for recovery than patients in a control condition? Will there be differences in state hope for recovery as a result of hope-oriented songwriting or lyric analysis interventions? Method: Participants (N = 169) were cluster randomized to one of three single-session conditions: lyric analysis, songwriting, or wait-list control. Results: There was no significant between-group difference. However, both music therapy conditions tended to have slightly higher mean pathway, agency, and total state hope scores than the control condition even within the temporal parameters of a single music therapy session. There was no between-group difference in the songwriting and lyric analysis interventions. Conclusion: Although not significant, results support that educational music therapy may impact state hope for recovery within the temporal parameters of a single session. The specific type of educational music therapy intervention did not affect results. Implications for practice, limitations, and suggestions for future research are provided. PMID:27774084

Comparing Foreshock Characteristics and Foreshock Forecasting in Observed and Simulated Earthquake Catalogs

NASA Astrophysics Data System (ADS)

Ogata, Y.

2014-12-01

In our previous papers (Ogata et al., 1995, 1996, 2012; GJI), we characterized foreshock activity in Japan, and then presented a model that forecasts the probability that one or more earthquakes form a foreshock sequence; then we tested prospectively foreshock probabilities in the JMA catalog. In this talk, I compare the empirical results with results for synthetic catalogs in order to clarify whether or not these results are consistent with the description of the seismicity by a superposition of background activity and epidemic-type aftershock sequences (ETAS models). This question is important, because it is still controversially discussed whether the nucleation process of large earthquakes is driven by seismically cascading (ETAS-type) or by aseismic accelerating processes. To explore the foreshock characteristics, I firstly applied the same clustering algorithms to real and synthetic catalogs and analyzed the temporal, spatial and magnitude distributions of the selected foreshocks, to find significant differences particularly in the temporal acceleration and magnitude dependence. Finally, I calculated forecast scores based on a single-link cluster algorithm which could be appropriate for real-time applications. I find that the JMA catalog yields higher scores than all synthetic catalogs and that the ETAS models having the same magnitude sequence as the original catalog performs significantly better (more close to the reality) than ETAS-models with randomly picked magnitudes.

Representation of Glossy Material Surface in Ventral Superior Temporal Sulcal Area of Common Marmosets

PubMed Central

Miyakawa, Naohisa; Banno, Taku; Abe, Hiroshi; Tani, Toshiki; Suzuki, Wataru; Ichinohe, Noritaka

2017-01-01

The common marmoset (Callithrix jacchus) is one of the smallest species of primates, with high visual recognition abilities that allow them to judge the identity and quality of food and objects in their environment. To address the cortical processing of visual information related to material surface features in marmosets, we presented a set of stimuli that have identical three-dimensional shapes (bone, torus or amorphous) but different material appearances (ceramic, glass, fur, leather, metal, stone, wood, or matte) to anesthetized marmoset, and recorded multiunit activities from an area ventral to the superior temporal sulcus (STS) using multi-shanked, and depth resolved multi-electrode array. Out of 143 visually responsive multiunits recorded from four animals, 29% had significant main effect only of the material, 3% only of the shape and 43% of both the material and the shape. Furthermore, we found neuronal cluster(s), in which most cells: (1) showed a significant main effect in material appearance; (2) the best stimulus was a glossy material (glass or metal); and (3) had reduced response to the pixel-shuffled version of the glossy material images. The location of the gloss-selective area was in agreement with previous macaque studies, showing activation in the ventral bank of STS. Our results suggest that perception of gloss is an important ability preserved across wide range of primate species. PMID:28367117

Representation of Glossy Material Surface in Ventral Superior Temporal Sulcal Area of Common Marmosets.

PubMed

Miyakawa, Naohisa; Banno, Taku; Abe, Hiroshi; Tani, Toshiki; Suzuki, Wataru; Ichinohe, Noritaka

2017-01-01

The common marmoset ( Callithrix jacchus ) is one of the smallest species of primates, with high visual recognition abilities that allow them to judge the identity and quality of food and objects in their environment. To address the cortical processing of visual information related to material surface features in marmosets, we presented a set of stimuli that have identical three-dimensional shapes (bone, torus or amorphous) but different material appearances (ceramic, glass, fur, leather, metal, stone, wood, or matte) to anesthetized marmoset, and recorded multiunit activities from an area ventral to the superior temporal sulcus (STS) using multi-shanked, and depth resolved multi-electrode array. Out of 143 visually responsive multiunits recorded from four animals, 29% had significant main effect only of the material, 3% only of the shape and 43% of both the material and the shape. Furthermore, we found neuronal cluster(s), in which most cells: (1) showed a significant main effect in material appearance; (2) the best stimulus was a glossy material (glass or metal); and (3) had reduced response to the pixel-shuffled version of the glossy material images. The location of the gloss-selective area was in agreement with previous macaque studies, showing activation in the ventral bank of STS. Our results suggest that perception of gloss is an important ability preserved across wide range of primate species.

Monitoring Wetland Hydro-dynamics in the Prairie Pothole Region Using Landsat Time Series

NASA Astrophysics Data System (ADS)

Zhou, Q.; Rover, J.; Gallant, A.

2017-12-01

Wetlands provide a variety of ecosystem functions, while it is spatially and temporally dynamic. We mapped the dynamics of wetlands in the North Dakota Prairie Pothole Region using all available clear observations of Landsat sensor data from 1985 to 2014. We used a cluster analysis to group pixels exhibiting similar long-term spectral trends over seven Landsat bands, then applied the tasseled-cap transformation to evaluate the temporal characteristics of brightness, greenness, and wetness for each cluster. We tested relations between these three indices and hydrologic conditions, as represented by the Palmer Hydrological Drought Index (PHDI), using the cross-correlation analysis for each cluster performed over an eight-year moving window for the 30 years covered by the study. This temporal window size coincided with the timing of a major shift from a prolonged drought that occurred within the first eight years of the study period to wetter conditions that prevailed throughout the remaining years. The 20 cluster we produced represented a gradient from locations that continuously held water throughout the study period to locations that, at most, held water only for short periods in some years. The spatial distribution of the cluster groups reflected patterns of regional geologic and geomorphologic features. Comparisons of the PHDI to tasseled-cap wetness were the most straightforward to interpret among the results from the three indices. Wetness for most cluster groups had high positive correlations with PHDI during drought years, with the correlations reduced as the landscape entered a lengthy, wetter period; however, wetness generally remained highly and positively correlated with PHDI across all years for four cluster groups where the area exhibited two or more multi-year dry-wet cycles. These same four groups also had strong, generally negative correlations with tasseled-cap brightness. For other cluster groups, brightness often was strongly negatively correlated with the PHDI during the drought years, with the relation weakening for subsequent years of adequate or high moisture. Relations between tasseled-cap greenness and PHDI were highly variable among and within cluster groups. Results from this analysis support ongoing efforts to develop new products that characterize wetland dynamics.

Spatio-temporal development of sinkholes on the eastern shore of the Dead Sea

NASA Astrophysics Data System (ADS)

Holohan, Eoghan; Saberi, Leila; Al-Halbouni, Djamil; Sawarieh, Ali; Closson, Damien; Alrshdan, Hussam; Walter, Thomas; Dahm, Torsten

2017-04-01

The ongoing, largely anthropogenically-forced decline of the Dead Sea is associated with the most prolific development of sinkholes worldwide. The fall in hydrological base level since the 1960s is thought to enable relatively fresh ground waters to dissolve underground salt deposits that were previously in equilibrium with hypersaline Dead Sea brine. Sinkhole development in response to this dissolution began in the 1980s and is still ongoing; it represents a significant geohazard in the Dead Sea region. We present new research undertaken within the Dead Sea Research Venue (DESERVE) on the spatio-temporal evolution of the main sinkhole-affected site on the Eastern shore of the Dead Sea, at Ghor Al-Haditha in Jordan. Our data set includes optical satellite imagery, aerial survey photographs and drone-based photogrammetric surveys with high spatial (< 1 m2 - 0.05 m per pixel) and temporal (decadal from 1970-2010, annual from 2004-2016) resolution. These enable new quantitative insights into this, the largest of all the Dead Sea sinkhole sites. Our analysis shows that there are now over 800 sinkholes at Ghor al-Haditha. Sinkholes initiated as spatially distinct clusters in the late 1980's to early 1990s. While some clusters have since become inactive, most have expanded and merged with time. New clusters have also developed, mainly in the more recently exposed north of the area. With the retreat of the Dead Sea, the roughly coastline-parallel zone of sinkhole formation has expanded unevenly but systematically seawards. Such a seaward migration of sinkhole formation is predicted from hydrogeological theory, but as yet not consistently observed elsewhere at the Dead Sea. The rate of sinkhole formation at Ghor Haditha accelerated markedly during the late 2000s to a peak of about 100 per year in 2009. Similar accelerations are observed on the western shore, but differ in timing. The rate of sinkhole formation on the Eastern shore has since declined to about 50 per year. Such differences in the overall spatio-temporal evolution of sinkholes on the eastern and western shores of the Dead Sea likely highlights the important role of local hydrogeological conditions and processes in governing sinkhole development.

Spontaneous brain activity in chronic smokers revealed by fractional amplitude of low frequency fluctuation analysis: a resting state functional magnetic resonance imaging study.

PubMed

Chu, Shuilian; Xiao, Dan; Wang, Shuangkun; Peng, Peng; Xie, Teng; He, Yong; Wang, Chen

2014-01-01

Nicotine is primarily rsponsible for the highly addictive properties of cigarettes. Similar to other substances, nicotine dependence is related to many important brain regions, particular in mesolimbic reward circuit. This study was to further reveal the alteration of brain function activity during resting state in chronic smokers by fractional amplitude of low frequency fluctuation (fALFF) based on functional magnetic resonance imaging (fMRI), in order to provide the evidence of neurobiological mechanism of smoking. This case control study involved twenty healthy smokers and nineteen healthy nonsmokers recruited by advertisement. Sociodemographic, smoking related characteristics and fMRI images were collected and the data analyzed. Compared with nonsmokers, smokers showed fALFF increased significantly in the left middle occipital gyrus, left limbic lobe and left cerebellum posterior lobe but decreases in the right middle frontal gyrus, right superior temporal gyrus, right extra nuclear, left postcentral gyrus and left cerebellum anterior lobe (cluster size >100 voxels). Compared with light smokers (pack years ≤ 20), heavy smokers (pack years >20) showed fALFF increased significantly in the right superior temporal gyrus, right precentral gyrus, and right occipital lobe/cuneus but decreased in the right/left limbic lobe/cingulate gyrus, right/left frontal lobe/sub gyral, right/left cerebellum posterior lobe (cluster size >50 voxels). Compared with nonsevere nicotine dependent smokers (Fagerstrőm test for nicotine dependence, score ≤ 6), severe nicotine dependent smokers (score >6) showed fALFF increased significantly in the right/left middle frontal gyrus, right superior frontal gyrus and left inferior parietal lobule but decreased in the left limbic lobe/cingulate gyrus (cluster size >25 voxels). In smokers during rest, the activity of addiction related regions were increased and the activity of smoking feeling, memory, related regions were also changed. The resting state activity changes in many regions were associated with the cumulative amount of nicotine intake and the severity of nicotine dependence.

Rolling epidemic of Legionnaires' disease outbreaks in small geographic areas.

PubMed

MacIntyre, C Raina; Dyda, Amalie; Bui, Chau Minh; Chughtai, Abrar Ahmad

2018-03-21

Legionnaires' disease (LD) is reported from many parts of the world, mostly linked to drinking water sources or cooling towers. We reviewed two unusual rolling outbreaks in Sydney and New York, each clustered in time and space. Data on these outbreaks were collected from public sources and compared to previous outbreaks in Australia and the US. While recurrent outbreaks of LD over time linked to an identified single source have been described, multiple unrelated outbreaks clustered in time and geography have not been previously described. We describe unusual geographic and temporal clustering of Legionella outbreaks in two cities, each of which experienced multiple different outbreaks within a small geographic area and within a short timeframe. The explanation for this temporal and spatial clustering of LD outbreaks in two cities is not clear, but climate variation and deteriorating water sanitation are two possible explanations. There is a need to critically analyse LD outbreaks and better understand changing trends to effectively prevent disease.

Characteristics of voxel prediction power in full-brain Granger causality analysis of fMRI data

NASA Astrophysics Data System (ADS)

Garg, Rahul; Cecchi, Guillermo A.; Rao, A. Ravishankar

2011-03-01

Functional neuroimaging research is moving from the study of "activations" to the study of "interactions" among brain regions. Granger causality analysis provides a powerful technique to model spatio-temporal interactions among brain regions. We apply this technique to full-brain fMRI data without aggregating any voxel data into regions of interest (ROIs). We circumvent the problem of dimensionality using sparse regression from machine learning. On a simple finger-tapping experiment we found that (1) a small number of voxels in the brain have very high prediction power, explaining the future time course of other voxels in the brain; (2) these voxels occur in small sized clusters (of size 1-4 voxels) distributed throughout the brain; (3) albeit small, these clusters overlap with most of the clusters identified with the non-temporal General Linear Model (GLM); and (4) the method identifies clusters which, while not determined by the task and not detectable by GLM, still influence brain activity.

Temporal and Spatial Diversity of Bacterial Communities in Coastal Waters of the South China Sea

PubMed Central

Du, Jikun; Xiao, Kai; Li, Li; Ding, Xian; Liu, Helu; Lu, Yongjun; Zhou, Shining

2013-01-01

Bacteria are recognized as important drivers of biogeochemical processes in all aquatic ecosystems. Temporal and geographical patterns in ocean bacterial communities have been observed in many studies, but the temporal and spatial patterns in the bacterial communities from the South China Sea remained unexplored. To determine the spatiotemporal patterns, we generated 16S rRNA datasets for 15 samples collected from the five regularly distributed sites of the South China Sea in three seasons (spring, summer, winter). A total of 491 representative sequences were analyzed by MOTHUR, yielding 282 operational taxonomic units (OTUs) grouped at 97% stringency. Significant temporal variations of bacterial diversity were observed. Richness and diversity indices indicated that summer samples were the most diverse. The main bacterial group in spring and summer samples was Alphaproteobacteria, followed by Cyanobacteria and Gammaproteobacteria, whereas Cyanobacteria dominated the winter samples. Spatial patterns in the samples were observed that samples collected from the coastal (D151, D221) waters and offshore (D157, D1512, D224) waters clustered separately, the coastal samples harbored more diverse bacterial communities. However, the temporal pattern of the coastal site D151 was contrary to that of the coastal site D221. The LIBSHUFF statistics revealed noticeable differences among the spring, summer and winter libraries collected at five sites. The UPGMA tree showed there were temporal and spatial heterogeneity of bacterial community composition in coastal waters of the South China Sea. The water salinity (P=0.001) contributed significantly to the bacteria-environment relationship. Our results revealed that bacterial community structures were influenced by environmental factors and community-level changes in 16S-based diversity were better explained by spatial patterns than by temporal patterns. PMID:23785512

Clusters of Earthquakes In The Southern of Iberian Peninsula

NASA Astrophysics Data System (ADS)

Posadas, A. M.; Luzón, F.; Vidal, F.

The southern part of the Iberian Peninsula forms part of the western border of Eurasia- Africa plate boundary. This area is characterized by the occurrence of earthquakes of moderate magnitude (the maximum magnitude ranging from 4.5 to 5.5). From the point of view of seismic activity, this region is the most active one in he Iberian Penin- sula. Until earlier 80, only the National Seismic Network belonging to the National Geographic Institute monitores the activity in the south of Iberian Peninsula. From 1983 to the actuality, the Andalusian Seismic Network belonging to the Andalusian Geophysics Institute and Seismic Disaster Prevention, records the microseismicity of the area. Nowadays, the earthquakes catalogue used belongs to the Andalusian Insti- tute of Geophysics and Seismic Disaster Prevention and it counts on more than 20000 events registered from 1985 to 2001. Today, after 20 years of recording seismic ac- tivity, statistics analysis of the catalogue have sense. In this paper we present a first approach to the clustering properties of the seismicity in the south of the Iberian Penin- sula. The analysis carried out starts with the study of clustering properties (temporal and spatial properties) in the Southern of Iberian Peninsula seismicity to demonstrate, by using the Fractal Dimension of the temporal earthquake distribution and the Mor- ishita Index of the spatial distribution of earthquakes, that this seismicity is charac- terized by a tendency to form earthquake clusters, both spatial and temporal clusters. As an example, five seismogenetic areas of the zone are analyzed (Adra-Berja, Agron, Alboran, Antequera and Loja). This particular study of the series find out the b param- eter from the Gutenberg-Richter's Law (which characterizes the energetic relaxation of events), the p parameter from Omori's Law (that characterizes the temporal relax- ation of aftershocks) and the Fractal Dimension of the spatial distribution of earth- quakes (to find the characteristic geometry seismogenetic zone).

Assessing SaTScan ability to detect space-time clusters in wildfires

NASA Astrophysics Data System (ADS)

Costa, Ricardo; Pereira, Mário; Caramelo, Liliana; Vega Orozco, Carmen; Kanevski, Mikhail

2013-04-01

Besides classical cluster analysis techniques which are able to analyse spatial and temporal data, SaTScan software analyses space-time data using the spatial, temporal or space-time scan statistics. This software requires the spatial coordinates of the fire, but since in the Rural Fire Portuguese Database (PRFD) (Pereira et al, 2011) the location of each fire is the parish where the ignition occurs, the fire spatial coordinates were considered as coordinates of the centroid of the parishes. Moreover, in general, the northern region is characterized by a large number of small parishes while the southern comprises parish much larger. The objectives of this study are: (i) to test the ability of SaTScan to detect the correct space-time clusters, in what respects to spatial and temporal location and size; and, (ii) to evaluate the effect of the dimensions of the parishes and of aggregating all fires occurred in a parish in a single point. Results obtained with a synthetic database where clusters were artificially created with different densities, in different regions of the country and with different sizes and durations, allow to conclude: the ability of SaTScan to correctly identify the clusters (location, shape and spatial and temporal dimension); and objectively assess the influence of the size of the parishes and windows used in space-time detection. Pereira, M. G., Malamud, B. D., Trigo, R. M., and Alves, P. I.: The history and characteristics of the 1980-2005 Portuguese rural fire database, Nat. Hazards Earth Syst. Sci., 11, 3343-3358, doi:10.5194/nhess-11-3343-2011, 2011 This work is supported by European Union Funds (FEDER/COMPETE - Operational Competitiveness Programme) and by national funds (FCT - Portuguese Foundation for Science and Technology) under the project FCOMP-01-0124-FEDER-022692, the project FLAIR (PTDC/AAC-AMB/104702/2008) and the EU 7th Framework Program through FUME (contract number 243888).

The Foxconn suicides and their media prominence: is the Werther Effect applicable in China?

PubMed

Cheng, Qijin; Chen, Feng; Yip, Paul S F

2011-11-02

Media reporting of suicide and its relationship with actual suicide has rarely been investigated in Mainland China. The "Foxconn suicides" is a description referring to a string of suicides/attempts during 2010, all of which were related to a giant electrical manufacturing company, Foxconn. This study aimed to examine the clustering and copycat effects of the Foxconn suicides, and to investigate temporal patterns in how they were reported by the media in Mainland China, Hong Kong (HK), and Taiwan (TW). Relevant articles were collected from representative newspapers published in three big cities in Mainland China (Beijing (BJ), Shenzhen (SZ), and Guangzhou (GZ)), HK, and TW, together with searching intensity data on the topic conducted using the Baidu search engine in Mainland China. The temporal clustering effects of the Foxconn suicides and their media prominence were assessed using the Kolmogorov-Smirnov test. The media reports of the Foxconn suicides' temporal patterns were explored using a nonparametric curve estimation method (that is, the local linear method). The potential mutual interactions between the Foxconn suicides and their media prominence were also examined, using logistic and Poisson regression methods. The results support a temporal clustering effect for the Foxconn suicides. The BJ-based newspapers' reporting and the occurrence of a Foxconn suicide/attempt are each found to be associated with an elevated chance of a further Foxconn suicide 3 days later. The occurrence of a Foxconn suicide also immediately influenced the intensity of both Baidu searching and newspaper reporting. Regional diversity in suicide reporting tempo-patterns within Mainland China, and similarities between HK and TW, are also demonstrated. The Foxconn suicides were temporally clustered. Their occurrences were influenced by the reporting of BJ-based newspapers, and contagion within the company itself. Further suicide research and prevention work in China should consider its special media environment.

The foxconn suicides and their media prominence: is the werther effect applicable in china?

PubMed Central

2011-01-01

Background Media reporting of suicide and its relationship with actual suicide has rarely been investigated in Mainland China. The "Foxconn suicides" is a description referring to a string of suicides/attempts during 2010, all of which were related to a giant electrical manufacturing company, Foxconn. This study aimed to examine the clustering and copycat effects of the Foxconn suicides, and to investigate temporal patterns in how they were reported by the media in Mainland China, Hong Kong (HK), and Taiwan (TW). Methods Relevant articles were collected from representative newspapers published in three big cities in Mainland China (Beijing (BJ), Shenzhen (SZ), and Guangzhou (GZ)), HK, and TW, together with searching intensity data on the topic conducted using the Baidu search engine in Mainland China. The temporal clustering effects of the Foxconn suicides and their media prominence were assessed using the Kolmogorov-Smirnov test. The media reports of the Foxconn suicides' temporal patterns were explored using a nonparametric curve estimation method (that is, the local linear method). The potential mutual interactions between the Foxconn suicides and their media prominence were also examined, using logistic and Poisson regression methods. Results The results support a temporal clustering effect for the Foxconn suicides. The BJ-based newspapers' reporting and the occurrence of a Foxconn suicide/attempt are each found to be associated with an elevated chance of a further Foxconn suicide 3 days later. The occurrence of a Foxconn suicide also immediately influenced the intensity of both Baidu searching and newspaper reporting. Regional diversity in suicide reporting tempo-patterns within Mainland China, and similarities between HK and TW, are also demonstrated. Conclusions The Foxconn suicides were temporally clustered. Their occurrences were influenced by the reporting of BJ-based newspapers, and contagion within the company itself. Further suicide research and prevention work in China should consider its special media environment. PMID:22044598

Ensemble and single particle fluorimetric techniques in concerted action to study the diffusion and aggregation of the glycine receptor α3 isoforms in the cell plasma membrane.

PubMed

Notelaers, Kristof; Smisdom, Nick; Rocha, Susana; Janssen, Daniel; Meier, Jochen C; Rigo, Jean-Michel; Hofkens, Johan; Ameloot, Marcel

2012-12-01

The spatio-temporal membrane behavior of glycine receptors (GlyRs) is known to be of influence on receptor homeostasis and functionality. In this work, an elaborate fluorimetric strategy was applied to study the GlyR α3K and L isoforms. Previously established differential clustering, desensitization and synaptic localization of these isoforms imply that membrane behavior is crucial in determining GlyR α3 physiology. Therefore diffusion and aggregation of homomeric α3 isoform-containing GlyRs were studied in HEK 293 cells. A unique combination of multiple diffraction-limited ensemble average methods and subdiffraction single particle techniques was used in order to achieve an integrated view of receptor properties. Static measurements of aggregation were performed with image correlation spectroscopy (ICS) and, single particle based, direct stochastic optical reconstruction microscopy (dSTORM). Receptor diffusion was measured by means of raster image correlation spectroscopy (RICS), temporal image correlation spectroscopy (TICS), fluorescence recovery after photobleaching (FRAP) and single particle tracking (SPT). The results show a significant difference in diffusion coefficient and cluster size between the isoforms. This reveals a positive correlation between desensitization and diffusion and disproves the notion that receptor aggregation is a universal mechanism for accelerated desensitization. The difference in diffusion coefficient between the clustering GlyR α3L and the non-clustering GlyR α3K cannot be explained by normal diffusion. SPT measurements indicate that the α3L receptors undergo transient trapping and directed motion, while the GlyR α3K displays mild hindered diffusion. These findings are suggestive of differential molecular interaction of the isoforms after incorporation in the membrane. Copyright © 2012 Elsevier B.V. All rights reserved.

Spatio-temporal diffusion pattern and hotspot detection of dengue in Chachoengsao province, Thailand.

PubMed

Jeefoo, Phaisarn; Tripathi, Nitin Kumar; Souris, Marc

2011-01-01

In recent years, dengue has become a major international public health concern. In Thailand it is also an important concern as several dengue outbreaks were reported in last decade. This paper presents a GIS approach to analyze the spatial and temporal dynamics of dengue epidemics. The major objective of this study was to examine spatial diffusion patterns and hotspot identification for reported dengue cases. Geospatial diffusion pattern of the 2007 dengue outbreak was investigated. Map of daily cases was generated for the 153 days of the outbreak. Epidemiological data from Chachoengsao province, Thailand (reported dengue cases for the years 1999-2007) was used for this study. To analyze the dynamic space-time pattern of dengue outbreaks, all cases were positioned in space at a village level. After a general statistical analysis (by gender and age group), data was subsequently analyzed for temporal patterns and correlation with climatic data (especially rainfall), spatial patterns and cluster analysis, and spatio-temporal patterns of hotspots during epidemics. The results revealed spatial diffusion patterns during the years 1999-2007 representing spatially clustered patterns with significant differences by village. Villages on the urban fringe reported higher incidences. The space and time of the cases showed outbreak movement and spread patterns that could be related to entomologic and epidemiologic factors. The hotspots showed the spatial trend of dengue diffusion. This study presents useful information related to the dengue outbreak patterns in space and time and may help public health departments to plan strategies to control the spread of disease. The methodology is general for space-time analysis and can be applied for other infectious diseases as well.

Dietary BMAA exposure in an amyotrophic lateral sclerosis cluster from southern France.

PubMed

Masseret, Estelle; Banack, Sandra; Boumédiène, Farid; Abadie, Eric; Brient, Luc; Pernet, Fabrice; Juntas-Morales, Raoul; Pageot, Nicolas; Metcalf, James; Cox, Paul; Camu, William

2013-01-01

Dietary exposure to the cyanotoxin BMAA is suspected to be the cause of amyotrophic lateral sclerosis in the Western Pacific Islands. In Europe and North America, this toxin has been identified in the marine environment of amyotrophic lateral sclerosis clusters but, to date, only few dietary exposures have been described. We aimed at identifying cluster(s) of amyotrophic lateral sclerosis in the Hérault district, a coastal district from Southern France, and to search, in the identified area(s), for the existence of a potential dietary source of BMAA. A spatio-temporal cluster analysis was performed in the district, considering all incident amyotrophic lateral sclerosis cases identified from 1994 to 2009 by our expert center. We investigated the cluster area with serial collections of oysters and mussels that were subsequently analyzed blind for BMAA concentrations. We found one significant amyotrophic lateral sclerosis cluster (p = 0.0024), surrounding the Thau lagoon, the most important area of shellfish production and consumption along the French Mediterranean coast. BMAA was identified in mussels (1.8 µg/g to 6.0 µg/g) and oysters (0.6 µg/g to 1.6 µg/g). The highest concentrations of BMAA were measured during summer when the highest picocyanobacteria abundances were recorded. While it is not possible to ascertain a direct link between shellfish consumption and the existence of this ALS cluster, these results add new data to the potential association of BMAA with sporadic amyotrophic lateral sclerosis, one of the most severe neurodegenerative disorder.

A typology of household-level adaptation to coastal flooding and its spatio-temporal patterns.

PubMed

Koerth, Jana; Vafeidis, Athanasios T; Carretero, Silvina; Sterr, Horst; Hinkel, Jochen

2014-01-01

The predicted sea-level rise and changes in storm surge regimes are expected to lead to an increasing risk of flooding in coastal regions. Accommodation can be an alternative to protection in many areas, with household-level adaptation potentially constituting an important element of such a strategy, as it can significantly reduce costs. To date, a systematic typology of household-level adaptation to coastal flooding does not exist. In order to bridge this gap, we conducted a series of quantitative surveys in different coastal areas in Denmark, Germany and Argentina. We applied a cluster analysis in order to categorise the adaptive behaviour of coastal households. Coastal households were found to cluster in four groups that we term: the comprehensives, the theoreticians, the minimalists and the structurals. With the exception of households focusing on the implementation of high-effort structural measures, our results show the affiliation to these groups to follow a specific temporal sequence. At the same time, large differences in category affiliation exist between the study areas. Risk communication tools can utilise our typology to selectively target specific types of households or to ensure that the information needs of all groups are addressed.

Testing the Prey-Trap Hypothesis at Two Wildlife Conservancies in Kenya.

PubMed

Dupuis-Desormeaux, Marc; Davidson, Zeke; Mwololo, Mary; Kisio, Edwin; Taylor, Sam; MacDonald, Suzanne E

2015-01-01

Protecting an endangered and highly poached species can conflict with providing an open and ecologically connected landscape for coexisting species. In Kenya, about half of the black rhino (Diceros bicornis) live in electrically fenced private conservancies. Purpose-built fence-gaps permit some landscape connectivity for elephant while restricting rhino from escaping. We monitored the usage patterns at these gaps by motion-triggered cameras and found high traffic volumes and predictable patterns of prey movement. The prey-trap hypothesis (PTH) proposes that predators exploit this predictable prey movement. We tested the PTH at two semi-porous reserves using two different methods: a spatial analysis and a temporal analysis. Using spatial analysis, we mapped the location of predation events with GPS and looked for concentration of kill sites near the gaps as well as conducting clustering and hot spot analysis to determine areas of statistically significant predation clustering. Using temporal analysis, we examined the time lapse between the passage of prey and predator and searched for evidence of active prey seeking and/or predator avoidance. We found no support for the PTH and conclude that the design of the fence-gaps is well suited to promoting connectivity in these types of conservancies.

Spatial Analysis of the Human Immunodeficiency Virus Epidemic among Men Who Have Sex with Men in China, 2006-2015.

PubMed

Qin, Qianqian; Guo, Wei; Tang, Weiming; Mahapatra, Tanmay; Wang, Liyan; Zhang, Nanci; Ding, Zhengwei; Cai, Chang; Cui, Yan; Sun, Jiangping

2017-04-01

Studies have shown a recent upsurge in human immunodeficiency virus (HIV) burden among men who have sex with men (MSM) in China, especially in urban areas. For intervention planning and resource allocation, spatial analyses of HIV/AIDS case-clusters were required to identify epidemic foci and trends among MSM in China. Information regarding MSM recorded as HIV/AIDS cases during 2006-2015 were extracted from the National Case Reporting System. Demographic trends were determined through Cochran-Armitage trend tests. Distribution of case-clusters was examined using spatial autocorrelation. Spatial-temporal scan was used to detect disease clustering. Spatial correlations between cases and socioenvironmental factors were determined by spatial regression. Between 2006 and 2015, in China, 120 371 HIV/AIDS cases were identified among MSM. Newly identified HIV/AIDS cases among self-reported MSM increased from 487 cases in 2006 to >30 000 cases in 2015. Among those HIV/AIDS cases recorded during 2006-2015, 47.0% were 20-29 years old and 24.9% were aged 30-39 years. Based on clusters of HIV/AIDS cases identified through spatial analysis, the epidemic was concentrated among MSM in large cities. Spatial-temporal clusters contained municipalities, provincial capitals, and main cities such as Beijing, Shanghai, Chongqing, Chengdu, and Guangzhou. Spatial regression analysis showed that sociodemographic indicators such as population density, per capita gross domestic product, and number of county-level medical institutions had statistically significant positive correlations with HIV/AIDS among MSM. Assorted spatial analyses revealed an increasingly concentrated HIV epidemic among young MSM in Chinese cities, calling for targeted health education and intensive interventions at an early age. © The Author 2017. Published by Oxford University Press for the Infectious Diseases Society of America. All rights reserved. For permissions, e-mail: journals.permissions@oup.com.

Temporal dynamics of retinal and extraretinal signals in the FEFsem during smooth pursuit eye movements

PubMed Central

Bakst, Leah; Fleuriet, Jérome

2017-01-01

Neurons in the smooth eye movement subregion of the frontal eye field (FEFsem) are known to play an important role in voluntary smooth pursuit eye movements. Underlying this function are projections to parietal and prefrontal visual association areas and subcortical structures, all known to play vital but differing roles in the execution of smooth pursuit. Additionally, the FEFsem has been shown to carry a diverse array of signals (e.g., eye velocity, acceleration, gain control). We hypothesized that distinct subpopulations of FEFsem neurons subserve these diverse functions and projections, and that the relative weights of retinal and extraretinal signals could form the basis for categorization of units. To investigate this, we used a step-ramp tracking task with a target blink to determine the relative contributions of retinal and extraretinal signals in individual FEFsem neurons throughout pursuit. We found that the contributions of retinal and extraretinal signals to neuronal activity and behavior change throughout the time course of pursuit. A clustering algorithm revealed three distinct neuronal subpopulations: cluster 1 was defined by a higher sensitivity to eye velocity, acceleration, and retinal image motion; cluster 2 had greater activity during blinks; and cluster 3 had significantly greater eye position sensitivity. We also performed a comparison with a sample of medial superior temporal neurons to assess similarities and differences between the two areas. Our results indicate the utility of simple tests such as the target blink for parsing the complex and multifaceted roles of cortical areas in behavior. NEW & NOTEWORTHY The frontal eye field (FEF) is known to play a critical role in volitional smooth pursuit, carrying a variety of signals that are distributed throughout the brain. This study used a novel application of a target blink task during step ramp tracking to determine, in combination with a clustering algorithm, the relative contributions of retinal and extraretinal signals to FEF activity and the extent to which these contributions could form the basis for a categorization of neurons. PMID:28202571

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

NASA Astrophysics Data System (ADS)

Salimi, F.; Ristovski, Z.; Mazaheri, M.; Laiman, R.; Crilley, L. R.; He, C.; Clifford, S.; Morawska, L.

2014-06-01

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods which have been recently employed to analyse PNSD data, however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K-means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and silhouette width validation values and the K-means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K-means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectra to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

Assessment and application of clustering techniques to atmospheric particle number size distribution for the purpose of source apportionment

NASA Astrophysics Data System (ADS)

Salimi, F.; Ristovski, Z.; Mazaheri, M.; Laiman, R.; Crilley, L. R.; He, C.; Clifford, S.; Morawska, L.

2014-11-01

Long-term measurements of particle number size distribution (PNSD) produce a very large number of observations and their analysis requires an efficient approach in order to produce results in the least possible time and with maximum accuracy. Clustering techniques are a family of sophisticated methods that have been recently employed to analyse PNSD data; however, very little information is available comparing the performance of different clustering techniques on PNSD data. This study aims to apply several clustering techniques (i.e. K means, PAM, CLARA and SOM) to PNSD data, in order to identify and apply the optimum technique to PNSD data measured at 25 sites across Brisbane, Australia. A new method, based on the Generalised Additive Model (GAM) with a basis of penalised B-splines, was proposed to parameterise the PNSD data and the temporal weight of each cluster was also estimated using the GAM. In addition, each cluster was associated with its possible source based on the results of this parameterisation, together with the characteristics of each cluster. The performances of four clustering techniques were compared using the Dunn index and Silhouette width validation values and the K means technique was found to have the highest performance, with five clusters being the optimum. Therefore, five clusters were found within the data using the K means technique. The diurnal occurrence of each cluster was used together with other air quality parameters, temporal trends and the physical properties of each cluster, in order to attribute each cluster to its source and origin. The five clusters were attributed to three major sources and origins, including regional background particles, photochemically induced nucleated particles and vehicle generated particles. Overall, clustering was found to be an effective technique for attributing each particle size spectrum to its source and the GAM was suitable to parameterise the PNSD data. These two techniques can help researchers immensely in analysing PNSD data for characterisation and source apportionment purposes.

GIS based spatial pattern analysis: Children with Hepatitis A in Turkey.

PubMed

Dogru, Ahmet Ozgur; David, Ruusa Magano; Ulugtekin, Necla; Goksel, Cigdem; Seker, Dursun Zafer; Sözen, Seval

2017-07-01

This study aimed to provide an insight into the geographic distribution of Hepatitis A incidence considering their temporal distribution, spatial patterns, hot spots and clusters identification in three different age-group (0-4, 5-9 and 10-14) in Turkey. Province based tabular data, including monthly numbers of Hepatitis A cases in children, and the populations from 2001 to 2011 were used as the basic input of the study. Time series maps were created using Geographic Information Systems (GIS) to introduce the temporal changes in the morbidity rates of Hepatitis A. The spatial variation of Hepatitis A was measured using Moran's I at the global level and the local indicators of spatial associations (LISAs) Moran's I and Getis-Ord G i *(d) in order to identify influential locations through clusters and hot spots detection of Hepatitis A cases. The morbidity rates in children under the age of 5 were found significantly lower than the other age-groups, whereas the age-group 5-9 revealed the highest morbidity rates in the study area. The morbidity of Hepatitis A was detected very high for the years 2001, and 2005-2007. The identification of the highly vulnerable provinces was conducted using local Moran's I and local Getis-Ord G i *(d). The majority of clusters and hot spots were detected to be agglomerated in the Eastern Mediterranean and South-Eastern Anatolian Regions and Ceyhan, Asi and Southeast part of Firat-Dicle river basins in Turkey. Copyright © 2017 Elsevier Inc. All rights reserved.

Geographical distribution and spatio-temporal patterns of hospitalization due to dengue infection at a leading specialist hospital in Malaysia.

PubMed

Low, Gary K K; Papapreponis, Panayoti; Isa, Ridzuan M; Gan, Seng Chiew; Chee, Hui Yee; Te, Kian Keong; Hatta, Nadia M

2018-05-07

Increasing numbers of dengue infection worldwide have led to a rise in deaths due to complications caused by this disease. We present here a cross-sectional study of dengue patients who attended the Emergency and Trauma Department of Ampang Hospital, one of Malaysia's leading specialist hospitals. The objective was to search for potential clustering of severe dengue, in space and/or time, among the annual admissions with the secondary objective to describe the spatio-temporal pattern of all dengue cases admitted to this hospital. The dengue status of the patients was confirmed serologically with the geographic location of the patients determined by residency, but not more specific than the street level. A total of 1165 dengue patients were included in the analysis using SaTScan software. The mean age of these patients was 27.8 years, with a standard deviation of 14.2 years and an age range from 1 to 77 years, among whom 54 (4.6%) were cases of severe dengue. A cluster of general dengue cases was identified occurring from October to December in the study year of 2015 but the inclusion of severe dengue in that cluster was not statistically significant (P=0.862). The standardized incidence ratio was 1.51. General presence of dengue cases was, however, detected to be concentrated at the end of the year, which should be useful for hospital planning and management if this pattern holds.

GPI-anchored proteins are confined in subdiffraction clusters at the apical surface of polarized epithelial cells.

PubMed

Paladino, Simona; Lebreton, Stéphanie; Lelek, Mickaël; Riccio, Patrizia; De Nicola, Sergio; Zimmer, Christophe; Zurzolo, Chiara

2017-12-01

Spatio-temporal compartmentalization of membrane proteins is critical for the regulation of diverse vital functions in eukaryotic cells. It was previously shown that, at the apical surface of polarized MDCK cells, glycosylphosphatidylinositol (GPI)-anchored proteins (GPI-APs) are organized in small cholesterol-independent clusters of single GPI-AP species (homoclusters), which are required for the formation of larger cholesterol-dependent clusters formed by multiple GPI-AP species (heteroclusters). This clustered organization is crucial for the biological activities of GPI-APs; hence, understanding the spatio-temporal properties of their membrane organization is of fundamental importance. Here, by using direct stochastic optical reconstruction microscopy coupled to pair correlation analysis (pc-STORM), we were able to visualize and measure the size of these clusters. Specifically, we show that they are non-randomly distributed and have an average size of 67 nm. We also demonstrated that polarized MDCK and non-polarized CHO cells have similar cluster distribution and size, but different sensitivity to cholesterol depletion. Finally, we derived a model that allowed a quantitative characterization of the cluster organization of GPI-APs at the apical surface of polarized MDCK cells for the first time. Experimental FRET (fluorescence resonance energy transfer)/FLIM (fluorescence-lifetime imaging microscopy) data were correlated to the theoretical predictions of the model. © 2017 The Author(s).

Behavioral training enhances cortical temporal processing in neonatally deafened juvenile cats

PubMed Central

Vollmer, Maike; Raggio, Marcia W.; Schreiner, Christoph E.

2011-01-01

Deaf humans implanted with a cochlear prosthesis depend largely on temporal cues for speech recognition because spectral information processing is severely impaired. Training with a cochlear prosthesis is typically required before speech perception shows improvement, suggesting that relevant experience modifies temporal processing in the central auditory system. We tested this hypothesis in neonatally deafened cats by comparing temporal processing in the primary auditory cortex (AI) of cats that received only chronic passive intracochlear electric stimulation (ICES) with cats that were also trained with ICES to detect temporally challenging trains of electric pulses. After months of chronic passive stimulation and several weeks of detection training in behaviorally trained cats, multineuronal AI responses evoked by temporally modulated ICES were recorded in anesthetized animals. The stimulus repetition rates that produced the maximum number of phase-locked spikes (best repetition rate) and 50% cutoff rate were significantly higher in behaviorally trained cats than the corresponding rates in cats that received only chronic passive ICES. Behavioral training restored neuronal temporal following ability to levels comparable with those recorded in naïve prior normal-hearing adult deafened animals. Importantly, best repetitition rates and cutoff rates were highest for neuronal clusters activated by the electrode configuration used in behavioral training. These results suggest that neuroplasticity in the AI is induced by behavioral training and perceptual learning in animals deprived of ordinary auditory experience during development and indicate that behavioral training can ameliorate or restore temporal processing in the AI of profoundly deaf animals. PMID:21543753

Spatio-temporal clustering and density estimation of lightning data for the tracking of convective events

NASA Astrophysics Data System (ADS)

Strauss, Cesar; Rosa, Marcelo Barbio; Stephany, Stephan

2013-12-01

Convective cells are cloud formations whose growth, maturation and dissipation are of great interest among meteorologists since they are associated with severe storms with large precipitation structures. Some works suggest a strong correlation between lightning occurrence and convective cells. The current work proposes a new approach to analyze the correlation between precipitation and lightning, and to identify electrically active cells. Such cells may be employed for tracking convective events in the absence of weather radar coverage. This approach employs a new spatio-temporal clustering technique based on a temporal sliding-window and a standard kernel density estimation to process lightning data. Clustering allows the identification of the cells from lightning data and density estimation bounds the contours of the cells. The proposed approach was evaluated for two convective events in Southeast Brazil. Image segmentation of radar data was performed to identify convective precipitation structures using the Steiner criteria. These structures were then compared and correlated to the electrically active cells in particular instants of time for both events. It was observed that most precipitation structures have associated cells, by comparing the ground tracks of their centroids. In addition, for one particular cell of each event, its temporal evolution was compared to that of the associated precipitation structure. Results show that the proposed approach may improve the use of lightning data for tracking convective events in countries that lack weather radar coverage.

Temporal models for the episodic volcanism of Campi Flegrei caldera (Italy) with uncertainty quantification

NASA Astrophysics Data System (ADS)

Bevilacqua, Andrea; Flandoli, Franco; Neri, Augusto; Isaia, Roberto; Vitale, Stefano

2016-11-01

After the large-scale event of Neapolitan Yellow Tuff ( 15 ka B.P.), intense and mostly explosive volcanism has occurred within and along the boundaries of the Campi Flegrei caldera (Italy). Eruptions occurred closely spaced in time, over periods from a few centuries to a few millennia, and were alternated with periods of quiescence lasting up to several millennia. Often events also occurred closely in space, thus generating a cluster of events. This study had two main objectives: (1) to describe the uncertainty in the geologic record by using a quantitative model and (2) to develop, based on the uncertainty assessment, a long-term subdomain specific temporal probability model that describes the temporal and spatial eruptive behavior of the caldera. In particular, the study adopts a space-time doubly stochastic nonhomogeneous Poisson-type model with a local self-excitation feature able to generate clustering of events which are consistent with the reconstructed record of Campi Flegrei. Results allow the evaluation of similarities and differences between the three epochs of activity as well as to derive eruptive base rate of the caldera and its capacity to generate clusters of events. The temporal probability model is also used to investigate the effect of the most recent eruption of Monte Nuovo (A.D. 1538) in a possible reactivation of the caldera and to estimate the time to the next eruption under different volcanological and modeling assumptions.

A Probabilistic Framework for Constructing Temporal Relations in Replica Exchange Molecular Trajectories.

PubMed

Chattopadhyay, Aditya; Zheng, Min; Waller, Mark Paul; Priyakumar, U Deva

2018-05-23

Knowledge of the structure and dynamics of biomolecules is essential for elucidating the underlying mechanisms of biological processes. Given the stochastic nature of many biological processes, like protein unfolding, it's almost impossible that two independent simulations will generate the exact same sequence of events, which makes direct analysis of simulations difficult. Statistical models like Markov Chains, transition networks etc. help in shedding some light on the mechanistic nature of such processes by predicting long-time dynamics of these systems from short simulations. However, such methods fall short in analyzing trajectories with partial or no temporal information, for example, replica exchange molecular dynamics or Monte Carlo simulations. In this work we propose a probabilistic algorithm, borrowing concepts from graph theory and machine learning, to extract reactive pathways from molecular trajectories in the absence of temporal data. A suitable vector representation was chosen to represent each frame in the macromolecular trajectory (as a series of interaction and conformational energies) and dimensionality reduction was performed using principal component analysis (PCA). The trajectory was then clustered using a density-based clustering algorithm, where each cluster represents a metastable state on the potential energy surface (PES) of the biomolecule under study. A graph was created with these clusters as nodes with the edges learnt using an iterative expectation maximization algorithm. The most reactive path is conceived as the widest path along this graph. We have tested our method on RNA hairpin unfolding trajectory in aqueous urea solution. Our method makes the understanding of the mechanism of unfolding in RNA hairpin molecule more tractable. As this method doesn't rely on temporal data it can be used to analyze trajectories from Monte Carlo sampling techniques and replica exchange molecular dynamics (REMD).

Dynamic transcriptomic analysis in hircine longissimus dorsi muscle from fetal to neonatal development stages.

PubMed

Zhan, Siyuan; Zhao, Wei; Song, Tianzeng; Dong, Yao; Guo, Jiazhong; Cao, Jiaxue; Zhong, Tao; Wang, Linjie; Li, Li; Zhang, Hongping

2018-01-01

Muscle growth and development from fetal to neonatal stages consist of a series of delicately regulated and orchestrated changes in expression of genes. In this study, we performed whole transcriptome profiling based on RNA-Seq of caprine longissimus dorsi muscle tissue obtained from prenatal stages (days 45, 60, and 105 of gestation) and neonatal stage (the 3-day-old newborn) to identify genes that are differentially expressed and investigate their temporal expression profiles. A total of 3276 differentially expressed genes (DEGs) were identified (Q value < 0.01). Time-series expression profile clustering analysis indicated that DEGs were significantly clustered into eight clusters which can be divided into two classes (Q value < 0.05), class I profiles with downregulated patterns and class II profiles with upregulated patterns. Based on cluster analysis, GO enrichment analysis found that 75, 25, and 8 terms to be significantly enriched in biological process (BP), cellular component (CC), and molecular function (MF) categories in class I profiles, while 35, 21, and 8 terms to be significantly enriched in BP, CC, and MF in class II profiles. KEGG pathway analysis revealed that DEGs from class I profiles were significantly enriched in 22 pathways and the most enriched pathway was Rap1 signaling pathway. DEGs from class II profiles were significantly enriched in 17 pathways and the mainly enriched pathway was AMPK signaling pathway. Finally, six selected DEGs from our sequencing results were confirmed by qPCR. Our study provides a comprehensive understanding of the molecular mechanisms during goat skeletal muscle development from fetal to neonatal stages and valuable information for future studies of muscle development in goats.

White matter alterations in college football players: a longitudinal diffusion tensor imaging study.

PubMed

Mayinger, Michael Christian; Merchant-Borna, Kian; Hufschmidt, Jakob; Muehlmann, Marc; Weir, Isabelle Ruth; Rauchmann, Boris-Stephan; Shenton, Martha Elizabeth; Koerte, Inga Katharina; Bazarian, Jeffrey John

2018-02-01

The aim of this study was to evaluate longitudinal changes in the diffusion characteristics of brain white matter (WM) in collegiate athletes at three time points: prior to the start of the football season (T1), after one season of football (T2), followed by six months of no-contact rest (T3). Fifteen male collegiate football players and 5 male non-athlete student controls underwent diffusion MR imaging and computerized cognitive testing at all three timepoints. Whole-brain tract-based spatial statistics (TBSS) were used to compare fractional anisotropy (FA), radial diffusivity (RD), axial diffusivity (AD), and trace between all timepoints. Average diffusion values were obtained from statistically significant clusters for each individual. No athlete suffered a concussion during the study period. After one season of play (T1 to T2), we observed a significant increase in trace in a cluster located in the brainstem and left temporal lobe, and a significant increase in FA in the left parietal lobe. After six months of no-contact rest (T2 to T3), there was a significant decrease in trace and FA in clusters that were partially overlapping or in close proximity with the initial clusters (T1 to T2), with no significant changes from T1 to T3. Repetitive head impacts (RHI) sustained during a single football season may result in alterations of the brain's WM in collegiate football players. These changes appear to return to baseline after 6 months of no-contact rest, suggesting remission of WM alterations. Our preliminary results suggest that collegiate football players might benefit from periods without exposure to RHI.

Evaluating spatial and temporal relationships between an earthquake cluster near Entiat, central Washington, and the large December 1872 Entiat earthquake

USGS Publications Warehouse

Brocher, Thomas M.; Blakely, Richard J.; Sherrod, Brian

2017-01-01

We investigate spatial and temporal relations between an ongoing and prolific seismicity cluster in central Washington, near Entiat, and the 14 December 1872 Entiat earthquake, the largest historic crustal earthquake in Washington. A fault scarp produced by the 1872 earthquake lies within the Entiat cluster; the locations and areas of both the cluster and the estimated 1872 rupture surface are comparable. Seismic intensities and the 1–2 m of coseismic displacement suggest a magnitude range between 6.5 and 7.0 for the 1872 earthquake. Aftershock forecast models for (1) the first several hours following the 1872 earthquake, (2) the largest felt earthquakes from 1900 to 1974, and (3) the seismicity within the Entiat cluster from 1976 through 2016 are also consistent with this magnitude range. Based on this aftershock modeling, most of the current seismicity in the Entiat cluster could represent aftershocks of the 1872 earthquake. Other earthquakes, especially those with long recurrence intervals, have long‐lived aftershock sequences, including the Mw">MwMw 7.5 1891 Nobi earthquake in Japan, with aftershocks continuing 100 yrs after the mainshock. Although we do not rule out ongoing tectonic deformation in this region, a long‐lived aftershock sequence can account for these observations.

Temporal clustering of tropical cyclones and its ecosystem impacts

PubMed Central

Mumby, Peter J.; Vitolo, Renato; Stephenson, David B.

2011-01-01

Tropical cyclones have massive economic, social, and ecological impacts, and models of their occurrence influence many planning activities from setting insurance premiums to conservation planning. Most impact models allow for geographically varying cyclone rates but assume that individual storm events occur randomly with constant rate in time. This study analyzes the statistical properties of Atlantic tropical cyclones and shows that local cyclone counts vary in time, with periods of elevated activity followed by relative quiescence. Such temporal clustering is particularly strong in the Caribbean Sea, along the coasts of Belize, Honduras, Costa Rica, Jamaica, the southwest of Haiti, and in the main hurricane development region in the North Atlantic between Africa and the Caribbean. Failing to recognize this natural nonstationarity in cyclone rates can give inaccurate impact predictions. We demonstrate this by exploring cyclone impacts on coral reefs. For a given cyclone rate, we find that clustered events have a less detrimental impact than independent random events. Predictions using a standard random hurricane model were overly pessimistic, predicting reef degradation more than a decade earlier than that expected under clustered disturbance. The presence of clustering allows coral reefs more time to recover to healthier states, but the impacts of clustering will vary from one ecosystem to another. PMID:22006300

Analysis of geographical disparities in temporal trends of health outcomes using space-time joinpoint regression

NASA Astrophysics Data System (ADS)

Goovaerts, Pierre

2013-06-01

Analyzing temporal trends in health outcomes can provide a more comprehensive picture of the burden of a disease like cancer and generate new insights about the impact of various interventions. In the United States such an analysis is increasingly conducted using joinpoint regression outside a spatial framework, which overlooks the existence of significant variation among U.S. counties and states with regard to the incidence of cancer. This paper presents several innovative ways to account for space in joinpoint regression: (1) prior filtering of noise in the data by binomial kriging and use of the kriging variance as measure of reliability in weighted least-square regression, (2) detection of significant boundaries between adjacent counties based on tests of parallelism of time trends and confidence intervals of annual percent change of rates, and (3) creation of spatially compact groups of counties with similar temporal trends through the application of hierarchical cluster analysis to the results of boundary analysis. The approach is illustrated using time series of proportions of prostate cancer late-stage cases diagnosed yearly in every county of Florida since 1980s. The annual percent change (APC) in late-stage diagnosis and the onset years for significant declines vary greatly across Florida. Most counties with non-significant average APC are located in the north-western part of Florida, known as the Panhandle, which is more rural than other parts of Florida. The number of significant boundaries peaked in the early 1990s when prostate-specific antigen (PSA) test became widely available, a temporal trend that suggests the existence of geographical disparities in the implementation and/or impact of the new screening procedure, in particular as it began available.

Synchrony in broadband fluctuation and the 2008 financial crisis.

PubMed

Lin, Der Chyan

2013-01-01

We propose phase-like characteristics in scale-free broadband processes and consider fluctuation synchrony based on the temporal signature of significant amplitude fluctuation. Using wavelet transform, successful captures of similar fluctuation pattern between such broadband processes are demonstrated. The application to the financial data leading to the 2008 financial crisis reveals the transition towards a qualitatively different dynamical regime with many equity price in fluctuation synchrony. Further analysis suggests an underlying scale free "price fluctuation network" with large clustering coefficient.

Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes

PubMed Central

Shimo, Hanae; Arjunan, Satya Nanda Vel; Machiyama, Hiroaki; Nishino, Taiko; Suematsu, Makoto; Fujita, Hideaki; Tomita, Masaru; Takahashi, Koichi

2015-01-01

Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs. PMID:26046580

Particle Simulation of Oxidation Induced Band 3 Clustering in Human Erythrocytes.

PubMed

Shimo, Hanae; Arjunan, Satya Nanda Vel; Machiyama, Hiroaki; Nishino, Taiko; Suematsu, Makoto; Fujita, Hideaki; Tomita, Masaru; Takahashi, Koichi

2015-06-01

Oxidative stress mediated clustering of membrane protein band 3 plays an essential role in the clearance of damaged and aged red blood cells (RBCs) from the circulation. While a number of previous experimental studies have observed changes in band 3 distribution after oxidative treatment, the details of how these clusters are formed and how their properties change under different conditions have remained poorly understood. To address these issues, a framework that enables the simultaneous monitoring of the temporal and spatial changes following oxidation is needed. In this study, we established a novel simulation strategy that incorporates deterministic and stochastic reactions with particle reaction-diffusion processes, to model band 3 cluster formation at single molecule resolution. By integrating a kinetic model of RBC antioxidant metabolism with a model of band 3 diffusion, we developed a model that reproduces the time-dependent changes of glutathione and clustered band 3 levels, as well as band 3 distribution during oxidative treatment, observed in prior studies. We predicted that cluster formation is largely dependent on fast reverse reaction rates, strong affinity between clustering molecules, and irreversible hemichrome binding. We further predicted that under repeated oxidative perturbations, clusters tended to progressively grow and shift towards an irreversible state. Application of our model to simulate oxidation in RBCs with cytoskeletal deficiency also suggested that oxidation leads to more enhanced clustering compared to healthy RBCs. Taken together, our model enables the prediction of band 3 spatio-temporal profiles under various situations, thus providing valuable insights to potentially aid understanding mechanisms for removing senescent and premature RBCs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kurt Derr; Milos Manic

Time and location data play a very significant role in a variety of factory automation scenarios, such as automated vehicles and robots, their navigation, tracking, and monitoring, to services of optimization and security. In addition, pervasive wireless capabilities combined with time and location information are enabling new applications in areas such as transportation systems, health care, elder care, military, emergency response, critical infrastructure, and law enforcement. A person/object in proximity to certain areas for specific durations of time may pose a risk hazard either to themselves, others, or the environment. This paper presents a novel fuzzy based spatio-temporal risk calculationmore » DSTiPE method that an object with wireless communications presents to the environment. The presented Matlab based application for fuzzy spatio-temporal risk cluster extraction is verified on a diagonal vehicle movement example.« less

Phylogenetic and Temporal Dynamics of Human Immunodeficiency Virus Type 1 CRF01_AE in China

PubMed Central

Su, Xueli; Lu, Hongyan; Pang, Xinghuo; Yan, Hong; Feng, Xia; He, Xiong; Zeng, Yi

2013-01-01

To explore the epidemic history of HIV-1 CRF01_AE in China, 408 fragments of gag gene sequences of CRF01_AE sampled in 2002–2010 were determined from different geographical regions and risk populations in China. Phylogenetic analysis indicates that the CRF01_AE sequences can be grouped into four clusters, suggesting that at least four genetically independent CRF01_AE descendants are circulating in China, of which two were closely related to the isolates from Thailand and Vietnam. Cluster 1 has the most extensive distribution in China. In North China, cluster 1 and cluster 4 were mainly transmitted through homosexuality.The real substance of the recent HIV-1 epidemic in men who have sex with men(MSM) of North China is a rapid spread of CRF01_AE, or rather two distinctive natives CRF01_AE.The time of the most recent common ancestor (tMRCA) of four CRF01_AE clusters ranged from the years 1990.9 to 2003.8 in different regions of China. This is the first phylogenetic and temporal dynamics study of HIV-1 CRF01_AE in China. PMID:23365653

Modeling spatio-temporal wildfire ignition point patterns

Treesearch

Amanda S. Hering; Cynthia L. Bell; Marc G. Genton

2009-01-01

We analyze and model the structure of spatio-temporal wildfire ignitions in the St. Johns River Water Management District in northeastern Florida. Previous studies, based on the K-function and an assumption of homogeneity, have shown that wildfire events occur in clusters. We revisit this analysis based on an inhomogeneous K-...

Egocentric Temporal Action Proposals.

PubMed

Shao Huang; Weiqiang Wang; Shengfeng He; Lau, Rynson W H

2018-02-01

We present an approach to localize generic actions in egocentric videos, called temporal action proposals (TAPs), for accelerating the action recognition step. An egocentric TAP refers to a sequence of frames that may contain a generic action performed by the wearer of a head-mounted camera, e.g., taking a knife, spreading jam, pouring milk, or cutting carrots. Inspired by object proposals, this paper aims at generating a small number of TAPs, thereby replacing the popular sliding window strategy, for localizing all action events in the input video. To this end, we first propose to temporally segment the input video into action atoms, which are the smallest units that may contain an action. We then apply a hierarchical clustering algorithm with several egocentric cues to generate TAPs. Finally, we propose two actionness networks to score the likelihood of each TAP containing an action. The top ranked candidates are returned as output TAPs. Experimental results show that the proposed TAP detection framework performs significantly better than relevant approaches for egocentric action detection.

Predominance and geo-mapping of avian influenza H5N1 in poultry sectors in Egypt.

PubMed

Arafa, Abdelsatar; El-Masry, Ihab; Khoulosy, Shereen; Hassan, Mohammed K; Soliman, Moussa; Fasanmi, Olubunmi G; Fasina, Folorunso O; Dauphin, Gwenaelle; Lubroth, Juan; Jobre, Yilma M

2016-11-28

Highly pathogenic avian influenza (HPAI) virus of the H5N1 subtype has been enzootic in the Egyptian poultry with significant human infections since 2008. This work evaluates the epidemiological and virological information from February 2006 to May 2015 in spatial and temporal terms. Only data with confirmed HPAI H5N1 sub-type were collected, and matched with the epidemiological data from various spatially and temporally-dispersed surveillances implemented between 2006 and 2015. Spatio-temporal analysis was conducted on a total of 3338 confirmed H5N1 HPAI poultry disease outbreaks and outputs described based on transmission patterns, poultry species, production types affected, trade, geographic and temporal distributions in Egypt. The H5N1 virus persists in the Egyptian poultry displaying a seasonal pattern with peak prevalence between January and March. There was no specific geographic pattern, but chickens and ducks were more affected. However, relatively higher disease incidences were recorded in the Nile Delta. Phylogenetic studies of the haemagglutinin gene sequences of H5N1 viruses indicated that multiple clusters circulated between 2006 and 2015, with significant deviations in circulation. Epidemiological dynamics of HPAI has changed with the origins of majority of outbreaks shifted to household poultry. The persistence of HPAI H5N1 in poultry with recurrent and sporadic infections in humans can influence virus evolution spatio-temporally. Household poultry plays significant roles in the H5N1 virus transmission to poultry and humans, but the role of commercial poultry needs further clarifications. While poultry trading supports the persistence and transmission of H5N1, the role of individual species may warrant further investigation. Surveillance activities, applying a multi-sectoral approach, are recommended.

Proper Motions and Structural Parameters of the Galactic Globular Cluster M71

NASA Astrophysics Data System (ADS)

Cadelano, M.; Dalessandro, E.; Ferraro, F. R.; Miocchi, P.; Lanzoni, B.; Pallanca, C.; Massari, D.

2017-02-01

By exploiting two ACS/HST data sets separated by a temporal baseline of ˜7 years, we have determined the relative stellar proper motions (PMs; providing membership) and the absolute PM of the Galactic globular cluster M71. The absolute PM has been used to reconstruct the cluster orbit within a Galactic, three-component, axisymmetric potential. M71 turns out to be in a low-latitude disk-like orbit inside the Galactic disk, further supporting the scenario in which it lost a significant fraction of its initial mass. Since large differential reddening is known to affect this system, we took advantage of near-infrared, ground-based observations to re-determine the cluster center and density profile from direct star counts. The new structural parameters turn out to be significantly different from the ones quoted in the literature. In particular, M71 has a core and a half-mass radii almost 50% larger than previously thought. Finally, we estimate that the initial mass of M71 was likely one order of magnitude larger than its current value, thus helping to solve the discrepancy with the observed number of X-ray sources. Based on observations collected with the NASA/ESA HST (GO10775, GO12932), obtained at the Space Telescope Science Institute, which is operated by AURA, Inc., under NASA contract NAS5-26555.

Modeling the spatio-temporal heterogeneity in the PM10-PM2.5 relationship

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Huang, Bo; Lin, Chuan-Yao

2015-02-01

This paper explores the spatio-temporal patterns of particulate matter (PM) in Taiwan based on a series of methods. Using fuzzy c-means clustering first, the spatial heterogeneity (six clusters) in the PM data collected between 2005 and 2009 in Taiwan are identified and the industrial and urban areas of Taiwan (southwestern, west central, northwestern, and northern Taiwan) are found to have high PM concentrations. The PM10-PM2.5 relationship is then modeled with global ordinary least squares regression, geographically weighted regression (GWR), and geographically and temporally weighted regression (GTWR). The GTWR and GWR produce consistent results; however, GTWR provides more detailed information of spatio-temporal variations of the PM10-PM2.5 relationship. The results also show that GTWR provides a relatively high goodness of fit and sufficient space-time explanatory power. In particular, the PM2.5 or PM10 varies with time and space, depending on weather conditions and the spatial distribution of land use and emission patterns in local areas. Such information can be used to determine patterns of spatio-temporal heterogeneity in PM that will allow the control of pollutants and the reduction of public exposure.

Decreased Metabolism in the Posterior Medial Network with Concomitantly Increased Metabolism in the Anterior Temporal Network During Transient Global Amnesia.

PubMed

Yi, SangHak; Park, Young Ho; Jang, Jae-Won; Lim, Jae-Sung; Chun, In Kook; Kim, SangYun

2018-05-01

Perturbation of corticohippocampal circuits is a key step in the pathogenesis of transient global amnesia. We evaluated the spatial distribution of altered cerebral metabolism to determine the location of the corticohippocampal circuits perturbed during the acute stage of transient global amnesia. A consecutive series of 12 patients with transient global amnesia who underwent 18 F-fluorodeoxyglucose positron emission tomography within 3 days after symptom onset was identified. We used statistical parametric mapping with two contrasts to identify regions of decreased and increased brain metabolism in transient global amnesia patients compared with 25 age-matched controls. Transient global amnesia patients showed hypometabolic clusters in the left temporal and bilateral parieto-occipital regions that belong to the posterior medial network as well as, hypermetabolic clusters in the bilateral inferior frontal regions that belong to the anterior temporal network. The posterior medial and anterior temporal networks are the two main corticohippocampal circuits involved in memory-guided behavior. Decreased metabolism in the posterior medial network might explain the impairment of episodic memory observed during the acute stage of transient global amnesia. Concomitant increased metabolism within the anterior temporal network might occur as a compensatory mechanism.

Spatio-temporal surveillance of water based infectious disease (malaria) in Rawalpindi, Pakistan using geostatistical modeling techniques.

PubMed

Ahmad, Sheikh Saeed; Aziz, Neelam; Butt, Amna; Shabbir, Rabia; Erum, Summra

2015-09-01

One of the features of medical geography that has made it so useful in health research is statistical spatial analysis, which enables the quantification and qualification of health events. The main objective of this research was to study the spatial distribution patterns of malaria in Rawalpindi district using spatial statistical techniques to identify the hot spots and the possible risk factor. Spatial statistical analyses were done in ArcGIS, and satellite images for land use classification were processed in ERDAS Imagine. Four hundred and fifty water samples were also collected from the study area to identify the presence or absence of any microbial contamination. The results of this study indicated that malaria incidence varied according to geographical location, with eco-climatic condition and showing significant positive spatial autocorrelation. Hotspots or location of clusters were identified using Getis-Ord Gi* statistic. Significant clustering of malaria incidence occurred in rural central part of the study area including Gujar Khan, Kaller Syedan, and some part of Kahuta and Rawalpindi Tehsil. Ordinary least square (OLS) regression analysis was conducted to analyze the relationship of risk factors with the disease cases. Relationship of different land cover with the disease cases indicated that malaria was more related with agriculture, low vegetation, and water class. Temporal variation of malaria cases showed significant positive association with the meteorological variables including average monthly rainfall and temperature. The results of the study further suggested that water supply and sewage system and solid waste collection system needs a serious attention to prevent any outbreak in the study area.

Spatio-Temporal Trends of Fire in Slash and Burn Agriculture Landscape: A Case Study from Nagaland, India

NASA Astrophysics Data System (ADS)

Padalia, H.; Mondal, P. P.

2014-11-01

Increasing incidences of fire from land conversion and residue burning in tropics is the major concern in global warming. Spatial and temporal monitoring of trends of fire incidences is, therefore, significant in order to determine contribution of carbon emissions from slash and burn agriculture. In this study, we analyzed time-series Terra / Aqua MODIS satellite hotspot products from 2001 to 2013 to derive intra- and inter-annual trends in fire incidences in Nagaland state, located in the Indo-Burma biodiversity hotspot. Time-series regression was applied to MODIS fire products at variable spatial scales in GIS. Significance of change in fire frequency at each grid level was tested using t statistic. Spatial clustering of higher or lower fire incidences across study area was determined using Getis-OrdGi statistic. Maximum fire incidences were encountered in moist mixed deciduous forests (46%) followed by secondary moist bamboo brakes (30%). In most parts of the study area fire incidences peaked during March while in warmer parts (e.g. Mon district dominated by indigenous people) fire activity starts as early as during November and peaks in January. Regression trend analysis captured noticeable areas with statistically significant positive (e.g. Mokokchung, Wokha, Mon, Tuensang and Kiphire districts) and negative (e.g. Kohima and north-western part of Mokokchung district) inter-annual fire frequency trends based on area-based aggregation of fire occurrences at different grid sizes. Localization of spatial clusters of high fire incidences was observed in Mokokchung, Wokha, Mon,Tuensang and Kiphire districts.

Temporal processing of audiovisual stimuli is enhanced in musicians: evidence from magnetoencephalography (MEG).

PubMed

Lu, Yao; Paraskevopoulos, Evangelos; Herholz, Sibylle C; Kuchenbuch, Anja; Pantev, Christo

2014-01-01

Numerous studies have demonstrated that the structural and functional differences between professional musicians and non-musicians are not only found within a single modality, but also with regard to multisensory integration. In this study we have combined psychophysical with neurophysiological measurements investigating the processing of non-musical, synchronous or various levels of asynchronous audiovisual events. We hypothesize that long-term multisensory experience alters temporal audiovisual processing already at a non-musical stage. Behaviorally, musicians scored significantly better than non-musicians in judging whether the auditory and visual stimuli were synchronous or asynchronous. At the neural level, the statistical analysis for the audiovisual asynchronous response revealed three clusters of activations including the ACC and the SFG and two bilaterally located activations in IFG and STG in both groups. Musicians, in comparison to the non-musicians, responded to synchronous audiovisual events with enhanced neuronal activity in a broad left posterior temporal region that covers the STG, the insula and the Postcentral Gyrus. Musicians also showed significantly greater activation in the left Cerebellum, when confronted with an audiovisual asynchrony. Taken together, our MEG results form a strong indication that long-term musical training alters the basic audiovisual temporal processing already in an early stage (direct after the auditory N1 wave), while the psychophysical results indicate that musical training may also provide behavioral benefits in the accuracy of the estimates regarding the timing of audiovisual events.

Universal quantum computation with temporal-mode bilayer square lattices

NASA Astrophysics Data System (ADS)

Alexander, Rafael N.; Yokoyama, Shota; Furusawa, Akira; Menicucci, Nicolas C.

2018-03-01

We propose an experimental design for universal continuous-variable quantum computation that incorporates recent innovations in linear-optics-based continuous-variable cluster state generation and cubic-phase gate teleportation. The first ingredient is a protocol for generating the bilayer-square-lattice cluster state (a universal resource state) with temporal modes of light. With this state, measurement-based implementation of Gaussian unitary gates requires only homodyne detection. Second, we describe a measurement device that implements an adaptive cubic-phase gate, up to a random phase-space displacement. It requires a two-step sequence of homodyne measurements and consumes a (non-Gaussian) cubic-phase state.

Deep Brain Stimulation of the Subthalamic Nucleus Improves Lexical Switching in Parkinsons Disease Patients.

PubMed

Vonberg, Isabelle; Ehlen, Felicitas; Fromm, Ortwin; Kühn, Andrea A; Klostermann, Fabian

2016-01-01

Reduced verbal fluency (VF) has been reported in patients with Parkinson's disease (PD), especially those treated by Deep Brain Stimulation of the subthalamic nucleus (STN DBS). To delineate the nature of this dysfunction we aimed at identifying the particular VF-related operations modified by STN DBS. Eleven PD patients performed VF tasks in their STN DBS ON and OFF condition. To differentiate VF-components modulated by the stimulation, a temporal cluster analysis was performed, separating production spurts (i.e., 'clusters' as correlates of automatic activation spread within lexical fields) from slower cluster transitions (i.e., 'switches' reflecting set-shifting towards new lexical fields). The results were compared to those of eleven healthy control subjects. PD patients produced significantly more switches accompanied by shorter switch times in the STN DBS ON compared to the STN DBS OFF condition. The number of clusters and time intervals between words within clusters were not affected by the treatment state. Although switch behavior in patients with DBS ON improved, their task performance was still lower compared to that of healthy controls. Beyond impacting on motor symptoms, STN DBS seems to influence the dynamics of cognitive procedures. Specifically, the results are in line with basal ganglia roles for cognitive switching, in the particular case of VF, from prevailing lexical concepts to new ones.

Intra-cluster Globular Clusters in a Simulated Galaxy Cluster

NASA Astrophysics Data System (ADS)

Ramos-Almendares, Felipe; Abadi, Mario; Muriel, Hernán; Coenda, Valeria

2018-01-01

Using a cosmological dark matter simulation of a galaxy-cluster halo, we follow the temporal evolution of its globular cluster population. To mimic the red and blue globular cluster populations, we select at high redshift (z∼ 1) two sets of particles from individual galactic halos constrained by the fact that, at redshift z = 0, they have density profiles similar to observed ones. At redshift z = 0, approximately 60% of our selected globular clusters were removed from their original halos building up the intra-cluster globular cluster population, while the remaining 40% are still gravitationally bound to their original galactic halos. As the blue population is more extended than the red one, the intra-cluster globular cluster population is dominated by blue globular clusters, with a relative fraction that grows from 60% at redshift z = 0 up to 83% for redshift z∼ 2. In agreement with observational results for the Virgo galaxy cluster, the blue intra-cluster globular cluster population is more spatially extended than the red one, pointing to a tidally disrupted origin.

Learning of spatio-temporal codes in a coupled oscillator system.

PubMed

Orosz, Gábor; Ashwin, Peter; Townley, Stuart

2009-07-01

In this paper, we consider a learning strategy that allows one to transmit information between two coupled phase oscillator systems (called teaching and learning systems) via frequency adaptation. The dynamics of these systems can be modeled with reference to a number of partially synchronized cluster states and transitions between them. Forcing the teaching system by steady but spatially nonhomogeneous inputs produces cyclic sequences of transitions between the cluster states, that is, information about inputs is encoded via a "winnerless competition" process into spatio-temporal codes. The large variety of codes can be learned by the learning system that adapts its frequencies to those of the teaching system. We visualize the dynamics using "weighted order parameters (WOPs)" that are analogous to "local field potentials" in neural systems. Since spatio-temporal coding is a mechanism that appears in olfactory systems, the developed learning rules may help to extract information from these neural ensembles.

Object Manifold Alignment for Multi-Temporal High Resolution Remote Sensing Images Classification

NASA Astrophysics Data System (ADS)

Gao, G.; Zhang, M.; Gu, Y.

2017-05-01

Multi-temporal remote sensing images classification is very useful for monitoring the land cover changes. Traditional approaches in this field mainly face to limited labelled samples and spectral drift of image information. With spatial resolution improvement, "pepper and salt" appears and classification results will be effected when the pixelwise classification algorithms are applied to high-resolution satellite images, in which the spatial relationship among the pixels is ignored. For classifying the multi-temporal high resolution images with limited labelled samples, spectral drift and "pepper and salt" problem, an object-based manifold alignment method is proposed. Firstly, multi-temporal multispectral images are cut to superpixels by simple linear iterative clustering (SLIC) respectively. Secondly, some features obtained from superpixels are formed as vector. Thirdly, a majority voting manifold alignment method aiming at solving high resolution problem is proposed and mapping the vector data to alignment space. At last, all the data in the alignment space are classified by using KNN method. Multi-temporal images from different areas or the same area are both considered in this paper. In the experiments, 2 groups of multi-temporal HR images collected by China GF1 and GF2 satellites are used for performance evaluation. Experimental results indicate that the proposed method not only has significantly outperforms than traditional domain adaptation methods in classification accuracy, but also effectively overcome the problem of "pepper and salt".

Source Identification of PM2.5 in Steubenville, Ohio Using a Hybrid Method for Highly Time-resolved Data

EPA Science Inventory

A new source-type identification method, Reduction and Species Clustering Using Episodes (ReSCUE), was developed to exploit the temporal synchronicity between species to form clusters of species that vary together. High time-resolution (30 min) PM_2.5 sampling was condu...

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm.

PubMed

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-05-21

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen's temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home.

Whole-brain structural topology in adult attention-deficit/hyperactivity disorder: Preserved global - disturbed local network organization.

PubMed

Sidlauskaite, Justina; Caeyenberghs, Karen; Sonuga-Barke, Edmund; Roeyers, Herbert; Wiersema, Jan R

2015-01-01

Prior studies demonstrate altered organization of functional brain networks in attention-deficit/hyperactivity disorder (ADHD). However, the structural underpinnings of these functional disturbances are poorly understood. In the current study, we applied a graph-theoretic approach to whole-brain diffusion magnetic resonance imaging data to investigate the organization of structural brain networks in adults with ADHD and unaffected controls using deterministic fiber tractography. Groups did not differ in terms of global network metrics - small-worldness, global efficiency and clustering coefficient. However, there were widespread ADHD-related effects at the nodal level in relation to local efficiency and clustering. The affected nodes included superior occipital, supramarginal, superior temporal, inferior parietal, angular and inferior frontal gyri, as well as putamen, thalamus and posterior cerebellum. Lower local efficiency of left superior temporal and supramarginal gyri was associated with higher ADHD symptom scores. Also greater local clustering of right putamen and lower local clustering of left supramarginal gyrus correlated with ADHD symptom severity. Overall, the findings indicate preserved global but altered local network organization in adult ADHD implicating regions underpinning putative ADHD-related neuropsychological deficits.

qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells.

PubMed

Andrews, J O; Conway, W; Cho, W -K; Narayanan, A; Spille, J -H; Jayanth, N; Inoue, T; Mullen, S; Thaler, J; Cissé, I I

2018-05-09

We present qSR, an analytical tool for the quantitative analysis of single molecule based super-resolution data. The software is created as an open-source platform integrating multiple algorithms for rigorous spatial and temporal characterizations of protein clusters in super-resolution data of living cells. First, we illustrate qSR using a sample live cell data of RNA Polymerase II (Pol II) as an example of highly dynamic sub-diffractive clusters. Then we utilize qSR to investigate the organization and dynamics of endogenous RNA Polymerase I (Pol I) in live human cells, throughout the cell cycle. Our analysis reveals a previously uncharacterized transient clustering of Pol I. Both stable and transient populations of Pol I clusters co-exist in individual living cells, and their relative fraction vary during cell cycle, in a manner correlating with global gene expression. Thus, qSR serves to facilitate the study of protein organization and dynamics with very high spatial and temporal resolutions directly in live cell.

Semantic search during divergent thinking.

PubMed

Hass, Richard W

2017-09-01

Divergent thinking, as a method of examining creative cognition, has not been adequately analyzed in the context of modern cognitive theories. This article casts divergent thinking responding in the context of theories of memory search. First, it was argued that divergent thinking tasks are similar to semantic fluency tasks, but are more constrained, and less well structured. Next, response time distributions from 54 participants were analyzed for temporal and semantic clustering. Participants responded to two prompts from the alternative uses test: uses for a brick and uses for a bottle, for two minutes each. Participants' cumulative response curves were negatively accelerating, in line with theories of search of associative memory. However, results of analyses of semantic and temporal clustering suggested that clustering is less evident in alternative uses responding compared to semantic fluency tasks. This suggests either that divergent thinking responding does not involve an exhaustive search through a clustered memory trace, but rather that the process is more exploratory, yielding fewer overall responses that tend to drift away from close associates of the divergent thinking prompt. Copyright © 2017 Elsevier B.V. All rights reserved.

Assessing historical rate changes in global tsunami occurrence

USGS Publications Warehouse

Geist, E.L.; Parsons, T.

2011-01-01

The global catalogue of tsunami events is examined to determine if transient variations in tsunami rates are consistent with a Poisson process commonly assumed for tsunami hazard assessments. The primary data analyzed are tsunamis with maximum sizes >1m. The record of these tsunamis appears to be complete since approximately 1890. A secondary data set of tsunamis >0.1m is also analyzed that appears to be complete since approximately 1960. Various kernel density estimates used to determine the rate distribution with time indicate a prominent rate change in global tsunamis during the mid-1990s. Less prominent rate changes occur in the early- and mid-20th century. To determine whether these rate fluctuations are anomalous, the distribution of annual event numbers for the tsunami catalogue is compared to Poisson and negative binomial distributions, the latter of which includes the effects of temporal clustering. Compared to a Poisson distribution, the negative binomial distribution model provides a consistent fit to tsunami event numbers for the >1m data set, but the Poisson null hypothesis cannot be falsified for the shorter duration >0.1m data set. Temporal clustering of tsunami sources is also indicated by the distribution of interevent times for both data sets. Tsunami event clusters consist only of two to four events, in contrast to protracted sequences of earthquakes that make up foreshock-main shock-aftershock sequences. From past studies of seismicity, it is likely that there is a physical triggering mechanism responsible for events within the tsunami source 'mini-clusters'. In conclusion, prominent transient rate increases in the occurrence of global tsunamis appear to be caused by temporal grouping of geographically distinct mini-clusters, in addition to the random preferential location of global M >7 earthquakes along offshore fault zones.

Promising Ideas for Collective Advancement of Communal Knowledge Using Temporal Analytics and Cluster Analysis

ERIC Educational Resources Information Center

Lee, Alwyn Vwen Yen; Tan, Seng Chee

2017-01-01

Understanding ideas in a discourse is challenging, especially in textual discourse analysis. We propose using temporal analytics with unsupervised machine learning techniques to investigate promising ideas for the collective advancement of communal knowledge in an online knowledge building discourse. A discourse unit network was constructed and…

Encoding of Spatio-Temporal Input Characteristics by a CA1 Pyramidal Neuron Model

PubMed Central

Pissadaki, Eleftheria Kyriaki; Sidiropoulou, Kyriaki; Reczko, Martin; Poirazi, Panayiota

2010-01-01

The in vivo activity of CA1 pyramidal neurons alternates between regular spiking and bursting, but how these changes affect information processing remains unclear. Using a detailed CA1 pyramidal neuron model, we investigate how timing and spatial arrangement variations in synaptic inputs to the distal and proximal dendritic layers influence the information content of model responses. We find that the temporal delay between activation of the two layers acts as a switch between excitability modes: short delays induce bursting while long delays decrease firing. For long delays, the average firing frequency of the model response discriminates spatially clustered from diffused inputs to the distal dendritic tree. For short delays, the onset latency and inter-spike-interval succession of model responses can accurately classify input signals as temporally close or distant and spatially clustered or diffused across different stimulation protocols. These findings suggest that a CA1 pyramidal neuron may be capable of encoding and transmitting presynaptic spatiotemporal information about the activity of the entorhinal cortex-hippocampal network to higher brain regions via the selective use of either a temporal or a rate code. PMID:21187899

Fluctuation scaling, Taylor's law, and crime.

PubMed

Hanley, Quentin S; Khatun, Suniya; Yosef, Amal; Dyer, Rachel-May

2014-01-01

Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor's law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor's law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057 ± 0.026) while burglary exhibited a greater exponent (α = 1.292 ± 0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor's law exponents from 1.43 ± 0.12 (Drugs) to 2.094 ± 0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation.

Fluctuation Scaling, Taylor’s Law, and Crime

PubMed Central

Hanley, Quentin S.; Khatun, Suniya; Yosef, Amal; Dyer, Rachel-May

2014-01-01

Fluctuation scaling relationships have been observed in a wide range of processes ranging from internet router traffic to measles cases. Taylor’s law is one such scaling relationship and has been widely applied in ecology to understand communities including trees, birds, human populations, and insects. We show that monthly crime reports in the UK show complex fluctuation scaling which can be approximated by Taylor’s law relationships corresponding to local policing neighborhoods and larger regional and countrywide scales. Regression models applied to local scale data from Derbyshire and Nottinghamshire found that different categories of crime exhibited different scaling exponents with no significant difference between the two regions. On this scale, violence reports were close to a Poisson distribution (α = 1.057±0.026) while burglary exhibited a greater exponent (α = 1.292±0.029) indicative of temporal clustering. These two regions exhibited significantly different pre-exponential factors for the categories of anti-social behavior and burglary indicating that local variations in crime reports can be assessed using fluctuation scaling methods. At regional and countrywide scales, all categories exhibited scaling behavior indicative of temporal clustering evidenced by Taylor’s law exponents from 1.43±0.12 (Drugs) to 2.094±0081 (Other Crimes). Investigating crime behavior via fluctuation scaling gives insight beyond that of raw numbers and is unique in reporting on all processes contributing to the observed variance and is either robust to or exhibits signs of many types of data manipulation. PMID:25271781

Finer parcellation reveals detailed correlational structure of resting-state fMRI signals.

PubMed

Dornas, João V; Braun, Jochen

2018-01-15

Even in resting state, the human brain generates functional signals (fMRI) with complex correlational structure. To simplify this structure, it is common to parcellate a standard brain into coarse chunks. Finer parcellations are considered less reproducible and informative, due to anatomical and functional variability of individual brains. Grouping signals with similar local correlation profiles, restricted to each anatomical region (Tzourio-Mazoyer et al., 2002), we divide a standard brain into 758 'functional clusters' averaging 1.7cm 3 gray matter volume ('MD758' parcellation). We compare 758 'spatial clusters' of similar size ('S758'). 'Functional clusters' are spatially contiguous and cluster quality (integration and segregation of temporal variance) is far superior to 'spatial clusters', comparable to multi-modal parcellations of half the resolution (Craddock et al., 2012; Glasser et al., 2016). Moreover, 'functional clusters' capture many long-range functional correlations, with O(10 5 ) reproducibly correlated cluster pairs in different anatomical regions. The pattern of functional correlations closely mirrors long-range anatomical connectivity established by fibre tracking. MD758 is comparable to coarser parcellations (Craddock et al., 2012; Glasser et al., 2016) in terms of cluster quality, correlational structure (54% relative mutual entropy vs 60% and 61%), and sparseness (35% significant pairwise correlations vs 36% and 44%). We describe and evaluate a simple path to finer functional parcellations of the human brain. Detailed correlational structure is surprisingly consistent between individuals, opening new possibilities for comparing functional correlations between cognitive conditions, states of health, or pharmacological interventions. Copyright © 2017 The Author(s). Published by Elsevier B.V. All rights reserved.

Comparative Study of Earthquake Clustering in Relation to Hydraulic Activities at Geothermal Fields in California

NASA Astrophysics Data System (ADS)

Martínez-Garzón, P.; Zaliapin, I. V.; Ben-Zion, Y.; Kwiatek, G.; Bohnhoff, M.

2017-12-01

We investigate earthquake clustering properties from three geothermal reservoirs to clarify how earthquake patterns respond to hydraulic activities. We process ≈ 9 years from four datasets corresponding to the Geysers (both the entire field and a local subset), Coso and Salton Sea geothermal fields, California. For each, the completeness magnitude, b-value and fractal dimension are calculated and used to identify seismicity clusters using the nearest-neighbor approach of Zaliapin and Ben-Zion [2013a, 2013b]. Estimations of temporal evolution of different clustering properties in relation to hydraulic parameters point to different responses of earthquake dynamics to hydraulic operations in each case study. The clustering at the Geysers at local scale and Salton Sea are most and least affected by hydraulic activities, respectively. The response of the earthquake clustering from different datasets to the hydraulic activities may reflect the regional seismo-tectonic complexity as well as the dimension of the geothermal activities performed (e.g. number of active wells and superposition of injection + production activities).Two clustering properties significantly respond to hydraulic changes across all datasets: the background rates and the proportion of clusters consisting of a single event. Background rates are larger at the Geysers and Coso during high injection-production periods, while the opposite holds for the Salton Sea. This possibly reflects the different physical mechanisms controlling seismicity at each geothermal field. Additionally, a lower proportion of singles is found during time periods with higher injection-production rates. This may reflect decreasing effective stress in areas subjected to higher pore pressure and larger earthquake triggering by stress transfer.

Dietary BMAA Exposure in an Amyotrophic Lateral Sclerosis Cluster from Southern France

PubMed Central

Masseret, Estelle; Banack, Sandra; Boumédiène, Farid; Abadie, Eric; Brient, Luc; Pernet, Fabrice; Juntas-Morales, Raoul; Pageot, Nicolas; Metcalf, James; Cox, Paul; Camu, William

2013-01-01

Background Dietary exposure to the cyanotoxin BMAA is suspected to be the cause of amyotrophic lateral sclerosis in the Western Pacific Islands. In Europe and North America, this toxin has been identified in the marine environment of amyotrophic lateral sclerosis clusters but, to date, only few dietary exposures have been described. Objectives We aimed at identifying cluster(s) of amyotrophic lateral sclerosis in the Hérault district, a coastal district from Southern France, and to search, in the identified area(s), for the existence of a potential dietary source of BMAA. Methods A spatio-temporal cluster analysis was performed in the district, considering all incident amyotrophic lateral sclerosis cases identified from 1994 to 2009 by our expert center. We investigated the cluster area with serial collections of oysters and mussels that were subsequently analyzed blind for BMAA concentrations. Results We found one significant amyotrophic lateral sclerosis cluster (p = 0.0024), surrounding the Thau lagoon, the most important area of shellfish production and consumption along the French Mediterranean coast. BMAA was identified in mussels (1.8 µg/g to 6.0 µg/g) and oysters (0.6 µg/g to 1.6 µg/g). The highest concentrations of BMAA were measured during summer when the highest picocyanobacteria abundances were recorded. Conclusions While it is not possible to ascertain a direct link between shellfish consumption and the existence of this ALS cluster, these results add new data to the potential association of BMAA with sporadic amyotrophic lateral sclerosis, one of the most severe neurodegenerative disorder. PMID:24349504

The distribution of saturated clusters in wetted granular materials

NASA Astrophysics Data System (ADS)

Li, Shuoqi; Hanaor, Dorian; Gan, Yixiang

2017-06-01

The hydro-mechanical behaviour of partially saturated granular materials is greatly influenced by the spatial and temporal distribution of liquid within the media. The aim of this paper is to characterise the distribution of saturated clusters in granular materials using an optical imaging method under different water drainage conditions. A saturated cluster is formed when a liquid phase fully occupies the pore space between solid grains in a localized region. The samples considered here were prepared by vibrating mono-sized glass beads to form closely packed assemblies in a rectangular container. A range of drainage conditions were applied to the specimen by tilting the container and employing different flow rates, and the liquid pressure was recorded at different positions in the experimental cell. The formation of saturated clusters during the liquid withdrawal processes is governed by three competing mechanisms arising from viscous, capillary, and gravitational forces. When the flow rate is sufficiently large and the gravity component is sufficiently small, the viscous force tends to destabilize the liquid front leading to the formation of narrow fingers of saturated material. As the water channels along these liquid fingers break, saturated clusters are formed inside the specimen. Subsequently, a spatial and temporal distribution of saturated clusters can be observed. We investigated the resulting saturated cluster distribution as a function of flow rate and gravity to achieve a fundamental understanding of the formation and evolution of such clusters in partially saturated granular materials. This study serves as a bridge between pore-scale behavior and the overall hydro-mechanical characteristics in partially saturated soils.

Using Fuzzy Clustering for Real-time Space Flight Safety

NASA Technical Reports Server (NTRS)

Lee, Charles; Haskell, Richard E.; Hanna, Darrin; Alena, Richard L.

2004-01-01

To ensure space flight safety, it is necessary to monitor myriad sensor readings on the ground and in flight. Since a space shuttle has many sensors, monitoring data and drawing conclusions from information contained within the data in real time is challenging. The nature of the information can be critical to the success of the mission and safety of the crew and therefore, must be processed with minimal data-processing time. Data analysis algorithms could be used to synthesize sensor readings and compare data associated with normal operation with the data obtained that contain fault patterns to draw conclusions. Detecting abnormal operation during early stages in the transition from safe to unsafe operation requires a large amount of historical data that can be categorized into different classes (non-risk, risk). Even though the 40 years of shuttle flight program has accumulated volumes of historical data, these data don t comprehensively represent all possible fault patterns since fault patterns are usually unknown before the fault occurs. This paper presents a method that uses a similarity measure between fuzzy clusters to detect possible faults in real time. A clustering technique based on a fuzzy equivalence relation is used to characterize temporal data. Data collected during an initial time period are separated into clusters. These clusters are characterized by their centroids. Clusters formed during subsequent time periods are either merged with an existing cluster or added to the cluster list. The resulting list of cluster centroids, called a cluster group, characterizes the behavior of a particular set of temporal data. The degree to which new clusters formed in a subsequent time period are similar to the cluster group is characterized by a similarity measure, q. This method is applied to downlink data from Columbia flights. The results show that this technique can detect an unexpected fault that has not been present in the training data set.

Comparative Performance Analysis of a Hyper-Temporal Ndvi Analysis Approach and a Landscape-Ecological Mapping Approach

NASA Astrophysics Data System (ADS)

Ali, A.; de Bie, C. A. J. M.; Scarrott, R. G.; Ha, N. T. T.; Skidmore, A. K.

2012-07-01

Both agricultural area expansion and intensification are necessary to cope with the growing demand for food, and the growing threat of food insecurity which is rapidly engulfing poor and under-privileged sections of the global population. Therefore, it is of paramount importance to have the ability to accurately estimate crop area and spatial distribution. Remote sensing has become a valuable tool for estimating and mapping cropland areas, useful in food security monitoring. This work contributes to addressing this broad issue, focusing on the comparative performance analysis of two mapping approaches (i) a hyper-temporal Normalized Difference Vegetation Index (NDVI) analysis approach and (ii) a Landscape-ecological approach. The hyper-temporal NDVI analysis approach utilized SPOT 10-day NDVI imagery from April 1998-December 2008, whilst the Landscape-ecological approach used multitemporal Landsat-7 ETM+ imagery acquired intermittently between 1992 and 2002. Pixels in the time-series NDVI dataset were clustered using an ISODATA clustering algorithm adapted to determine the optimal number of pixel clusters to successfully generalize hyper-temporal datasets. Clusters were then characterized with crop cycle information, and flooding information to produce an NDVI unit map of rice classes with flood regime and NDVI profile information. A Landscape-ecological map was generated using a combination of digitized homogenous map units in the Landsat-7 ETM+ imagery, a Land use map 2005 of the Mekong delta, and supplementary datasets on the regions terrain, geo-morphology and flooding depths. The output maps were validated using reported crop statistics, and regression analyses were used to ascertain the relationship between land use area estimated from maps, and those reported in district crop statistics. The regression analysis showed that the hyper-temporal NDVI analysis approach explained 74% and 76% of the variability in reported crop statistics in two rice crop and three rice crop land use systems respectively. In contrast, 64% and 63% of the variability was explained respectively by the Landscape-ecological map. Overall, the results indicate the hyper-temporal NDVI analysis approach is more accurate and more useful in exploring when, why and how agricultural land use manifests itself in space and time. Furthermore, the NDVI analysis approach was found to be easier to implement, was more cost effective, and involved less subjective user intervention than the landscape-ecological approach.

Spatio-Temporal Epidemiology of Viral Hepatitis in China (2003-2015): Implications for Prevention and Control Policies.

PubMed

Zhu, Bin; Liu, Jinlin; Fu, Yang; Zhang, Bo; Mao, Ying

2018-04-02

Viral hepatitis, as one of the most serious notifiable infectious diseases in China, takes heavy tolls from the infected and causes a severe economic burden to society, yet few studies have systematically explored the spatio-temporal epidemiology of viral hepatitis in China. This study aims to explore, visualize and compare the epidemiologic trends and spatial changing patterns of different types of viral hepatitis (A, B, C, E and unspecified, based on the classification of CDC) at the provincial level in China. The growth rates of incidence are used and converted to box plots to visualize the epidemiologic trends, with the linear trend being tested by chi-square linear by linear association test. Two complementary spatial cluster methods are used to explore the overall agglomeration level and identify spatial clusters: spatial autocorrelation analysis (measured by global and local Moran's I) and space-time scan analysis. Based on the spatial autocorrelation analysis, the hotspots of hepatitis A remain relatively stable and gradually shrunk, with Yunnan and Sichuan successively moving out the high-high (HH) cluster area. The HH clustering feature of hepatitis B in China gradually disappeared with time. However, the HH cluster area of hepatitis C has gradually moved towards the west, while for hepatitis E, the provincial units around the Yangtze River Delta region have been revealing HH cluster features since 2005. The space-time scan analysis also indicates the distinct spatial changing patterns of different types of viral hepatitis in China. It is easy to conclude that there is no one-size-fits-all plan for the prevention and control of viral hepatitis in all the provincial units. An effective response requires a package of coordinated actions, which should vary across localities regarding the spatial-temporal epidemic dynamics of each type of virus and the specific conditions of each provincial unit.

A spatio-temporal analysis of suicide in El Salvador.

PubMed

Carcach, Carlos

2017-04-20

In 2012, international statistics showed El Salvador's suicide rate as 40th in the world and the highest in Latin America. Over the last 15 years, national statistics show the suicide death rate declining as opposed to an increasing rate of homicide. Though completed suicide is an important social and health issue, little is known about its prevalence, incidence, etiology and spatio-temporal behavior. The primary objective of this study was to examine completed suicide and homicide using the stream analogy to lethal violence within a spatio-temporal framework. A Bayesian model was applied to examine the spatio-temporal evolution of the tendency of completed suicide over homicide in El Salvador. Data on numbers of suicides and homicides at the municipal level were obtained from the Instituto de Medicina Legal (IML) and population counts, from the Dirección General de Estadística y Censos (DIGESTYC), for the period of 2002 to 2012. Data on migration were derived from the 2007 Population Census, and inequality data were obtained from a study by Damianović, Valenzuela and Vera. The data reveal a stable standardized rate of total lethal violence (completed suicide plus homicide) across municipalities over time; a decline in suicide; and a standardized suicide rate decreasing with income inequality but increasing with social isolation. Municipalities clustered in terms of both total lethal violence and suicide standardized rates. Spatial effects for suicide were stronger among municipalities located in the north-east and center-south sides of the country. New clusters of municipalities with large suicide standardized rates were detected in the north-west, south-west and center-south regions, all of which are part of time-stable clusters of homicide. Prevention efforts to reduce income inequality and mitigate the negative effects of weak relational systems should focus upon municipalities forming time-persistent clusters with a large rate of death by suicide. In municipalities that are part of newly-formed suicide clusters and also are located in areas with a large rate of homicide, interrupting the expansion of spatial concentrations of suicide over time may require the implementation of both public health and public safety interventions.

[Analysis of epidemic features of scrub typhus between year 2006 and 2010 in Shandong province, China].

PubMed

Ding, Lei; Li, Zhong; Wang, Xian-jun; Ding, Shu-jun; Zhang, Meng; Zhao, Zhong-tang

2012-04-01

To explore the epidemic features of scrub typhus between year 2006 and 2010 in Shandong Province. Based on the data collected through Diseases Reporting Information System between year 2006 and 2010 in Shandong province, 1291 cases of scrub typhus were selected. The study described the population distribution features of the scrub typhus patients, and explored the temporal and spatial distribution features of the disease by applying the methods of spatial thematic mapping, inverse distance weighted, spatial autocorrelation analysis, spatial clustering analysis, temporal clustering analysis and spatial variation analysis in temporal trends based on Geographic Information software (ArcGIS 9.3) and Spatial Clustering Software (SatScan 7.0). The onset age of the 1291 patients ranged between 1 and 92 years old.639 out of 1291 patients were over 55 years old, accounting for 49.5%.640 patients were male and the other 651 patients were female, occupying 49.6% and 50.4% respectively. The gender ratio was 1:1.02. Patients were found in farmers, workers, students and preschool children. However, most of the cases were farmers, up to 84.8% (1095/1291). Global Moran's I index was 0.324 (P < 0.01). The local Moran's I index in 8 locations were proved to have statistical significance (P < 0.01); all of which were H-H clustering areas. Gangcheng (38 cases), Laicheng (154 cases), Xintai (160 cases) and Donggang (105 cases) were important locations, whose local Moran's I index were 2.111, 1.642, 1.277 and 0.775 respectively. The clustering period of scrub typhus in respective year were as follows: 2006.09.23 - 2006.11.20 (202 cases), 2007.10.02 - 2007.11.11 (197 cases), 2008.09.30 - 2008.11.07 (302 cases), 2009.09.25 - 2009.11.10 (204 cases), and 2010.10.05 - 2010.11.13 (226 cases), whose RR values were separately 45.55, 34.60, 50.64, 53.09 and 79.84 (P < 0.01). Two spatial clustering area were found in the study, one was the area centered Taian and Xintai with radiation radius at 58.28 km (542 cases) and the other one was the area centered Rizhao and Donggang with radiation radius at 22.68 km (134 cases), whose RR values were 4.52 and 3.96 (P < 0.01). The spatial features of the two clustering areas were inland low hills area and coastal hills area. The highest annual growth rate of the disease was 45.04%, found in the area centered Linyi and Mengyin counties, with the radiation radius at 45.82 km. The RR value was 3.68 (P < 0.01). The majority of the scrub typhus patients were middle-aged and elderly farmers. The epidemic peak was between the last 10 days of September and the first 10 days of November. A positive spatial correlation of the disease was found; and most cases clustered in inland low hills area and costal hills area; especially the area around Linyi and Mengyin, with the highest annual growth rates of the disease.

Spatial and temporal assessment of cumulative disturbance impacts due to military training, burning, haying, and their interactions on land condition of Fort Riley.

PubMed

Wang, Guangxing; Murphy, Dana; Oller, Adam; Howard, Heidi R; Anderson, Alan B; Rijal, Santosh; Myers, Natalie R; Woodford, Philip

2014-07-01

The effects of military training activities on the land condition of Army installations vary spatially and temporally. Training activities observably degrade land condition while also increasing biodiversity and stabilizing ecosystems. Moreover, other anthropogenic activities regularly occur on military lands such as prescribed burns and agricultural haying-adding to the dynamics of land condition. Thus, spatially and temporally assessing the impacts of military training, prescribed burning, agricultural haying, and their interactions is critical to the management of military lands. In this study, the spatial distributions and patterns of military training-induced disturbance frequency were derived using plot observation and point observation-based method, at Fort Riley, Kansas from 1989 to 2001. Moreover, spatial and variance analysis of cumulative impacts due to military training, burning, haying, and their interactions on the land condition of Fort Riley were conducted. The results showed that: (1) low disturbance intensity dominated the majority of the study area with exception of concentrated training within centralized areas; (2) high and low values of disturbance frequency were spatially clustered and had spatial patterns that differed significantly from a random distribution; and (3) interactions between prescribed burning and agricultural haying were not significant in terms of either soil erosion or disturbance intensity although their means and variances differed significantly between the burned and non-burned areas and between the hayed and non-hayed areas.

Characterization of atypical language activation patterns in focal epilepsy.

PubMed

Berl, Madison M; Zimmaro, Lauren A; Khan, Omar I; Dustin, Irene; Ritzl, Eva; Duke, Elizabeth S; Sepeta, Leigh N; Sato, Susumu; Theodore, William H; Gaillard, William D

2014-01-01

Functional magnetic resonance imaging is sensitive to the variation in language network patterns. Large populations are needed to rigorously assess atypical patterns, which, even in neurological populations, are a minority. We studied 220 patients with focal epilepsy and 118 healthy volunteers who performed an auditory description decision task. We compared a data-driven hierarchical clustering approach to the commonly used a priori laterality index (LI) threshold (LI < 0.20 as atypical) to classify language patterns within frontal and temporal regions of interest. We explored (n = 128) whether IQ varied with different language activation patterns. The rate of atypical language among healthy volunteers (2.5%) and patients (24.5%) agreed with previous studies; however, we found 6 patterns of atypical language: a symmetrically bilateral, 2 unilaterally crossed, and 3 right dominant patterns. There was high agreement between classification methods, yet the cluster analysis revealed novel correlations with clinical features. Beyond the established association of left-handedness, early seizure onset, and vascular pathology with atypical language, cluster analysis identified an association of handedness with frontal lateralization, early seizure onset with temporal lateralization, and left hemisphere focus with a unilateral right pattern. Intelligence quotient was not significantly different among patterns. Language dominance is a continuum; however, our results demonstrate meaningful thresholds in classifying laterality. Atypical language patterns are less frequent but more variable than typical language patterns, posing challenges for accurate presurgical planning. Language dominance should be assessed on a regional rather than hemispheric basis, and clinical characteristics should inform evaluation of atypical language dominance. Reorganization of language is not uniformly detrimental to language functioning. © 2014 American Neurological Association.

Spatio-Temporal Structure, Path Characteristics, and Perceptual Grouping in Immediate Serial Spatial Recall

PubMed Central

De Lillo, Carlo; Kirby, Melissa; Poole, Daniel

2016-01-01

Immediate serial spatial recall measures the ability to retain sequences of locations in short-term memory and is considered the spatial equivalent of digit span. It is tested by requiring participants to reproduce sequences of movements performed by an experimenter or displayed on a monitor. Different organizational factors dramatically affect serial spatial recall but they are often confounded or underspecified. Untangling them is crucial for the characterization of working-memory models and for establishing the contribution of structure and memory capacity to spatial span. We report five experiments assessing the relative role and independence of factors that have been reported in the literature. Experiment 1 disentangled the effects of spatial clustering and path-length by manipulating the distance of items displayed on a touchscreen monitor. Long-path sequences segregated by spatial clusters were compared with short-path sequences not segregated by clusters. Recall was more accurate for sequences segregated by clusters independently from path-length. Experiment 2 featured conditions where temporal pauses were introduced between or within cluster boundaries during the presentation of sequences with the same paths. Thus, the temporal structure of the sequences was either consistent or inconsistent with a hierarchical representation based on segmentation by spatial clusters but the effect of structure could not be confounded with effects of path-characteristics. Pauses at cluster boundaries yielded more accurate recall, as predicted by a hierarchical model. In Experiment 3, the systematic manipulation of sequence structure, path-length, and presence of path-crossings of sequences showed that structure explained most of the variance, followed by the presence/absence of path-crossings, and path-length. Experiments 4 and 5 replicated the results of the previous experiments in immersive virtual reality navigation tasks where the viewpoint of the observer changed dynamically during encoding and recall. This suggested that the effects of structure in spatial span are not dependent on perceptual grouping processes induced by the aerial view of the stimulus array typically afforded by spatial recall tasks. These results demonstrate the independence of coding strategies based on structure from effects of path characteristics and perceptual grouping in immediate serial spatial recall. PMID:27891101

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

PubMed

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-04-08

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression

PubMed Central

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-01-01

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale. PMID:28397745

Disrupted Cerebro-cerebellar Intrinsic Functional Connectivity in Young Adults with High-functioning Autism Spectrum Disorder: A Data-driven, Whole-brain, High Temporal Resolution fMRI Study.

PubMed

Arnold Anteraper, Sheeba; Guell, Xavier; D'Mello, Anila; Joshi, Neha; Whitfield-Gabrieli, Susan; Joshi, Gagan

2018-06-13

To examine the resting-state functional-connectivity (RsFc) in young adults with high-functioning autism spectrum disorder (HF-ASD) using state-of-the-art fMRI data acquisition and analysis techniques. Simultaneous multi-slice, high temporal resolution fMRI acquisition; unbiased whole-brain connectome-wide multivariate pattern analysis (MVPA) techniques for assessing RsFc; and post-hoc whole-brain seed-to-voxel analyses using MVPA results as seeds. MVPA revealed two clusters of abnormal connectivity in the cerebellum. Whole-brain seed-based functional connectivity analyses informed by MVPA-derived clusters showed significant under connectivity between the cerebellum and social, emotional, and language brain regions in the HF-ASD group compared to healthy controls. The results we report are coherent with existing structural, functional, and RsFc literature in autism, extend previous literature reporting cerebellar abnormalities in the neuropathology of autism, and highlight the cerebellum as a potential target for therapeutic, diagnostic, predictive, and prognostic developments in ASD. The description of functional connectivity abnormalities using whole-brain, data-driven analyses as reported in the present study may crucially advance the development of ASD biomarkers, targets for therapeutic interventions, and neural predictors for measuring treatment response.

Effect of transmission intensity on hotspots and micro-epidemiology of malaria in sub-Saharan Africa.

PubMed

Mogeni, Polycarp; Omedo, Irene; Nyundo, Christopher; Kamau, Alice; Noor, Abdisalan; Bejon, Philip

2017-06-30

Malaria transmission intensity is heterogeneous, complicating the implementation of malaria control interventions. We provide a description of the spatial micro-epidemiology of symptomatic malaria and asymptomatic parasitaemia in multiple sites. We assembled data from 19 studies conducted between 1996 and 2015 in seven countries of sub-Saharan Africa with homestead-level geospatial data. Data from each site were used to quantify spatial autocorrelation and examine the temporal stability of hotspots. Parameters from these analyses were examined to identify trends over varying transmission intensity. Significant hotspots of malaria transmission were observed in most years and sites. The risk ratios of malaria within hotspots were highest at low malaria positive fractions (MPFs) and decreased with increasing MPF (p < 0.001). However, statistical significance of hotspots was lowest at extremely low and extremely high MPFs, with a peak in statistical significance at an MPF of ~0.3. In four sites with longitudinal data we noted temporal instability and variable negative correlations between MPF and average age of symptomatic malaria across all sites, suggesting varying degrees of temporal stability. We observed geographical micro-variation in malaria transmission at sites with a variety of transmission intensities across sub-Saharan Africa. Hotspots are marked at lower transmission intensity, but it becomes difficult to show statistical significance when cases are sparse at very low transmission intensity. Given the predictability with which hotspots occur as transmission intensity falls, malaria control programmes should have a low threshold for responding to apparent clustering of cases.

Strong and weak plasma response to dietary carotenoids identified by cluster analysis and linked to beta-carotene 15,15'-monooxygenase 1 single nucleotide polymorphisms

USDA-ARS?s Scientific Manuscript database

The mechanisms as well the genetics underlying bioavailability and metabolism of carotenoids in humans remains unclear. The individual temporal response of plasma carotenoids was analyzed in adults who consumed carotenoid-containing juices on a controlled-diet study using cluster analysis. Treatmen...

Geographical Analysis of the Distribution and Spread of Human Rabies in China from 2005 to 2011

PubMed Central

Yin, Wenwu; Yu, Hongjie; Si, Yali; Li, Jianhui; Zhou, Yuanchun; Zhou, Xiaoyan; Magalhães, Ricardo J. Soares.

2013-01-01

Background Rabies is a significant public health problem in China in that it records the second highest case incidence globally. Surveillance data on canine rabies in China is lacking and human rabies notifications can be a useful indicator of areas where animal and human rabies control could be integrated. Previous spatial epidemiological studies lacked adequate spatial resolution to inform targeted rabies control decisions. We aimed to describe the spatiotemporal distribution of human rabies and model its geographical spread to provide an evidence base to inform future integrated rabies control strategies in China. Methods We geo-referenced a total of 17,760 human rabies cases of China from 2005 to 2011. In our spatial analyses we used Gaussian kernel density analysis, average nearest neighbor distance, Spatial Temporal Density-Based Spatial Clustering of Applications with Noise and developed a model of rabies spatiotemporal spread. Findings Human rabies cases increased from 2005 to 2007 and decreased during 2008 to 2011 companying change of the spatial distribution. The ANN distance among human rabies cases increased between 2005 and 2011, and the degree of clustering of human rabies cases decreased during that period. A total 480 clusters were detected by ST-DBSCAN, 89.4% clusters initiated before 2007. Most of clusters were mainly found in South of China. The number and duration of cluster decreased significantly after 2008. Areas with the highest density of human rabies cases varied spatially each year and in some areas remained with high outbreak density for several years. Though few places have recovered from human rabies, most of affected places are still suffering from the disease. Conclusion Human rabies in mainland China is geographically clustered and its spatial extent changed during 2005 to 2011. The results provide a scientific basis for public health authorities in China to improve human rabies control and prevention program. PMID:23991098

Voxel-level comparison of arterial spin-labeled perfusion magnetic resonance imaging in adolescents with internet gaming addiction

PubMed Central

2013-01-01

Background Although recent studies have clearly demonstrated functional and structural abnormalities in adolescents with internet gaming addiction (IGA), less is known about how IGA affects perfusion in the human brain. We used pseudocontinuous arterial spin-labeling (ASL) perfusion functional magnetic resonance imaging (fMRI) to measure the effects of IGA on resting brain functions by comparing resting cerebral blood flow in adolescents with IGA and normal subjects. Methods Fifteen adolescents with IGA and 18 matched normal adolescents underwent structural and perfusion fMRI in the resting state. Direct subtraction, voxel-wise general linear modeling was performed to compare resting cerebral blood flow (CBF) between the 2 groups. Correlations were calculated between the mean CBF value in all clusters that survived AlphaSim correction and the Chen Internet Addiction Scale (CIAS) scores, Barratt Impulsiveness Scale-11 (BIS-11) scores, or hours of Internet use per week (hours) in the 15 subjects with IGA. Results Compared with control subjects, adolescents with IGA showed significantly higher global CBF in the left inferior temporal lobe/fusiform gyrus, left parahippocampal gyrus/amygdala, right medial frontal lobe/anterior cingulate cortex, left insula, right insula, right middle temporal gyrus, right precentral gyrus, left supplementary motor area, left cingulate gyrus, and right inferior parietal lobe. Lower CBF was found in the left middle temporal gyrus, left middle occipital gyrus, and right cingulate gyrus. There were no significant correlations between mean CBF values in all clusters that survived AlphaSim correction and CIAS or BIS-11 scores or hours of Internet use per week. Conclusions In this study, we used ASL perfusion fMRI and noninvasively quantified resting CBF to demonstrate that IGA alters the CBF distribution in the adolescent brain. The results support the hypothesis that IGA is a behavioral addiction that may share similar neurobiological abnormalities with other addictive disorders. PMID:23937918

Assessment of the vision-specific quality of life using clustered visual field in glaucoma patients.

PubMed

Sawada, Hideko; Yoshino, Takaiko; Fukuchi, Takeo; Abe, Haruki

2014-02-01

To investigate the significance of vision-specific quality of life (QOL) in glaucoma patients based on the location of visual field defects. We examined 336 eyes of 168 patients. The 25-item National Eye Institute Visual Function Questionnaire was used to evaluate patients' QOL. Visual field testing was performed using the Humphrey Field Analyzer; the visual field was divided into 10 clusters. We defined the eye with better mean deviation as the better eye and the fellow eye as the worse eye. A single linear regression analysis was applied to assess the significance of the relationship between QOL and the clustered visual field. The strongest correlation was observed in the lower paracentral visual field in the better eye. The lower peripheral visual field in the better eye also showed a good correlation. Correlation coefficients in the better eye were generally higher than those in the worse eye. For driving, the upper temporal visual field in the better eye was the most strongly correlated (r=0.509). For role limitation and peripheral vision, the lower peripheral visual field in the better eye had the highest correlation coefficients at 0.459 and 0.425, respectively. Overall, clusters in the lower hemifield in the better eye were more strongly correlated with QOL than those in the worse eye. In particular, the lower paracentral visual field in the better eye was correlated most strongly of all. Driving, however, strongly correlated with the upper hemifield in the better eye.

A Predictive Risk Model for A(H7N9) Human Infections Based on Spatial-Temporal Autocorrelation and Risk Factors: China, 2013–2014

PubMed Central

Dong, Wen; Yang, Kun; Xu, Quan-Li; Yang, Yu-Lian

2015-01-01

This study investigated the spatial distribution, spatial autocorrelation, temporal cluster, spatial-temporal autocorrelation and probable risk factors of H7N9 outbreaks in humans from March 2013 to December 2014 in China. The results showed that the epidemic spread with significant spatial-temporal autocorrelation. In order to describe the spatial-temporal autocorrelation of H7N9, an improved model was developed by introducing a spatial-temporal factor in this paper. Logistic regression analyses were utilized to investigate the risk factors associated with their distribution, and nine risk factors were significantly associated with the occurrence of A(H7N9) human infections: the spatial-temporal factor φ (OR = 2546669.382, p < 0.001), migration route (OR = 0.993, p < 0.01), river (OR = 0.861, p < 0.001), lake(OR = 0.992, p < 0.001), road (OR = 0.906, p < 0.001), railway (OR = 0.980, p < 0.001), temperature (OR = 1.170, p < 0.01), precipitation (OR = 0.615, p < 0.001) and relative humidity (OR = 1.337, p < 0.001). The improved model obtained a better prediction performance and a higher fitting accuracy than the traditional model: in the improved model 90.1% (91/101) of the cases during February 2014 occurred in the high risk areas (the predictive risk > 0.70) of the predictive risk map, whereas 44.6% (45/101) of which overlaid on the high risk areas (the predictive risk > 0.70) for the traditional model, and the fitting accuracy of the improved model was 91.6% which was superior to the traditional model (86.1%). The predictive risk map generated based on the improved model revealed that the east and southeast of China were the high risk areas of A(H7N9) human infections in February 2014. These results provided baseline data for the control and prevention of future human infections. PMID:26633446

Beta Oscillatory Dynamics in the Prefrontal and Superior Temporal Cortices Predict Spatial Working Memory Performance.

PubMed

Proskovec, Amy L; Wiesman, Alex I; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2018-05-31

The oscillatory dynamics serving spatial working memory (SWM), and how such dynamics relate to performance, are poorly understood. To address these topics, the present study recruited 22 healthy adults to perform a SWM task during magnetoencephalography (MEG). The resulting MEG data were transformed into the time-frequency domain, and significant oscillatory responses were imaged using a beamformer. Voxel time series data were extracted from the cluster peaks to quantify the dynamics, while whole-brain partial correlation maps were computed to identify regions where oscillatory strength varied with accuracy on the SWM task. The results indicated transient theta oscillations in spatially distinct subregions of the prefrontal cortices at the onset of encoding and maintenance, which may underlie selection of goal-relevant information. Additionally, strong and persistent decreases in alpha and beta oscillations were observed throughout encoding and maintenance in parietal, temporal, and occipital regions, which could serve sustained attention and maintenance processes during SWM performance. The neuro-behavioral correlations revealed that beta activity within left dorsolateral prefrontal control regions and bilateral superior temporal integration regions was negatively correlated with SWM accuracy. Notably, this is the first study to employ a whole-brain approach to significantly link neural oscillations to behavioral performance in the context of SWM.

Simplified Summative Temporal Bone Dissection Scale Demonstrates Equivalence to Existing Measures.

PubMed

Pisa, Justyn; Gousseau, Michael; Mowat, Stephanie; Westerberg, Brian; Unger, Bert; Hochman, Jordan B

2018-01-01

Emphasis on patient safety has created the need for quality assessment of fundamental surgical skills. Existing temporal bone rating scales are laborious, subject to evaluator fatigue, and contain inconsistencies when conferring points. To address these deficiencies, a novel binary assessment tool was designed and validated against a well-established rating scale. Residents completed a mastoidectomy with posterior tympanotomy on identical 3D-printed temporal bone models. Four neurotologists evaluated each specimen using a validated scale (Welling) and a newly developed "CanadaWest" scale, with scoring repeated after a 4-week interval. Nineteen participants were clustered into junior, intermediate, and senior cohorts. An ANOVA found significant differences between performance of the junior-intermediate and junior-senior cohorts for both Welling and CanadaWest scales ( P < .05). Neither scale found a significant difference between intermediate-senior resident performance ( P > .05). Cohen's kappa found strong intrarater reliability (0.711) with a high degree of interrater reliability of (0.858) for the CanadaWest scale, similar to scores on the Welling scale of (0.713) and (0.917), respectively. The CanadaWest scale was facile and delineated performance by experience level with strong intrarater reliability. Comparable to the validated Welling Scale, it distinguished junior from senior trainees but was challenged in differentiating intermediate and senior trainee performance.

Identifying patterns of general practitioner service utilisation and their relationship with potentially preventable hospitalisations in people with diabetes: The utility of a cluster analysis approach.

PubMed

Ha, Ninh Thi; Harris, Mark; Preen, David; Robinson, Suzanne; Moorin, Rachael

2018-04-01

We aimed to characterise use of general practitioners (GP) simultaneously across multiple attributes in people with diabetes and examine its impact on diabetes related potentially preventable hospitalisations (PPHs). Five-years of panel data from 40,625 adults with diabetes were sourced from Western Australian administrative health records. Cluster analysis (CA) was used to group individuals with similar patterns of GP utilisation characterised by frequency and recency of services. The relationship between GP utilisation cluster and the risk of PPHs was examined using multivariable random-effects negative binomial regression. CA categorised GP utilisation into three clusters: moderate; high and very high usage, having distinct patient characteristics. After adjusting for potential confounders, the rate of PPHs was significantly lower across all GP usage clusters compared with those with no GP usage; IRR = 0.67 (95%CI: 0.62-0.71) among the moderate, IRR = 0.70 (95%CI 0.66-0.73) high and IRR = 0.76 (95%CI 0.72-0.80) very high GP usage clusters. Combination of temporal factors with measures of frequency of use of GP services revealed patterns of primary health care utilisation associated with different underlying patient characteristics. Incorporation of multiple attributes, that go beyond frequency-based approaches may better characterise the complex relationship between use of GP services and diabetes-related hospitalisation. Copyright © 2018 Elsevier B.V. All rights reserved.

Temporal Processing of Audiovisual Stimuli Is Enhanced in Musicians: Evidence from Magnetoencephalography (MEG)

PubMed Central

Lu, Yao; Paraskevopoulos, Evangelos; Herholz, Sibylle C.; Kuchenbuch, Anja; Pantev, Christo

2014-01-01

Numerous studies have demonstrated that the structural and functional differences between professional musicians and non-musicians are not only found within a single modality, but also with regard to multisensory integration. In this study we have combined psychophysical with neurophysiological measurements investigating the processing of non-musical, synchronous or various levels of asynchronous audiovisual events. We hypothesize that long-term multisensory experience alters temporal audiovisual processing already at a non-musical stage. Behaviorally, musicians scored significantly better than non-musicians in judging whether the auditory and visual stimuli were synchronous or asynchronous. At the neural level, the statistical analysis for the audiovisual asynchronous response revealed three clusters of activations including the ACC and the SFG and two bilaterally located activations in IFG and STG in both groups. Musicians, in comparison to the non-musicians, responded to synchronous audiovisual events with enhanced neuronal activity in a broad left posterior temporal region that covers the STG, the insula and the Postcentral Gyrus. Musicians also showed significantly greater activation in the left Cerebellum, when confronted with an audiovisual asynchrony. Taken together, our MEG results form a strong indication that long-term musical training alters the basic audiovisual temporal processing already in an early stage (direct after the auditory N1 wave), while the psychophysical results indicate that musical training may also provide behavioral benefits in the accuracy of the estimates regarding the timing of audiovisual events. PMID:24595014

Polarity-Dependent Misperception of Subjective Visual Vertical during and after Transcranial Direct Current Stimulation (tDCS).

PubMed

Santos-Pontelli, Taiza E G; Rimoli, Brunna P; Favoretto, Diandra B; Mazin, Suleimy C; Truong, Dennis Q; Leite, Joao P; Pontes-Neto, Octavio M; Babyar, Suzanne R; Reding, Michael; Bikson, Marom; Edwards, Dylan J

2016-01-01

Pathologic tilt of subjective visual vertical (SVV) frequently has adverse functional consequences for patients with stroke and vestibular disorders. Repetitive transcranial magnetic stimulation (rTMS) of the supramarginal gyrus can produce a transitory tilt on SVV in healthy subjects. However, the effect of transcranial direct current stimulation (tDCS) on SVV has never been systematically studied. We investigated whether bilateral tDCS over the temporal-parietal region could result in both online and offline SVV misperception in healthy subjects. In a randomized, sham-controlled, single-blind crossover pilot study, thirteen healthy subjects performed tests of SVV before, during and after the tDCS applied over the temporal-parietal region in three conditions used on different days: right anode/left cathode; right cathode/left anode; and sham. Subjects were blind to the tDCS conditions. Montage-specific current flow patterns were investigated using computational models. SVV was significantly displaced towards the anode during both active stimulation conditions when compared to sham condition. Immediately after both active conditions, there were rebound effects. Longer lasting after-effects towards the anode occurred only in the right cathode/left anode condition. Current flow models predicted the stimulation of temporal-parietal regions under the electrodes and deep clusters in the posterior limb of the internal capsule. The present findings indicate that tDCS over the temporal-parietal region can significantly alter human SVV perception. This tDCS approach may be a potential clinical tool for the treatment of SVV misperception in neurological patients.

Spatiotemporal analysis of dengue fever in Nepal from 2010 to 2014.

PubMed

Acharya, Bipin Kumar; Cao, ChunXiang; Lakes, Tobia; Chen, Wei; Naeem, Shahid

2016-08-22

Due to recent emergence, dengue is becoming one of the major public health problems in Nepal. The numbers of reported dengue cases in general and the area with reported dengue cases are both continuously increasing in recent years. However, spatiotemporal patterns and clusters of dengue have not been investigated yet. This study aims to fill this gap by analyzing spatiotemporal patterns based on monthly surveillance data aggregated at district. Dengue cases from 2010 to 2014 at district level were collected from the Nepal government's health and mapping agencies respectively. GeoDa software was used to map crude incidence, excess hazard and spatially smoothed incidence. Cluster analysis was performed in SaTScan software to explore spatiotemporal clusters of dengue during the above-mentioned time period. Spatiotemporal distribution of dengue fever in Nepal from 2010 to 2014 was mapped at district level in terms of crude incidence, excess risk and spatially smoothed incidence. Results show that the distribution of dengue fever was not random but clustered in space and time. Chitwan district was identified as the most likely cluster and Jhapa district was the first secondary cluster in both spatial and spatiotemporal scan. July to September of 2010 was identified as a significant temporal cluster. This study assessed and mapped for the first time the spatiotemporal pattern of dengue fever in Nepal. Two districts namely Chitwan and Jhapa were found highly affected by dengue fever. The current study also demonstrated the importance of geospatial approach in epidemiological research. The initial result on dengue patterns and risk of this study may assist institutions and policy makers to develop better preventive strategies.

An in-depth look into PTSD-depression comorbidity: A longitudinal study of chronically-exposed Detroit residents.

PubMed

Horesh, Danny; Lowe, Sarah R; Galea, Sandro; Aiello, Allison E; Uddin, Monica; Koenen, Karestan C

2017-01-15

Although PTSD-major depressive disorder (MDD) co-morbidity is well-established, the vast majority of studies have examined comorbidity at the level of PTSD total severity, rather than at the level of specific PTSD symptom clusters. This study aimed to examine the long-term associations between MDD and PTSD symptom clusters (intrusion, avoidance, hyperarousal), and the moderating role of gender in these associations. 942 residents of urban Detroit neighborhoods were interviewed at 3 waves, 1 year apart. At each wave, they were assessed for PTSD, depression, trauma exposure, and stressful life events. At all waves, hyperarousal was the PTSD cluster most strongly correlated with MDD. For the full sample, a reciprocal relationship was found between MDD and all three PTSD clusters across time. Interestingly, the relative strength of associations between MDD and specific PTSD clusters changed over time. Women showed the same bidirectional MDD-PTSD pattern as in the entire sample, while men sometimes showed non-significant associations between early MDD and subsequent PTSD clusters. First, our analyses are based on DSM-IV criteria, as this was the existing edition at the time of this study. Second, although this is a longitudinal study, inferences regarding temporal precedence of one disorder over another must be made with caution. Early identification of either PTSD or MDD following trauma may be crucial in order to prevent the development of the other disorder over time. The PTSD cluster of hyper-arousal may require special therapeutic attention. Also, professionals are encouraged to develop more gender-specific interventions post-trauma. Copyright © 2016 Elsevier B.V. All rights reserved.

Location of microseismic swarms induced by salt solution mining

NASA Astrophysics Data System (ADS)

Kinscher, J.; Bernard, P.; Contrucci, I.; Mangeney, A.; Piguet, J. P.; Bigarre, P.

2015-01-01

Ground failures, caving processes and collapses of large natural or man-made underground cavities can produce significant socio-economic damages and represent a serious risk envisaged by the mine managements and municipalities. In order to improve our understanding of the mechanisms governing such a geohazard and to test the potential of geophysical methods to prevent them, the development and collapse of a salt solution mining cavity was monitored in the Lorraine basin in northeastern France. During the experiment, a huge microseismic data set (˜50 000 event files) was recorded by a local microseismic network. 80 per cent of the data comprised unusual swarming sequences with complex clusters of superimposed microseismic events which could not be processed through standard automatic detection and location routines. Here, we present two probabilistic methods which provide a powerful tool to assess the spatio-temporal characteristics of these swarming sequences in an automatic manner. Both methods take advantage of strong attenuation effects and significantly polarized P-wave energies at higher frequencies (>100 Hz). The first location approach uses simple signal amplitude estimates for different frequency bands, and an attenuation model to constrain the hypocentre locations. The second approach was designed to identify significantly polarized P-wave energies and the associated polarization angles which provide very valuable information on the hypocentre location. Both methods are applied to a microseismic data set recorded during an important step of the development of the cavity, that is, before its collapse. From our results, systematic spatio-temporal epicentre migration trends are observed in the order of seconds to minutes and several tens of meters which are partially associated with cyclic behaviours. In addition, from spatio-temporal distribution of epicentre clusters we observed similar epicentre migration in the order of hours and days. All together, we suggest that the recorded microseismicity mainly represents detachment and block breakage processes acting at the cavity's roof, indicating a zone of critical state of stress and where partial fractures cause chain reaction failures as a result of stress redistribution processes.

Temporality in British young women's magazines: food, cooking and weight loss.

PubMed

Spencer, Rosemary J; Russell, Jean M; Barker, Margo E

2014-10-01

The present study examines seasonal and temporal patterns in food-related content of two UK magazines for young women focusing on food types, cooking and weight loss. Content analysis of magazines from three time blocks between 1999 and 2011. Desk-based study. Ninety-seven magazines yielding 590 advertisements and 148 articles. Cluster analysis of type of food advertising produced three clusters of magazines, which reflected recognised food behaviours of young women: vegetarianism, convenience eating and weight control. The first cluster of magazines was associated with Christmas and Millennium time periods, with advertising of alcohol, coffee, cheese, vegetarian meat substitutes and weight-loss pills. Recipes were prominent in article content and tended to be for cakes/desserts, luxury meals and party food. The second cluster was associated with summer months and 2010 issues. There was little advertising for conventional foods in cluster 2, but strong representation of diet plans and foods for weight loss. Weight-loss messages in articles focused on short-term aesthetic goals, emphasising speedy weight loss without giving up nice foods or exercising. Cluster 3 magazines were associated with post-New Year and 2005 periods. Food advertising was for everyday foods and convenience products, with fewer weight-loss products than other clusters; conversely, article content had a greater prevalence of weight-loss messages. The cyclical nature of magazine content - indulgence and excess encouraged at Christmas, restraint recommended post-New Year and severe dieting advocated in the summer months - endorses yo-yo dieting behaviour and may not be conducive to public health.

Hierarchical Bayesian modelling of gene expression time series across irregularly sampled replicates and clusters.

PubMed

Hensman, James; Lawrence, Neil D; Rattray, Magnus

2013-08-20

Time course data from microarrays and high-throughput sequencing experiments require simple, computationally efficient and powerful statistical models to extract meaningful biological signal, and for tasks such as data fusion and clustering. Existing methodologies fail to capture either the temporal or replicated nature of the experiments, and often impose constraints on the data collection process, such as regularly spaced samples, or similar sampling schema across replications. We propose hierarchical Gaussian processes as a general model of gene expression time-series, with application to a variety of problems. In particular, we illustrate the method's capacity for missing data imputation, data fusion and clustering.The method can impute data which is missing both systematically and at random: in a hold-out test on real data, performance is significantly better than commonly used imputation methods. The method's ability to model inter- and intra-cluster variance leads to more biologically meaningful clusters. The approach removes the necessity for evenly spaced samples, an advantage illustrated on a developmental Drosophila dataset with irregular replications. The hierarchical Gaussian process model provides an excellent statistical basis for several gene-expression time-series tasks. It has only a few additional parameters over a regular GP, has negligible additional complexity, is easily implemented and can be integrated into several existing algorithms. Our experiments were implemented in python, and are available from the authors' website: http://staffwww.dcs.shef.ac.uk/people/J.Hensman/.

Broca’s area network in language function: a pooling-data connectivity study

PubMed Central

Bernal, Byron; Ardila, Alfredo; Rosselli, Monica

2015-01-01

Background and Objective: Modern neuroimaging developments have demonstrated that cognitive functions correlate with brain networks rather than specific areas. The purpose of this paper was to analyze the connectivity of Broca’s area based on language tasks. Methods: A connectivity modeling study was performed by pooling data of Broca’s activation in language tasks. Fifty-seven papers that included 883 subjects in 84 experiments were analyzed. Analysis of Likelihood Estimates of pooled data was utilized to generate the map; thresholds at p < 0.01 were corrected for multiple comparisons and false discovery rate. Resulting images were co-registered into MNI standard space. Results: A network consisting of 16 clusters of activation was obtained. Main clusters were located in the frontal operculum, left posterior temporal region, supplementary motor area, and the parietal lobe. Less common clusters were seen in the sub-cortical structures including the left thalamus, left putamen, secondary visual areas, and the right cerebellum. Conclusion: Broca’s area-44-related networks involved in language processing were demonstrated utilizing a pooling-data connectivity study. Significance, interpretation, and limitations of the results are discussed. PMID:26074842

Heavy-ion dominance near Cluster perigees

NASA Astrophysics Data System (ADS)

Ferradas, C. P.; Zhang, J.-C.; Kistler, L. M.; Spence, H. E.

2015-12-01

Time periods in which heavy ions dominate over H+ in the energy range of 1-40 keV were observed by the Cluster Ion Spectrometry (CIS)/COmposition DIstribution Function (CODIF) instrument onboard Cluster Spacecraft 4 at L values less than 4. The characteristic feature is a narrow flux peak at around 10 keV that extends into low L values, with He+ and/or O+ dominating. In the present work we perform a statistical study of these events and examine their temporal occurrence and spatial distribution. The observed features, both the narrow energy range and the heavy-ion dominance, can be interpreted using a model of ion drift from the plasma sheet, subject to charge exchange losses. The narrow energy range corresponds to the only energy range that has direct drift access from the plasma sheet during quiet times. The drift time to these locations from the plasma sheet is > 30 h, so that charge exchange has a significant impact on the population. We show that a simple drift/loss model can explain the dependence on L shell and MLT of these heavy-ion-dominant time periods.

Temporal dynamics of retinal and extraretinal signals in the FEFsem during smooth pursuit eye movements.

PubMed

Bakst, Leah; Fleuriet, Jérome; Mustari, Michael J

2017-05-01

Neurons in the smooth eye movement subregion of the frontal eye field (FEFsem) are known to play an important role in voluntary smooth pursuit eye movements. Underlying this function are projections to parietal and prefrontal visual association areas and subcortical structures, all known to play vital but differing roles in the execution of smooth pursuit. Additionally, the FEFsem has been shown to carry a diverse array of signals (e.g., eye velocity, acceleration, gain control). We hypothesized that distinct subpopulations of FEFsem neurons subserve these diverse functions and projections, and that the relative weights of retinal and extraretinal signals could form the basis for categorization of units. To investigate this, we used a step-ramp tracking task with a target blink to determine the relative contributions of retinal and extraretinal signals in individual FEFsem neurons throughout pursuit. We found that the contributions of retinal and extraretinal signals to neuronal activity and behavior change throughout the time course of pursuit. A clustering algorithm revealed three distinct neuronal subpopulations: cluster 1 was defined by a higher sensitivity to eye velocity, acceleration, and retinal image motion; cluster 2 had greater activity during blinks; and cluster 3 had significantly greater eye position sensitivity. We also performed a comparison with a sample of medial superior temporal neurons to assess similarities and differences between the two areas. Our results indicate the utility of simple tests such as the target blink for parsing the complex and multifaceted roles of cortical areas in behavior. NEW & NOTEWORTHY The frontal eye field (FEF) is known to play a critical role in volitional smooth pursuit, carrying a variety of signals that are distributed throughout the brain. This study used a novel application of a target blink task during step ramp tracking to determine, in combination with a clustering algorithm, the relative contributions of retinal and extraretinal signals to FEF activity and the extent to which these contributions could form the basis for a categorization of neurons. Copyright © 2017 the American Physiological Society.

Temporal variability of spectro-temporal receptive fields in the anesthetized auditory cortex.

PubMed

Meyer, Arne F; Diepenbrock, Jan-Philipp; Ohl, Frank W; Anemüller, Jörn

2014-01-01

Temporal variability of neuronal response characteristics during sensory stimulation is a ubiquitous phenomenon that may reflect processes such as stimulus-driven adaptation, top-down modulation or spontaneous fluctuations. It poses a challenge to functional characterization methods such as the receptive field, since these often assume stationarity. We propose a novel method for estimation of sensory neurons' receptive fields that extends the classic static linear receptive field model to the time-varying case. Here, the long-term estimate of the static receptive field serves as the mean of a probabilistic prior distribution from which the short-term temporally localized receptive field may deviate stochastically with time-varying standard deviation. The derived corresponding generalized linear model permits robust characterization of temporal variability in receptive field structure also for highly non-Gaussian stimulus ensembles. We computed and analyzed short-term auditory spectro-temporal receptive field (STRF) estimates with characteristic temporal resolution 5-30 s based on model simulations and responses from in total 60 single-unit recordings in anesthetized Mongolian gerbil auditory midbrain and cortex. Stimulation was performed with short (100 ms) overlapping frequency-modulated tones. Results demonstrate identification of time-varying STRFs, with obtained predictive model likelihoods exceeding those from baseline static STRF estimation. Quantitative characterization of STRF variability reveals a higher degree thereof in auditory cortex compared to midbrain. Cluster analysis indicates that significant deviations from the long-term static STRF are brief, but reliably estimated. We hypothesize that the observed variability more likely reflects spontaneous or state-dependent internal fluctuations that interact with stimulus-induced processing, rather than experimental or stimulus design.

Hierarchical temporal structure in music, speech and animal vocalizations: jazz is like a conversation, humpbacks sing like hermit thrushes.

PubMed

Kello, Christopher T; Bella, Simone Dalla; Médé, Butovens; Balasubramaniam, Ramesh

2017-10-01

Humans talk, sing and play music. Some species of birds and whales sing long and complex songs. All these behaviours and sounds exhibit hierarchical structure-syllables and notes are positioned within words and musical phrases, words and motives in sentences and musical phrases, and so on. We developed a new method to measure and compare hierarchical temporal structures in speech, song and music. The method identifies temporal events as peaks in the sound amplitude envelope, and quantifies event clustering across a range of timescales using Allan factor (AF) variance. AF variances were analysed and compared for over 200 different recordings from more than 16 different categories of signals, including recordings of speech in different contexts and languages, musical compositions and performances from different genres. Non-human vocalizations from two bird species and two types of marine mammals were also analysed for comparison. The resulting patterns of AF variance across timescales were distinct to each of four natural categories of complex sound: speech, popular music, classical music and complex animal vocalizations. Comparisons within and across categories indicated that nested clustering in longer timescales was more prominent when prosodic variation was greater, and when sounds came from interactions among individuals, including interactions between speakers, musicians, and even killer whales. Nested clustering also was more prominent for music compared with speech, and reflected beat structure for popular music and self-similarity across timescales for classical music. In summary, hierarchical temporal structures reflect the behavioural and social processes underlying complex vocalizations and musical performances. © 2017 The Author(s).

User Activity Recognition in Smart Homes Using Pattern Clustering Applied to Temporal ANN Algorithm

PubMed Central

Bourobou, Serge Thomas Mickala; Yoo, Younghwan

2015-01-01

This paper discusses the possibility of recognizing and predicting user activities in the IoT (Internet of Things) based smart environment. The activity recognition is usually done through two steps: activity pattern clustering and activity type decision. Although many related works have been suggested, they had some limited performance because they focused only on one part between the two steps. This paper tries to find the best combination of a pattern clustering method and an activity decision algorithm among various existing works. For the first step, in order to classify so varied and complex user activities, we use a relevant and efficient unsupervised learning method called the K-pattern clustering algorithm. In the second step, the training of smart environment for recognizing and predicting user activities inside his/her personal space is done by utilizing the artificial neural network based on the Allen’s temporal relations. The experimental results show that our combined method provides the higher recognition accuracy for various activities, as compared with other data mining classification algorithms. Furthermore, it is more appropriate for a dynamic environment like an IoT based smart home. PMID:26007738

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE PAGES

Vasylkivska, Veronika S.; Huerta, Nicolas J.

2017-06-24

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Spatio-temporal distribution of Oklahoma earthquakes: Exploring relationships using a nearest-neighbor approach: Nearest-neighbor analysis of Oklahoma

DOE Office of Scientific and Technical Information (OSTI.GOV)

Vasylkivska, Veronika S.; Huerta, Nicolas J.

Determining the spatiotemporal characteristics of natural and induced seismic events holds the opportunity to gain new insights into why these events occur. Linking the seismicity characteristics with other geologic, geographic, natural, or anthropogenic factors could help to identify the causes and suggest mitigation strategies that reduce the risk associated with such events. The nearest-neighbor approach utilized in this work represents a practical first step toward identifying statistically correlated clusters of recorded earthquake events. Detailed study of the Oklahoma earthquake catalog’s inherent errors, empirical model parameters, and model assumptions is presented. We found that the cluster analysis results are stable withmore » respect to empirical parameters (e.g., fractal dimension) but were sensitive to epicenter location errors and seismicity rates. Most critically, we show that the patterns in the distribution of earthquake clusters in Oklahoma are primarily defined by spatial relationships between events. This observation is a stark contrast to California (also known for induced seismicity) where a comparable cluster distribution is defined by both spatial and temporal interactions between events. These results highlight the difficulty in understanding the mechanisms and behavior of induced seismicity but provide insights for future work.« less

Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy.

PubMed

Marchione, Elio; Johnson, Shane D

2013-11-01

To examine patterns in the timing and location of incidents of maritime piracy to see whether, like many urban crimes, attacks cluster in space and time. Data for all incidents of maritime piracy worldwide recorded by the National Geospatial Intelligence Agency are analyzed using time-series models and methods originally developed to detect disease contagion. At the macro level, analyses suggest that incidents of pirate attacks are concentrated in five subregions of the earth's oceans and that the time series for these different subregions differ. At the micro level, analyses suggest that for the last 16 years (or more), pirate attacks appear to cluster in space and time suggesting that patterns are not static but are also not random. Much like other types of crime, pirate attacks cluster in space, and following an attack at one location the risk of others at the same location or nearby is temporarily elevated. The identification of such regularities has implications for the understanding of maritime piracy and for predicting the future locations of attacks.

Spatio-temporal distribution and natural variation of metabolites in citrus fruits.

PubMed

Wang, Shouchuang; Tu, Hong; Wan, Jian; Chen, Wei; Liu, Xianqing; Luo, Jie; Xu, Juan; Zhang, Hongyan

2016-05-15

To study the natural variation and spatio-temporal accumulation of citrus metabolites, liquid chromatography tandem mass spectrometry (LC-MS) based metabolome analysis was performed on four fruit tissues (flavedo, albedo, segment membrane and juice sacs) and different Citrus species (lemon, pummelo and grapefruit, sweet orange and mandarin). Using a non-targeted metabolomics approach, more than 2000 metabolite signals were detected, from which more than 54 metabolites, including amino acids, flavonoids and limonoids, were identified/annotated. Differential accumulation patterns of both primary metabolites and secondary metabolites in various tissues and species were revealed by our study. Further investigation indicated that flavedo accumulates more flavonoids while juice sacs contain more amino acids. Besides this, cluster analysis based on the levels of metabolites detected in 47 individual Citrus accessions clearly grouped them into four distinct clusters: pummelos and grapefruits, lemons, sweet oranges and mandarins, while the cluster of pummelos and grapefruits lay distinctly apart from the other three species. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial and space-time distribution of Plasmodium vivax and Plasmodium falciparum malaria in China, 2005-2014.

PubMed

Hundessa, Samuel H; Williams, Gail; Li, Shanshan; Guo, Jinpeng; Chen, Linping; Zhang, Wenyi; Guo, Yuming

2016-12-19

Despite the declining burden of malaria in China, the disease remains a significant public health problem with periodic outbreaks and spatial variation across the country. A better understanding of the spatial and temporal characteristics of malaria is essential for consolidating the disease control and elimination programme. This study aims to understand the spatial and spatiotemporal distribution of Plasmodium vivax and Plasmodium falciparum malaria in China during 2005-2009. Global Moran's I statistics was used to detect a spatial distribution of local P. falciparum and P. vivax malaria at the county level. Spatial and space-time scan statistics were applied to detect spatial and spatiotemporal clusters, respectively. Both P. vivax and P. falciparum malaria showed spatial autocorrelation. The most likely spatial cluster of P. vivax was detected in northern Anhui province between 2005 and 2009, and western Yunnan province between 2010 and 2014. For P. falciparum, the clusters included several counties of western Yunnan province from 2005 to 2011, Guangxi from 2012 to 2013, and Anhui in 2014. The most likely space-time clusters of P. vivax malaria and P. falciparum malaria were detected in northern Anhui province and western Yunnan province, respectively, during 2005-2009. The spatial and space-time cluster analysis identified high-risk areas and periods for both P. vivax and P. falciparum malaria. Both malaria types showed significant spatial and spatiotemporal variations. Contrary to P. vivax, the high-risk areas for P. falciparum malaria shifted from the west to the east of China. Further studies are required to examine the spatial changes in risk of malaria transmission and identify the underlying causes of elevated risk in the high-risk areas.

Analysis of EEG-fMRI data in focal epilepsy based on automated spike classification and Signal Space Projection.

PubMed

Liston, Adam D; De Munck, Jan C; Hamandi, Khalid; Laufs, Helmut; Ossenblok, Pauly; Duncan, John S; Lemieux, Louis

2006-07-01

Simultaneous acquisition of EEG and fMRI data enables the investigation of the hemodynamic correlates of interictal epileptiform discharges (IEDs) during the resting state in patients with epilepsy. This paper addresses two issues: (1) the semi-automation of IED classification in statistical modelling for fMRI analysis and (2) the improvement of IED detection to increase experimental fMRI efficiency. For patients with multiple IED generators, sensitivity to IED-correlated BOLD signal changes can be improved when the fMRI analysis model distinguishes between IEDs of differing morphology and field. In an attempt to reduce the subjectivity of visual IED classification, we implemented a semi-automated system, based on the spatio-temporal clustering of EEG events. We illustrate the technique's usefulness using EEG-fMRI data from a subject with focal epilepsy in whom 202 IEDs were visually identified and then clustered semi-automatically into four clusters. Each cluster of IEDs was modelled separately for the purpose of fMRI analysis. This revealed IED-correlated BOLD activations in distinct regions corresponding to three different IED categories. In a second step, Signal Space Projection (SSP) was used to project the scalp EEG onto the dipoles corresponding to each IED cluster. This resulted in 123 previously unrecognised IEDs, the inclusion of which, in the General Linear Model (GLM), increased the experimental efficiency as reflected by significant BOLD activations. We have also shown that the detection of extra IEDs is robust in the face of fluctuations in the set of visually detected IEDs. We conclude that automated IED classification can result in more objective fMRI models of IEDs and significantly increased sensitivity.

Statistical Analysis of Small-Scale Magnetic Flux Emergence Patterns: A Useful Subsurface Diagnostic?

NASA Astrophysics Data System (ADS)

Lamb, Derek A.

2016-10-01

While sunspots follow a well-defined pattern of emergence in space and time, small-scale flux emergence is assumed to occur randomly at all times in the quiet Sun. HMI's full-disk coverage, high cadence, spatial resolution, and duty cycle allow us to probe that basic assumption. Some case studies of emergence suggest that temporal clustering on spatial scales of 50-150 Mm may occur. If clustering is present, it could serve as a diagnostic of large-scale subsurface magnetic field structures. We present the results of a manual survey of small-scale flux emergence events over a short time period, and a statistical analysis addressing the question of whether these events show spatio-temporal behavior that is anything other than random.

Clustering stock market companies via chaotic map synchronization

NASA Astrophysics Data System (ADS)

Basalto, N.; Bellotti, R.; De Carlo, F.; Facchi, P.; Pascazio, S.

2005-01-01

A pairwise clustering approach is applied to the analysis of the Dow Jones index companies, in order to identify similar temporal behavior of the traded stock prices. To this end, the chaotic map clustering algorithm is used, where a map is associated to each company and the correlation coefficients of the financial time series to the coupling strengths between maps. The simulation of a chaotic map dynamics gives rise to a natural partition of the data, as companies belonging to the same industrial branch are often grouped together. The identification of clusters of companies of a given stock market index can be exploited in the portfolio optimization strategies.

Research on classified real-time flood forecasting framework based on K-means cluster and rough set.

PubMed

Xu, Wei; Peng, Yong

2015-01-01

This research presents a new classified real-time flood forecasting framework. In this framework, historical floods are classified by a K-means cluster according to the spatial and temporal distribution of precipitation, the time variance of precipitation intensity and other hydrological factors. Based on the classified results, a rough set is used to extract the identification rules for real-time flood forecasting. Then, the parameters of different categories within the conceptual hydrological model are calibrated using a genetic algorithm. In real-time forecasting, the corresponding category of parameters is selected for flood forecasting according to the obtained flood information. This research tests the new classified framework on Guanyinge Reservoir and compares the framework with the traditional flood forecasting method. It finds that the performance of the new classified framework is significantly better in terms of accuracy. Furthermore, the framework can be considered in a catchment with fewer historical floods.

The Hungarian congenital malformation monitoring system.

PubMed

Czeizel, A

1978-01-01

The Hungarian Congenital Malformation Monitor has been operating since 1973 in order to detect the temporal and regional clusters of 12 indicator congenital malformations as early as possible. This Monitor takes part in the International Clearinghouse for Birth Defects Monitoring System. Three continuously increasing trends were detected in 1973--1976. They may be connected with the more complete notifications, although the increase of limb reduction deformities are only partly explained by this factor. Transitional (quarterly) significant clusters were observed in the case of anencephaly (1974, IV), spina bifida (1974, II; and 1975, III; 1976, III), cleft lip +/- cleft palate (1974, III). The possibility of three technical biases (changes in diagnosis, notification and evaluation of the given congenital malformation) has to be excluded before accepting the fact of a real epidemic. Subsequently, a case-control epidemiological study by personal interviews and with matched controls has to be performed.

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: A multiscale joinpoint regression analysis

PubMed Central

2011-01-01

Background Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Methods Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. Results State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males. Conclusions Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes. PMID:22142274

Geographical, temporal and racial disparities in late-stage prostate cancer incidence across Florida: a multiscale joinpoint regression analysis.

PubMed

Goovaerts, Pierre; Xiao, Hong

2011-12-05

Although prostate cancer-related incidence and mortality have declined recently, striking racial/ethnic differences persist in the United States. Visualizing and modelling temporal trends of prostate cancer late-stage incidence, and how they vary according to geographic locations and race, should help explaining such disparities. Joinpoint regression is increasingly used to identify the timing and extent of changes in time series of health outcomes. Yet, most analyses of temporal trends are aspatial and conducted at the national level or for a single cancer registry. Time series (1981-2007) of annual proportions of prostate cancer late-stage cases were analyzed for non-Hispanic Whites and non-Hispanic Blacks in each county of Florida. Noise in the data was first filtered by binomial kriging and results were modelled using joinpoint regression. A similar analysis was also conducted at the state level and for groups of metropolitan and non-metropolitan counties. Significant racial differences were detected using tests of parallelism and coincidence of time trends. A new disparity statistic was introduced to measure spatial and temporal changes in the frequency of racial disparities. State-level percentage of late-stage diagnosis decreased 50% since 1981; a decline that accelerated in the 90's when Prostate Specific Antigen (PSA) screening was introduced. Analysis at the metropolitan and non-metropolitan levels revealed that the frequency of late-stage diagnosis increased recently in urban areas, and this trend was significant for white males. The annual rate of decrease in late-stage diagnosis and the onset years for significant declines varied greatly among counties and racial groups. Most counties with non-significant average annual percent change (AAPC) were located in the Florida Panhandle for white males, whereas they clustered in South-eastern Florida for black males. The new disparity statistic indicated that the spatial extent of racial disparities reached a peak in 1990 because of an early decline in frequency of late-stage diagnosis observed for black males. Analyzing temporal trends in cancer incidence and mortality rates outside a spatial framework is unsatisfactory, since it leads one to overlook significant geographical variation which can potentially generate new insights about the impact of various interventions. Differences observed among nested geographies in Florida show how the modifiable areal unit problem (MAUP) also impacts the analysis of temporal changes.

Investigation of a Guillain-Barré syndrome cluster in the Republic of Fiji.

PubMed

Pastula, Daniel M; Khan, Aalisha Sahu; Sharp, Tyler M; Biaukula, Viema L; Naivalu, Taina K; Rafai, Eric; Ermias Belay; Staples, J Erin; Fischer, Marc; Kosoy, Olga I; Laven, Janeen J; Bennett, Elizabeth J; Jenney, Adam W J; Naidu, Ravi Narayan; Lanciotti, Robert S; Galloway, Renee L; Nilles, Eric J; Sejvar, James J; Kama, Mike

2017-01-15

In 2014, we investigated a cluster of Guillain-Barre syndrome (GBS) in Fiji that occurred during a dengue epidemic. We designed a case-control study to determine the etiology. Cases were patients meeting Brighton Collaboration criteria for GBS with onset from February 2014 to May 2014. Controls were persons without symptoms of GBS who were matched by age group and location. We collected information on demographics and potential exposures. Serum samples were tested for evidence of recent arboviral or Leptospira spp. infections. Nine cases of GBS were identified for an incidence of five cases per 100,000 population/year. Median age of cases was 27years (range: 0.8-52); five (56%) were male. Six (67%) reported an acute illness prior to GBS onset. Among the 9 cases and 28 controls enrolled, odds ratios for reported exposures or antibodies against various arboviruses or Leptospira spp. were not statistically significant. No clear etiologies were identified for this unusual GBS cluster. There was a temporal association between the GBS cluster and a dengue epidemic, but we were unable to substantiate an epidemiologic or laboratory association. Further study is needed to explore potential associations between arboviral infections and GBS. Copyright © 2016. Published by Elsevier B.V.

Eye-gaze determination of user intent at the computer interface

DOE Office of Scientific and Technical Information (OSTI.GOV)

Goldberg, J.H.; Schryver, J.C.

1993-12-31

Determination of user intent at the computer interface through eye-gaze monitoring can significantly aid applications for the disabled, as well as telerobotics and process control interfaces. Whereas current eye-gaze control applications are limited to object selection and x/y gazepoint tracking, a methodology was developed here to discriminate a more abstract interface operation: zooming-in or out. This methodology first collects samples of eve-gaze location looking at controlled stimuli, at 30 Hz, just prior to a user`s decision to zoom. The sample is broken into data frames, or temporal snapshots. Within a data frame, all spatial samples are connected into a minimummore » spanning tree, then clustered, according to user defined parameters. Each cluster is mapped to one in the prior data frame, and statistics are computed from each cluster. These characteristics include cluster size, position, and pupil size. A multiple discriminant analysis uses these statistics both within and between data frames to formulate optimal rules for assigning the observations into zooming, zoom-out, or no zoom conditions. The statistical procedure effectively generates heuristics for future assignments, based upon these variables. Future work will enhance the accuracy and precision of the modeling technique, and will empirically test users in controlled experiments.« less

DISCOVERY OF A DISSOCIATIVE GALAXY CLUSTER MERGER WITH LARGE PHYSICAL SEPARATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dawson, William A.; Wittman, David; Jee, M. James

2012-03-10

We present DLSCL J0916.2+2951 (z = 0.53), a newly discovered major cluster merger in which the collisional cluster gas has become dissociated from the collisionless galaxies and dark matter (DM). We identified the cluster using optical and weak-lensing observations as part of the Deep Lens Survey. Our follow-up observations with Keck, Subaru, Hubble Space Telescope, and Chandra show that the cluster is a dissociative merger and constrain the DM self-interaction cross-section {sigma}{sub DM} m{sup -1}{sub DM} {approx}< 7 cm{sup 2} g{sup -1}. The system is observed at least 0.7 {+-} 0.2 Gyr since first pass-through, thus providing a picture ofmore » cluster mergers 2-5 times further progressed than similar systems observed to date. This improved temporal leverage has implications for our understanding of merging clusters and their impact on galaxy evolution.« less

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs

PubMed Central

Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

2015-01-01

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources. PMID:26492263

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

PubMed

Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

2015-10-20

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

Characterization and analysis of temporal and spatial variations in habitat and macroinvertebrate community structure, Fountain Creek basin, Colorado Springs and vicinity, Colorado, 1998-2001

USGS Publications Warehouse

Bruce, James F.

2002-01-01

The Fountain Creek Basin in and around Colorado Springs, Colorado, is affected by various land- and water-use activities. Biological, hydrological, water-quality, and land-use data were collected at 10 sites in the Fountain Creek Basin from April 1998 through April 2001 to provide a baseline characterization of macroinvertebrate communities and habitat conditions for comparison in subsequent studies; and to assess variation in macroinvertebrate community structure relative to habitat quality. Analysis of variance results indicated that instream and riparian variables were not affected by season, but significant differences were found among sites. Nine metrics were used to describe and evaluate macroinvertebrate community structure. Statistical analysis indicated that for six of the nine metrics, significant variability occurred between spring and fall seasons for 60 percent of the sites. Cluster analysis (unweighted pair group method average) using macroinvertebrate presence-absence data showed a well-defined separation between spring and fall samples. Six of the nine metrics had significant spatial variation. Cluster analysis using Sorenson?s Coefficient of Community values computed from macroinvertebrate density (number of organisms per square meter) data showed that macroinvertebrate community structure was more similar among tributary sites than main-stem sites. Canonical correspondence analysis identified a substrate particle-size gradient from site-specific species-abundance data and environmental correlates that decreased the 10 sites to 5 site clusters and their associated taxa.

Oxygen transport and stem cell aggregation in stirred-suspension bioreactor cultures.

PubMed

Wu, Jincheng; Rostami, Mahboubeh Rahmati; Cadavid Olaya, Diana P; Tzanakakis, Emmanuel S

2014-01-01

Stirred-suspension bioreactors are a promising modality for large-scale culture of 3D aggregates of pluripotent stem cells and their progeny. Yet, cells within these clusters experience limitations in the transfer of factors and particularly O2 which is characterized by low solubility in aqueous media. Cultured stem cells under different O2 levels may exhibit significantly different proliferation, viability and differentiation potential. Here, a transient diffusion-reaction model was built encompassing the size distribution and ultrastructural characteristics of embryonic stem cell (ESC) aggregates. The model was coupled to experimental data from bioreactor and static cultures for extracting the effective diffusivity and kinetics of consumption of O2 within mouse (mESC) and human ESC (hESC) clusters. Under agitation, mESC aggregates exhibited a higher maximum consumption rate than hESC aggregates. Moreover, the reaction-diffusion model was integrated with a population balance equation (PBE) for the temporal distribution of ESC clusters changing due to aggregation and cell proliferation. Hypoxia was found to be negligible for ESCs with a smaller radius than 100 µm but became appreciable for aggregates larger than 300 µm. The integrated model not only captured the O2 profile both in the bioreactor bulk and inside ESC aggregates but also led to the calculation of the duration that fractions of cells experience a certain range of O2 concentrations. The approach described in this study can be employed for gaining a deeper understanding of the effects of O2 on the physiology of stem cells organized in 3D structures. Such frameworks can be extended to encompass the spatial and temporal availability of nutrients and differentiation factors and facilitate the design and control of relevant bioprocesses for the production of stem cell therapeutics.

Neural activity in relation to empirically derived personality syndromes in depression using a psychodynamic fMRI paradigm

PubMed Central

Taubner, Svenja; Wiswede, Daniel; Kessler, Henrik

2013-01-01

Objective: The heterogeneity between patients with depression cannot be captured adequately with existing descriptive systems of diagnosis and neurobiological models of depression. Furthermore, considering the highly individual nature of depression, the application of general stimuli in past research efforts may not capture the essence of the disorder. This study aims to identify subtypes of depression by using empirically derived personality syndromes, and to explore neural correlates of the derived personality syndromes. Materials and Methods: In the present exploratory study, an individually tailored and psychodynamically based functional magnetic resonance imaging paradigm using dysfunctional relationship patterns was presented to 20 chronically depressed patients. Results from the Shedler–Westen Assessment Procedure (SWAP-200) were analyzed by Q-factor analysis to identify clinically relevant subgroups of depression and related brain activation. Results: The principle component analysis of SWAP-200 items from all 20 patients lead to a two-factor solution: “Depressive Personality” and “Emotional-Hostile-Externalizing Personality.” Both factors were used in a whole-brain correlational analysis but only the second factor yielded significant positive correlations in four regions: a large cluster in the right orbitofrontal cortex (OFC), the left ventral striatum, a small cluster in the left temporal pole, and another small cluster in the right middle frontal gyrus. Discussion: The degree to which patients with depression score high on the factor “Emotional-Hostile-Externalizing Personality” correlated with relatively higher activity in three key areas involved in emotion processing, evaluation of reward/punishment, negative cognitions, depressive pathology, and social knowledge (OFC, ventral striatum, temporal pole). Results may contribute to an alternative description of neural correlates of depression showing differential brain activation dependent on the extent of specific personality syndromes in depression. PMID:24363644

Identification of segregated regions in the functional brain connectome of autistic patients by a combination of fuzzy spectral clustering and entropy analysis

PubMed Central

Sato, João Ricardo; Balardin, Joana; Vidal, Maciel Calebe; Fujita, André

2016-01-01

Background Several neuroimaging studies support the model of abnormal development of brain connectivity in patients with autism-spectrum disorders (ASD). In this study, we aimed to test the hypothesis of reduced functional network segregation in autistic patients compared with controls. Methods Functional MRI data from children acquired under a resting-state protocol (Autism Brain Imaging Data Exchange [ABIDE]) were submitted to both fuzzy spectral clustering (FSC) with entropy analysis and graph modularity analysis. Results We included data from 814 children in our analysis. We identified 5 regions of interest comprising the motor, temporal and occipito-temporal cortices with increased entropy (p < 0.05) in the clustering structure (i.e., more segregation in the controls). Moreover, we noticed a statistically reduced modularity (p < 0.001) in the autistic patients compared with the controls. Significantly reduced eigenvector centrality values (p < 0.05) in the patients were observed in the same regions that were identified in the FSC analysis. Limitations There is considerable heterogeneity in the fMRI acquisition protocols among the sites that contributed to the ABIDE data set (e.g., scanner type, pulse sequence, duration of scan and resting-state protocol). Moreover, the sites differed in many variables related to sample characterization (e.g., age, IQ and ASD diagnostic criteria). Therefore, we cannot rule out the possibility that additional differences in functional network organization would be found in a more homogeneous data sample of individuals with ASD. Conclusion Our results suggest that the organization of the whole-brain functional network in patients with ASD is different from that observed in controls, which implies a reduced modularity of the brain functional networks involved in sensorimotor, social, affective and cognitive processing. PMID:26505141

SERA Scenarios of Early Market Fuel Cell Electric Vehicle Introductions: Modeling Framework, Regional Markets, and Station Clustering

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bush, B.; Melaina, M.; Penev, M.

This report describes the development and analysis of detailed temporal and spatial scenarios for early market hydrogen fueling infrastructure clustering and fuel cell electric vehicle rollout using the Scenario Evaluation, Regionalization and Analysis (SERA) model. The report provides an overview of the SERA scenario development framework and discusses the approach used to develop the nationwidescenario.

A practical Bayesian stepped wedge design for community-based cluster-randomized clinical trials: The British Columbia Telehealth Trial.

PubMed

Cunanan, Kristen M; Carlin, Bradley P; Peterson, Kevin A

2016-12-01

Many clinical trial designs are impractical for community-based clinical intervention trials. Stepped wedge trial designs provide practical advantages, but few descriptions exist of their clinical implementational features, statistical design efficiencies, and limitations. Enhance efficiency of stepped wedge trial designs by evaluating the impact of design characteristics on statistical power for the British Columbia Telehealth Trial. The British Columbia Telehealth Trial is a community-based, cluster-randomized, controlled clinical trial in rural and urban British Columbia. To determine the effect of an Internet-based telehealth intervention on healthcare utilization, 1000 subjects with an existing diagnosis of congestive heart failure or type 2 diabetes will be enrolled from 50 clinical practices. Hospital utilization is measured using a composite of disease-specific hospital admissions and emergency visits. The intervention comprises online telehealth data collection and counseling provided to support a disease-specific action plan developed by the primary care provider. The planned intervention is sequentially introduced across all participating practices. We adopt a fully Bayesian, Markov chain Monte Carlo-driven statistical approach, wherein we use simulation to determine the effect of cluster size, sample size, and crossover interval choice on type I error and power to evaluate differences in hospital utilization. For our Bayesian stepped wedge trial design, simulations suggest moderate decreases in power when crossover intervals from control to intervention are reduced from every 3 to 2 weeks, and dramatic decreases in power as the numbers of clusters decrease. Power and type I error performance were not notably affected by the addition of nonzero cluster effects or a temporal trend in hospitalization intensity. Stepped wedge trial designs that intervene in small clusters across longer periods can provide enhanced power to evaluate comparative effectiveness, while offering practical implementation advantages in geographic stratification, temporal change, use of existing data, and resource distribution. Current population estimates were used; however, models may not reflect actual event rates during the trial. In addition, temporal or spatial heterogeneity can bias treatment effect estimates. © The Author(s) 2016.

Spatio-temporal Organization During Ventricular Fibrillation in the Human Heart.

PubMed

Robson, Jinny; Aram, Parham; Nash, Martyn P; Bradley, Chris P; Hayward, Martin; Paterson, David J; Taggart, Peter; Clayton, Richard H; Kadirkamanathan, Visakan

2018-06-01

In this paper, we present a novel approach to quantify the spatio-temporal organization of electrical activation during human ventricular fibrillation (VF). We propose three different methods based on correlation analysis, graph theoretical measures and hierarchical clustering. Using the proposed approach, we quantified the level of spatio-temporal organization during three episodes of VF in ten patients, recorded using multi-electrode epicardial recordings with 30 s coronary perfusion, 150 s global myocardial ischaemia and 30 s reflow. Our findings show a steady decline in spatio-temporal organization from the onset of VF with coronary perfusion. We observed transient increases in spatio-temporal organization during global myocardial ischaemia. However, the decline in spatio-temporal organization continued during reflow. Our results were consistent across all patients, and were consistent with the numbers of phase singularities. Our findings show that the complex spatio-temporal patterns can be studied using complex network analysis.

Atomistic observation and simulation analysis of spatio-temporal fluctuations during radiation-induced amorphization.

PubMed

Watanabe, Seiichi; Hoshino, Misaki; Koike, Takuto; Suda, Takanori; Ohnuki, Soumei; Takahashi, Heishichirou; Lam, Nighi Q

2003-01-01

We performed a dynamical-atomistic study of radiation-induced amorphization in the NiTi intermetallic compound using in situ high-resolution high-voltage electron microscopy and molecular dynamics simulations in connection with image simulation. Spatio-temporal fluctuations as non-equilibrium fluctuations in an energy-dissipative system, due to transient atom-cluster formation during amorphization, were revealed by the present spatial autocorrelation analysis.

Porphyry copper deposits distribution along the western Tethyan and Andean subductions: insights from a paleogeographic approach

NASA Astrophysics Data System (ADS)

Bertrand, G.

2012-12-01

The genesis of many types of mineral deposits is closely linked to tectonic and petrographic conditions resulting from specific geodynamic contexts. Porphyry deposits, for instance, are associated to calc-alkaline magmatism of subduction zones. In order to better understand the relationships between ore deposit distribution and their tectonic context, and help identifying geodynamic-related criteria of favorability that would, in turn, help mineral exploration, we propose a paleogeographic approach. Paleogeographic reconstructions, based on global or regional plate tectonic models, are crucial tools to assess tectonic and kinematic contexts of the past. We use this approach to study the distribution of porphyry copper deposits along the western Tethyan and Andean subductions since Lower Cretaceous and Paleocene, respectively. For both convergent contexts, databases of porphyry copper deposits, including, among other data, their age and location, were compiled. Spatial and temporal distribution of the deposits is not random and show that they were emplaced in distinct clusters. Five clusters are identified along the western Tethyan suture, from Lower Cretaceous to Pleistocene, and at least three along the Andes, from Paleocene to Miocene. Two clusters in the Aegean-Balkan-Carpathian area, that were emplaced in Upper Cretaceous and Oligo-Miocene, and two others in the Andes, that were emplaced in late Eocene and Miocene, are studied in details and correlated with the past kinematics of the Africa-Eurasia and Nazca-South America plate convergences, respectively. All these clusters are associated with a similar polyphased kinematic context that is closely related to the dynamics of the subductions. This context is characterized by 1) a relatively fast convergence rate, shortly followed by 2) a drastic decrease of this rate. To explain these results, we propose a polyphased genetic model for porphyry copper deposits with 1) a first stage of rapid subduction rate, favoring high melt production in the mantle wedge, by dehydration of the subducted oceanic crust, and increased influx of mafic magmas in the MASH (Melting, Assimilation, Storage, Homogenization) zone, and 2) a subsequent significant decrease in subduction rate, favoring extensional regime within the upper plate and easing upward migration of fertile magmas to the upper crust. This second effect seems to be confirmed in the Aegean-Balkan-Carpathian area where the two clusters are spatially and temporally correlated with known extensional regimes. Although preliminary, these results highlight the control of the geodynamic context, and especially the subduction kinematics, on the spatial and temporal distribution of porphyry copper deposits. This study also confirms that the paleogeographic approach is a promising tool that could help identifying geodynamic and tectonic criteria favoring the genesis of various ore deposit types. Correlatively, ore deposits may be considered, in future studies, as possible markers of past geodynamic contexts.

Explanation of temporal clustering of tsunami sources using the epidemic-type aftershock sequence model

USGS Publications Warehouse

Geist, Eric L.

2014-01-01

Temporal clustering of tsunami sources is examined in terms of a branching process model. It previously was observed that there are more short interevent times between consecutive tsunami sources than expected from a stationary Poisson process. The epidemic‐type aftershock sequence (ETAS) branching process model is fitted to tsunami catalog events, using the earthquake magnitude of the causative event from the Centennial and Global Centroid Moment Tensor (CMT) catalogs and tsunami sizes above a completeness level as a mark to indicate that a tsunami was generated. The ETAS parameters are estimated using the maximum‐likelihood method. The interevent distribution associated with the ETAS model provides a better fit to the data than the Poisson model or other temporal clustering models. When tsunamigenic conditions (magnitude threshold, submarine location, dip‐slip mechanism) are applied to the Global CMT catalog, ETAS parameters are obtained that are consistent with those estimated from the tsunami catalog. In particular, the dip‐slip condition appears to result in a near zero magnitude effect for triggered tsunami sources. The overall consistency between results from the tsunami catalog and that from the earthquake catalog under tsunamigenic conditions indicates that ETAS models based on seismicity can provide the structure for understanding patterns of tsunami source occurrence. The fractional rate of triggered tsunami sources on a global basis is approximately 14%.

The Spread of Dengue in an Endemic Urban Milieu–The Case of Delhi, India

PubMed Central

Telle, Olivier; Vaguet, Alain; Yadav, N. K.; Lefebvre, B.; Daudé, Eric; Paul, Richard E.; Cebeillac, A.; Nagpal, B. N.

2016-01-01

Background Dengue is a major international public health concern, one of the most important arthropod-borne diseases. More than 3.5 billion people are at risk of dengue infection and there are an estimated 390 million dengue infections annually. This prolific increase has been connected to societal changes such as population growth and increasing urbanization generating intense agglomeration leading to proliferation of synanthropic mosquito species. Quantifying the spatio-temporal epidemiology of dengue in large cities within the context of a Geographic Information System is a first step in the identification of socio-economic risk factors. Methodology/Principal Findings This Project has been approved by the ethical committee of Institut Pasteur. Data has been anonymized and de-identified prior to geolocalisation and analysis. A GIS was developed for Delhi, enabling typological characterization of the urban environment. Dengue cases identified in the Delhi surveillance system from 2008 to 2010 were collated, localised and embedded within this GIS. The spatio-temporal distribution of dengue cases and extent of clustering were analyzed. Increasing distance from the forest in Delhi reduced the risk of occurrence of a dengue case. Proximity to a hospital did not increase risk of a notified dengue case. Overall, there was high heterogeneity in incidence rate within areas with the same socio-economical profiles and substantial inter-annual variability. Dengue affected the poorest areas with high density of humans, but rich areas were also found to be infected, potentially because of their central location with respect to the daily mobility network of Delhi. Dengue cases were highly clustered in space and there was a strong relationship between the time of introduction of the virus and subsequent cluster size. At a larger scale, earlier introduction predicted the total number of cases. Conclusions/Significance DENV epidemiology within Delhi has a forest fire signature. The stochastic nature of this invasion process likely smothers any detectable socio-economic risk factors. However, the significant finding that the size of the dengue case cluster depends on the timing of its emergence emphasizes the need for early case detection and implementation of effective mosquito control. A better understanding of the role of population mobility in contributing to dengue risk could also help focus control on areas at particular risk of dengue virus importation. PMID:26808518

Analysis of earthquake clustering and source spectra in the Salton Sea Geothermal Field

NASA Astrophysics Data System (ADS)

Cheng, Y.; Chen, X.

2015-12-01

The Salton Sea Geothermal field is located within the tectonic step-over between San Andreas Fault and Imperial Fault. Since the 1980s, geothermal energy exploration has resulted with step-like increase of microearthquake activities, which mirror the expansion of geothermal field. Distinguishing naturally occurred and induced seismicity, and their corresponding characteristics (e.g., energy release) is important for hazard assessment. Between 2008 and 2014, seismic data recorded by a local borehole array were provided public access from CalEnergy through SCEC data center; and the high quality local recording of over 7000 microearthquakes provides unique opportunity to sort out characteristics of induced versus natural activities. We obtain high-resolution earthquake location using improved S-wave picks, waveform cross-correlation and a new 3D velocity model. We then develop method to identify spatial-temporally isolated earthquake clusters. These clusters are classified into aftershock-type, swarm-type, and mixed-type (aftershock-like, with low skew, low magnitude and shorter duration), based on the relative timing of largest earthquakes and moment-release. The mixed-type clusters are mostly located at 3 - 4 km depth near injection well; while aftershock-type clusters and swarm-type clusters also occur further from injection well. By counting number of aftershocks within 1day following mainshock in each cluster, we find that the mixed-type clusters have much higher aftershock productivity compared with other types and historic M4 earthquakes. We analyze detailed spatial variation of 'b-value'. We find that the mixed-type clusters are mostly located within high b-value patches, while large (M>3) earthquakes and other types of clusters are located within low b-value patches. We are currently processing P and S-wave spectra to analyze the spatial-temporal correlation of earthquake stress parameter and seismicity characteristics. Preliminary results suggest that the mixed-type clusters and high b-value patches are spatially correlated with low stress drop earthquakes, indicating high-productivity microearthquakes within low differential stress region, potentially due to deeper injection activities.

Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011.

PubMed

Shields, Timothy; Pinchoff, Jessie; Lubinda, Jailos; Hamapumbu, Harry; Searle, Kelly; Kobayashi, Tamaki; Thuma, Philip E; Moss, William J; Curriero, Frank C

2016-05-31

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

Spatial-temporal cluster analysis of mortality from road traffic injuries using geographic information systems in West of Iran during 2009-2014.

PubMed

Zangeneh, Alireza; Najafi, Farid; Karimi, Saeed; Saeidi, Shahram; Izadi, Neda

2018-04-01

Road traffic injuries (RTIs) are considered as one of the most important health problems endangering people's life. The examination of the geographical distribution of RTIs could help policymakers in better planning to reduce RTIs. This study, therefore, aimed to determine the spatial-temporal clustering of mortality from RTIs in West of Iran. Deaths from RTIs, registered in Forensic Medicine Organization of Kermanshah province over a period of six years (2009-2014), were used. Using negative binomial regression, the mortality trend was investigated. In order to investigate the spatial distribution of RTIs, we used ArcGIS. (Version 10.3). The median age of the 3231 people died in RTIs was 37 (IQR = 31) year, 78.4% were male. The 6-year average mortality rate from RTIs was 27.8/100,000 deaths, and the average rate had a declining trend. The dispersion of RTIs showed that most deaths occurred in Kermanshah, Islamabad, Bisotun, and Harsin road axes, respectively. The mean center of all deaths from RTIs occurred in Kermanshah province, the central area of Kermanshah district. The spatial trend of such deaths has moved to the northeast-southwest, and such deaths were geographically centralized. Results of Moran's I with respect to cluster analysis also indicated positive spatial autocorrelations. The results showed that the mortality rate from RTIs, despite the decline in recent years, is still high when compared with other countries. The clustering of accidents raises the concern that road infrastructure in certain locations may also be a factor. Regarding the results related to the temporal analysis, it is suggested that the enforcement of traffic rules be stricter at rush hours. Copyright © 2018 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Combined multivariate statistical techniques, Water Pollution Index (WPI) and Daniel Trend Test methods to evaluate temporal and spatial variations and trends of water quality at Shanchong River in the Northwest Basin of Lake Fuxian, China.

PubMed

Wang, Quan; Wu, Xianhua; Zhao, Bin; Qin, Jie; Peng, Tingchun

2015-01-01

Understanding spatial and temporal variations in river water quality and quantitatively evaluating the trend of changes are important in order to study and efficiently manage water resources. In this study, an analysis of Water Pollution Index (WPI), Daniel Trend Test, Cluster Analysis and Discriminant Analysis are applied as an integrated approach to quantitatively explore the spatial and temporal variations and the latent sources of water pollution in the Shanchong River basin, Northwest Basin of Lake Fuxian, China. We group all field surveys into 2 clusters (dry season and rainy season). Moreover, 14 sampling sites have been grouped into 3 clusters for the rainy season (highly polluted, moderately polluted and less polluted sites) and 2 clusters for the dry season (highly polluted and less polluted sites) based on their similarities and the level of pollution during the two seasons. The results show that the main trend of pollution was aggravated during the transition from the dry to the rainy season. The Water Pollution Index of Total Nitrogen is the highest of all pollution parameters, whereas the Chemical Oxygen Demand (Chromium) is the lowest. Our results also show that the main sources of pollution are farming activities alongside the Shanchong River, soil erosion and fish culture at Shanchong River reservoir area and domestic sewage from scattered rural residential area. Our results suggest that strategies to prevent water pollutionat the Shanchong River basin need to focus on non-point pollution control by employing appropriate fertilizer formulas in farming, and take the measures of soil and water conservation at Shanchong reservoir area, and purifying sewage from scattered villages.

Combined Multivariate Statistical Techniques, Water Pollution Index (WPI) and Daniel Trend Test Methods to Evaluate Temporal and Spatial Variations and Trends of Water Quality at Shanchong River in the Northwest Basin of Lake Fuxian, China

PubMed Central

Wang, Quan; Wu, Xianhua; Zhao, Bin; Qin, Jie; Peng, Tingchun

2015-01-01

Understanding spatial and temporal variations in river water quality and quantitatively evaluating the trend of changes are important in order to study and efficiently manage water resources. In this study, an analysis of Water Pollution Index (WPI), Daniel Trend Test, Cluster Analysis and Discriminant Analysis are applied as an integrated approach to quantitatively explore the spatial and temporal variations and the latent sources of water pollution in the Shanchong River basin, Northwest Basin of Lake Fuxian, China. We group all field surveys into 2 clusters (dry season and rainy season). Moreover, 14 sampling sites have been grouped into 3 clusters for the rainy season (highly polluted, moderately polluted and less polluted sites) and 2 clusters for the dry season (highly polluted and less polluted sites) based on their similarities and the level of pollution during the two seasons. The results show that the main trend of pollution was aggravated during the transition from the dry to the rainy season. The Water Pollution Index of Total Nitrogen is the highest of all pollution parameters, whereas the Chemical Oxygen Demand (Chromium) is the lowest. Our results also show that the main sources of pollution are farming activities alongside the Shanchong River, soil erosion and fish culture at Shanchong River reservoir area and domestic sewage from scattered rural residential area. Our results suggest that strategies to prevent water pollutionat the Shanchong River basin need to focus on non-point pollution control by employing appropriate fertilizer formulas in farming, and take the measures of soil and water conservation at Shanchong reservoir area, and purifying sewage from scattered villages. PMID:25837673

Regional frequency analysis to asses wind resource spatial and temporal variations in Washington State

NASA Astrophysics Data System (ADS)

Mortuza, M.; Demissie, D.

2013-12-01

According to the U.S. Department of Energy's annual wind technologies market report, the wind power capacity in the country grew from 2.5 gigawatts in early 2000 to 60 gigawatts in 2012, making it one of the largest new sources of electric capacity additions in the U.S. in recent years. With over 2.8 gigawatts of current capacity (eighth largest in the nation), Washington State plays a significant role in this rapidly increasing energy resource. To further expand and/or optimize these capacities, assessment of wind resource and its spatial and temporal variations are important. However, since at-site frequency analysis using meteorological data is not adequate for extending wind frequency to locations with no data, longer return period, and heterogeneous topography and surface, a regional frequency analysis based on L-moment method is adopted in this study to estimate regional wind speed patterns and return periods in Washington State using hourly mean wind speed data from 1979 - 2010. The analysis applies the k-means, hierarchical and self-organizing map clustering techniques to explore potential clusters or regions; statistical tests are then applied to identify homogeneous regions and appropriate probability distribution models. The result from the analysis is expected to provide essential knowledge about the areas with potential capacity of constructing wind power plants, which can also be readily extended to assist decisions on their daily operations.

Quantitative assessment of Hox complex expression in the indirect development of the polychaete annelid Chaetopterus sp

NASA Technical Reports Server (NTRS)

Peterson, K. J.; Irvine, S. Q.; Cameron, R. A.; Davidson, E. H.

2000-01-01

A prediction from the set-aside theory of bilaterian origins is that pattern formation processes such as those controlled by the Hox cluster genes are required specifically for adult body plan formation. This prediction can be tested in animals that use maximal indirect development, in which the embryonic formation of the larva and the postembryonic formation of the adult body plan are temporally and spatially distinct. To this end, we quantitatively measured the amount of transcripts for five Hox genes in embryos of a lophotrochozoan, the polychaete annelid Chaetopterus sp. The polychaete Hox complex is shown not to be expressed during embryogenesis, but transcripts of all measured Hox complex genes are detected at significant levels during the initial stages of adult body plan formation. Temporal colinearity in the sequence of their activation is observed, so that activation follows the 3'-5' arrangement of the genes. Moreover, Hox gene expression is spatially localized to the region of teloblastic set-aside cells of the later-stage embryos. This study shows that an indirectly developing lophotrochozoan shares with an indirectly developing deuterostome, the sea urchin, a common mode of Hox complex utilization: construction of the larva, whether a trochophore or dipleurula, does not involve Hox cluster expression, but in both forms the complex is expressed in the set-aside cells from which the adult body plan derives.

Multi-spacecraft studies of the auroral acceleration region: From cluster to nanosatellites

NASA Astrophysics Data System (ADS)

Sadeghi, S.; Emami, M. R.

2017-03-01

This paper discusses the utilization of multiple Cubesats in various formations for studies in the auroral acceleration region. The focus is on the quasi-static properties, spatio-temporal features, electric potential structures, field-aligned currents, and their relationships, all of which are fundamentally important for an understanding of the magnetosphere-ionosphere coupling. It is argued that a multitude of nanosatellites can address some of the relevant outstanding questions in a broader range of spatial, temporal, and geometrical features, with higher redundancy and data consistency, potentially resulting in a shorter mission period and a higher chance of mission success. A number of mission concepts consisting of a cluster of 6-12 Cubesats with their specific onboard payloads are suggested for such missions over a period of as short as two months.

Temporal Order in Periodically Driven Spins in Star-Shaped Clusters

NASA Astrophysics Data System (ADS)

Pal, Soham; Nishad, Naveen; Mahesh, T. S.; Sreejith, G. J.

2018-05-01

We experimentally study the response of star-shaped clusters of initially unentangled N =4 , 10, and 37 nuclear spin-1 /2 moments to an inexact π -pulse sequence and show that an Ising coupling between the center and the satellite spins results in robust period-2 magnetization oscillations. The period is stable against bath effects, but the amplitude decays with a timescale that depends on the inexactness of the pulse. Simulations reveal a semiclassical picture in which the rigidity of the period is due to a randomizing effect of the Larmor precession under the magnetization of surrounding spins. The timescales with stable periodicity increase with net initial magnetization, even in the presence of perturbations, indicating a robust temporal ordered phase for large systems with finite magnetization per spin.

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

NASA Astrophysics Data System (ADS)

Grasha, K.; Elmegreen, B. G.; Calzetti, D.; Adamo, A.; Aloisi, A.; Bright, S. N.; Cook, D. O.; Dale, D. A.; Fumagalli, M.; Gallagher, J. S., III; Gouliermis, D. A.; Grebel, E. K.; Kahre, L.; Kim, H.; Krumholz, M. R.; Lee, J. C.; Messa, M.; Ryon, J. E.; Ubeda, L.

2017-06-01

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25-0.6 power, and that the maximum size over which star formation is physically correlated ranges from ˜200 pc to ˜1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are close to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.

Neural plasticity associated with recently versus often heard objects.

PubMed

Bourquin, Nathalie M-P; Spierer, Lucas; Murray, Micah M; Clarke, Stephanie

2012-09-01

In natural settings the same sound source is often heard repeatedly, with variations in spectro-temporal and spatial characteristics. We investigated how such repetitions influence sound representations and in particular how auditory cortices keep track of recently vs. often heard objects. A set of 40 environmental sounds was presented twice, i.e. as prime and as repeat, while subjects categorized the corresponding sound sources as living vs. non-living. Electrical neuroimaging analyses were applied to auditory evoked potentials (AEPs) comparing primes vs. repeats (effect of presentation) and the four experimental sections. Dynamic analysis of distributed source estimations revealed i) a significant main effect of presentation within the left temporal convexity at 164-215 ms post-stimulus onset; and ii) a significant main effect of section in the right temporo-parietal junction at 166-213 ms. A 3-way repeated measures ANOVA (hemisphere×presentation×section) applied to neural activity of the above clusters during the common time window confirmed the specificity of the left hemisphere for the effect of presentation, but not that of the right hemisphere for the effect of section. In conclusion, spatio-temporal dynamics of neural activity encode the temporal history of exposure to sound objects. Rapidly occurring plastic changes within the semantic representations of the left hemisphere keep track of objects heard a few seconds before, independent of the more general sound exposure history. Progressively occurring and more long-lasting plastic changes occurring predominantly within right hemispheric networks, which are known to code for perceptual, semantic and spatial aspects of sound objects, keep track of multiple exposures. Copyright © 2012 Elsevier Inc. All rights reserved.

Polarity-Dependent Misperception of Subjective Visual Vertical during and after Transcranial Direct Current Stimulation (tDCS)

PubMed Central

Santos-Pontelli, Taiza E. G.; Rimoli, Brunna P.; Favoretto, Diandra B.; Mazin, Suleimy C.; Truong, Dennis Q.; Leite, Joao P.; Pontes-Neto, Octavio M.; Babyar, Suzanne R.; Reding, Michael; Bikson, Marom; Edwards, Dylan J.

2016-01-01

Pathologic tilt of subjective visual vertical (SVV) frequently has adverse functional consequences for patients with stroke and vestibular disorders. Repetitive transcranial magnetic stimulation (rTMS) of the supramarginal gyrus can produce a transitory tilt on SVV in healthy subjects. However, the effect of transcranial direct current stimulation (tDCS) on SVV has never been systematically studied. We investigated whether bilateral tDCS over the temporal-parietal region could result in both online and offline SVV misperception in healthy subjects. In a randomized, sham-controlled, single-blind crossover pilot study, thirteen healthy subjects performed tests of SVV before, during and after the tDCS applied over the temporal-parietal region in three conditions used on different days: right anode/left cathode; right cathode/left anode; and sham. Subjects were blind to the tDCS conditions. Montage-specific current flow patterns were investigated using computational models. SVV was significantly displaced towards the anode during both active stimulation conditions when compared to sham condition. Immediately after both active conditions, there were rebound effects. Longer lasting after-effects towards the anode occurred only in the right cathode/left anode condition. Current flow models predicted the stimulation of temporal-parietal regions under the electrodes and deep clusters in the posterior limb of the internal capsule. The present findings indicate that tDCS over the temporal-parietal region can significantly alter human SVV perception. This tDCS approach may be a potential clinical tool for the treatment of SVV misperception in neurological patients. PMID:27031726

Sensitivity evaluation of dynamic speckle activity measurements using clustering methods.

PubMed

Etchepareborda, Pablo; Federico, Alejandro; Kaufmann, Guillermo H

2010-07-01

We evaluate and compare the use of competitive neural networks, self-organizing maps, the expectation-maximization algorithm, K-means, and fuzzy C-means techniques as partitional clustering methods, when the sensitivity of the activity measurement of dynamic speckle images needs to be improved. The temporal history of the acquired intensity generated by each pixel is analyzed in a wavelet decomposition framework, and it is shown that the mean energy of its corresponding wavelet coefficients provides a suited feature space for clustering purposes. The sensitivity obtained by using the evaluated clustering techniques is also compared with the well-known methods of Konishi-Fujii, weighted generalized differences, and wavelet entropy. The performance of the partitional clustering approach is evaluated using simulated dynamic speckle patterns and also experimental data.

Asthma length of stay in hospitals in London 2001-2006: demographic, diagnostic and temporal factors.

PubMed

Soyiri, Ireneous N; Reidpath, Daniel D; Sarran, Christophe

2011-01-01

Asthma is a condition of significant public health concern associated with morbidity, mortality and healthcare utilisation. This study identifies key determinants of length of stay (LOS) associated with asthma-related hospital admissions in London, and further explores their effects on individuals. Subjects were primarily diagnosed and admitted for asthma in London between 1(st) January 2001 and 31(st) December 2006. All repeated admissions were treated uniquely as independent cases. Negative binomial regression was used to model the effect(s) of demographic, temporal and diagnostic factors on the LOS, taking into account the cluster effect of each patient's hospital attendance in London. The median and mean asthma LOS over the period of study were 2 and 3 days respectively. Admissions increased over the years from 8,308 (2001) to 10,554 (2006), but LOS consistently declined within the same period. Younger individuals were more likely to be admitted than the elderly, but the latter significantly had higher LOS (p<0.001). Respiratory related secondary diagnoses, age, and gender of the patient as well as day of the week and year of admission were important predictors of LOS. Asthma LOS can be predicted by socio-demographic factors, temporal and clinical factors using count models on hospital admission data. The procedure can be a useful tool for planning and resource allocation in health service provision.

Sirenomelia in Argentina: Prevalence, geographic clusters and temporal trends analysis.

PubMed

Groisman, Boris; Liascovich, Rosa; Gili, Juan Antonio; Barbero, Pablo; Bidondo, María Paz

2016-07-01

Sirenomelia is a severe malformation of the lower body characterized by a single medial lower limb and a variable combination of visceral abnormalities. Given that Sirenomelia is a very rare birth defect, epidemiological studies are scarce. The aim of this study is to evaluate prevalence, geographic clusters and time trends of sirenomelia in Argentina, using data from the National Network of Congenital Anomalies of Argentina (RENAC) from November 2009 until December 2014. This is a descriptive study using data from the RENAC, a hospital-based surveillance system for newborns affected with major morphological congenital anomalies. We calculated sirenomelia prevalence throughout the period, searched for geographical clusters, and evaluated time trends. The prevalence of confirmed cases of sirenomelia throughout the period was 2.35 per 100,000 births. Cluster analysis showed no statistically significant geographical aggregates. Time-trends analysis showed that the prevalence was higher in years 2009 to 2010. The observed prevalence was higher than the observed in previous epidemiological studies in other geographic regions. We observed a likely real increase in the initial period of our study. We used strict diagnostic criteria, excluding cases that only had clinical diagnosis of sirenomelia. Therefore, real prevalence could be even higher. This study did not show any geographic clusters. Because etiology of sirenomelia has not yet been established, studies of epidemiological features of this defect may contribute to define its causes. Birth Defects Research (Part A) 106:604-611, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A multi-Poisson dynamic mixture model to cluster developmental patterns of gene expression by RNA-seq.

PubMed

Ye, Meixia; Wang, Zhong; Wang, Yaqun; Wu, Rongling

2015-03-01

Dynamic changes of gene expression reflect an intrinsic mechanism of how an organism responds to developmental and environmental signals. With the increasing availability of expression data across a time-space scale by RNA-seq, the classification of genes as per their biological function using RNA-seq data has become one of the most significant challenges in contemporary biology. Here we develop a clustering mixture model to discover distinct groups of genes expressed during a period of organ development. By integrating the density function of multivariate Poisson distribution, the model accommodates the discrete property of read counts characteristic of RNA-seq data. The temporal dependence of gene expression is modeled by the first-order autoregressive process. The model is implemented with the Expectation-Maximization algorithm and model selection to determine the optimal number of gene clusters and obtain the estimates of Poisson parameters that describe the pattern of time-dependent expression of genes from each cluster. The model has been demonstrated by analyzing a real data from an experiment aimed to link the pattern of gene expression to catkin development in white poplar. The usefulness of the model has been validated through computer simulation. The model provides a valuable tool for clustering RNA-seq data, facilitating our global view of expression dynamics and understanding of gene regulation mechanisms. © The Author 2014. Published by Oxford University Press. For Permissions, please email: journals.permissions@oup.com.

Dynamical Friction in Multi-component Evolving Globular Clusters

NASA Astrophysics Data System (ADS)

Alessandrini, Emiliano; Lanzoni, Barbara; Miocchi, Paolo; Ciotti, Luca; Ferraro, Francesco R.

2014-11-01

We use the Chandrasekhar formalism and direct N-body simulations to study the effect of dynamical friction on a test object only slightly more massive than the field stars, orbiting a spherically symmetric background of particles with a mass spectrum. The main goal is to verify whether the dynamical friction time (t DF) develops a non-monotonic radial dependence that could explain the bimodality of the blue straggler radial distributions observed in globular clusters. In these systems, in fact, relaxation effects lead to a mass and velocity radial segregation of the different mass components, so that mass-spectrum effects on t DF are expected to be dependent on radius. We find that in spite of the presence of different masses, t DF is always a monotonic function of radius, at all evolutionary times and independently of the initial concentration of the simulated cluster. This is because the radial dependence of t DF is largely dominated by the total mass density profile of the background stars (which is monotonically decreasing with radius). Hence, a progressive temporal erosion of the blue straggler star (BSS) population at larger and larger distances from the cluster center remains the simplest and the most likely explanation of the shape of the observed BSS radial distributions, as suggested in previous works. We also confirm the theoretical expectation that approximating a multi-mass globular cluster as made of (averaged) equal-mass stars can lead to significant overestimations of t DF within the half-mass radius.

Temporal Features of Word-Initial /s/+Stop Clusters in Bilingual Mandarin-English Children and Monolingual English Children and Adults

ERIC Educational Resources Information Center

Yang, Jing

2018-01-01

This study investigated the durational features of English word-initial /s/+stop clusters produced by bilingual Mandarin (L1)-English (L2) children and monolingual English children and adults. The participants included two groups of five- to six-year-old bilingual children: low proficiency in the L2 (Bi-low) and high proficiency in the L2…

Geotemporal Analysis of Neisseria meningitidis Clones in the United States: 2000–2005

PubMed Central

Wiringa, Ann E.; Shutt, Kathleen A.; Marsh, Jane W.; Cohn, Amanda C.; Messonnier, Nancy E.; Zansky, Shelley M.; Petit, Susan; Farley, Monica M.; Gershman, Ken; Lynfield, Ruth; Reingold, Arthur; Schaffner, William; Thompson, Jamie; Brown, Shawn T.; Lee, Bruce Y.; Harrison, Lee H.

2013-01-01

Background The detection of meningococcal outbreaks relies on serogrouping and epidemiologic definitions. Advances in molecular epidemiology have improved the ability to distinguish unique Neisseria meningitidis strains, enabling the classification of isolates into clones. Around 98% of meningococcal cases in the United States are believed to be sporadic. Methods Meningococcal isolates from 9 Active Bacterial Core surveillance sites throughout the United States from 2000 through 2005 were classified according to serogroup, multilocus sequence typing, and outer membrane protein (porA, porB, and fetA) genotyping. Clones were defined as isolates that were indistinguishable according to this characterization. Case data were aggregated to the census tract level and all non-singleton clones were assessed for non-random spatial and temporal clustering using retrospective space-time analyses with a discrete Poisson probability model. Results Among 1,062 geocoded cases with available isolates, 438 unique clones were identified, 78 of which had ≥2 isolates. 702 cases were attributable to non-singleton clones, accounting for 66.0% of all geocoded cases. 32 statistically significant clusters comprised of 107 cases (10.1% of all geocoded cases) were identified. Clusters had the following attributes: included 2 to 11 cases; 1 day to 33 months duration; radius of 0 to 61.7 km; and attack rate of 0.7 to 57.8 cases per 100,000 population. Serogroups represented among the clusters were: B (n = 12 clusters, 45 cases), C (n = 11 clusters, 27 cases), and Y (n = 9 clusters, 35 cases); 20 clusters (62.5%) were caused by serogroups represented in meningococcal vaccines that are commercially available in the United States. Conclusions Around 10% of meningococcal disease cases in the U.S. could be assigned to a geotemporal cluster. Molecular characterization of isolates, combined with geotemporal analysis, is a useful tool for understanding the spread of virulent meningococcal clones and patterns of transmission in populations. PMID:24349182

Syndromic surveillance of abortions in beef cattle based on the prospective analysis of spatio-temporal variations of calvings.

PubMed

Bronner, A; Morignat, E; Fournié, G; Vergne, T; Vinard, J-L; Gay, E; Calavas, D

2015-12-21

Our objective was to study the ability of a syndromic surveillance system to identify spatio-temporal clusters of drops in the number of calvings among beef cows during the Bluetongue epizootic of 2007 and 2008, based on calving seasons. France was partitioned into 300 iso-populated units, i.e. units with quite the same number of beef cattle. Only 1% of clusters were unlikely to be related to Bluetongue. Clusters were detected during the calving season of primary infection by Bluetongue in 28% (n = 23) of the units first infected in 2007, and in 87% (n = 184) of the units first infected in 2008. In units in which a first cluster was detected over their calving season of primary infection, Bluetongue was detected more rapidly after the start of the calving season and its prevalence was higher than in other units. We believe that this type of syndromic surveillance system could improve the surveillance of abortive events in French cattle. Besides, our approach should be used to develop syndromic surveillance systems for other diseases and purposes, and in other settings, to avoid "false" alarms due to isolated events and homogenize the ability to detect abnormal variations of indicator amongst iso-populated units.

Syndromic surveillance of abortions in beef cattle based on the prospective analysis of spatio-temporal variations of calvings

PubMed Central

Bronner, A.; Morignat, E.; Fournié, G.; Vergne, T.; Vinard, J-L; Gay, E.; Calavas, D.

2015-01-01

Our objective was to study the ability of a syndromic surveillance system to identify spatio-temporal clusters of drops in the number of calvings among beef cows during the Bluetongue epizootic of 2007 and 2008, based on calving seasons. France was partitioned into 300 iso-populated units, i.e. units with quite the same number of beef cattle. Only 1% of clusters were unlikely to be related to Bluetongue. Clusters were detected during the calving season of primary infection by Bluetongue in 28% (n = 23) of the units first infected in 2007, and in 87% (n = 184) of the units first infected in 2008. In units in which a first cluster was detected over their calving season of primary infection, Bluetongue was detected more rapidly after the start of the calving season and its prevalence was higher than in other units. We believe that this type of syndromic surveillance system could improve the surveillance of abortive events in French cattle. Besides, our approach should be used to develop syndromic surveillance systems for other diseases and purposes, and in other settings, to avoid “false” alarms due to isolated events and homogenize the ability to detect abnormal variations of indicator amongst iso-populated units. PMID:26687099

Spatial, Temporal and Spatio-Temporal Patterns of Maritime Piracy

PubMed Central

Marchione, Elio

2013-01-01

Objectives: To examine patterns in the timing and location of incidents of maritime piracy to see whether, like many urban crimes, attacks cluster in space and time. Methods: Data for all incidents of maritime piracy worldwide recorded by the National Geospatial Intelligence Agency are analyzed using time-series models and methods originally developed to detect disease contagion. Results: At the macro level, analyses suggest that incidents of pirate attacks are concentrated in five subregions of the earth’s oceans and that the time series for these different subregions differ. At the micro level, analyses suggest that for the last 16 years (or more), pirate attacks appear to cluster in space and time suggesting that patterns are not static but are also not random. Conclusions: Much like other types of crime, pirate attacks cluster in space, and following an attack at one location the risk of others at the same location or nearby is temporarily elevated. The identification of such regularities has implications for the understanding of maritime piracy and for predicting the future locations of attacks. PMID:25076796

Acoustic Cluster Therapy: In Vitro and Ex Vivo Measurement of Activated Bubble Size Distribution and Temporal Dynamics.

PubMed

Healey, Andrew John; Sontum, Per Christian; Kvåle, Svein; Eriksen, Morten; Bendiksen, Ragnar; Tornes, Audun; Østensen, Jonny

2016-05-01

Acoustic cluster technology (ACT) is a two-component, microparticle formulation platform being developed for ultrasound-mediated drug delivery. Sonazoid microbubbles, which have a negative surface charge, are mixed with micron-sized perfluoromethylcyclopentane droplets stabilized with a positively charged surface membrane to form microbubble/microdroplet clusters. On exposure to ultrasound, the oil undergoes a phase change to the gaseous state, generating 20- to 40-μm ACT bubbles. An acoustic transmission technique is used to measure absorption and velocity dispersion of the ACT bubbles. An inversion technique computes bubble size population with temporal resolution of seconds. Bubble populations are measured both in vitro and in vivo after activation within the cardiac chambers of a dog model, with catheter-based flow through an extracorporeal measurement flow chamber. Volume-weighted mean diameter in arterial blood after activation in the left ventricle was 22 μm, with no bubbles >44 μm in diameter. After intravenous administration, 24.4% of the oil is activated in the cardiac chambers. Copyright © 2016 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Epilepsy, hippocampal sclerosis and febrile seizures linked by common genetic variation around SCN1A

PubMed Central

Kasperavičiūtė, Dalia; Catarino, Claudia B.; Matarin, Mar; Leu, Costin; Novy, Jan; Tostevin, Anna; Leal, Bárbara; Hessel, Ellen V. S.; Hallmann, Kerstin; Hildebrand, Michael S.; Dahl, Hans-Henrik M.; Ryten, Mina; Trabzuni, Daniah; Ramasamy, Adaikalavan; Alhusaini, Saud; Doherty, Colin P.; Dorn, Thomas; Hansen, Jörg; Krämer, Günter; Steinhoff, Bernhard J.; Zumsteg, Dominik; Duncan, Susan; Kälviäinen, Reetta K.; Eriksson, Kai J.; Kantanen, Anne-Mari; Pandolfo, Massimo; Gruber-Sedlmayr, Ursula; Schlachter, Kurt; Reinthaler, Eva M.; Stogmann, Elisabeth; Zimprich, Fritz; Théâtre, Emilie; Smith, Colin; O’Brien, Terence J.; Meng Tan, K.; Petrovski, Slave; Robbiano, Angela; Paravidino, Roberta; Zara, Federico; Striano, Pasquale; Sperling, Michael R.; Buono, Russell J.; Hakonarson, Hakon; Chaves, João; Costa, Paulo P.; Silva, Berta M.; da Silva, António M.; de Graan, Pierre N. E.; Koeleman, Bobby P. C.; Becker, Albert; Schoch, Susanne; von Lehe, Marec; Reif, Philipp S.; Rosenow, Felix; Becker, Felicitas; Weber, Yvonne; Lerche, Holger; Rössler, Karl; Buchfelder, Michael; Hamer, Hajo M.; Kobow, Katja; Coras, Roland; Blumcke, Ingmar; Scheffer, Ingrid E.; Berkovic, Samuel F.; Weale, Michael E.; Delanty, Norman; Depondt, Chantal; Cavalleri, Gianpiero L.; Kunz, Wolfram S.

2013-01-01

Epilepsy comprises several syndromes, amongst the most common being mesial temporal lobe epilepsy with hippocampal sclerosis. Seizures in mesial temporal lobe epilepsy with hippocampal sclerosis are typically drug-resistant, and mesial temporal lobe epilepsy with hippocampal sclerosis is frequently associated with important co-morbidities, mandating the search for better understanding and treatment. The cause of mesial temporal lobe epilepsy with hippocampal sclerosis is unknown, but there is an association with childhood febrile seizures. Several rarer epilepsies featuring febrile seizures are caused by mutations in SCN1A, which encodes a brain-expressed sodium channel subunit targeted by many anti-epileptic drugs. We undertook a genome-wide association study in 1018 people with mesial temporal lobe epilepsy with hippocampal sclerosis and 7552 control subjects, with validation in an independent sample set comprising 959 people with mesial temporal lobe epilepsy with hippocampal sclerosis and 3591 control subjects. To dissect out variants related to a history of febrile seizures, we tested cases with mesial temporal lobe epilepsy with hippocampal sclerosis with (overall n = 757) and without (overall n = 803) a history of febrile seizures. Meta-analysis revealed a genome-wide significant association for mesial temporal lobe epilepsy with hippocampal sclerosis with febrile seizures at the sodium channel gene cluster on chromosome 2q24.3 [rs7587026, within an intron of the SCN1A gene, P = 3.36 × 10−9, odds ratio (A) = 1.42, 95% confidence interval: 1.26–1.59]. In a cohort of 172 individuals with febrile seizures, who did not develop epilepsy during prospective follow-up to age 13 years, and 6456 controls, no association was found for rs7587026 and febrile seizures. These findings suggest SCN1A involvement in a common epilepsy syndrome, give new direction to biological understanding of mesial temporal lobe epilepsy with hippocampal sclerosis with febrile seizures, and open avenues for investigation of prognostic factors and possible prevention of epilepsy in some children with febrile seizures. PMID:24014518

Extracting the Textual and Temporal Structure of Supercomputing Logs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jain, S; Singh, I; Chandra, A

2009-05-26

Supercomputers are prone to frequent faults that adversely affect their performance, reliability and functionality. System logs collected on these systems are a valuable resource of information about their operational status and health. However, their massive size, complexity, and lack of standard format makes it difficult to automatically extract information that can be used to improve system management. In this work we propose a novel method to succinctly represent the contents of supercomputing logs, by using textual clustering to automatically find the syntactic structures of log messages. This information is used to automatically classify messages into semantic groups via an onlinemore » clustering algorithm. Further, we describe a methodology for using the temporal proximity between groups of log messages to identify correlated events in the system. We apply our proposed methods to two large, publicly available supercomputing logs and show that our technique features nearly perfect accuracy for online log-classification and extracts meaningful structural and temporal message patterns that can be used to improve the accuracy of other log analysis techniques.« less

Statistical indicators of collective behavior and functional clusters in gene networks of yeast

NASA Astrophysics Data System (ADS)

Živković, J.; Tadić, B.; Wick, N.; Thurner, S.

2006-03-01

We analyze gene expression time-series data of yeast (S. cerevisiae) measured along two full cell-cycles. We quantify these data by using q-exponentials, gene expression ranking and a temporal mean-variance analysis. We construct gene interaction networks based on correlation coefficients and study the formation of the corresponding giant components and minimum spanning trees. By coloring genes according to their cell function we find functional clusters in the correlation networks and functional branches in the associated trees. Our results suggest that a percolation point of functional clusters can be identified on these gene expression correlation networks.

Sequential detection of temporal communities by estrangement confinement.

PubMed

Kawadia, Vikas; Sreenivasan, Sameet

2012-01-01

Temporal communities are the result of a consistent partitioning of nodes across multiple snapshots of an evolving network, and they provide insights into how dense clusters in a network emerge, combine, split and decay over time. To reliably detect temporal communities we need to not only find a good community partition in a given snapshot but also ensure that it bears some similarity to the partition(s) found in the previous snapshot(s), a particularly difficult task given the extreme sensitivity of community structure yielded by current methods to changes in the network structure. Here, motivated by the inertia of inter-node relationships, we present a new measure of partition distance called estrangement, and show that constraining estrangement enables one to find meaningful temporal communities at various degrees of temporal smoothness in diverse real-world datasets. Estrangement confinement thus provides a principled approach to uncovering temporal communities in evolving networks.

The Elbmarsch leukemia cluster: are there conceptual limitations in controlling immission from nuclear establishments in Germany?

PubMed

Schmitz-Feuerhake, I; Dieckmann, H; Hoffmann, W; Lengfelder, E; Pflugbeil, S; Stevenson, A F

2005-11-01

The childhood leukemia cluster in the proximity of the German nuclear establishments of Geesthacht is unique in its spatial and temporal concentration. After a steep increase in cases in 1990, the cluster continues to show a significant increase up to the present. Early investigations of blood samples from a casual sample of local residents showed an increase in dicentric chromosomes in lymphocytes, indicating exposure exceeding dose limits. Analyses of the immission data revealed several unexpected deliveries of fission and activation products in the environment but provided no explanation of the source. Because of the observed overdispersion of dicentric chromosomes in cells, the idea of a contribution by densely ionizing emitters was compelling. The routine programs, however, do not include alpha emitters. These were measured in specific studies that proved contamination by transuranic nuclides. As shown in the present investigation, routine environmental surveillance programs support the occurrence of an accidental event near Geesthacht in September 1986. Until now, neither the cause nor the complete scenario of the activity release could be established. The ongoing discussion highlights limitations in the immission-control concept, which is predominantly based on gamma-radiation monitoring.

A diffusion perspective on temporal networks: A case study on a supermarket

NASA Astrophysics Data System (ADS)

Deng, Shiguo; Qiu, Lu; Yang, Yue; Yang, Huijie

2016-01-01

From a large amount of records, one can extract behavioral characteristics of a social system at different scales. Theoretically, it can help us to know how the global behavior of a social system is formed from individual activities. Practically, it can be used to optimize and even to control the social system. Complicated relationships between the individuals form a network, which evolves with time. The behavior of the system can be accordingly understood in the framework of temporal network. In the present paper, instead of focusing on microscopic structures, we develop a framework to investigate temporal networks from the viewpoint of diffusion process, in which each snapshot network is divided into groups and the ID number of the group a node belongs to is used to measure its state. By this way trajectories of the nodes form an ensemble of realizations of a stochastic process. As an illustration, we investigate the diffusion behavior of a supermarket. One can find that with the increase of time the customers cluster and separate into different groups. Meanwhile, the system evolves in a significant order way, instead of a complete random one.

Sustainable microbial water quality monitoring programme design using phage-lysis and multivariate techniques.

PubMed

Nnane, Daniel Ekane

2011-11-15

Contamination of surface waters is a pervasive threat to human health, hence, the need to better understand the sources and spatio-temporal variations of contaminants within river catchments. River catchment managers are required to sustainably monitor and manage the quality of surface waters. Catchment managers therefore need cost-effective low-cost long-term sustainable water quality monitoring and management designs to proactively protect public health and aquatic ecosystems. Multivariate and phage-lysis techniques were used to investigate spatio-temporal variations of water quality, main polluting chemophysical and microbial parameters, faecal micro-organisms sources, and to establish 'sentry' sampling sites in the Ouse River catchment, southeast England, UK. 350 river water samples were analysed for fourteen chemophysical and microbial water quality parameters in conjunction with the novel human-specific phages of Bacteroides GB-124 (Bacteroides GB-124). Annual, autumn, spring, summer, and winter principal components (PCs) explained approximately 54%, 75%, 62%, 48%, and 60%, respectively, of the total variance present in the datasets. Significant loadings of Escherichia coli, intestinal enterococci, turbidity, and human-specific Bacteroides GB-124 were observed in all datasets. Cluster analysis successfully grouped sampling sites into five clusters. Importantly, multivariate and phage-lysis techniques were useful in determining the sources and spatial extent of water contamination in the catchment. Though human faecal contamination was significant during dry periods, the main source of contamination was non-human. Bacteroides GB-124 could potentially be used for catchment routine microbial water quality monitoring. For a cost-effective low-cost long-term sustainable water quality monitoring design, E. coli or intestinal enterococci, turbidity, and Bacteroides GB-124 should be monitored all-year round in this river catchment. Copyright © 2011 Elsevier B.V. All rights reserved.

Spatial Distribution of Megacopta cribraria (Hemiptera: Plataspidae) Adults, Eggs and Parasitism by Paratelenomus saccharalis (Hymenoptera: Platygastridae) in Soybean.

PubMed

Knight, Ian A; Roberts, Phillip M; Gardner, Wayne A; Oliver, Kerry M; Reay-Jones, Francis P F; Reisig, Dominic D; Toews, Michael D

2017-12-08

Since 2014, populations of the kudzu bug, Megacopta cribraria (F.) (Hemiptera: Plataspidae), have declined in the southeastern United States and seldom require treatment. This decline follows the discovery of Paratelenomus saccharalis (Dodd; Hymenoptera: Platygastridae), a non-native egg parasitoid. The objective of this project was to observe the temporal and spatial dynamics of P. saccharalis parasitism of kudzu bug egg masses in commercial soybean fields. Four fields were sampled weekly for kudzu bugs and egg masses at a density of one sample per 0.6 ha. Sampling commenced when soybean reached the R2 maturity stage and continued until no more egg masses were present. Responses including kudzu bugs, egg masses, and parasitism rates were analyzed using ANOVA, Spatial Analysis by Distance Indices (SADIE), and SaTScan spatial analysis software. Egg masses were collected from the field, held in the lab and monitored for emergence of kudzu bug nymphs or P. saccharalis. Kudzu bug populations were generally lower than previously reported in the literature and spatial aggregation was not consistently observed. Egg parasitism was first detected in early July and increased to nearly 40% in mid-August. Significant spatial patterns in parasitism were observed with spatio-temporal clusters being loosely associated with clusters of egg masses. There were no significant differences in parasitism rates between field margins and interiors, suggesting that P. saccharalis is an effective parasitoid of kudzu bug egg masses on a whole-field scale. © The Authors 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Temporal Trends and Temperature-Related Incidence of Electrical Storm: The TEMPEST Study (Temperature-Related Incidence of Electrical Storm).

PubMed

Guerra, Federico; Bonelli, Paolo; Flori, Marco; Cipolletta, Laura; Carbucicchio, Corrado; Izquierdo, Maite; Kozluk, Edward; Shivkumar, Kalyanam; Vaseghi, Marmar; Patani, Francesca; Cupido, Claudio; Pala, Salvatore; Ruiz-Granell, Ricardo; Ferrero, Angel; Tondo, Claudio; Capucci, Alessandro

2017-03-01

The occurrence of ventricular tachyarrhythmias seems to follow circadian, daily, and seasonal distributions. Our aim is to identify potential temporal patterns of electrical storm (ES), in which a cluster of ventricular tachycardias or ventricular fibrillation, negatively affects short- and long-term survival. The TEMPEST study (Circannual Pattern and Temperature-Related Incidence of Electrical Storm) is a patient-level, pooled analysis of previously published data sets. Study selection criteria included diagnosis of ES, absence of acute coronary syndrome as the arrhythmic trigger, and ≥10 patients included. At the end of the selection and collection processes, 5 centers had the data set from their article pooled into the present registry. Temperature data and sunrise and sunset hours were retrieved from Weather Underground, the largest weather database available online. Total sample included 246 patients presenting with ES (221 men; age: 65±9 years). Each ES episode included a median of 7 ventricular tachycardia/ventricular fibrillation episodes. Fifty-nine percent of patients experienced ES during daytime hours ( P <0.001). The prevalence of ES was significantly higher during workdays, with Saturdays and Sundays registering the lowest rates of ES (10.4% and 7.2%, respectively, versus 16.5% daily mean from Monday to Friday; P <0.001). ES occurrence was significantly associated with increased monthly temperature range when compared with the month before ( P =0.003). ES incidence is not homogenous over time but seems to have a clustered pattern, with a higher incidence during daytime hours and working days. ES is associated with an increase in monthly temperature variation. https://www.crd.york.ac.uk. Unique identifier: CRD42013003744. © 2017 American Heart Association, Inc.

Clustering in Cell Cycle Dynamics with General Response/Signaling Feedback

PubMed Central

Young, Todd R.; Fernandez, Bastien; Buckalew, Richard; Moses, Gregory; Boczko, Erik M.

2011-01-01

Motivated by experimental and theoretical work on autonomous oscillations in yeast, we analyze ordinary differential equations models of large populations of cells with cell-cycle dependent feedback. We assume a particular type of feedback that we call Responsive/Signaling (RS), but do not specify a functional form of the feedback. We study the dynamics and emergent behaviour of solutions, particularly temporal clustering and stability of clustered solutions. We establish the existence of certain periodic clustered solutions as well as “uniform” solutions and add to the evidence that cell-cycle dependent feedback robustly leads to cell-cycle clustering. We highlight the fundamental differences in dynamics between systems with negative and positive feedback. For positive feedback systems the most important mechanism seems to be the stability of individual isolated clusters. On the other hand we find that in negative feedback systems, clusters must interact with each other to reinforce coherence. We conclude from various details of the mathematical analysis that negative feedback is most consistent with observations in yeast experiments. PMID:22001733

Segmentation and clustering as complementary sources of information

NASA Astrophysics Data System (ADS)

Dale, Michael B.; Allison, Lloyd; Dale, Patricia E. R.

2007-03-01

This paper examines the effects of using a segmentation method to identify change-points or edges in vegetation. It identifies coherence (spatial or temporal) in place of unconstrained clustering. The segmentation method involves change-point detection along a sequence of observations so that each cluster formed is composed of adjacent samples; this is a form of constrained clustering. The protocol identifies one or more models, one for each section identified, and the quality of each is assessed using a minimum message length criterion, which provides a rational basis for selecting an appropriate model. Although the segmentation is less efficient than clustering, it does provide other information because it incorporates textural similarity as well as homogeneity. In addition it can be useful in determining various scales of variation that may apply to the data, providing a general method of small-scale pattern analysis.

Cluster headache: present and future therapy.

PubMed

Leone, Massimo; Giustiniani, Alessandro; Cecchini, Alberto Proietti

2017-05-01

Cluster headache is characterized by severe, unilateral headache attacks of orbital, supraorbital or temporal pain lasting 15-180 min accompanied by ipsilateral lacrimation, rhinorrhea and other cranial autonomic manifestations. Cluster headache attacks need fast-acting abortive agents because the pain peaks very quickly; sumatriptan injection is the gold standard acute treatment. First-line preventative drugs include verapamil and carbolithium. Other drugs demonstrated effective in open trials include topiramate, valproic acid, gabapentin and others. Steroids are very effective; local injection in the occipital area is also effective but its prolonged use needs caution. Monoclonal antibodies against calcitonin gene-related peptide are under investigation as prophylactic agents in both episodic and chronic cluster headache. A number of neurostimulation procedures including occipital nerve stimulation, vagus nerve stimulation, sphenopalatine ganglion stimulation and the more invasive hypothalamic stimulation are employed in chronic intractable cluster headache.

An investigation on thermal patterns in Iran based on spatial autocorrelation

NASA Astrophysics Data System (ADS)

Fallah Ghalhari, Gholamabbas; Dadashi Roudbari, Abbasali

2018-02-01

The present study aimed at investigating temporal-spatial patterns and monthly patterns of temperature in Iran using new spatial statistical methods such as cluster and outlier analysis, and hotspot analysis. To do so, climatic parameters, monthly average temperature of 122 synoptic stations, were assessed. Statistical analysis showed that January with 120.75% had the most fluctuation among the studied months. Global Moran's Index revealed that yearly changes of temperature in Iran followed a strong spatially clustered pattern. Findings showed that the biggest thermal cluster pattern in Iran, 0.975388, occurred in May. Cluster and outlier analyses showed that thermal homogeneity in Iran decreases in cold months, while it increases in warm months. This is due to the radiation angle and synoptic systems which strongly influence thermal order in Iran. The elevations, however, have the most notable part proved by Geographically weighted regression model. Iran's thermal analysis through hotspot showed that hot thermal patterns (very hot, hot, and semi-hot) were dominant in the South, covering an area of 33.5% (about 552,145.3 km2). Regions such as mountain foot and low lands lack any significant spatial autocorrelation, 25.2% covering about 415,345.1 km2. The last is the cold thermal area (very cold, cold, and semi-cold) with about 25.2% covering about 552,145.3 km2 of the whole area of Iran.

Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China

PubMed Central

Bao, Changjun; Hu, Jianli; Liu, Wendong; Liang, Qi; Wu, Ying; Norris, Jessie; Peng, Zhihang; Yu, Rongbin; Shen, Hongbing; Chen, Feng

2014-01-01

Objective This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. Methods County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. Results The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province. Conclusion Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time. PMID:24416167

Hot spot detection and spatio-temporal dispersion of dengue fever in Hanoi, Vietnam

PubMed Central

Toan, Do Thi Thanh; Hu, Wenbiao; Thai, Pham Quang; Hoat, Luu Ngoc; Wright, Pamela; Martens, Pim

2013-01-01

Introduction Dengue fever (DF) in Vietnam remains a serious emerging arboviral disease, which generates significant concerns among international health authorities. Incidence rates of DF have increased significantly during the last few years in many provinces and cities, especially Hanoi. The purpose of this study was to detect DF hot spots and identify the disease dynamics dispersion of DF over the period between 2004 and 2009 in Hanoi, Vietnam. Methods Daily data on DF cases and population data for each postcode area of Hanoi between January 1998 and December 2009 were obtained from the Hanoi Center for Preventive Health and the General Statistic Office of Vietnam. Moran's I statistic was used to assess the spatial autocorrelation of reported DF. Spatial scan statistics and logistic regression were used to identify space–time clusters and dispersion of DF. Results The study revealed a clear trend of geographic expansion of DF transmission in Hanoi through the study periods (OR 1.17, 95% CI 1.02–1.34). The spatial scan statistics showed that 6/14 (42.9%) districts in Hanoi had significant cluster patterns, which lasted 29 days and were limited to a radius of 1,000 m. The study also demonstrated that most DF cases occurred between June and November, during which the rainfall and temperatures are highest. Conclusions There is evidence for the existence of statistically significant clusters of DF in Hanoi, and that the geographical distribution of DF has expanded over recent years. This finding provides a foundation for further investigation into the social and environmental factors responsible for changing disease patterns, and provides data to inform program planning for DF control. PMID:23364076

Hot spot detection and spatio-temporal dispersion of dengue fever in Hanoi, Vietnam.

PubMed

Toan, Do Thi Thanh; Hu, Wenbiao; Quang Thai, Pham; Hoat, Luu Ngoc; Wright, Pamela; Martens, Pim

2013-01-24

Dengue fever (DF) in Vietnam remains a serious emerging arboviral disease, which generates significant concerns among international health authorities. Incidence rates of DF have increased significantly during the last few years in many provinces and cities, especially Hanoi. The purpose of this study was to detect DF hot spots and identify the disease dynamics dispersion of DF over the period between 2004 and 2009 in Hanoi, Vietnam. Daily data on DF cases and population data for each postcode area of Hanoi between January 1998 and December 2009 were obtained from the Hanoi Center for Preventive Health and the General Statistic Office of Vietnam. Moran's I statistic was used to assess the spatial autocorrelation of reported DF. Spatial scan statistics and logistic regression were used to identify space-time clusters and dispersion of DF. The study revealed a clear trend of geographic expansion of DF transmission in Hanoi through the study periods (OR 1.17, 95% CI 1.02-1.34). The spatial scan statistics showed that 6/14 (42.9%) districts in Hanoi had significant cluster patterns, which lasted 29 days and were limited to a radius of 1,000 m. The study also demonstrated that most DF cases occurred between June and November, during which the rainfall and temperatures are highest. There is evidence for the existence of statistically significant clusters of DF in Hanoi, and that the geographical distribution of DF has expanded over recent years. This finding provides a foundation for further investigation into the social and environmental factors responsible for changing disease patterns, and provides data to inform program planning for DF control.

Regional gray matter density associated with emotional intelligence: evidence from voxel-based morphometry.

PubMed

Takeuchi, Hikaru; Taki, Yasuyuki; Sassa, Yuko; Hashizume, Hiroshi; Sekiguchi, Atsushi; Fukushima, Ai; Kawashima, Ryuta

2011-09-01

Emotional Intelligence (EI) is the ability to monitor one's own and others' emotions and the ability to use the gathered information to guide one's thinking and action. EI is thought to be important for social life making it a popular subject of research. However, despite the existence of previous functional imaging studies on EI, the relationship between regional gray matter morphology and EI has never been investigated. We used voxel-based morphometry (VBM) and a questionnaire (Emotional Intelligence Scale) to measure EI to identify the gray matter correlates of each factor of individual EI (Intrapersonal factor, Interpersonal factor, Situation Management factor). We found significant negative relationships between the Intrapersonal factor and regional gray matter density (rGMD) (1-a) in an anatomical cluster that included the right anterior insula, (1-b) in the right cerebellum, (1-c) in an anatomical cluster that extends from the cuneus to the precuneus, (1-d) and in an anatomical cluster that extends from the medial prefrontal cortex to the left lateral fronto-polar cortex. We also found significant positive correlations between the Interpersonal factor and rGMD in the right superior temporal sulcus, and significant negative correlations between the Situation Management factor and rGMD in the ventromedial prefrontal cortex. These findings suggest that each factor of EI in healthy young people is related to the specific brain regions known to be involved in the networks of social cognition and self-related recognition, and in the somatic marker circuitry. Copyright © 2010 Wiley-Liss, Inc.

Spatial and Temporal Pattern of Rift Valley Fever Outbreaks in Tanzania; 1930 to 2007

PubMed Central

Sindato, Calvin; Karimuribo, Esron D.; Pfeiffer, Dirk U.; Mboera, Leonard E. G.; Kivaria, Fredrick; Dautu, George; Bernard, Bett; Paweska, Janusz T.

2014-01-01

Background Rift Valley fever (RVF)-like disease was first reported in Tanzania more than eight decades ago and the last large outbreak of the disease occurred in 2006–07. This study investigates the spatial and temporal pattern of RVF outbreaks in Tanzania over the past 80 years in order to guide prevention and control strategies. Materials and Methods A retrospective study was carried out based on disease reporting data from Tanzania at district or village level. The data were sourced from the Ministries responsible for livestock and human health, Tanzania Meteorological Agency and research institutions involved in RVF surveillance and diagnosis. The spatial distribution of outbreaks was mapped using ArcGIS 10. The space-time permutation model was applied to identify clusters of cases, and a multivariable logistic regression model was used to identify risk factors associated with the occurrence of outbreaks in the district. Principal Findings RVF outbreaks were reported between December and June in 1930, 1947, 1957, 1960, 1963, 1968, 1977–79, 1989, 1997–98 and 2006–07 in 39.2% of the districts in Tanzania. There was statistically significant spatio-temporal clustering of outbreaks. RVF occurrence was associated with the eastern Rift Valley ecosystem (OR = 6.14, CI: 1.96, 19.28), total amount of rainfall of >405.4 mm (OR = 12.36, CI: 3.06, 49.88), soil texture (clay [OR = 8.76, CI: 2.52, 30.50], and loam [OR = 8.79, CI: 2.04, 37.82]). Conclusion/Significance RVF outbreaks were found to be distributed heterogeneously and transmission dynamics appeared to vary between areas. The sequence of outbreak waves, continuously cover more parts of the country. Whenever infection has been introduced into an area, it is likely to be involved in future outbreaks. The cases were more likely to be reported from the eastern Rift Valley than from the western Rift Valley ecosystem and from areas with clay and loam rather than sandy soil texture. PMID:24586433

Temporal trends (1977-2007) and ethnic inequity in child mortality in rural villages of southern Guinea Bissau.

PubMed

Fazzio, Ila; Mann, Vera; Boone, Peter

2011-09-02

Guinea Bissau is one of the poorest countries in the world, with one of the highest under-5 mortality rate. Despite its importance for policy planning, data on child mortality are often not available or of poor quality in low-income countries like Guinea Bissau. Our aim in this study was to use the baseline survey to estimate child mortality in rural villages in southern Guinea Bissau for a 30 years period prior to a planned cluster randomised intervention. We aimed to investigate temporal trends with emphasis on historical events and the effect of ethnicity, polygyny and distance to the health centre on child mortality. A baseline survey was conducted prior to a planned cluster randomised intervention to estimate child mortality in 241 rural villages in southern Guinea Bissau between 1977 and 2007. Crude child mortality rates were estimated by Kaplan-Meier method from birth history of 7854 women. Cox regression models were used to investigate the effects of birth periods with emphasis on historical events, ethnicity, polygyny and distance to the health centre on child mortality. High levels of child mortality were found at all ages under five with a significant reduction in child mortality over the time periods of birth except for 1997-2001. That period comprises the 1998/99 civil war interval, when child mortality was 1.5% higher than in the previous period. Children of Balanta ethnic group had higher hazard of dying under five years of age than children from other groups until 2001. Between 2002 and 2007, Fula children showed the highest mortality. Increasing walking distance to the nearest health centre increased the hazard, though not substantially, and polygyny had a negligible and statistically not significant effect on the hazard. Child mortality is strongly associated with ethnicity and it should be considered in health policy planning. Child mortality, though considerably decreased during the past 30 years, remains high in rural Guinea Bissau. Temporal trends also suggest that civil wars have detrimental effects on child mortality. Current Controlled Trials ISRCTN52433336.

Spatial and temporal analyses of metrics of tuberculosis infection in badgers (Meles meles) from the Republic of Ireland: Trends in apparent prevalence.

PubMed

Byrne, A W; Kenny, K; Fogarty, U; O'Keeffe, J J; More, S J; McGrath, G; Teeling, M; Martin, S W; Dohoo, I R

2015-12-01

Badgers are a wildlife host of Mycobacterium bovis, the causative agent of bovine tuberculosis (bTB), and an important contributor to the epidemiology of bTB in cattle in Ireland and Britain. Repeated culling of badgers in high prevalence cattle bTB areas has been used in the Republic of Ireland as one tool to reduce intra- and interspecific transmission of M. bovis. We assessed factors that influenced infection prevalence of culled badgers from 2009 to 2012 (n=4948) where spatial, temporal and intrinsic factor data were available using multivariable modelling. Prevalence appeared higher in western areas than eastern areas of Ireland and badgers were more likely to be test-positive if caught at a sett (burrow system) which was close to other infected setts (spatial clustering of infection). There was a significant positive association between badger test-status and cattle prevalence of M. bovis infection at a spatial scale of 1km around setts. Badgers were more likely to be deemed test positive if they were male (OR: 1.9) or a parous female (OR: 1.7), compared to a female who had never conceived. Our results are consistent with different groups within badger populations having differential exposures and therefore infection risk (for example, parous vs. non-parous females). Furthermore, bTB clusters within the badger population, with greater risk to badgers in setts that are closest to other infected setts. The effective scale of the association of bTB risk between badger and cattle populations may be relatively large in Ireland. Our data indicate that the overall trend in prevalence of M. bovis infection in badgers has decreased in Ireland (P<0.001) while controlling for significant confounders over the study period, and follows a longer temporal trend from 2007 to 2013, where unadjusted apparent prevalence declined from 26% to 11% during 2007 to mid-2011, followed by a stable trend between 9 and 11% thereafter (n=10,267). Copyright © 2015 Elsevier B.V. All rights reserved.

Improving exposure assessment in environmental epidemiology: Application of spatio-temporal visualization tools

NASA Astrophysics Data System (ADS)

Meliker, Jaymie R.; Slotnick, Melissa J.; Avruskin, Gillian A.; Kaufmann, Andrew; Jacquez, Geoffrey M.; Nriagu, Jerome O.

2005-05-01

A thorough assessment of human exposure to environmental agents should incorporate mobility patterns and temporal changes in human behaviors and concentrations of contaminants; yet the temporal dimension is often under-emphasized in exposure assessment endeavors, due in part to insufficient tools for visualizing and examining temporal datasets. Spatio-temporal visualization tools are valuable for integrating a temporal component, thus allowing for examination of continuous exposure histories in environmental epidemiologic investigations. An application of these tools to a bladder cancer case-control study in Michigan illustrates continuous exposure life-lines and maps that display smooth, continuous changes over time. Preliminary results suggest increased risk of bladder cancer from combined exposure to arsenic in drinking water (>25 μg/day) and heavy smoking (>30 cigarettes/day) in the 1970s and 1980s, and a possible cancer cluster around automotive, paint, and organic chemical industries in the early 1970s. These tools have broad application for examining spatially- and temporally-specific relationships between exposures to environmental risk factors and disease.

Hunting for origins of migraine pain: cluster analysis of spontaneous and capsaicin-induced firing in meningeal trigeminal nerve fibers

PubMed Central

Zakharov, A.; Vitale, C.; Kilinc, E.; Koroleva, K.; Fayuk, D.; Shelukhina, I.; Naumenko, N.; Skorinkin, A.; Khazipov, R.; Giniatullin, R.

2015-01-01

Trigeminal nerves in meninges are implicated in generation of nociceptive firing underlying migraine pain. However, the neurochemical mechanisms of nociceptive firing in meningeal trigeminal nerves are little understood. In this study, using suction electrode recordings from peripheral branches of the trigeminal nerve in isolated rat meninges, we analyzed spontaneous and capsaicin-induced orthodromic spiking activity. In control, biphasic single spikes with variable amplitude and shapes were observed. Application of the transient receptor potential vanilloid 1 (TRPV1) agonist capsaicin to meninges dramatically increased firing whereas the amplitudes and shapes of spikes remained essentially unchanged. This effect was antagonized by the specific TRPV1 antagonist capsazepine. Using the clustering approach, several groups of uniform spikes (clusters) were identified. The clustering approach combined with capsaicin application allowed us to detect and to distinguish “responder” (65%) from “non-responder” clusters (35%). Notably, responders fired spikes at frequencies exceeding 10 Hz, high enough to provide postsynaptic temporal summation of excitation at brainstem and spinal cord level. Almost all spikes were suppressed by tetrodotoxin (TTX) suggesting an involvement of the TTX-sensitive sodium channels in nociceptive signaling at the peripheral branches of trigeminal neurons. Our analysis also identified transient (desensitizing) and long-lasting (slowly desensitizing) responses to the continuous application of capsaicin. Thus, the persistent activation of nociceptors in capsaicin-sensitive nerve fibers shown here may be involved in trigeminal pain signaling and plasticity along with the release of migraine-related neuropeptides from TRPV1 positive neurons. Furthermore, cluster analysis could be widely used to characterize the temporal and neurochemical profiles of other pain transducers likely implicated in migraine. PMID:26283923

Multi-scale visual analysis of time-varying electrocorticography data via clustering of brain regions

DOE PAGES

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward; ...

2017-06-06

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

A cluster of immunoresolvents links coagulation to innate host defense in human blood.

PubMed

Norris, Paul C; Libreros, Stephania; Chiang, Nan; Serhan, Charles N

2017-08-01

Blood coagulation is a protective response that prevents excessive bleeding upon blood vessel injury. We investigated the relationship between coagulation and the resolution of inflammation and infection by lipid mediators (LMs) through metabololipidomics-based profiling of human whole blood (WB) during coagulation. We identified temporal clusters of endogenously produced prothrombotic and proinflammatory LMs (eicosanoids), as well as specialized proresolving mediators (SPMs). In addition to eicosanoids, a specific SPM cluster was identified that consisted of resolvin E1 (RvE1), RvD1, RvD5, lipoxin B 4 , and maresin 1, each of which was present at bioactive concentrations (0.1 to 1 nM). Removal of adenosine from the coagulating blood markedly enhanced the amounts of SPMs produced and further increased the biosynthesis of RvD3, RvD4, and RvD6. The cyclooxygenase inhibitors celecoxib and indomethacin, which block the production of thromboxanes and prostanoids, did not block the production of clot-driven SPMs. Unbiased mass cytometry analysis demonstrated that the SPM cluster produced in human blood targeted leukocytes at the single-cell level, directly activating ERK and CREB signaling in neutrophils and CD14 + monocytes. Treatment of human WB with the components of this SPM cluster enhanced both the phagocytosis and killing of Escherichia coli by leukocytes. Together, these data identify a proresolving LM circuit, including endogenous molecular brakes and accelerators, which promoted host defense. These temporal LM-SPM clusters can provide accessible metabolomic profiles for precision and personalized medicine. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Quantifying temporal bone morphology of great apes and humans: an approach using geometric morphometrics.

PubMed

Lockwood, Charles A; Lynch, John M; Kimbel, William H

2002-12-01

The hominid temporal bone offers a complex array of morphology that is linked to several different functional systems. Its frequent preservation in the fossil record gives the temporal bone added significance in the study of human evolution, but its morphology has proven difficult to quantify. In this study we use techniques of 3D geometric morphometrics to quantify differences among humans and great apes and discuss the results in a phylogenetic context. Twenty-three landmarks on the ectocranial surface of the temporal bone provide a high level of anatomical detail. Generalized Procrustes analysis (GPA) is used to register (adjust for position, orientation and scale) landmark data from 405 adults representing Homo, Pan, Gorilla and Pongo. Principal components analysis of residuals from the GPA shows that the major source of variation is between humans and apes. Human characteristics such as a coronally orientated petrous axis, a deep mandibular fossa, a projecting mastoid process, and reduced lateral extension of the tympanic element strongly impact the analysis. In phenetic cluster analyses, gorillas and orangutans group together with respect to chimpanzees, and all apes group together with respect to humans. Thus, the analysis contradicts depictions of African apes as a single morphotype. Gorillas and orangutans lack the extensive preglenoid surface of chimpanzees, and their mastoid processes are less medially inflected. These and other characters shared by gorillas and orangutans are probably primitive for the African hominid clade.

Spatial-Temporal Modeling of Neighborhood Sociodemographic Characteristics and Food Stores

PubMed Central

Lamichhane, Archana P.; Warren, Joshua L.; Peterson, Marc; Rummo, Pasquale; Gordon-Larsen, Penny

2015-01-01

The literature on food stores, neighborhood poverty, and race/ethnicity is mixed and lacks methods of accounting for complex spatial and temporal clustering of food resources. We used quarterly data on supermarket and convenience store locations from Nielsen TDLinx (Nielsen Holdings N.V., New York, New York) spanning 7 years (2006–2012) and census tract-based neighborhood sociodemographic data from the American Community Survey (2006–2010) to assess associations between neighborhood sociodemographic characteristics and food store distributions in the Metropolitan Statistical Areas (MSAs) of 4 US cities (Birmingham, Alabama; Chicago, Illinois; Minneapolis, Minnesota; and San Francisco, California). We fitted a space-time Poisson regression model that accounted for the complex spatial-temporal correlation structure of store locations by introducing space-time random effects in an intrinsic conditionally autoregressive model within a Bayesian framework. After accounting for census tract–level area, population, their interaction, and spatial and temporal variability, census tract poverty was significantly and positively associated with increasing expected numbers of supermarkets among tracts in all 4 MSAs. A similar positive association was observed for convenience stores in Birmingham, Minneapolis, and San Francisco; in Chicago, a positive association was observed only for predominantly white and predominantly black tracts. Our findings suggest a positive association between greater numbers of food stores and higher neighborhood poverty, with implications for policy approaches related to food store access by neighborhood poverty. PMID:25515169

Temporal and micro-spatial heterogeneity in the distribution of Anopheles vectors of malaria along the Kenyan coast

PubMed Central

2013-01-01

Background The distribution of anopheline mosquitoes is determined by temporally dynamic environmental and human-associated variables, operating over a range of spatial scales. Macro-spatial short-term trends are driven predominantly by prior (lagged) seasonal changes in climate, which regulate the abundance of suitable aquatic larval habitats. Micro-spatial distribution is determined by the location of these habitats, proximity and abundance of available human bloodmeals and prevailing micro-climatic conditions. The challenge of analysing—in a single coherent statistical framework—the lagged and distributed effect of seasonal climate changes simultaneously with the effects of an underlying hierarchy of spatial factors has hitherto not been addressed. Methods Data on Anopheles gambiae sensu stricto and A. funestus collected from households in Kilifi district, Kenya, were analysed using polynomial distributed lag generalized linear mixed models (PDL GLMMs). Results Anopheline density was positively and significantly associated with amount of rainfall between 4 to 47 days, negatively and significantly associated with maximum daily temperature between 5 and 35 days, and positively and significantly associated with maximum daily temperature between 29 and 48 days in the past (depending on Anopheles species). Multiple-occupancy households harboured greater mosquito numbers than single-occupancy households. A significant degree of mosquito clustering within households was identified. Conclusions The PDL GLMMs developed here represent a generalizable framework for analysing hierarchically-structured data in combination with explanatory variables which elicit lagged effects. The framework is a valuable tool for facilitating detailed understanding of determinants of the spatio-temporal distribution of Anopheles. Such understanding facilitates delivery of targeted, cost-effective and, in certain circumstances, preventative antivectorial interventions against malaria. PMID:24330615

A novel sub-shot segmentation method for user-generated video

NASA Astrophysics Data System (ADS)

Lei, Zhuo; Zhang, Qian; Zheng, Chi; Qiu, Guoping

2018-04-01

With the proliferation of the user-generated videos, temporal segmentation is becoming a challengeable problem. Traditional video temporal segmentation methods like shot detection are not able to work on unedited user-generated videos, since they often only contain one single long shot. We propose a novel temporal segmentation framework for user-generated video. It finds similar frames with a tree partitioning min-Hash technique, constructs sparse temporal constrained affinity sub-graphs, and finally divides the video into sub-shot-level segments with a dense-neighbor-based clustering method. Experimental results show that our approach outperforms all the other related works. Furthermore, it is indicated that the proposed approach is able to segment user-generated videos at an average human level.

Typhoid Fever and Its Association with Environmental Factors in the Dhaka Metropolitan Area of Bangladesh: A Spatial and Time-Series Approach

PubMed Central

Dewan, Ashraf M.; Corner, Robert; Hashizume, Masahiro; Ongee, Emmanuel T.

2013-01-01

Typhoid fever is a major cause of death worldwide with a major part of the disease burden in developing regions such as the Indian sub-continent. Bangladesh is part of this highly endemic region, yet little is known about the spatial and temporal distribution of the disease at a regional scale. This research used a Geographic Information System to explore, spatially and temporally, the prevalence of typhoid in Dhaka Metropolitan Area (DMA) of Bangladesh over the period 2005–9. This paper provides the first study of the spatio-temporal epidemiology of typhoid for this region. The aims of the study were: (i) to analyse the epidemiology of cases from 2005 to 2009; (ii) to identify spatial patterns of infection based on two spatial hypotheses; and (iii) to determine the hydro-climatological factors associated with typhoid prevalence. Case occurrences data were collected from 11 major hospitals in DMA, geocoded to census tract level, and used in a spatio-temporal analysis with a range of demographic, environmental and meteorological variables. Analyses revealed distinct seasonality as well as age and gender differences, with males and very young children being disproportionately infected. The male-female ratio of typhoid cases was found to be 1.36, and the median age of the cases was 14 years. Typhoid incidence was higher in male population than female (χ2 = 5.88, p<0.05). The age-specific incidence rate was highest for the 0–4 years age group (277 cases), followed by the 60+ years age group (51 cases), then there were 45 cases for 15–17 years, 37 cases for 18–34 years, 34 cases for 35–39 years and 11 cases for 10–14 years per 100,000 people. Monsoon months had the highest disease occurrences (44.62%) followed by the pre-monsoon (30.54%) and post-monsoon (24.85%) season. The Student's t test revealed that there is no significant difference on the occurrence of typhoid between urban and rural environments (p>0.05). A statistically significant inverse association was found between typhoid incidence and distance to major waterbodies. Spatial pattern analysis showed that there was a significant clustering of typhoid distribution in the study area. Moran's I was highest (0.879; p<0.01) in 2008 and lowest (0.075; p<0.05) in 2009. Incidence rates were found to form three large, multi-centred, spatial clusters with no significant difference between urban and rural rates. Temporally, typhoid incidence was seen to increase with temperature, rainfall and river level at time lags ranging from three to five weeks. For example, for a 0.1 metre rise in river levels, the number of typhoid cases increased by 4.6% (95% CI: 2.4–2.8) above the threshold of 4.0 metres (95% CI: 2.4–4.3). On the other hand, with a 1°C rise in temperature, the number of typhoid cases could increase by 14.2% (95% CI: 4.4–25.0). PMID:23359825

[Spatio-temporal process and the influencing factors on influenza A (H1N1) pandemic in Changsha].

PubMed

Xiao, Hong; Tian, Huai-yu; Zhao, Jian; Zhang, Xi-xing; Zhu, Pei-juan; Liu, Ru-chun; Chen, Tian-mu

2011-06-01

To analyze the spatio-temporal process on 2009 influenza A (H1N1) pandemic in Changsha and the influencing factors during the diffusion process. Data were from the following 5 sources, influenza A (H1N1) pandemic gathered in 2009, Geographic Information System (GIS) of Changsha, the broad range of theorems and techniques of hot spot analysis, spatio-temporal process analysis and Spearman correlation analysis. Hot spot areas appeared to be more in the economically developed areas, such as cities and townships. The cluster of spatial-temporal distribution of influenza A (H1N1) pandemic was most likely appearing in Liuyang city (RR = 22.70, P < 0.01). The secondary cluster would include districts as Yuelu (RR = 6.49, P < 0.01), Yuhua (RR = 81.63, P < 0.01). Xingsha township appeared as the center in the Changsha county (RR = 2.90, P < 0.01) while townships as Yutangping (RR = 19.31, P < 0.01), Chengjiao (RR = 73.14, P < 0.01) and Longtian appeared as the center in the west of Ningxiang county (RR = 14.43, P < 0.01) and Wushan as the center in the Wangcheng county (RR = 13.84, P < 0.01). As time went on, the epidemic moved towards the eastern and more developed regions. Regarding factor analysis, population, the amount of students, geographic relationship and business activities etc. appeared to be the key elements influencing the transmission of influenza A (H1N1) pandemic. At the beginning of the epidemic, population density served as the main factor (r = 0.477, P < 0.05) but during the initial and fast growing stages, it was replaced by the size of students to serve as the important indicator (r = 0.831, P < 0.01; r = 0.518, P < 0.01). However, during the peak of the epidemics, the business activities played an important role (r = -0.676, P < 0.01). Groups under high risk and districts with high incidence rates were shifting, along with the temporal process of influenza A (H1N1) pandemic, suggesting that the protection measures need to be adjusted, according to the significance of influencing factors at different stages.

Monogenetic Volcano Clusters within the wider Michoacán-Guanajuato Volcanic Field (México) and their Significance

NASA Astrophysics Data System (ADS)

Siebe, C.

2017-12-01

The Trans-Mexican Volcanic Belt, one of the most complex and active continental arcs worldwide, displays several volcanic fields dominated by monogenetic volcanoes. Of these, the Plio-Quaternary Michoacán-Guanajuato Volcanic Field (MGVF) situated in central Mexico, is the largest monogenetic volcanic field in the world and includes more than 1000 scoria cones and associated lava flows and about 400 medium-sized volcanoes (Mexican shields). The smaller monogenetic vents occur either isolated or form small clusters within the wider MGVF. The recent identification of small clusters comprising several monogenetic volcanoes that erupted in a sequence of geologically short time intervals (hundreds to few thousands of years) in small areas within the much wider MGVF opens several questions in regard to future volcanic hazard assessments in this region: Are the youngest (Holocene) clusters still "active" and is a new eruption likely to occur within their surroundings? How long are such clusters "active"? Will the next monogenetic eruption in the MGVF be a single short-lived isolated eruption, or the beginning of a cluster? Furthermore, is it possible that the historic eruptions of Jorullo (1759) and Paricutin (1943) represent each the beginning of a cluster and should a new eruption in their proximity be expected in the future? In order to address these questions, two Holocene clusters, namely Tacámbaro and Malpaís de Zacapu are currently under study and preliminary results will be presented. Each comprises four monogenetic vents that erupted in a sequence of geologically short time intervals (hundreds to few thousands of years) within a small area (few tens of km2) Geologic mapping, geochemical analyses, radiometric dating, and paleomagnetic studies will help to establish the sequence of eruption of the different vents, and shed more light on the conditions that allow several magma sources to be formed and then tapped in close temporal and spatial proximity to each other and produce such small "flare-ups".

Integrating Data Clustering and Visualization for the Analysis of 3D Gene Expression Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Data Analysis and Visualization; nternational Research Training Group ``Visualization of Large and Unstructured Data Sets,'' University of Kaiserslautern, Germany; Computational Research Division, Lawrence Berkeley National Laboratory, One Cyclotron Road, Berkeley, CA 94720, USA

2008-05-12

The recent development of methods for extracting precise measurements of spatial gene expression patterns from three-dimensional (3D) image data opens the way for new analyses of the complex gene regulatory networks controlling animal development. We present an integrated visualization and analysis framework that supports user-guided data clustering to aid exploration of these new complex datasets. The interplay of data visualization and clustering-based data classification leads to improved visualization and enables a more detailed analysis than previously possible. We discuss (i) integration of data clustering and visualization into one framework; (ii) application of data clustering to 3D gene expression data; (iii)more » evaluation of the number of clusters k in the context of 3D gene expression clustering; and (iv) improvement of overall analysis quality via dedicated post-processing of clustering results based on visualization. We discuss the use of this framework to objectively define spatial pattern boundaries and temporal profiles of genes and to analyze how mRNA patterns are controlled by their regulatory transcription factors.« less

Hierarchical Star Formation in Turbulent Media: Evidence from Young Star Clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grasha, K.; Calzetti, D.; Elmegreen, B. G.

We present an analysis of the positions and ages of young star clusters in eight local galaxies to investigate the connection between the age difference and separation of cluster pairs. We find that star clusters do not form uniformly but instead are distributed so that the age difference increases with the cluster pair separation to the 0.25–0.6 power, and that the maximum size over which star formation is physically correlated ranges from ∼200 pc to ∼1 kpc. The observed trends between age difference and separation suggest that cluster formation is hierarchical both in space and time: clusters that are closemore » to each other are more similar in age than clusters born further apart. The temporal correlations between stellar aggregates have slopes that are consistent with predictions of turbulence acting as the primary driver of star formation. The velocity associated with the maximum size is proportional to the galaxy’s shear, suggesting that the galactic environment influences the maximum size of the star-forming structures.« less

Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran.

PubMed

Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

2016-01-01

HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug networks and mass migration of Afghan refugees and labours to Iran, which calls for extensive preventive efforts.

Spatio-Temporal History of HIV-1 CRF35_AD in Afghanistan and Iran

PubMed Central

Eybpoosh, Sana; Bahrampour, Abbas; Karamouzian, Mohammad; Azadmanesh, Kayhan; Jahanbakhsh, Fatemeh; Mostafavi, Ehsan; Zolala, Farzaneh; Haghdoost, Ali Akbar

2016-01-01

HIV-1 Circulating Recombinant Form 35_AD (CRF35_AD) has an important position in the epidemiological profile of Afghanistan and Iran. Despite the presence of this clade in Afghanistan and Iran for over a decade, our understanding of its origin and dissemination patterns is limited. In this study, we performed a Bayesian phylogeographic analysis to reconstruct the spatio-temporal dispersion pattern of this clade using eligible CRF35_AD gag and pol sequences available in the Los Alamos HIV database (432 sequences available from Iran, 16 sequences available from Afghanistan, and a single CRF35_AD-like pol sequence available from USA). Bayesian Markov Chain Monte Carlo algorithm was implemented in BEAST v1.8.1. Between-country dispersion rates were tested with Bayesian stochastic search variable selection method and were considered significant where Bayes factor values were greater than three. The findings suggested that CRF35_AD sequences were genetically similar to parental sequences from Kenya and Uganda, and to a set of subtype A1 sequences available from Afghan refugees living in Pakistan. Our results also showed that across all phylogenies, Afghan and Iranian CRF35_AD sequences formed a monophyletic cluster (posterior clade credibility> 0.7). The divergence date of this cluster was estimated to be between 1990 and 1992. Within this cluster, a bidirectional dispersion of the virus was observed across Afghanistan and Iran. We could not clearly identify if Afghanistan or Iran first established or received this epidemic, as the root location of this cluster could not be robustly estimated. Three CRF35_AD sequences from Afghan refugees living in Pakistan nested among Afghan and Iranian CRF35_AD branches. However, the CRF35_AD-like sequence available from USA diverged independently from Kenyan subtype A1 sequences, suggesting it not to be a true CRF35_AD lineage. Potential factors contributing to viral exchange between Afghanistan and Iran could be injection drug networks and mass migration of Afghan refugees and labours to Iran, which calls for extensive preventive efforts. PMID:27280293

Space and space-time distributions of dengue in a hyper-endemic urban space: the case of Girardot, Colombia.

PubMed

Fuentes-Vallejo, Mauricio

2017-07-24

Dengue is a widely spread vector-borne disease. Dengue cases in the Americas have increased over the last few decades, affecting various urban spaces throughout these continents, including the tourism-oriented city of Girardot, Colombia. Interactions among mosquitoes, pathogens and humans have recently been examined using different temporal and spatial scales in attempts to determine the roles that social and ecological systems play in dengue transmission. The current work characterizes the spatial and temporal behaviours of dengue in Girardot and discusses the potential territorial dynamics related to the distribution of this disease. Based on officially reported dengue cases (2012-2015) corresponding to epidemic (2013) and inter-epidemic years (2012, 2014, 2015), space (Getis-Ord index) and space-time (Kulldorff's scan statistics) analyses were performed. Geocoded dengue cases (n = 2027) were slightly overrepresented by men (52.1%). As expected, the cases were concentrated in the 0- to 15-year-old age group according to the actual trends of Colombia. The incidence rates of dengue during the rainy and dry seasons as well as those for individual years (2012, 2013 and 2014) were significant using the global Getis-Ord index. Local clusters shifted across seasons and years; nevertheless, the incidence rates clustered towards the southwest region of the city under different residential conditions. Space-time clusters shifted from the northeast to the southwest of the city (2012-2014). These clusters represented only 4.25% of the total cases over the same period (n = 1623). A general trend was observed, in which dengue cases increased during the dry seasons, especially between December and February. Despite study limitations related to official dengue records and available fine-scale demographic information, the spatial analysis results were promising from a geography of health perspective. Dengue did not show linear association with poverty or with vulnerable peripheral spaces in intra-urban settings, supporting the idea that the pathogenic complex of dengue is driven by different factors. A coordinated collaboration of epidemiological, public health and social science expertise is needed to assess the effect of "place" from a relational perspective in which geography has an important role to play.

Evidence of Increased Antibiotic Resistance in Phylogenetically-Diverse Aeromonas Isolates from Semi-Intensive Fish Ponds Treated with Antibiotics.

PubMed

Patil, Hemant J; Benet-Perelberg, Ayana; Naor, Alon; Smirnov, Margarita; Ofek, Tamir; Nasser, Ahmed; Minz, Dror; Cytryn, Eddie

2016-01-01

The genus Aeromonas is ubiquitous in aquatic environments encompassing a broad range of fish and human pathogens. Aeromonas strains are known for their enhanced capacity to acquire and exchange antibiotic resistance genes and therefore, are frequently targeted as indicator bacteria for monitoring antimicrobial resistance in aquatic environments. This study evaluated temporal trends in Aeromonas diversity and antibiotic resistance in two adjacent semi-intensive aquaculture facilities to ascertain the effects of antibiotic treatment on antimicrobial resistance. In the first facility, sulfadiazine-trimethoprim was added prophylactically to fingerling stocks and water column-associated Aeromonas were monitored periodically over an 11-month fish fattening cycle to assess temporal dynamics in taxonomy and antibiotic resistance. In the second facility, Aeromonas were isolated from fish skin ulcers sampled over a 3-year period and from pond water samples to assess associations between pathogenic strains to those in the water column. A total of 1200 Aeromonas isolates were initially screened for sulfadiazine resistance and further screened against five additional antimicrobials. In both facilities, strong correlations were observed between sulfadiazine resistance and trimethoprim and tetracycline resistances, whereas correlations between sulfadiazine resistance and ceftriaxone, gentamicin, and chloramphenicol resistances were low. Multidrug resistant strains as well as sul1, tetA , and intI1 gene-harboring strains were significantly higher in profiles sampled during the fish cycle than those isolated prior to stocking and these genes were extremely abundant in the pathogenic strains. Five phylogenetically distinct Aeromonas clusters were identified using partial rpoD gene sequence analysis. Interestingly, prior to fingerling stocking the diversity of water column strains was high, and representatives from all five clusters were identified, including an A. salmonicida cluster that harbored all characterized fish skin ulcer samples. Subsequent to stocking, diversity was much lower and most water column isolates in both facilities segregated into an A. veronii -associated cluster. This study demonstrated a strong correlation between aquaculture, Aeromonas diversity and antibiotic resistance. It provides strong evidence for linkage between prophylactic and systemic use of antibiotics in aquaculture and the propagation of antibiotic resistance.

Evidence of Increased Antibiotic Resistance in Phylogenetically-Diverse Aeromonas Isolates from Semi-Intensive Fish Ponds Treated with Antibiotics

PubMed Central

Patil, Hemant J.; Benet-Perelberg, Ayana; Naor, Alon; Smirnov, Margarita; Ofek, Tamir; Nasser, Ahmed; Minz, Dror; Cytryn, Eddie

2016-01-01

The genus Aeromonas is ubiquitous in aquatic environments encompassing a broad range of fish and human pathogens. Aeromonas strains are known for their enhanced capacity to acquire and exchange antibiotic resistance genes and therefore, are frequently targeted as indicator bacteria for monitoring antimicrobial resistance in aquatic environments. This study evaluated temporal trends in Aeromonas diversity and antibiotic resistance in two adjacent semi-intensive aquaculture facilities to ascertain the effects of antibiotic treatment on antimicrobial resistance. In the first facility, sulfadiazine-trimethoprim was added prophylactically to fingerling stocks and water column-associated Aeromonas were monitored periodically over an 11-month fish fattening cycle to assess temporal dynamics in taxonomy and antibiotic resistance. In the second facility, Aeromonas were isolated from fish skin ulcers sampled over a 3-year period and from pond water samples to assess associations between pathogenic strains to those in the water column. A total of 1200 Aeromonas isolates were initially screened for sulfadiazine resistance and further screened against five additional antimicrobials. In both facilities, strong correlations were observed between sulfadiazine resistance and trimethoprim and tetracycline resistances, whereas correlations between sulfadiazine resistance and ceftriaxone, gentamicin, and chloramphenicol resistances were low. Multidrug resistant strains as well as sul1, tetA, and intI1 gene-harboring strains were significantly higher in profiles sampled during the fish cycle than those isolated prior to stocking and these genes were extremely abundant in the pathogenic strains. Five phylogenetically distinct Aeromonas clusters were identified using partial rpoD gene sequence analysis. Interestingly, prior to fingerling stocking the diversity of water column strains was high, and representatives from all five clusters were identified, including an A. salmonicida cluster that harbored all characterized fish skin ulcer samples. Subsequent to stocking, diversity was much lower and most water column isolates in both facilities segregated into an A. veronii-associated cluster. This study demonstrated a strong correlation between aquaculture, Aeromonas diversity and antibiotic resistance. It provides strong evidence for linkage between prophylactic and systemic use of antibiotics in aquaculture and the propagation of antibiotic resistance. PMID:27965628

Phylogeographic analysis of rabies viruses in the Philippines.

PubMed

Tohma, Kentaro; Saito, Mariko; Kamigaki, Taro; Tuason, Laarni T; Demetria, Catalino S; Orbina, Jun Ryan C; Manalo, Daria L; Miranda, Mary E; Noguchi, Akira; Inoue, Satoshi; Suzuki, Akira; Quiambao, Beatriz P; Oshitani, Hitoshi

2014-04-01

Rabies still remains a public health threat in the Philippines. A significant number of human rabies cases, about 200-300 cases annually, have been reported, and the country needs an effective strategy for rabies control. To develop an effective control strategy, it is important to understand the transmission patterns of the rabies viruses. We conducted phylogenetic analyses by considering the temporal and spatial evolution of rabies viruses to reveal the transmission dynamics in the Philippines. After evaluating the molecular clock and phylogeographic analysis, we estimated that the Philippine strains were introduced from China around the beginning of 20th century. Upon this introduction, the rabies viruses evolved within the Philippines to form three major clades, and there was no indication of introduction of other rabies viruses from any other country. However, within the Philippines, island-to-island migrations were observed. Since then, the rabies viruses have diffused and only evolved within each island group. The evolutionary pattern of these viruses was strongly shaped by geographical boundaries. The association index statistics demonstrated a strong spatial structure within the island group, indicating that the seas were a significant geographical barrier for viral dispersal. Strong spatial structure was also observed even at a regional level, and most of the viral migrations (79.7% of the total median number) in Luzon were observed between neighboring regions. Rabies viruses were genetically clustered at a regional level, and this strong spatial structure suggests a geographical clustering of transmission chains and the potential effectiveness of rabies control that targets geographical clustering. Dog vaccination campaigns have been conducted independently by local governments in the Philippines, but it could be more effective to implement a coordinated vaccination campaign among neighboring areas to eliminate geographically-clustered rabies transmission chains. Copyright © 2014 The Authors. Published by Elsevier B.V. All rights reserved.

Lipid-protein interaction induced domains: Kinetics and conformational changes in multicomponent vesicles

NASA Astrophysics Data System (ADS)

Sreeja, K. K.; Sunil Kumar, P. B.

2018-04-01

The spatio-temporal organization of proteins and the associated morphological changes in membranes are of importance in cell signaling. Several mechanisms that promote the aggregation of proteins at low cell surface concentrations have been investigated in the past. We show, using Monte Carlo simulations, that the affinity of proteins for specific lipids can hasten their aggregation kinetics. The lipid membrane is modeled as a dynamically triangulated surface with the proteins defined as in-plane fields at the vertices. We show that, even at low protein concentrations, strong lipid-protein interactions can result in large protein clusters indicating a route to lipid mediated signal amplification. At high protein concentrations, the domains form buds similar to that seen in lipid-lipid interaction induced phase separation. Protein interaction induced domain budding is suppressed when proteins act as anisotropic inclusions and exhibit nematic orientational order. The kinetics of protein clustering and resulting conformational changes are shown to be significantly different for the isotropic and anisotropic curvature inducing proteins.

An Aggregate of Four Anthrax Cases during the Dry Summer of 2011 in Epirus, Greece.

PubMed

Gaitanis, Georgios; Lolis, Christos J; Tsartsarakis, Antonios; Kalogeropoulos, Chris; Leveidiotou-Stefanou, Stamatina; Bartzokas, Aristidis; Bassukas, Ioannis D

2016-01-01

Human anthrax is currently a sporadic disease in Europe, without significant regional clustering. To report an unexpected aggregate of anthrax cases and correlate local climatic factors with yearly anthrax admissions. Clinical description of a geographical-temporal anthrax aggregate, correlation of disease admissions with local weather data in the period 2001-2014 and literature reports of anthrax clusters from Europe in the last 20 years. We identified 5 cases, all cutaneous: an unexpected aggregate of 4 cases in mid-summer 2011 (including a probable human-to-human transmission) and a sporadic case in August 2005, all in relatively dry periods (p < 0.05). Remarkably, 3/6 reports of human anthrax aggregates from Europe were observed in Balkan Peninsula countries in the year 2011. In the light of the predicted climatic change, unexpected anthrax aggregates during dry periods in southern Europe underscore the risk of future anthrax re-emergence on this continent. © 2015 S. Karger AG, Basel.

Temporal and spatial mapping of hand, foot and mouth disease in Sarawak, Malaysia.

PubMed

Sham, Noraishah M; Krishnarajah, Isthrinayagy; Ibrahim, Noor Akma; Lye, Munn-Sann

2014-05-01

Hand, foot and mouth disease (HFMD) is endemic in Sarawak, Malaysia. In this study, a geographical information system (GIS) was used to investigate the relationship between the reported HFMD cases and the spatial patterns in 11 districts of Sarawak from 2006 to 2012. Within this 7-years period, the highest number of reported HFMD cases occurred in 2006, followed by 2012, 2008, 2009, 2007, 2010 and 2011, in descending order. However, while there was no significant distribution pattern or clustering in the first part of the study period (2006 to 2011) based on Moran's I statistic, spatial autocorrelation (P = 0.068) was observed in 2012.

Expression patterns of WRKY genes in di-haploid Populus simonii × P. nigra in response to salinity stress revealed by quantitative real-time PCR and RNA sequencing.

PubMed

Wang, Shengji; Wang, Jiying; Yao, Wenjing; Zhou, Boru; Li, Renhua; Jiang, Tingbo

2014-10-01

Spatio-temporal expression patterns of 13 out of 119 poplar WRKY genes indicated dynamic and tissue-specific roles of WRKY family proteins in salinity stress tolerance. To understand the expression patterns of poplar WRKY genes under salinity stress, 51 of the 119 WRKY genes were selected from di-haploid Populus simonii × P. nigra by quantitative real-time PCR (qRT-PCR). We used qRT-PCR to profile the expression of the top 13 genes under salinity stress across seven time points, and employed RNA-Seq platforms to cross-validate it. Results demonstrated that all the 13 WRKY genes were expressed in root, stem, and leaf tissues, but their expression levels and overall patterns varied notably in these tissues. Regarding overall gene expression in roots, the 13 genes were significantly highly expressed at all six time points after the treatment, reaching the plateau of expression at hour 9. In leaves, the 13 genes were similarly up-regulated from 3 to 12 h in response to NaCl treatment. In stems, however, expression levels of the 13 genes did not show significant changes after the NaCl treatment. Regarding individual gene expression across the time points and the three tissues, the 13 genes can be classified into three clusters: the lowly expressed Cluster 1 containing PthWRKY28, 45 and 105; intermediately expressed Clusters 2 including PthWRKY56, 88 and 116; and highly expressed Cluster 3 consisting of PthWRKY41, 44, 51, 61, 62, 75 and 106. In general, genes in Cluster 2 and 3 displayed a dynamic pattern of "induced amplification-recovering", suggesting that these WRKY genes and corresponding pathways may play a critical role in mediating salt response and tolerance in a dynamic and tissue-specific manner.

Self-government of complex reading and writing brains informed by cingulo-opercular network for adaptive control and working memory components for language learning.

PubMed

Richards, Todd L; Abbott, Robert D; Yagle, Kevin; Peterson, Dan; Raskind, Wendy; Berninger, Virginia W

2017-01-01

To understand mental self-government of the developing reading and writing brain, correlations of clustering coefficients on fMRI reading or writing tasks with BASC 2 Adaptivity ratings (time 1 only) or working memory components (time 1 before and time 2 after instruction previously shown to improve achievement and change magnitude of fMRI connectivity) were investigated in 39 students in grades 4 to 9 who varied along a continuum of reading and writing skills. A Philips 3T scanner measured connectivity during six leveled fMRI reading tasks (subword-letters and sounds, word-word-specific spellings or affixed words, syntax comprehension-with and without homonym foils or with and without affix foils, and text comprehension) and three fMRI writing tasks-writing next letter in alphabet, adding missing letter in word spelling, and planning for composing. The Brain Connectivity Toolbox generated clustering coefficients based on the cingulo-opercular (CO) network; after controlling for multiple comparisons and movement, significant fMRI connectivity clustering coefficients for CO were identified in 8 brain regions bilaterally (cingulate gyrus, superior frontal gyrus, middle frontal gyrus, inferior frontal gyrus, superior temporal gyrus, insula, cingulum-cingulate gyrus, and cingulum-hippocampus). BASC2 Parent Ratings for Adaptivity were correlated with CO clustering coefficients on three reading tasks (letter-sound, word affix judgments and sentence comprehension) and one writing task (writing next letter in alphabet). Before instruction, each behavioral working memory measure (phonology, orthography, morphology, and syntax coding, phonological and orthographic loops for integrating internal language and output codes, and supervisory focused and switching attention) correlated significantly with at least one CO clustering coefficient. After instruction, the patterning of correlations changed with new correlations emerging. Results show that the reading and writing brain's mental government, supported by both CO Adaptive Control and multiple working memory components, had changed in response to instruction during middle childhood/early adolescence.

Reduced cortical complexity in children with Prader-Willi Syndrome and its association with cognitive impairment and developmental delay.

PubMed

Lukoshe, Akvile; Hokken-Koelega, Anita C; van der Lugt, Aad; White, Tonya

2014-01-01

Prader-Willi Syndrome (PWS) is a complex neurogenetic disorder with symptoms involving not only hypothalamic, but also a global, central nervous system dysfunction. Previously, qualitative studies reported polymicrogyria in adults with PWS. However, there have been no quantitative neuroimaging studies of cortical morphology in PWS and no studies to date in children with PWS. Thus, our aim was to investigate and quantify cortical complexity in children with PWS compared to healthy controls. In addition, we investigated differences between genetic subtypes of PWS and the relationship between cortical complexity and intelligence within the PWS group. High-resolution structural magnetic resonance images were acquired in 24 children with genetically confirmed PWS (12 carrying a deletion (DEL), 12 with maternal uniparental disomy (mUPD)) and 11 age- and sex-matched typically developing siblings as healthy controls. Local gyrification index (lGI) was obtained using the FreeSurfer software suite. Four large clusters, two in each hemisphere, comprising frontal, parietal and temporal lobes, had lower lGI in children with PWS, compared to healthy controls. Clusters with lower lGI also had significantly lower cortical surface area in children with PWS. No differences in cortical thickness of the clusters were found between the PWS and healthy controls. lGI correlated significantly with cortical surface area, but not with cortical thickness. Within the PWS group, lGI in both hemispheres correlated with Total IQ and Verbal IQ, but not with Performance IQ. Children with mUPD, compared to children with DEL, had two small clusters with lower lGI in the right hemisphere. lGI of these clusters correlated with cortical surface area, but not with cortical thickness or IQ. These results suggest that lower cortical complexity in children with PWS partially underlies cognitive impairment and developmental delay, probably due to alterations in gene networks that play a prominent role in early brain development.

Reduced Cortical Complexity in Children with Prader-Willi Syndrome and Its Association with Cognitive Impairment and Developmental Delay

PubMed Central

Lukoshe, Akvile; Hokken-Koelega, Anita C.; van der Lugt, Aad; White, Tonya

2014-01-01

Background Prader-Willi Syndrome (PWS) is a complex neurogenetic disorder with symptoms involving not only hypothalamic, but also a global, central nervous system dysfunction. Previously, qualitative studies reported polymicrogyria in adults with PWS. However, there have been no quantitative neuroimaging studies of cortical morphology in PWS and no studies to date in children with PWS. Thus, our aim was to investigate and quantify cortical complexity in children with PWS compared to healthy controls. In addition, we investigated differences between genetic subtypes of PWS and the relationship between cortical complexity and intelligence within the PWS group. Methods High-resolution structural magnetic resonance images were acquired in 24 children with genetically confirmed PWS (12 carrying a deletion (DEL), 12 with maternal uniparental disomy (mUPD)) and 11 age- and sex-matched typically developing siblings as healthy controls. Local gyrification index (lGI) was obtained using the FreeSurfer software suite. Results Four large clusters, two in each hemisphere, comprising frontal, parietal and temporal lobes, had lower lGI in children with PWS, compared to healthy controls. Clusters with lower lGI also had significantly lower cortical surface area in children with PWS. No differences in cortical thickness of the clusters were found between the PWS and healthy controls. lGI correlated significantly with cortical surface area, but not with cortical thickness. Within the PWS group, lGI in both hemispheres correlated with Total IQ and Verbal IQ, but not with Performance IQ. Children with mUPD, compared to children with DEL, had two small clusters with lower lGI in the right hemisphere. lGI of these clusters correlated with cortical surface area, but not with cortical thickness or IQ. Conclusions These results suggest that lower cortical complexity in children with PWS partially underlies cognitive impairment and developmental delay, probably due to alterations in gene networks that play a prominent role in early brain development. PMID:25226172

A Kinetic Analysis of the Auxin Transcriptome Reveals Cell Wall Remodeling Proteins That Modulate Lateral Root Development in Arabidopsis[W][OPEN

PubMed Central

Lewis, Daniel R.; Olex, Amy L.; Lundy, Stacey R.; Turkett, William H.; Fetrow, Jacquelyn S.; Muday, Gloria K.

2013-01-01

To identify gene products that participate in auxin-dependent lateral root formation, a high temporal resolution, genome-wide transcript abundance analysis was performed with auxin-treated Arabidopsis thaliana roots. Data analysis identified 1246 transcripts that were consistently regulated by indole-3-acetic acid (IAA), partitioning into 60 clusters with distinct response kinetics. We identified rapidly induced clusters containing auxin-response functional annotations and clusters exhibiting delayed induction linked to cell division temporally correlated with lateral root induction. Several clusters were enriched with genes encoding proteins involved in cell wall modification, opening the possibility for understanding mechanistic details of cell structural changes that result in root formation following auxin treatment. Mutants with insertions in 72 genes annotated with a cell wall remodeling function were examined for alterations in IAA-regulated root growth and development. This reverse-genetic screen yielded eight mutants with root phenotypes. Detailed characterization of seedlings with mutations in CELLULASE3/GLYCOSYLHYDROLASE9B3 and LEUCINE RICH EXTENSIN2, genes not normally linked to auxin response, revealed defects in the early and late stages of lateral root development, respectively. The genes identified here using kinetic insight into expression changes lay the foundation for mechanistic understanding of auxin-mediated cell wall remodeling as an essential feature of lateral root development. PMID:24045021

Molecular epidemiology of Escherichia coli O157:H7 strains by bacteriophage lambda restriction fragment length polymorphism analysis: application to a multistate foodborne outbreak and a day-care center cluster.

PubMed

Samadpour, M; Grimm, L M; Desai, B; Alfi, D; Ongerth, J E; Tarr, P I

1993-12-01

Genomic DNAs prepared from 168 isolates of Escherichia coli O157:H7 were analyzed for restriction fragment length polymorphisms on Southern blots probed with bacteriophage lambda DNA. The isolates analyzed included strains from a recent large multistate outbreak of E. coli O157:H7 infection associated with consumption of poorly cooked beef in restaurants, a day-care center cluster, and temporally and geographically unrelated isolates. E. coli O157:H7 isolates recovered from the incriminated meat and from 61 (96.8%) of 63 patients from Washington and Nevada possessed identical lambda restriction fragment length patterns. The lambda restriction fragment length polymorphisms observed in 11 (91.7%) of 12 day-care center patients were identical, but they differed from that of the strain associated with the multistate outbreak. E. coli O157:H7 from 42 patients temporally or geographically unrelated to either cluster of infection possessed unique and different lambda restriction fragment length patterns, except for paired isolates from three separate clusters of infection. These data demonstrate that the hybridization of DNA digests of E. coli O157:H7 with radiolabelled bacteriophage lambda DNA can be a useful, stable, and discriminatory epidemiologic tool for analyzing the linkage between strains of E. coli O157:H7.

A non-voxel-based broad-beam (NVBB) framework for IMRT treatment planning.

PubMed

Lu, Weiguo

2010-12-07

We present a novel framework that enables very large scale intensity-modulated radiation therapy (IMRT) planning in limited computation resources with improvements in cost, plan quality and planning throughput. Current IMRT optimization uses a voxel-based beamlet superposition (VBS) framework that requires pre-calculation and storage of a large amount of beamlet data, resulting in large temporal and spatial complexity. We developed a non-voxel-based broad-beam (NVBB) framework for IMRT capable of direct treatment parameter optimization (DTPO). In this framework, both objective function and derivative are evaluated based on the continuous viewpoint, abandoning 'voxel' and 'beamlet' representations. Thus pre-calculation and storage of beamlets are no longer needed. The NVBB framework has linear complexities (O(N(3))) in both space and time. The low memory, full computation and data parallelization nature of the framework render its efficient implementation on the graphic processing unit (GPU). We implemented the NVBB framework and incorporated it with the TomoTherapy treatment planning system (TPS). The new TPS runs on a single workstation with one GPU card (NVBB-GPU). Extensive verification/validation tests were performed in house and via third parties. Benchmarks on dose accuracy, plan quality and throughput were compared with the commercial TomoTherapy TPS that is based on the VBS framework and uses a computer cluster with 14 nodes (VBS-cluster). For all tests, the dose accuracy of these two TPSs is comparable (within 1%). Plan qualities were comparable with no clinically significant difference for most cases except that superior target uniformity was seen in the NVBB-GPU for some cases. However, the planning time using the NVBB-GPU was reduced many folds over the VBS-cluster. In conclusion, we developed a novel NVBB framework for IMRT optimization. The continuous viewpoint and DTPO nature of the algorithm eliminate the need for beamlets and lead to better plan quality. The computation parallelization on a GPU instead of a computer cluster significantly reduces hardware and service costs. Compared with using the current VBS framework on a computer cluster, the planning time is significantly reduced using the NVBB framework on a single workstation with a GPU card.

20 Years Spatial-Temporal Analysis of Dengue Fever and Hemorrhagic Fever in Mexico.

PubMed

Hernández-Gaytán, Sendy Isarel; Díaz-Vásquez, Francisco Javier; Duran-Arenas, Luis Gerardo; López Cervantes, Malaquías; Rothenberg, Stephen J

2017-10-01

Dengue Fever (DF) is a human vector-borne disease and a major public health problem worldwide. In Mexico, DF and Dengue Hemorrhagic Fever (DHF) cases have increased in recent years. The aim of this study was to identify variations in the spatial distribution of DF and DHF cases over time using space-time statistical analysis and geographic information systems. Official data of DF and DHF cases were obtained in 32 states from 1995-2015. Space-time scan statistics were used to determine the space-time clusters of DF and DHF cases nationwide, and a geographic information system was used to display the location of clusters. A total of 885,748 DF cases was registered of which 13.4% (n = 119,174) correspond to DHF in the 32 states from 1995-2015. The most likely cluster of DF (relative risk = 25.5) contained the states of Jalisco, Colima, and Nayarit, on the Pacific coast in 2009, and the most likely cluster of DHF (relative risk = 8.5) was in the states of Chiapas, Tabasco, Campeche, Oaxaca, Veracruz, Quintana Roo, Yucatán, Puebla, Morelos, and Guerrero principally on the Gulf coast over 2006-2015. The geographic distribution of DF and DHF cases has increased in recent years and cases are significantly clustered in two coastal areas (Pacific and Gulf of Mexico). This provides the basis for further investigation of risk factors as well as interventions in specific areas. Copyright © 2018 IMSS. Published by Elsevier Inc. All rights reserved.

Spatial and Temporal Variation of Japanese encephalitis Disease and Detection of Disease Hotspots: a Case Study of Gorakhpur District, Uttar Pradesh, India

NASA Astrophysics Data System (ADS)

Verma, S.; Gupta, R. D.

2014-11-01

In recent times, Japanese Encephalitis (JE) has emerged as a serious public health problem. In India, JE outbreaks were recently reported in Uttar Pradesh, Gorakhpur. The present study presents an approach to use GIS for analyzing the reported cases of JE in the Gorakhpur district based on spatial analysis to bring out the spatial and temporal dynamics of the JE epidemic. The study investigates spatiotemporal pattern of the occurrence of disease and detection of the JE hotspot. Spatial patterns of the JE disease can provide an understanding of geographical changes. Geospatial distribution of the JE disease outbreak is being investigated since 2005 in this study. The JE incidence data for the years 2005 to 2010 is used. The data is then geo-coded at block level. Spatial analysis is used to evaluate autocorrelation in JE distribution and to test the cases that are clustered or dispersed in space. The Inverse Distance Weighting interpolation technique is used to predict the pattern of JE incidence distribution prevalent across the study area. Moran's I Index (Moran's I) statistics is used to evaluate autocorrelation in spatial distribution. The Getis-Ord Gi*(d) is used to identify the disease areas. The results represent spatial disease patterns from 2005 to 2010, depicting spatially clustered patterns with significant differences between the blocks. It is observed that the blocks on the built up areas reported higher incidences.

Pain sensitivity profiles in patients with advanced knee osteoarthritis

PubMed Central

Frey-Law, Laura A.; Bohr, Nicole L.; Sluka, Kathleen A.; Herr, Keela; Clark, Charles R.; Noiseux, Nicolas O.; Callaghan, John J; Zimmerman, M Bridget; Rakel, Barbara A.

2016-01-01

The development of patient profiles to subgroup individuals on a variety of variables has gained attention as a potential means to better inform clinical decision-making. Patterns of pain sensitivity response specific to quantitative sensory testing (QST) modality have been demonstrated in healthy subjects. It has not been determined if these patterns persist in a knee osteoarthritis population. In a sample of 218 participants, 19 QST measures along with pain, psychological factors, self-reported function, and quality of life were assessed prior to total knee arthroplasty. Component analysis was used to identify commonalities across the 19 QST assessments to produce standardized pain sensitivity factors. Cluster analysis then grouped individuals that exhibited similar patterns of standardized pain sensitivity component scores. The QST resulted in four pain sensitivity components: heat, punctate, temporal summation, and pressure. Cluster analysis resulted in five pain sensitivity profiles: a “low pressure pain” group, an “average pain” group, and three “high pain” sensitivity groups who were sensitive to different modalities (punctate, heat, and temporal summation). Pain and function differed between pain sensitivity profiles, along with sex distribution; however no differences in OA grade, medication use, or psychological traits were found. Residualizing QST data by age and sex resulted in similar components and pain sensitivity profiles. Further, these profiles are surprisingly similar to those reported in healthy populations suggesting that individual differences in pain sensitivity are a robust finding even in an older population with significant disease. PMID:27152688

DOE Office of Scientific and Technical Information (OSTI.GOV)

Murugesan, Sugeerth; Bouchard, Kristofer; Chang, Edward

There exists a need for effective and easy-to-use software tools supporting the analysis of complex Electrocorticography (ECoG) data. Understanding how epileptic seizures develop or identifying diagnostic indicators for neurological diseases require the in-depth analysis of neural activity data from ECoG. Such data is multi-scale and is of high spatio-temporal resolution. Comprehensive analysis of this data should be supported by interactive visual analysis methods that allow a scientist to understand functional patterns at varying levels of granularity and comprehend its time-varying behavior. We introduce a novel multi-scale visual analysis system, ECoG ClusterFlow, for the detailed exploration of ECoG data. Our systemmore » detects and visualizes dynamic high-level structures, such as communities, derived from the time-varying connectivity network. The system supports two major views: 1) an overview summarizing the evolution of clusters over time and 2) an electrode view using hierarchical glyph-based design to visualize the propagation of clusters in their spatial, anatomical context. We present case studies that were performed in collaboration with neuroscientists and neurosurgeons using simulated and recorded epileptic seizure data to demonstrate our system's effectiveness. ECoG ClusterFlow supports the comparison of spatio-temporal patterns for specific time intervals and allows a user to utilize various clustering algorithms. Neuroscientists can identify the site of seizure genesis and its spatial progression during various the stages of a seizure. Our system serves as a fast and powerful means for the generation of preliminary hypotheses that can be used as a basis for subsequent application of rigorous statistical methods, with the ultimate goal being the clinical treatment of epileptogenic zones.« less

Parallel Multivariate Spatio-Temporal Clustering of Large Ecological Datasets on Hybrid Supercomputers

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sreepathi, Sarat; Kumar, Jitendra; Mills, Richard T.

A proliferation of data from vast networks of remote sensing platforms (satellites, unmanned aircraft systems (UAS), airborne etc.), observational facilities (meteorological, eddy covariance etc.), state-of-the-art sensors, and simulation models offer unprecedented opportunities for scientific discovery. Unsupervised classification is a widely applied data mining approach to derive insights from such data. However, classification of very large data sets is a complex computational problem that requires efficient numerical algorithms and implementations on high performance computing (HPC) platforms. Additionally, increasing power, space, cooling and efficiency requirements has led to the deployment of hybrid supercomputing platforms with complex architectures and memory hierarchies like themore » Titan system at Oak Ridge National Laboratory. The advent of such accelerated computing architectures offers new challenges and opportunities for big data analytics in general and specifically, large scale cluster analysis in our case. Although there is an existing body of work on parallel cluster analysis, those approaches do not fully meet the needs imposed by the nature and size of our large data sets. Moreover, they had scaling limitations and were mostly limited to traditional distributed memory computing platforms. We present a parallel Multivariate Spatio-Temporal Clustering (MSTC) technique based on k-means cluster analysis that can target hybrid supercomputers like Titan. We developed a hybrid MPI, CUDA and OpenACC implementation that can utilize both CPU and GPU resources on computational nodes. We describe performance results on Titan that demonstrate the scalability and efficacy of our approach in processing large ecological data sets.« less

A dynamic scheduling algorithm for singe-arm two-cluster tools with flexible processing times

NASA Astrophysics Data System (ADS)

Li, Xin; Fung, Richard Y. K.

2018-02-01

This article presents a dynamic algorithm for job scheduling in two-cluster tools producing multi-type wafers with flexible processing times. Flexible processing times mean that the actual times for processing wafers should be within given time intervals. The objective of the work is to minimize the completion time of the newly inserted wafer. To deal with this issue, a two-cluster tool is decomposed into three reduced single-cluster tools (RCTs) in a series based on a decomposition approach proposed in this article. For each single-cluster tool, a dynamic scheduling algorithm based on temporal constraints is developed to schedule the newly inserted wafer. Three experiments have been carried out to test the dynamic scheduling algorithm proposed, comparing with the results the 'earliest starting time' heuristic (EST) adopted in previous literature. The results show that the dynamic algorithm proposed in this article is effective and practical.

Multi-mode clustering model for hierarchical wireless sensor networks

NASA Astrophysics Data System (ADS)

Hu, Xiangdong; Li, Yongfu; Xu, Huifen

2017-03-01

The topology management, i.e., clusters maintenance, of wireless sensor networks (WSNs) is still a challenge due to its numerous nodes, diverse application scenarios and limited resources as well as complex dynamics. To address this issue, a multi-mode clustering model (M2 CM) is proposed to maintain the clusters for hierarchical WSNs in this study. In particular, unlike the traditional time-trigger model based on the whole-network and periodic style, the M2 CM is proposed based on the local and event-trigger operations. In addition, an adaptive local maintenance algorithm is designed for the broken clusters in the WSNs using the spatial-temporal demand changes accordingly. Numerical experiments are performed using the NS2 network simulation platform. Results validate the effectiveness of the proposed model with respect to the network maintenance costs, node energy consumption and transmitted data as well as the network lifetime.

Spatial and temporal dynamics of the microbial community in the Hanford unconfined aquifer

PubMed Central

Lin, Xueju; McKinley, James; Resch, Charles T; Kaluzny, Rachael; Lauber, Christian L; Fredrickson, James; Knight, Rob; Konopka, Allan

2012-01-01

Pyrosequencing analysis of 16S rRNA genes was used to study temporal dynamics of groundwater bacteria and archaea over 10 months within three well clusters separated by ∼30 m and located 250 m from the Columbia River on the Hanford Site, WA. Each cluster contained three wells screened at different depths ranging from 10 to 17 m that differed in hydraulic conductivities. Representative samples were selected for analyses of prokaryotic 16S and eukaryotic 18S rRNA gene copy numbers. Temporal changes in community composition occurred in all nine wells over the 10-month sampling period. However, there were particularly strong effects near the top of the water table when the seasonal rise in the Columbia River caused river water intrusion at the top of the aquifer. The occurrence and disappearance of some microbial assemblages (such as Actinobacteria ACK-M1) were correlated with river water intrusion. This seasonal impact on microbial community structure was greater in the shallow saturated zone than deeper zone in the aquifer. Spatial and temporal patterns for several 16S rRNA gene operational taxonomic units associated with particular physiological functions (for example, methane oxidizers and metal reducers) suggests dynamic changes in fluxes of electron donors and acceptors over an annual cycle. In addition, temporal dynamics in eukaryotic 18S rRNA gene copies and the dominance of protozoa in 18S clone libraries suggest that bacterial community dynamics could be affected not only by the physical and chemical environment but also by top-down biological control. PMID:22456444

Spatial and temporal dynamics of the microbial community in the Hanford unconfined aquifer.

PubMed

Lin, Xueju; McKinley, James; Resch, Charles T; Kaluzny, Rachael; Lauber, Christian L; Fredrickson, James; Knight, Rob; Konopka, Allan

2012-09-01

Pyrosequencing analysis of 16S rRNA genes was used to study temporal dynamics of groundwater bacteria and archaea over 10 months within three well clusters separated by ~30 m and located 250 m from the Columbia River on the Hanford Site, WA. Each cluster contained three wells screened at different depths ranging from 10 to 17 m that differed in hydraulic conductivities. Representative samples were selected for analyses of prokaryotic 16S and eukaryotic 18S rRNA gene copy numbers. Temporal changes in community composition occurred in all nine wells over the 10-month sampling period. However, there were particularly strong effects near the top of the water table when the seasonal rise in the Columbia River caused river water intrusion at the top of the aquifer. The occurrence and disappearance of some microbial assemblages (such as Actinobacteria ACK-M1) were correlated with river water intrusion. This seasonal impact on microbial community structure was greater in the shallow saturated zone than deeper zone in the aquifer. Spatial and temporal patterns for several 16S rRNA gene operational taxonomic units associated with particular physiological functions (for example, methane oxidizers and metal reducers) suggests dynamic changes in fluxes of electron donors and acceptors over an annual cycle. In addition, temporal dynamics in eukaryotic 18S rRNA gene copies and the dominance of protozoa in 18S clone libraries suggest that bacterial community dynamics could be affected not only by the physical and chemical environment but also by top-down biological control.

A review on the temporal pattern of deer-vehicle accidents: impact of seasonal, diurnal and lunar effects in cervids.

PubMed

Steiner, Wolfgang; Leisch, Friedrich; Hackländer, Klaus

2014-05-01

The increasing number of deer-vehicle-accidents (DVAs) and the resulting economic costs have promoted numerous studies on behavioural and environmental factors which may contribute to the quantity, spatiotemporal distribution and characteristics of DVAs. Contrary to the spatial pattern of DVAs, data of their temporal pattern is scarce and difficult to obtain because of insufficient accuracy in available datasets, missing standardization in data aquisition, legal terms and low reporting rates to authorities. Literature of deer-traffic collisions on roads and railways is reviewed to examine current understanding of DVA temporal trends. Seasonal, diurnal and lunar peak accident periods are identified for deer, although seasonal pattern are not consistent among and within species or regions and data on effects of lunar cycles on DVAs is almost non-existent. Cluster analysis of seasonal DVA data shows nine distinct clusters of different seasonal DVA pattern for cervid species within the reviewed literature. Studies analyzing the relationship between time-related traffic predictors and DVAs yield mixed results. Despite the seasonal dissimilarity, diurnal DVA pattern are comparatively constant in deer, resulting in pronounced DVA peaks during the hours of dusk and dawn frequently described as bimodal crepuscular pattern. Behavioural aspects in activity seem to have the highest impact in DVAs temporal trends. Differences and variations are related to habitat-, climatic- and traffic characteristics as well as effects of predation, hunting and disturbance. Knowledge of detailed temporal DVA pattern is essential for prevention management as well as for the application and evaluation of mitigation measures. Copyright © 2014 Elsevier Ltd. All rights reserved.

Analysis of the spatial and temporal distribution of malaria in an area of Northern Guatemala with seasonal malaria transmission.

PubMed

Malvisi, Lucio; Troisi, Catherine L; Selwyn, Beatrice J

2018-06-23

The risk of malaria infection displays spatial and temporal variability that is likely due to interaction between the physical environment and the human population. In this study, we performed a spatial analysis at three different time points, corresponding to three cross-sectional surveys conducted as part of an insecticide-treated bed nets efficacy study, to reveal patterns of malaria incidence distribution in an area of Northern Guatemala characterized by low malaria endemicity. A thorough understanding of the spatial and temporal patterns of malaria distribution is essential for targeted malaria control programs. Two methods, the local Moran's I and the Getis-Ord G * (d), were used for the analysis, providing two different statistical approaches and allowing for a comparison of results. A distance band of 3.5 km was considered to be the most appropriate distance for the analysis of data based on epidemiological and entomological factors. Incidence rates were higher at the first cross-sectional survey conducted prior to the intervention compared to the following two surveys. Clusters or hot spots of malaria incidence exhibited high spatial and temporal variations. Findings from the two statistics were similar, though the G * (d) detected cold spots using a higher distance band (5.5 km). The high spatial and temporal variability in the distribution of clusters of high malaria incidence seems to be consistent with an area of unstable malaria transmission. In such a context, a strong surveillance system and the use of spatial analysis may be crucial for targeted malaria control activities.

Relationship between Guillain-Barré syndrome, influenza-related hospitalizations, and influenza vaccine coverage.

PubMed

Iqbal, Shahed; Li, Rongxia; Gargiullo, Paul; Vellozzi, Claudia

2015-04-21

Some studies reported an increased risk of Guillain-Barré syndrome (GBS) within six weeks of influenza vaccination. It has also been suggested that this finding could have been confounded by influenza illnesses. We explored the complex relationship between influenza illness, influenza vaccination, and GBS, from an ecologic perspective using nationally representative data. We also studied seasonal patterns for GBS hospitalizations. Monthly hospitalization data (2000-2009) for GBS, and pneumonia and influenza (P&I) in the Nationwide Inpatient Sample were included. Seasonal influenza vaccination coverage for 2004-2005 through the 2008-2009 influenza seasons (August-May) was estimated from the National Health Interview Survey data. GBS seasonality was determined using Poisson regression. GBS and P&I temporal clusters were identified using scan statistics. The association between P&I and GBS hospitalizations in the same month (concurrent) or in the following month (lagged) were determined using negative binomial regression. Vaccine coverage increased over the years (from 19.7% during 2004-2005 to 35.5% during 2008-2009 season) but GBS hospitalization did not follow a similar pattern. Overall, a significant correlation between monthly P&I and GBS hospitalizations was observed (Spearman's correlation coefficient=0.7016, p<0.0001). A significant (p=0.001) cluster of P&I hospitalizations during December 2004-March 2005 overlapped a significant (p=0.001) cluster of GBS hospitalizations during January 2005-February 2005. After accounting for effects of monthly vaccine coverage and age, P&I hospitalization was significantly associated (p<0.0001) with GBS hospitalization in the concurrent month but not with GBS hospitalization in the following month. Monthly vaccine coverage was not associated with GBS hospitalization in adjusted models (both concurrent and lagged). GBS hospitalizations demonstrated a seasonal pattern with winter months having higher rates compared to the month of June. P&I hospitalization rates were significantly correlated with hospitalization rates for GBS. Vaccine coverage did not significantly affect the rates of GBS hospitalization at the population level. Published by Elsevier Ltd.

Temporal Patterns and Environmental Correlates of Macroinvertebrate Communities in Temporary Streams.

PubMed

Botwe, Paul K; Barmuta, Leon A; Magierowski, Regina; McEvoy, Paul; Goonan, Peter; Carver, Scott

2015-01-01

Temporary streams are characterised by short periods of seasonal or annual stream flow after which streams contract into waterholes or pools of varying hydrological connectivity and permanence. Although these streams are widespread globally, temporal variability of their ecology is understudied, and understanding the processes that structure community composition in these systems is vital for predicting and managing the consequences of anthropogenic impacts. We used multivariate and univariate approaches to investigate temporal variability in macroinvertebrate compositional data from 13 years of sampling across multiple sites from autumn and spring, in South Australia, the driest state in the driest inhabited continent in the world. We examined the potential of land-use, geographic and environmental variables to predict the temporal variability in macroinvertebrate assemblages, and also identified indicator taxa, that is, those highly correlated with the most significantly associated physical variables. Temporal trajectories of macroinvertebrate communities varied within site in both seasons and across years. A combination of land-use, geographic and environmental variables accounted for 24% of the variation in community structure in autumn and 27% in spring. In autumn, community composition among sites were more closely clustered together relative to spring suggesting that communities were more similar in autumn than in spring. In both seasons, community structure was most strongly correlated with conductivity and latitude, and community structure was more associated with cover by agriculture than urban land-use. Maintaining temporary streams will require improved catchment management aimed at sustaining seasonal flows and critical refuge habitats, while also limiting the damaging effects from increased agriculture and urban developments.

Temporal Patterns and Environmental Correlates of Macroinvertebrate Communities in Temporary Streams

PubMed Central

Botwe, Paul K.; Barmuta, Leon A.; Magierowski, Regina; McEvoy, Paul; Goonan, Peter; Carver, Scott

2015-01-01

Temporary streams are characterised by short periods of seasonal or annual stream flow after which streams contract into waterholes or pools of varying hydrological connectivity and permanence. Although these streams are widespread globally, temporal variability of their ecology is understudied, and understanding the processes that structure community composition in these systems is vital for predicting and managing the consequences of anthropogenic impacts. We used multivariate and univariate approaches to investigate temporal variability in macroinvertebrate compositional data from 13 years of sampling across multiple sites from autumn and spring, in South Australia, the driest state in the driest inhabited continent in the world. We examined the potential of land-use, geographic and environmental variables to predict the temporal variability in macroinvertebrate assemblages, and also identified indicator taxa, that is, those highly correlated with the most significantly associated physical variables. Temporal trajectories of macroinvertebrate communities varied within site in both seasons and across years. A combination of land-use, geographic and environmental variables accounted for 24% of the variation in community structure in autumn and 27% in spring. In autumn, community composition among sites were more closely clustered together relative to spring suggesting that communities were more similar in autumn than in spring. In both seasons, community structure was most strongly correlated with conductivity and latitude, and community structure was more associated with cover by agriculture than urban land-use. Maintaining temporary streams will require improved catchment management aimed at sustaining seasonal flows and critical refuge habitats, while also limiting the damaging effects from increased agriculture and urban developments. PMID:26556711

Variation in the macrofaunal community over large temporal and spatial scales in the southern Yellow Sea

NASA Astrophysics Data System (ADS)

Xu, Yong; Sui, Jixing; Yang, Mei; Sun, Yue; Li, Xinzheng; Wang, Hongfa; Zhang, Baolin

2017-09-01

To detect large, temporal- and spatial-scale variations in the macrofaunal community in the southern Yellow Sea, data collected along the western, middle and eastern regions of the southern Yellow Sea from 1958 to 2014 were organized and analyzed. Statistical methods such as cluster analysis, non-metric multidimensional scaling ordination (nMDS), permutational multivariate analysis of variance (PERMANOVA), redundancy analysis (RDA) and canonical correspondence analysis (CCA) were applied. The abundance of polychaetes increased in the western region but decreased in the eastern region from 1958 to 2014, whereas the abundance of echinoderms showed an opposite trend. For the entire macrofaunal community, Margalef's richness (d), the Shannon-Wiener index (H‧) and Pielou's evenness (J‧) were significantly lower in the eastern region when compared with the other two regions. No significant temporal differences were found for d and H‧, but there were significantly lower values of J‧ in 2014. Considerable variation in the macrofaunal community structure over the past several decades and among the geographical regions at the species, genus and family levels were observed. The species, genera and families that contributed to the temporal variation in each region were also identified. The most conspicuous pattern was the increase in the species Ophiura sarsii vadicola in the eastern region. In the western region, five polychaetes (Ninoe palmata, Notomastus latericeus, Paralacydonia paradoxa, Paraprionospio pinnata and Sternaspis scutata) increased consistently from 1958 to 2014. The dominance curves showed that both the species diversity and the dominance patterns were relatively stable in the western and middle regions. Environmental parameters such as depth, temperature and salinity could only partially explain the observed biological variation in the southern Yellow Sea. Anthropogenic activities such as demersal fishing and other unmeasured environmental variables may be more responsible for the long-term changes in the macrofaunal community.

Satellite remote sensing data can be used to model marine microbial metabolite turnover

PubMed Central

Larsen, Peter E; Scott, Nicole; Post, Anton F; Field, Dawn; Knight, Rob; Hamada, Yuki; Gilbert, Jack A

2015-01-01

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes' predicted relative abundance was highly correlated (Pearson Correlation 0.72, P-value <10−6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ∼3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology. PMID:25072414

Regional cerebral blood flow in Parkinson disease with nonpsychotic visual hallucinations.

PubMed

Oishi, N; Udaka, F; Kameyama, M; Sawamoto, N; Hashikawa, K; Fukuyama, H

2005-12-13

Patients with Parkinson disease (PD) often experience visual hallucinations (VH) with retained insight (nonpsychotic) but the precise mechanism remains unclear. To clarify which neural substrates participate in nonpsychotic VH in PD, the authors evaluated regional cerebral blood flow (rCBF) changes in patients with PD and VH. The authors compared 24 patients with PD who had nonpsychotic VH (hallucinators) and 41 patients with PD who had never experienced VH (non-hallucinators) using SPECT images with N-isopropyl-p-[(123)I]iodoamphetamine. There were no significant differences in age, sex, duration of disease, doses of PD medications, Hoehn and Yahr scale, or Mini-Mental State Examination (MMSE) scores between the two groups. The rCBF data were analyzed using statistical parametric mapping (SPM). The rCBF in the right fusiform gyrus was lower in the hallucinators than in the non-hallucinators (corrected p < 0.05 at cluster levels). The hallucinators revealed higher rCBF in the right superior and middle temporal gyri than the non-hallucinators (uncorrected p < 0.001). These significant differences were demonstrated after MMSE scores and duration of disease, which are the relevant factors associated with VH, were covariated out. Nonpsychotic visual hallucinations in Parkinson disease (PD) may be associated with hypoperfusion in the right fusiform gyrus and hyperperfusion in the right superior and middle temporal gyri. These temporal regions are important for visual object recognition and these regional cerebral blood flow changes are associated with inappropriate visual processing and are responsible for nonpsychotic visual hallucinations in PD.

Satellite remote sensing data can be used to model marine microbial metabolite turnover

DOE Office of Scientific and Technical Information (OSTI.GOV)

Larsen, Peter E.; Scott, Nicole; Post, Anton F.

Sampling ecosystems, even at a local scale, at the temporal and spatial resolution necessary to capture natural variability in microbial communities are prohibitively expensive. We extrapolated marine surface microbial community structure and metabolic potential from 72 16S rRNA amplicon and 8 metagenomic observations using remotely sensed environmental parameters to create a system-scale model of marine microbial metabolism for 5904 grid cells (49 km2) in the Western English Chanel, across 3 years of weekly averages. Thirteen environmental variables predicted the relative abundance of 24 bacterial Orders and 1715 unique enzyme-encoding genes that encode turnover of 2893 metabolites. The genes’ predicted relativemore » abundance was highly correlated (Pearson Correlation 0.72, P-value <10-6) with their observed relative abundance in sequenced metagenomes. Predictions of the relative turnover (synthesis or consumption) of CO2 were significantly correlated with observed surface CO2 fugacity. The spatial and temporal variation in the predicted relative abundances of genes coding for cyanase, carbon monoxide and malate dehydrogenase were investigated along with the predicted inter-annual variation in relative consumption or production of ~3000 metabolites forming six significant temporal clusters. These spatiotemporal distributions could possibly be explained by the co-occurrence of anaerobic and aerobic metabolisms associated with localized plankton blooms or sediment resuspension, which facilitate the presence of anaerobic micro-niches. This predictive model provides a general framework for focusing future sampling and experimental design to relate biogeochemical turnover to microbial ecology.« less

Modeling tensional homeostasis in multicellular clusters.

PubMed

Tam, Sze Nok; Smith, Michael L; Stamenović, Dimitrije

2017-03-01

Homeostasis of mechanical stress in cells, or tensional homeostasis, is essential for normal physiological function of tissues and organs and is protective against disease progression, including atherosclerosis and cancer. Recent experimental studies have shown that isolated cells are not capable of maintaining tensional homeostasis, whereas multicellular clusters are, with stability increasing with the size of the clusters. Here, we proposed simple mathematical models to interpret experimental results and to obtain insight into factors that determine homeostasis. Multicellular clusters were modeled as one-dimensional arrays of linearly elastic blocks that were either jointed or disjointed. Fluctuating forces that mimicked experimentally measured cell-substrate tractions were obtained from Monte Carlo simulations. These forces were applied to the cluster models, and the corresponding stress field in the cluster was calculated by solving the equilibrium equation. It was found that temporal fluctuations of the cluster stress field became attenuated with increasing cluster size, indicating that the cluster approached tensional homeostasis. These results were consistent with previously reported experimental data. Furthermore, the models revealed that key determinants of tensional homeostasis in multicellular clusters included the cluster size, the distribution of traction forces, and mechanical coupling between adjacent cells. Based on these findings, we concluded that tensional homeostasis was a multicellular phenomenon. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Hydraulic fracturing and the Crooked Lake Sequences: Insights gleaned from regional seismic networks

NASA Astrophysics Data System (ADS)

Schultz, Ryan; Stern, Virginia; Novakovic, Mark; Atkinson, Gail; Gu, Yu Jeffrey

2015-04-01

Within central Alberta, Canada, a new sequence of earthquakes has been recognized as of 1 December 2013 in a region of previous seismic quiescence near Crooked Lake, ~30 km west of the town of Fox Creek. We utilize a cross-correlation detection algorithm to detect more than 160 events to the end of 2014, which is temporally distinguished into five subsequences. This observation is corroborated by the uniqueness of waveforms clustered by subsequence. The Crooked Lake Sequences have come under scrutiny due to its strong temporal correlation (>99.99%) to the timing of hydraulic fracturing operations in the Duvernay Formation. We assert that individual subsequences are related to fracturing stimulation and, despite adverse initial station geometry, double-difference techniques allow us to spatially relate each cluster back to a unique horizontal well. Overall, we find that seismicity in the Crooked Lake Sequences is consistent with first-order observations of hydraulic fracturing induced seismicity.

Clustering is a feature of the spiral ganglion in the basal turn.

PubMed

Gacek, Richard R

2012-01-01

To demonstrate the organization of the spiral ganglion in the mammalian species. Temporal bone (TB) specimens from man (n = 2), monkey (n = 2), lion (n = 2) and cat (n = 20) were stained, decalcified and dissected according to the Sudan black B method of Rasmussen. These TB specimens were examined under a Zeiss operating microscope and photographed with a Canon 100 camera interfaced with the microscope. Spiral ganglion cells occurred in clusters within Rosenthal's canal in all four species. The location of the clusters was marked by the interface between axon and dendritic bundles as well as groups of ganglion cells. In monkey and man the clusters were more separated than in lion and cat. These observations indicate that the spiral ganglion forms clusters of neurons within Rosenthal's canal at the basal cochlear turn in the mammals investigated here. The formation of clusters may be related to the principles of neurogenesis. Copyright © 2011 S. Karger AG, Basel.

Observing large-scale temporal variability of ocean currents by satellite altimetry - With application to the Antarctic circumpolar current

NASA Technical Reports Server (NTRS)

Fu, L.-L.; Chelton, D. B.

1985-01-01

A new method is developed for studying large-scale temporal variability of ocean currents from satellite altimetric sea level measurements at intersections (crossovers) of ascending and descending orbit ground tracks. Using this method, sea level time series can be constructed from crossover sea level differences in small sample areas where altimetric crossovers are clustered. The method is applied to Seasat altimeter data to study the temporal evolution of the Antarctic Circumpolar Current (ACC) over the 3-month Seasat mission (July-October 1978). The results reveal a generally eastward acceleration of the ACC around the Southern Ocean with meridional disturbances which appear to be associated with bottom topographic features. This is the first direct observational evidence for large-scale coherence in the temporal variability of the ACC. It demonstrates the great potential of satellite altimetry for synoptic observation of temporal variability of the world ocean circulation.

The Spatial-Temporal Characteristics of Air Pollution in China from 2001–2014

PubMed Central

Bao, Junzhe; Yang, Xiping; Zhao, Zhiyuan; Wang, Zhenkun; Yu, Chuanhua; Li, Xudong

2015-01-01

To provide some useful information about the control of air pollution in China, we studied the spatial-temporal characteristics of air pollution in China from 2001–2014. First, we drew several line charts and histograms of the Air Pollution Index (API) and Air Quality Index (AQI) of 31 capital cities and municipalities to research the distribution across different times and cities; then, we researched the spatial clustering of API and AQI; finally, we examined the shift of the gravity center of API and AQI in different years and months. The API values had a decreasing trend: the high values had a clustering trend in some northern cities, and the low values had a clustering trend in some southern cities. The AQI values were relatively low, from 15:00–17:00 during the day. The gravity center of API had a trend of moving south from 2001–2003, then fluctuated in an unordered pattern and moved north in the winter. The AQI gravity center did not have a regular shift during different months. In conclusion, the government should take action to mitigate air pollution in some typical cities, as well as air pollution during the winter. PMID:26694427

Agent-based model with multi-level herding for complex financial systems

NASA Astrophysics Data System (ADS)

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-02-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level.

Agent-based model with multi-level herding for complex financial systems

PubMed Central

Chen, Jun-Jie; Tan, Lei; Zheng, Bo

2015-01-01

In complex financial systems, the sector structure and volatility clustering are respectively important features of the spatial and temporal correlations. However, the microscopic generation mechanism of the sector structure is not yet understood. Especially, how to produce these two features in one model remains challenging. We introduce a novel interaction mechanism, i.e., the multi-level herding, in constructing an agent-based model to investigate the sector structure combined with volatility clustering. According to the previous market performance, agents trade in groups, and their herding behavior comprises the herding at stock, sector and market levels. Further, we propose methods to determine the key model parameters from historical market data, rather than from statistical fitting of the results. From the simulation, we obtain the sector structure and volatility clustering, as well as the eigenvalue distribution of the cross-correlation matrix, for the New York and Hong Kong stock exchanges. These properties are in agreement with the empirical ones. Our results quantitatively reveal that the multi-level herding is the microscopic generation mechanism of the sector structure, and provide new insight into the spatio-temporal interactions in financial systems at the microscopic level. PMID:25669427

Cluster Observations of Non-Time Continuous Magnetosonic Waves

NASA Technical Reports Server (NTRS)

Walker, Simon N.; Demekhov, Andrei G.; Boardsen, Scott A.; Ganushkina, Natalia Y.; Sibeck, David G.; Balikhin, Michael A.

2016-01-01

Equatorial magnetosonic waves are normally observed as temporally continuous sets of emissions lasting from minutes to hours. Recent observations, however, have shown that this is not always the case. Using Cluster data, this study identifies two distinct forms of these non temporally continuous use missions. The first, referred to as rising tone emissions, are characterized by the systematic onset of wave activity at increasing proton gyroharmonic frequencies. Sets of harmonic emissions (emission elements)are observed to occur periodically in the region +/- 10 off the geomagnetic equator. The sweep rate of these emissions maximizes at the geomagnetic equator. In addition, the ellipticity and propagation direction also change systematically as Cluster crosses the geomagnetic equator. It is shown that the observed frequency sweep rate is unlikely to result from the sideband instability related to nonlinear trapping of suprathermal protons in the wave field. The second form of emissions is characterized by the simultaneous onset of activity across a range of harmonic frequencies. These waves are observed at irregular intervals. Their occurrence correlates with changes in the spacecraft potential, a measurement that is used as a proxy for electron density. Thus, these waves appear to be trapped within regions of localized enhancement of the electron density.

Heart morphogenesis gene regulatory networks revealed by temporal expression analysis.

PubMed

Hill, Jonathon T; Demarest, Bradley; Gorsi, Bushra; Smith, Megan; Yost, H Joseph

2017-10-01

During embryogenesis the heart forms as a linear tube that then undergoes multiple simultaneous morphogenetic events to obtain its mature shape. To understand the gene regulatory networks (GRNs) driving this phase of heart development, during which many congenital heart disease malformations likely arise, we conducted an RNA-seq timecourse in zebrafish from 30 hpf to 72 hpf and identified 5861 genes with altered expression. We clustered the genes by temporal expression pattern, identified transcription factor binding motifs enriched in each cluster, and generated a model GRN for the major gene batteries in heart morphogenesis. This approach predicted hundreds of regulatory interactions and found batteries enriched in specific cell and tissue types, indicating that the approach can be used to narrow the search for novel genetic markers and regulatory interactions. Subsequent analyses confirmed the GRN using two mutants, Tbx5 and nkx2-5 , and identified sets of duplicated zebrafish genes that do not show temporal subfunctionalization. This dataset provides an essential resource for future studies on the genetic/epigenetic pathways implicated in congenital heart defects and the mechanisms of cardiac transcriptional regulation. © 2017. Published by The Company of Biologists Ltd.

Time Clustered Sampling Can Inflate the Inferred Substitution Rate in Foot-And-Mouth Disease Virus Analyses.

PubMed

Pedersen, Casper-Emil T; Frandsen, Peter; Wekesa, Sabenzia N; Heller, Rasmus; Sangula, Abraham K; Wadsworth, Jemma; Knowles, Nick J; Muwanika, Vincent B; Siegismund, Hans R

2015-01-01

With the emergence of analytical software for the inference of viral evolution, a number of studies have focused on estimating important parameters such as the substitution rate and the time to the most recent common ancestor (tMRCA) for rapidly evolving viruses. Coupled with an increasing abundance of sequence data sampled under widely different schemes, an effort to keep results consistent and comparable is needed. This study emphasizes commonly disregarded problems in the inference of evolutionary rates in viral sequence data when sampling is unevenly distributed on a temporal scale through a study of the foot-and-mouth (FMD) disease virus serotypes SAT 1 and SAT 2. Our study shows that clustered temporal sampling in phylogenetic analyses of FMD viruses will strongly bias the inferences of substitution rates and tMRCA because the inferred rates in such data sets reflect a rate closer to the mutation rate rather than the substitution rate. Estimating evolutionary parameters from viral sequences should be performed with due consideration of the differences in short-term and longer-term evolutionary processes occurring within sets of temporally sampled viruses, and studies should carefully consider how samples are combined.

Spatiotemporal clustering of the epigenome reveals rules of dynamic gene regulation

PubMed Central

Yu, Pengfei; Xiao, Shu; Xin, Xiaoyun; Song, Chun-Xiao; Huang, Wei; McDee, Darina; Tanaka, Tetsuya; Wang, Ting; He, Chuan; Zhong, Sheng

2013-01-01

Spatial organization of different epigenomic marks was used to infer functions of the epigenome. It remains unclear what can be learned from the temporal changes of the epigenome. Here, we developed a probabilistic model to cluster genomic sequences based on the similarity of temporal changes of multiple epigenomic marks during a cellular differentiation process. We differentiated mouse embryonic stem (ES) cells into mesendoderm cells. At three time points during this differentiation process, we used high-throughput sequencing to measure seven histone modifications and variants—H3K4me1/2/3, H3K27ac, H3K27me3, H3K36me3, and H2A.Z; two DNA modifications—5-mC and 5-hmC; and transcribed mRNAs and noncoding RNAs (ncRNAs). Genomic sequences were clustered based on the spatiotemporal epigenomic information. These clusters not only clearly distinguished gene bodies, promoters, and enhancers, but also were predictive of bidirectional promoters, miRNA promoters, and piRNAs. This suggests specific epigenomic patterns exist on piRNA genes much earlier than germ cell development. Temporal changes of H3K4me2, unmethylated CpG, and H2A.Z were predictive of 5-hmC changes, suggesting unmethylated CpG and H3K4me2 as potential upstream signals guiding TETs to specific sequences. Several rules on combinatorial epigenomic changes and their effects on mRNA expression and ncRNA expression were derived, including a simple rule governing the relationship between 5-hmC and gene expression levels. A Sox17 enhancer containing a FOXA2 binding site and a Foxa2 enhancer containing a SOX17 binding site were identified, suggesting a positive feedback loop between the two mesendoderm transcription factors. These data illustrate the power of using epigenome dynamics to investigate regulatory functions. PMID:23033340

Cluster analysis applied to the spatial and temporal variability of monthly rainfall in Mato Grosso do Sul State, Brazil

NASA Astrophysics Data System (ADS)

Teodoro, Paulo Eduardo; de Oliveira-Júnior, José Francisco; da Cunha, Elias Rodrigues; Correa, Caio Cezar Guedes; Torres, Francisco Eduardo; Bacani, Vitor Matheus; Gois, Givanildo; Ribeiro, Larissa Pereira

2016-04-01

The State of Mato Grosso do Sul (MS) located in Brazil Midwest is devoid of climatological studies, mainly in the characterization of rainfall regime and producers' meteorological systems and rain inhibitors. This state has different soil and climatic characteristics distributed among three biomes: Cerrado, Atlantic Forest and Pantanal. This study aimed to apply the cluster analysis using Ward's algorithm and identify those meteorological systems that affect the rainfall regime in the biomes. The rainfall data of 32 stations (sites) of the MS State were obtained from the Agência Nacional de Águas (ANA) database, collected from 1954 to 2013. In each of the 384 monthly rainfall temporal series was calculated the average and applied the Ward's algorithm to identify spatial and temporal variability of rainfall. Bartlett's test revealed only in January homogeneous variance at all sites. Run test showed that there was no increase or decrease in trend of monthly rainfall. Cluster analysis identified five rainfall homogeneous regions in the MS State, followed by three seasons (rainy, transitional and dry). The rainy season occurs during the months of November, December, January, February and March. The transitional season ranges between the months of April and May, September and October. The dry season occurs in June, July and August. The groups G1, G4 and G5 are influenced by South Atlantic Subtropical Anticyclone (SASA), Chaco's Low (CL), Bolivia's High (BH), Low Levels Jet (LLJ) and South Atlantic Convergence Zone (SACZ) and Maden-Julian Oscillation (MJO). Group G2 is influenced by Upper Tropospheric Cyclonic Vortex (UTCV) and Front Systems (FS). The group G3 is affected by UTCV, FS and SACZ. The meteorological systems' interaction that operates in each biome and the altitude causes the rainfall spatial and temporal diversity in MS State.

Fine Scale Spatiotemporal Clustering of Dengue Virus Transmission in Children and Aedes aegypti in Rural Thai Villages

DTIC Science & Technology

2012-07-01

as an ‘‘index’’ case to initiate a positive cluster investigation around the index case house. Cohort children who were dengue PCR-negative from an ...were collected on days 0 and 15. Paired day 0 and 15 blood samples from child contacts were tested by both dengue PCR and an in-house dengue /Japanese...viral infections globally. An improved understanding of the spatial and temporal distribution of dengue virus (DENV) transmission between humans and

High-throughput analysis of spatio-temporal dynamics in Dictyostelium

PubMed Central

Sawai, Satoshi; Guan, Xiao-Juan; Kuspa, Adam; Cox, Edward C

2007-01-01

We demonstrate a time-lapse video approach that allows rapid examination of the spatio-temporal dynamics of Dictyostelium cell populations. Quantitative information was gathered by sampling life histories of more than 2,000 mutant clones from a large mutagenesis collection. Approximately 4% of the clonal lines showed a mutant phenotype at one stage. Many of these could be ordered by clustering into functional groups. The dataset allows one to search and retrieve movies on a gene-by-gene and phenotype-by-phenotype basis. PMID:17659086

a Three-Step Spatial-Temporal Clustering Method for Human Activity Pattern Analysis

NASA Astrophysics Data System (ADS)

Huang, W.; Li, S.; Xu, S.

2016-06-01

How people move in cities and what they do in various locations at different times form human activity patterns. Human activity pattern plays a key role in in urban planning, traffic forecasting, public health and safety, emergency response, friend recommendation, and so on. Therefore, scholars from different fields, such as social science, geography, transportation, physics and computer science, have made great efforts in modelling and analysing human activity patterns or human mobility patterns. One of the essential tasks in such studies is to find the locations or places where individuals stay to perform some kind of activities before further activity pattern analysis. In the era of Big Data, the emerging of social media along with wearable devices enables human activity data to be collected more easily and efficiently. Furthermore, the dimension of the accessible human activity data has been extended from two to three (space or space-time) to four dimensions (space, time and semantics). More specifically, not only a location and time that people stay and spend are collected, but also what people "say" for in a location at a time can be obtained. The characteristics of these datasets shed new light on the analysis of human mobility, where some of new methodologies should be accordingly developed to handle them. Traditional methods such as neural networks, statistics and clustering have been applied to study human activity patterns using geosocial media data. Among them, clustering methods have been widely used to analyse spatiotemporal patterns. However, to our best knowledge, few of clustering algorithms are specifically developed for handling the datasets that contain spatial, temporal and semantic aspects all together. In this work, we propose a three-step human activity clustering method based on space, time and semantics to fill this gap. One-year Twitter data, posted in Toronto, Canada, is used to test the clustering-based method. The results show that the approximate 55% spatiotemporal clusters distributed in different locations can be eventually grouped as the same type of clusters with consideration of semantic aspect.

miRNA Temporal Analyzer (mirnaTA): a bioinformatics tool for identifying differentially expressed microRNAs in temporal studies using normal quantile transformation.

PubMed

Cer, Regina Z; Herrera-Galeano, J Enrique; Anderson, Joseph J; Bishop-Lilly, Kimberly A; Mokashi, Vishwesh P

2014-01-01

Understanding the biological roles of microRNAs (miRNAs) is a an active area of research that has produced a surge of publications in PubMed, particularly in cancer research. Along with this increasing interest, many open-source bioinformatics tools to identify existing and/or discover novel miRNAs in next-generation sequencing (NGS) reads become available. While miRNA identification and discovery tools are significantly improved, the development of miRNA differential expression analysis tools, especially in temporal studies, remains substantially challenging. Further, the installation of currently available software is non-trivial and steps of testing with example datasets, trying with one's own dataset, and interpreting the results require notable expertise and time. Subsequently, there is a strong need for a tool that allows scientists to normalize raw data, perform statistical analyses, and provide intuitive results without having to invest significant efforts. We have developed miRNA Temporal Analyzer (mirnaTA), a bioinformatics package to identify differentially expressed miRNAs in temporal studies. mirnaTA is written in Perl and R (Version 2.13.0 or later) and can be run across multiple platforms, such as Linux, Mac and Windows. In the current version, mirnaTA requires users to provide a simple, tab-delimited, matrix file containing miRNA name and count data from a minimum of two to a maximum of 20 time points and three replicates. To recalibrate data and remove technical variability, raw data is normalized using Normal Quantile Transformation (NQT), and linear regression model is used to locate any miRNAs which are differentially expressed in a linear pattern. Subsequently, remaining miRNAs which do not fit a linear model are further analyzed in two different non-linear methods 1) cumulative distribution function (CDF) or 2) analysis of variances (ANOVA). After both linear and non-linear analyses are completed, statistically significant miRNAs (P < 0.05) are plotted as heat maps using hierarchical cluster analysis and Euclidean distance matrix computation methods. mirnaTA is an open-source, bioinformatics tool to aid scientists in identifying differentially expressed miRNAs which could be further mined for biological significance. It is expected to provide researchers with a means of interpreting raw data to statistical summaries in a fast and intuitive manner.

Integrated community profiling indicates long-term temporal stability of the predominant faecal microbiota in captive cheetahs.

PubMed

Becker, Anne A M J; Janssens, Geert P J; Snauwaert, Cindy; Hesta, Myriam; Huys, Geert

2015-01-01

Understanding the symbiotic relationship between gut microbes and their animal host requires characterization of the core microbiota across populations and in time. Especially in captive populations of endangered wildlife species such as the cheetah (Acinonyx jubatus), this knowledge is a key element to enhance feeding strategies and reduce gastrointestinal disorders. In order to investigate the temporal stability of the intestinal microbiota in cheetahs under human care, we conducted a longitudinal study over a 3-year period with bimonthly faecal sampling of 5 cheetahs housed in two European zoos. For this purpose, an integrated 16S rRNA DGGE-clone library approach was used in combination with a series of real-time PCR assays. Our findings disclosed a stable faecal microbiota, beyond intestinal community variations that were detected between zoo sample sets or between animals. The core of this microbiota was dominated by members of Clostridium clusters I, XI and XIVa, with mean concentrations ranging from 7.5-9.2 log10 CFU/g faeces and with significant positive correlations between these clusters (P<0.05), and by Lactobacillaceae. Moving window analysis of DGGE profiles revealed 23.3-25.6% change between consecutive samples for four of the cheetahs. The fifth animal in the study suffered from intermediate episodes of vomiting and diarrhea during the monitoring period and exhibited remarkably more change (39.4%). This observation may reflect the temporary impact of perturbations such as the animal's compromised health, antibiotic administration or a combination thereof, which temporarily altered the relative proportions of Clostridium clusters I and XIVa. In conclusion, this first long-term monitoring study of the faecal microbiota in feline strict carnivores not only reveals a remarkable compositional stability of this ecosystem, but also shows a qualitative and quantitative similarity in a defined set of faecal bacterial lineages across the five animals under study that may typify the core phylogenetic microbiome of cheetahs.

Integrated Community Profiling Indicates Long-Term Temporal Stability of the Predominant Faecal Microbiota in Captive Cheetahs

PubMed Central

Becker, Anne A. M. J.; Janssens, Geert P. J.; Snauwaert, Cindy; Hesta, Myriam; Huys, Geert

2015-01-01

Understanding the symbiotic relationship between gut microbes and their animal host requires characterization of the core microbiota across populations and in time. Especially in captive populations of endangered wildlife species such as the cheetah (Acinonyx jubatus), this knowledge is a key element to enhance feeding strategies and reduce gastrointestinal disorders. In order to investigate the temporal stability of the intestinal microbiota in cheetahs under human care, we conducted a longitudinal study over a 3-year period with bimonthly faecal sampling of 5 cheetahs housed in two European zoos. For this purpose, an integrated 16S rRNA DGGE-clone library approach was used in combination with a series of real-time PCR assays. Our findings disclosed a stable faecal microbiota, beyond intestinal community variations that were detected between zoo sample sets or between animals. The core of this microbiota was dominated by members of Clostridium clusters I, XI and XIVa, with mean concentrations ranging from 7.5-9.2 log10 CFU/g faeces and with significant positive correlations between these clusters (P<0.05), and by Lactobacillaceae. Moving window analysis of DGGE profiles revealed 23.3-25.6% change between consecutive samples for four of the cheetahs. The fifth animal in the study suffered from intermediate episodes of vomiting and diarrhea during the monitoring period and exhibited remarkably more change (39.4%). This observation may reflect the temporary impact of perturbations such as the animal’s compromised health, antibiotic administration or a combination thereof, which temporarily altered the relative proportions of Clostridium clusters I and XIVa. In conclusion, this first long-term monitoring study of the faecal microbiota in feline strict carnivores not only reveals a remarkable compositional stability of this ecosystem, but also shows a qualitative and quantitative similarity in a defined set of faecal bacterial lineages across the five animals under study that may typify the core phylogenetic microbiome of cheetahs. PMID:25905625

Abnormal small-world architecture of top–down control networks in obsessive–compulsive disorder

PubMed Central

Zhang, Tijiang; Wang, Jinhui; Yang, Yanchun; Wu, Qizhu; Li, Bin; Chen, Long; Yue, Qiang; Tang, Hehan; Yan, Chaogan; Lui, Su; Huang, Xiaoqi; Chan, Raymond C.K.; Zang, Yufeng; He, Yong; Gong, Qiyong

2011-01-01

Background Obsessive–compulsive disorder (OCD) is a common neuropsychiatric disorder that is characterized by recurrent intrusive thoughts, ideas or images and repetitive ritualistic behaviours. Although focal structural and functional abnormalities in specific brain regions have been widely studied in populations with OCD, changes in the functional relations among them remain poorly understood. This study examined OCD–related alterations in functional connectivity patterns in the brain’s top–down control network. Methods We applied resting-state functional magnetic resonance imaging to investigate the correlation patterns of intrinsic or spontaneous blood oxygen level–dependent signal fluctuations in 18 patients with OCD and 16 healthy controls. The brain control networks were first constructed by thresholding temporal correlation matrices of 39 brain regions associated with top–down control and then analyzed using graph theory-based approaches. Results Compared with healthy controls, the patients with OCD showed decreased functional connectivity in the posterior temporal regions and increased connectivity in various control regions such as the cingulate, precuneus, thalamus and cerebellum. Furthermore, the brain’s control networks in the healthy controls showed small-world architecture (high clustering coefficients and short path lengths), suggesting an optimal balance between modularized and distributed information processing. In contrast, the patients with OCD showed significantly higher local clustering, implying abnormal functional organization in the control network. Further analysis revealed that the changes in network properties occurred in regions of increased functional connectivity strength in patients with OCD. Limitations The patient group in the present study was heterogeneous in terms of symptom clusters, and most of the patients with OCD were medicated. Conclusion Our preliminary results suggest that the organizational patterns of intrinsic brain activity in the control networks are altered in patients with OCD and thus provide empirical evidence for aberrant functional connectivity in the large-scale brain systems in people with this disorder. PMID:20964957

Evolution of auroral acceleration region field-aligned current systems, plasma, and potentials observed by Cluster during substorms

NASA Astrophysics Data System (ADS)

Hull, A. J.; Chaston, C. C.; Fillingim, M. O.; Frey, H. U.; Goldstein, M. L.; Bonnell, J. W.; Mozer, F.

2015-12-01

The auroral acceleration region is an integral link in the chain of events that transpire during substorms, and the currents, plasma and electric fields undergo significant changes driven by complex dynamical processes deep in the magnetotail. The acceleration processes that occur therein accelerate and heat the plasma that ultimately leads to some of the most intense global substorm auroral displays. Though this region has garnered considerable attention, the temporal evolution of field-aligned current systems, associated acceleration processes, and resultant changes in the plasma constituents that occur during key stages of substorm development remain unclear. In this study we present a survey of Cluster traversals within and just above the auroral acceleration region (≤3 Re altitude) during substorms. Particular emphasis is on the spatial morphology and developmental sequence of auroral acceleration current systems, potentials and plasma constituents, with the aim of identifying controlling factors, and assessing auroral emmission consequences. Exploiting multi-point measurements from Cluster in combination with auroral imaging, we reveal the injection powered, Alfvenic nature of both the substorm onset and expansion of auroral particle acceleration. We show evidence that indicates substorm onsets are characterized by the gross-intensification and filamentation/striation of pre-existing large-scale current systems to smaller/dispersive scale Alfven waves. Such an evolutionary sequence has been suggested in theoretical models or single spacecraft data, but has not been demonstrated or characterized in multispacecraft observations until now. It is also shown how the Alfvenic variations over time may dissipate to form large-scale inverted-V structures characteristic of the quasi-static aurora. These findings suggest that, in addition to playing active roles in driving substorm aurora, inverted-V and Alfvenic acceleration processes are causally linked. Key elements of substorm current spatial structure and temporal development, relationship to electric fields/potentials, plasma moment and distribution features, causal linkages to auroral emission features, and other properties will be discussed.

Detecting space-time disease clusters with arbitrary shapes and sizes using a co-clustering approach.

PubMed

Ullah, Sami; Daud, Hanita; Dass, Sarat C; Khan, Habib Nawaz; Khalil, Alamgir

2017-11-06

Ability to detect potential space-time clusters in spatio-temporal data on disease occurrences is necessary for conducting surveillance and implementing disease prevention policies. Most existing techniques use geometrically shaped (circular, elliptical or square) scanning windows to discover disease clusters. In certain situations, where the disease occurrences tend to cluster in very irregularly shaped areas, these algorithms are not feasible in practise for the detection of space-time clusters. To address this problem, a new algorithm is proposed, which uses a co-clustering strategy to detect prospective and retrospective space-time disease clusters with no restriction on shape and size. The proposed method detects space-time disease clusters by tracking the changes in space-time occurrence structure instead of an in-depth search over space. This method was utilised to detect potential clusters in the annual and monthly malaria data in Khyber Pakhtunkhwa Province, Pakistan from 2012 to 2016 visualising the results on a heat map. The results of the annual data analysis showed that the most likely hotspot emerged in three sub-regions in the years 2013-2014. The most likely hotspots in monthly data appeared in the month of July to October in each year and showed a strong periodic trend.

Spatio-temporal Hotelling observer for signal detection from image sequences

PubMed Central

Caucci, Luca; Barrett, Harrison H.; Rodríguez, Jeffrey J.

2010-01-01

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection. PMID:19550494

Spatio-temporal Hotelling observer for signal detection from image sequences.

PubMed

Caucci, Luca; Barrett, Harrison H; Rodriguez, Jeffrey J

2009-06-22

Detection of signals in noisy images is necessary in many applications, including astronomy and medical imaging. The optimal linear observer for performing a detection task, called the Hotelling observer in the medical literature, can be regarded as a generalization of the familiar prewhitening matched filter. Performance on the detection task is limited by randomness in the image data, which stems from randomness in the object, randomness in the imaging system, and randomness in the detector outputs due to photon and readout noise, and the Hotelling observer accounts for all of these effects in an optimal way. If multiple temporal frames of images are acquired, the resulting data set is a spatio-temporal random process, and the Hotelling observer becomes a spatio-temporal linear operator. This paper discusses the theory of the spatio-temporal Hotelling observer and estimation of the required spatio-temporal covariance matrices. It also presents a parallel implementation of the observer on a cluster of Sony PLAYSTATION 3 gaming consoles. As an example, we consider the use of the spatio-temporal Hotelling observer for exoplanet detection.

A longitudinal study of feed contamination by European starling excreta in Ohio dairy farms (2007-2008).

PubMed

Medhanie, G A; Pearl, D L; McEwen, S A; Guerin, M T; Jardine, C M; Schrock, J; LeJeune, J T

2014-01-01

The objectives of this study were to understand the temporal pattern of contamination of cattle feed by starling excrement on dairy farms and to evaluate the temporal pattern in recovering Escherichia coli O157:H7 or Salmonella in relation to the absolute mass of excrement recovered. A longitudinal study was conducted on 15 dairy farms in Ohio from July 2007 to October 2008. One open-topped tray filled with bird feed was placed near a cattle feeding site; bird excrement from the tray was weighed monthly for 12 consecutive months. Linear regression models with a random intercept for farm were computed to examine the association between the absolute weight of excrement recovered each month or the farm-specific standard score for weight of excrement, and month or season. Exact logistic regression was used to determine whether an association between recovering E. coli O157:H7 or Salmonella was present and the amount of excrement recovered and season. A spatial scan statistic was used to test for evidence of space-time clustering of excrement, based on the standard score for the weight of the excrement, among our study farms. A total of 5 of 179 excrement samples (2.79%) were positive for E. coli O157:H7 and 2 (1.12%) were positive for Salmonella. A significantly higher level of contamination with excrement was observed during the winter. The odds of recovering a pathogen increased with the amount of excrement recovered and decreased if the excrement was collected in the winter. A spatio-temporal cluster of contamination with excrement was detected. These findings provide basic information for future quantitative microbial risk assessments concerning the role of starlings in spreading enteric pathogens on dairy farms. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Voxel-based mapping of grey matter volume and glucose metabolism profiles in amyotrophic lateral sclerosis.

PubMed

Buhour, M-S; Doidy, F; Mondou, A; Pélerin, A; Carluer, L; Eustache, F; Viader, F; Desgranges, B

2017-12-01

Amyotrophic lateral sclerosis (ALS) is a rapidly progressive disease of the nervous system involving both upper and lower motor neurons. The patterns of structural and metabolic brain alterations are still unclear. Several studies using anatomical MRI yielded a number of discrepancies in their results, and a few PET studies investigated the effect of ALS on cerebral glucose metabolism. The aim of this study was threefold: to highlight the patterns of grey matter (GM) atrophy, hypometabolism and hypermetabolism in patients with ALS, then to understand the neurobehavioral significance of hypermetabolism and, finally, to investigate the regional differences between the morphologic and functional changes in ALS patients, using a specially designed voxel-based method. Thirty-seven patients with ALS and 37 age- and sex-matched healthy individuals underwent both structural MRI and 18 [F]-fluorodeoxyglucose (FDG) PET examinations. PET data were corrected for partial volume effects. Structural and metabolic abnormalities were examined in ALS patients compared with control subjects using two-sample t tests in statistical parametric mapping (SPM). Then, we extracted the metabolic values of clusters presenting hypermetabolism to correlate with selected cognitive scores. Finally, GM atrophy and hypometabolism patterns were directly compared with a one-paired t test in SPM. We found GM atrophy as well as hypometabolism in motor and extra motor regions and hypermetabolism in medial temporal lobe and cerebellum. We observed negative correlations between the metabolism of the right and left parahippocampal gyri and episodic memory and between the metabolism of right temporal pole and cognitive theory of mind. GM atrophy predominated in the temporal pole, left hippocampus and right thalamus, while hypometabolism predominated in a single cluster in the left frontal superior medial cortex. Our findings provide direct evidence of regional variations in the hierarchy and relationships between GM atrophy and hypometabolism in ALS. Moreover, the 18 FDG-PET investigation suggests that cerebral hypermetabolism is deleterious to cognitive function in ALS.

Reduced frequency and severity of residential fires following delivery of fire prevention education by on-duty fire fighters: cluster randomized controlled study.

PubMed

Clare, Joseph; Garis, Len; Plecas, Darryl; Jennings, Charles

2012-04-01

In 2008, Surrey Fire Services, British Columbia, commenced a firefighter-delivered, door-to-door fire-prevention education and smoke alarm examination/installation initiative with the intention of reducing the frequency and severity of residential structure fires in the City of Surrey. High-risk zones within the city were identified and 18,473 home visits were undertaken across seven temporal delivery cohorts (13.8% of non-apartment dwellings in the city). The frequency and severity of fires pre- and post- the home visit intervention was examined in comparison to randomized high-risk cluster controls. Overall, the frequency of fires was found to have reduced in the city overall, however, the reduction in the intervention cohorts was significantly larger than for controls. Furthermore, when fires did occur within the intervention cohorts, smoke detectors were activated more frequently and the fires were confined to the object of origin more often post-home visits. No equivalent pattern was observed for the cluster control. On-duty fire fighters can reduce the frequency and severity of residential fires through targeted, door-to-door distribution of fire prevention education in high-risk areas. Copyright © 2012 Elsevier Ltd. All rights reserved.

A Perfusion MRI Study of Emotional Valence and Arousal in Parkinson's Disease

PubMed Central

Limsoontarakul, Sunsern; Campbell, Meghan C.; Black, Kevin J.

2011-01-01

Background. Brain regions subserving emotion have mostly been studied using functional magnetic resonance imaging (fMRI) during emotion provocation procedures in healthy participants. Objective. To identify neuroanatomical regions associated with spontaneous changes in emotional state over time. Methods. Self-rated emotional valence and arousal scores, and regional cerebral blood flow (rCBF) measured by perfusion MRI, were measured 4 or 8 times spanning at least 2 weeks in each of 21 subjects with Parkinson's disease (PD). A random-effects SPM analysis, corrected for multiple comparisons, identified significant clusters of contiguous voxels in which rCBF varied with valence or arousal. Results. Emotional valence correlated positively with rCBF in several brain regions, including medial globus pallidus, orbital prefrontal cortex (PFC), and white matter near putamen, thalamus, insula, and medial PFC. Valence correlated negatively with rCBF in striatum, subgenual cingulate cortex, ventrolateral PFC, and precuneus—posterior cingulate cortex (PCC). Arousal correlated positively with rCBF in clusters including claustrum-thalamus-ventral striatum and inferior parietal lobule and correlated negatively in clusters including posterior insula—mediodorsal thalamus and midbrain. Conclusion. This study demonstrates that the temporal stability of perfusion MRI allows within-subject investigations of spontaneous fluctuations in mental state, such as mood, over relatively long-time intervals. PMID:21969917

Micro-epidemiology and spatial heterogeneity of P. vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis.

PubMed

Carrasco-Escobar, Gabriel; Gamboa, Dionicia; Castro, Marcia C; Bangdiwala, Shrikant I; Rodriguez, Hugo; Contreras-Mancilla, Juan; Alava, Freddy; Speybroeck, Niko; Lescano, Andres G; Vinetz, Joseph M; Rosas-Aguirre, Angel; Llanos-Cuentas, Alejandro

2017-08-14

Malaria has steadily increased in the Peruvian Amazon over the last five years. This study aimed to determine the parasite prevalence and micro-geographical heterogeneity of Plasmodium vivax parasitaemia in communities of the Peruvian Amazon. Four cross-sectional active case detection surveys were conducted between May and July 2015 in four riverine communities in Mazan district. Analysis of 2785 samples of 820 individuals nested within 154 households for Plasmodium parasitaemia was carried out using light microscopy and qPCR. The spatio-temporal distribution of Plasmodium parasitaemia, dominated by P. vivax, was shown to cluster at both household and community levels. Of enrolled individuals, 47% had at least one P. vivax parasitaemia and 10% P. falciparum, by qPCR, both of which were predominantly sub-microscopic and asymptomatic. Spatial analysis detected significant clustering in three communities. Our findings showed that communities at small-to-moderate spatial scales differed in P. vivax parasite prevalence, and multilevel Poisson regression models showed that such differences were influenced by factors such as age, education, and location of households within high-risk clusters, as well as factors linked to a local micro-geographic context, such as travel and occupation. Complex transmission patterns were found to be related to human mobility among communities in the same micro-basin.

The acquired immunodeficiency syndrome in the State of Rio de Janeiro, Brazil: a spatio-temporal analysis of cases reported in the period 2001-2010.

PubMed

Alves, André T J; Nobre, Flávio F

2014-05-01

Despite increased funding for research on the human immunodeficiency virus (HIV) and the acquired immunodeficiency syndrome (AIDS), neither vaccine nor cure is yet in sight. Surveillance and prevention are essential for disease intervention, and it is recognised that spatio-temporal analysis of AIDS cases can assist the decision-making process for control of the disease. This study investigated the dynamic, spatial distribution of notified AIDS cases in the State of Rio de Janeiro, Brazil, between 2001 and 2010, based on the annual incidence in each municipality. Sequential choropleth maps were developed and used to analyse the incidence distribution and Moran's I spatial autocorrelation statistics was applied for characterisation of the spatio-temporal distribution pattern. A significant, positive spatial autocorrelation of AIDS incidence was observed indicating that municipalities with high incidence are likely to be close to other municipalities with similarly high incidence and, conversely, municipalities with low incidence are likely to be surrounded by municipalities with low incidence. Two clusters were identified; one hotspot related to the State Capital and the other with low to intermediate AIDS incidence comprising municipalities in the north-eastern region of the State of Rio de Janeiro.

Foreshock and aftershocks in simple earthquake models.

PubMed

Kazemian, J; Tiampo, K F; Klein, W; Dominguez, R

2015-02-27

Many models of earthquake faults have been introduced that connect Gutenberg-Richter (GR) scaling to triggering processes. However, natural earthquake fault systems are composed of a variety of different geometries and materials and the associated heterogeneity in physical properties can cause a variety of spatial and temporal behaviors. This raises the question of how the triggering process and the structure interact to produce the observed phenomena. Here we present a simple earthquake fault model based on the Olami-Feder-Christensen and Rundle-Jackson-Brown cellular automata models with long-range interactions that incorporates a fixed percentage of stronger sites, or asperity cells, into the lattice. These asperity cells are significantly stronger than the surrounding lattice sites but eventually rupture when the applied stress reaches their higher threshold stress. The introduction of these spatial heterogeneities results in temporal clustering in the model that mimics that seen in natural fault systems along with GR scaling. In addition, we observe sequences of activity that start with a gradually accelerating number of larger events (foreshocks) prior to a main shock that is followed by a tail of decreasing activity (aftershocks). This work provides further evidence that the spatial and temporal patterns observed in natural seismicity are strongly influenced by the underlying physical properties and are not solely the result of a simple cascade mechanism.

The pace of Holocene vegetation change - testing for synchronous developments

NASA Astrophysics Data System (ADS)

Giesecke, Thomas; Bennett, K. D.; Birks, H. John B.; Bjune, Anne E.; Bozilova, Elisaveta; Feurdean, Angelica; Finsinger, Walter; Froyd, Cynthia; Pokorný, Petr; Rösch, Manfred; Seppä, Heikki; Tonkov, Spasimir; Valsecchi, Verushka; Wolters, Steffen

2011-09-01

Mid to high latitude forest ecosystems have undergone several major compositional changes during the Holocene. The temporal and spatial patterns of these vegetation changes hold potential information to their causes and triggers. Here we test the hypothesis that the timing of vegetation change was synchronous on a sub-continental scale, which implies a common trigger or a step-like change in climate parameters. Pollen diagrams from selected European regions were statistically divided into assemblage zones and the temporal pattern of the zone boundaries analysed. The results show that the temporal pattern of vegetation change was significantly different from random. Times of change cluster around 8.2, 4.8, 3.7, and 1.2 ka, while times of higher than average stability were found around 2.1 and 5.1 ka. Compositional changes linked to the expansion of Corylus avellana and Alnus glutinosa centre around 10.6 and 9.5 ka, respectively. A climatic trigger initiating these changes may have occurred 0.5 to 1 ka earlier, respectively. The synchronous expansion of C. avellana and A. glutinosa exemplify that dispersal is not necessarily followed by population expansion. The partly synchronous, partly random expansion of A. glutinosa in adjacent European regions exemplifies that sudden synchronous population expansions are not species specific traits but vary regionally.

Quantifying temporal bone morphology of great apes and humans: an approach using geometric morphometrics

PubMed Central

Lockwood, Charles A; Lynch, John M; Kimbel, William H

2002-01-01

The hominid temporal bone offers a complex array of morphology that is linked to several different functional systems. Its frequent preservation in the fossil record gives the temporal bone added significance in the study of human evolution, but its morphology has proven difficult to quantify. In this study we use techniques of 3D geometric morphometrics to quantify differences among humans and great apes and discuss the results in a phylogenetic context. Twenty-three landmarks on the ectocranial surface of the temporal bone provide a high level of anatomical detail. Generalized Procrustes analysis (GPA) is used to register (adjust for position, orientation and scale) landmark data from 405 adults representing Homo, Pan, Gorilla and Pongo. Principal components analysis of residuals from the GPA shows that the major source of variation is between humans and apes. Human characteristics such as a coronally orientated petrous axis, a deep mandibular fossa, a projecting mastoid process, and reduced lateral extension of the tympanic element strongly impact the analysis. In phenetic cluster analyses, gorillas and orangutans group together with respect to chimpanzees, and all apes group together with respect to humans. Thus, the analysis contradicts depictions of African apes as a single morphotype. Gorillas and orangutans lack the extensive preglenoid surface of chimpanzees, and their mastoid processes are less medially inflected. These and other characters shared by gorillas and orangutans are probably primitive for the African hominid clade. PMID:12489757

Simultaneous ERP and fMRI of the auditory cortex in a passive oddball paradigm.

PubMed

Liebenthal, Einat; Ellingson, Michael L; Spanaki, Marianna V; Prieto, Thomas E; Ropella, Kristina M; Binder, Jeffrey R

2003-08-01

Infrequent occurrences of a deviant sound within a sequence of repetitive standard sounds elicit the automatic mismatch negativity (MMN) event-related potential (ERP). The main MMN generators are located in the superior temporal cortex, but their number, precise location, and temporal sequence of activation remain unclear. In this study, ERP and functional magnetic resonance imaging (fMRI) data were obtained simultaneously during a passive frequency oddball paradigm. There were three conditions, a STANDARD, a SMALL deviant, and a LARGE deviant. A clustered image acquisition technique was applied to prevent contamination of the fMRI data by the acoustic noise of the scanner and to limit contamination of the electroencephalogram (EEG) by the gradient-switching artifact. The ERP data were used to identify areas in which the blood oxygenation (BOLD) signal varied with the magnitude of the negativity in each condition. A significant ERP MMN was obtained, with larger peaks to LARGE deviants and with frontocentral scalp distribution, consistent with the MMN reported outside the magnetic field. This result validates the experimental procedures for simultaneous ERP/fMRI of the auditory cortex. Main foci of increased BOLD signal were observed in the right superior temporal gyrus [STG; Brodmann area (BA) 22] and right superior temporal plane (STP; BA 41 and 42). The imaging results provide new information supporting the idea that generators in the right lateral aspect of the STG are implicated in processes of frequency deviant detection, in addition to generators in the right and left STP.

Can the effects of temporal grouping explain the similarities and differences between free recall and serial recall?

PubMed

Spurgeon, Jessica; Ward, Geoff; Matthews, William J; Farrell, Simon

2015-04-01

Temporal grouping can provide a principled explanation for changes in the serial position curves and output orders that occur with increasing list length in immediate free recall (IFR) and immediate serial recall (ISR). To test these claims, we examined the effects of temporal grouping on the order of recall in IFR and ISR of lists of between one and 12 words. Consistent with prior research, there were significant effects of temporal grouping in the ISR task with mid-length lists using serial recall scoring, and no overall grouping advantage in the IFR task with longer list lengths using free recall scoring. In all conditions, there was a general tendency to initiate recall with either the first list item or with one of the last four items, and then to recall in a forward serial order. In the grouped IFR conditions, when participants started with one of the last four words, there were particularly heightened tendencies to initiate recall with the first item of the most recent group. Moreover, there was an increased degree of forward-ordered transitions within groups than across groups in IFR. These findings are broadly consistent with Farrell's model, in which lists of items in immediate memory are parsed into distinct groups and participants initiate recall with the first item of a chosen cluster, but also highlight shortcomings of that model. The data support the claim that grouping may offer an important element in the theoretical integration of IFR and ISR.

Fish assemblage in a semi-arid Neotropical reservoir: composition, structure and patterns of diversity and abundance.

PubMed

Novaes, J L C; Moreira, S I L; Freire, C E C; Sousa, M M O; Costa, R S

2014-05-01

The aim of this study was to analyse the composition, structure and spatial and temporal patterns of diversity and abundance of the ichthyofauna of the Santa Cruz Reservoir in semi-arid Brazil. Data were collected quarterly at eight sampling locations on the reservoir between February 2010 and November 2011 using gillnets from 12- to 70-mm mesh that were left in the water for 12h00min during the night. We evaluated the composition, structure and assemblage descriptors (Shannon-Wiener diversity index and equitability, respectively) and catch per unit effort by the number (CPUEn) and biomass (CPUEb) of the ichthyofauna. The 6,047 individuals (399,211.6 g) captured represented three orders, ten families and 20 species, of which four belonged to introduced species. The family Characidae was the most abundant with a total of 2,772 (45.8%) individuals captured. The species-abundance curve fit the log-normal model. In the spatial analysis of diversity, there were significant differences between sampling sites in the lacustrine and fluvial regions, and the highest values were found in the lacustrine region. In the temporal analysis of diversity, significant differences were also observed between the rainy and dry seasons, and the higher values were found during the dry season. Equitability followed the same spatiotemporal pattern as diversity. The Spearman correlation was significantly negative between diversity and rainfall. A cluster analysis spatially separated the ichthyofauna into two groups: one group formed by sampling sites in the fluvial region and another group formed by the remainder of the points in the lacustrine region. Both the CPUEn and CPUEb values were higher at point 8 (fluvial region) and during the rainy season. A two-way ANOVA showed that the CPUEn and CPUEb values were spatially and temporally significant. We conclude that the spatial and temporal trends of diversity in the Santa Cruz reservoir differ from those of other Brazilian reservoirs but that the fish community composition and spatiotemporal patterns of abundance were similar.

A spatio-temporal analysis of forest loss related to cocaine trafficking in Central America

NASA Astrophysics Data System (ADS)

Sesnie, Steven E.; Tellman, Beth; Wrathall, David; McSweeney, Kendra; Nielsen, Erik; Benessaiah, Karina; Wang, Ophelia; Rey, Luis

2017-05-01

A growing body of evidence suggests that criminal activities associated with drug trafficking networks are a progressively important driver of forest loss in Central America. However, the scale at which drug trafficking represents a driver of forest loss is not presently known. We estimated the degree to which narcotics trafficking may contribute to forest loss using an unsupervised spatial clustering of 15 spatial and temporal forest loss patch metrics developed from global forest change data. We distinguished anomalous forest loss from background loss patches for each country exhibiting potential ‘narco-capitalized’ signatures which showed a statistically significant dissimilarity from other patches in terms of size, timing, and rate of forest loss. We also compared annual anomalous forest loss with the number of cocaine shipments and volume of cocaine seized, lost, or delivered at country- and department-level. For Honduras, results from linear mixed effects models showed a highly significant relationship between anomalous forest loss and the timing of increased drug trafficking (F = 9.90, p = 0.009) that also differed significantly from temporal patterns of background forest loss (t-ratio = 2.98, p = 0.004). Other locations of high forest loss in Central America showed mixed results. The timing of increased trafficking was not significantly related to anomalous forest loss in Guatemala and Nicaragua, but significantly differed in patch size compared to background losses. We estimated that cocaine trafficking could account for between 15% and 30% of annual national forest loss in these three countries over the past decade, and 30% to 60% of loss occurred within nationally and internationally designated protected areas. Cocaine trafficking is likely to have severe and lasting consequences in terms of maintaining moist tropical forest cover in Central America. Addressing forest loss in these and other tropical locations will require a stronger linkage between national and international drug interdiction and conservation policies.

Improvements on GPS Location Cluster Analysis for the Prediction of Large Carnivore Feeding Activities: Ground-Truth Detection Probability and Inclusion of Activity Sensor Measures

PubMed Central

Blecha, Kevin A.; Alldredge, Mat W.

2015-01-01

Animal space use studies using GPS collar technology are increasingly incorporating behavior based analysis of spatio-temporal data in order to expand inferences of resource use. GPS location cluster analysis is one such technique applied to large carnivores to identify the timing and location of feeding events. For logistical and financial reasons, researchers often implement predictive models for identifying these events. We present two separate improvements for predictive models that future practitioners can implement. Thus far, feeding prediction models have incorporated a small range of covariates, usually limited to spatio-temporal characteristics of the GPS data. Using GPS collared cougar (Puma concolor) we include activity sensor data as an additional covariate to increase prediction performance of feeding presence/absence. Integral to the predictive modeling of feeding events is a ground-truthing component, in which GPS location clusters are visited by human observers to confirm the presence or absence of feeding remains. Failing to account for sources of ground-truthing false-absences can bias the number of predicted feeding events to be low. Thus we account for some ground-truthing error sources directly in the model with covariates and when applying model predictions. Accounting for these errors resulted in a 10% increase in the number of clusters predicted to be feeding events. Using a double-observer design, we show that the ground-truthing false-absence rate is relatively low (4%) using a search delay of 2–60 days. Overall, we provide two separate improvements to the GPS cluster analysis techniques that can be expanded upon and implemented in future studies interested in identifying feeding behaviors of large carnivores. PMID:26398546

Localized shape abnormalities in the thalamus and pallidum are associated with secondarily generalized seizures in mesial temporal lobe epilepsy.

PubMed

Yang, Linglin; Li, Hong; Zhu, Lujia; Yu, Xinfeng; Jin, Bo; Chen, Cong; Wang, Shan; Ding, Meiping; Zhang, Minming; Chen, Zhong; Wang, Shuang

2017-05-01

Mesial temporal lobe epilepsy (mTLE) is a common type of drug-resistant epilepsy and secondarily generalized tonic-clonic seizures (sGTCS) have devastating consequences for patients' safety and quality of life. To probe the mechanism underlying the genesis of sGTCS, we investigated the structural differences between patients with and without sGTCS in a cohort of mTLE with radiologically defined unilateral hippocampal sclerosis. We performed voxel-based morphometric analysis of cortex and vertex-wise shape analysis of subcortical structures (the basal ganglia and thalamus) on MRI of 39 patients (21 with and 18 without sGTCS). Comparisons were initially made between sGTCS and non-sGTCS groups, and subsequently made between uncontrolled-sGTCS and controlled-sGTCS subgroups. Regional atrophy of the ipsilateral ventral pallidum (cluster size=450 voxels, corrected p=0.047, Max voxel coordinate=107, 120, 65), medial thalamus (cluster size=1128 voxels, corrected p=0.049, Max voxel coordinate=107, 93, 67), middle frontal gyrus (cluster size=60 voxels, corrected p<0.05, Max voxel coordinate=-30, 49.5, 6), and contralateral posterior cingulate cortex (cluster size=130 voxels, corrected p<0.05, Max voxel coordinate=16.5, -57, 27) was found in the sGTCS group relative to the non-sGTCS group. Furthermore, the uncontrolled-sGTCS subgroup showed more pronounced atrophy of the ipsilateral medial thalamus (cluster size=1240 voxels, corrected p=0.014, Max voxel coordinate=107, 93, 67) than the controlled-sGTCS subgroup. These findings indicate a central role of thalamus and pallidum in the pathophysiology of sGTCS in mTLE. Copyright © 2017 Elsevier Inc. All rights reserved.

A mathematical programming approach for sequential clustering of dynamic networks

NASA Astrophysics Data System (ADS)

Silva, Jonathan C.; Bennett, Laura; Papageorgiou, Lazaros G.; Tsoka, Sophia

2016-02-01

A common analysis performed on dynamic networks is community structure detection, a challenging problem that aims to track the temporal evolution of network modules. An emerging area in this field is evolutionary clustering, where the community structure of a network snapshot is identified by taking into account both its current state as well as previous time points. Based on this concept, we have developed a mixed integer non-linear programming (MINLP) model, SeqMod, that sequentially clusters each snapshot of a dynamic network. The modularity metric is used to determine the quality of community structure of the current snapshot and the historical cost is accounted for by optimising the number of node pairs co-clustered at the previous time point that remain so in the current snapshot partition. Our method is tested on social networks of interactions among high school students, college students and members of the Brazilian Congress. We show that, for an adequate parameter setting, our algorithm detects the classes that these students belong more accurately than partitioning each time step individually or by partitioning the aggregated snapshots. Our method also detects drastic discontinuities in interaction patterns across network snapshots. Finally, we present comparative results with similar community detection methods for time-dependent networks from the literature. Overall, we illustrate the applicability of mathematical programming as a flexible, adaptable and systematic approach for these community detection problems. Contribution to the Topical Issue "Temporal Network Theory and Applications", edited by Petter Holme.

Spatio-Temporal Regression Based Clustering of Precipitation Extremes in a Presence of Systematically Missing Covariates

NASA Astrophysics Data System (ADS)

Kaiser, Olga; Martius, Olivia; Horenko, Illia

2017-04-01

Regression based Generalized Pareto Distribution (GPD) models are often used to describe the dynamics of hydrological threshold excesses relying on the explicit availability of all of the relevant covariates. But, in real application the complete set of relevant covariates might be not available. In this context, it was shown that under weak assumptions the influence coming from systematically missing covariates can be reflected by a nonstationary and nonhomogenous dynamics. We present a data-driven, semiparametric and an adaptive approach for spatio-temporal regression based clustering of threshold excesses in a presence of systematically missing covariates. The nonstationary and nonhomogenous behavior of threshold excesses is describes by a set of local stationary GPD models, where the parameters are expressed as regression models, and a non-parametric spatio-temporal hidden switching process. Exploiting nonparametric Finite Element time-series analysis Methodology (FEM) with Bounded Variation of the model parameters (BV) for resolving the spatio-temporal switching process, the approach goes beyond strong a priori assumptions made is standard latent class models like Mixture Models and Hidden Markov Models. Additionally, the presented FEM-BV-GPD provides a pragmatic description of the corresponding spatial dependence structure by grouping together all locations that exhibit similar behavior of the switching process. The performance of the framework is demonstrated on daily accumulated precipitation series over 17 different locations in Switzerland from 1981 till 2013 - showing that the introduced approach allows for a better description of the historical data.

Visualizing Confidence in Cluster-Based Ensemble Weather Forecast Analyses.

PubMed

Kumpf, Alexander; Tost, Bianca; Baumgart, Marlene; Riemer, Michael; Westermann, Rudiger; Rautenhaus, Marc

2018-01-01

In meteorology, cluster analysis is frequently used to determine representative trends in ensemble weather predictions in a selected spatio-temporal region, e.g., to reduce a set of ensemble members to simplify and improve their analysis. Identified clusters (i.e., groups of similar members), however, can be very sensitive to small changes of the selected region, so that clustering results can be misleading and bias subsequent analyses. In this article, we - a team of visualization scientists and meteorologists-deliver visual analytics solutions to analyze the sensitivity of clustering results with respect to changes of a selected region. We propose an interactive visual interface that enables simultaneous visualization of a) the variation in composition of identified clusters (i.e., their robustness), b) the variability in cluster membership for individual ensemble members, and c) the uncertainty in the spatial locations of identified trends. We demonstrate that our solution shows meteorologists how representative a clustering result is, and with respect to which changes in the selected region it becomes unstable. Furthermore, our solution helps to identify those ensemble members which stably belong to a given cluster and can thus be considered similar. In a real-world application case we show how our approach is used to analyze the clustering behavior of different regions in a forecast of "Tropical Cyclone Karl", guiding the user towards the cluster robustness information required for subsequent ensemble analysis.

Application of Scan Statistics to Detect Suicide Clusters in Australia

PubMed Central

Cheung, Yee Tak Derek; Spittal, Matthew J.; Williamson, Michelle Kate; Tung, Sui Jay; Pirkis, Jane

2013-01-01

Background Suicide clustering occurs when multiple suicide incidents take place in a small area or/and within a short period of time. In spite of the multi-national research attention and particular efforts in preparing guidelines for tackling suicide clusters, the broader picture of epidemiology of suicide clustering remains unclear. This study aimed to develop techniques in using scan statistics to detect clusters, with the detection of suicide clusters in Australia as example. Methods and Findings Scan statistics was applied to detect clusters among suicides occurring between 2004 and 2008. Manipulation of parameter settings and change of area for scan statistics were performed to remedy shortcomings in existing methods. In total, 243 suicides out of 10,176 (2.4%) were identified as belonging to 15 suicide clusters. These clusters were mainly located in the Northern Territory, the northern part of Western Australia, and the northern part of Queensland. Among the 15 clusters, 4 (26.7%) were detected by both national and state cluster detections, 8 (53.3%) were only detected by the state cluster detection, and 3 (20%) were only detected by the national cluster detection. Conclusions These findings illustrate that the majority of spatial-temporal clusters of suicide were located in the inland northern areas, with socio-economic deprivation and higher proportions of indigenous people. Discrepancies between national and state/territory cluster detection by scan statistics were due to the contrast of the underlying suicide rates across states/territories. Performing both small-area and large-area analyses, and applying multiple parameter settings may yield the maximum benefits for exploring clusters. PMID:23342098

Evaluation of Solute Clusters Associated with Bake-Hardening Response in Isothermal Aged Al-Mg-Si Alloys Using a Three-Dimensional Atom Probe

NASA Astrophysics Data System (ADS)

Aruga, Yasuhiro; Kozuka, Masaya; Takaki, Yasuo; Sato, Tatsuo

2014-12-01

Temporal changes in the number density, size distribution, and chemical composition of clusters formed during natural aging at room temperature and pre-aging at 363 K (90 °C) in an Al-0.62Mg-0.93Si (mass pct) alloy were evaluated using atom probe tomography. More than 10 million atoms were examined in the cluster analysis, in which about 1000 clusters were obtained for each material after various aging treatments. The statistically proven records show that both number density and the average radius of clusters in pre-aged materials are larger than in naturally aged materials. It was revealed that the fraction of clusters with a low Mg/Si ratio after natural aging for a short time is higher than with other aging treatments, regardless of cluster size. This indicates that Si-rich clusters form more easily after short-period natural aging, and that Mg atoms can diffuse into the clusters or possibly form another type of Mg-Si cluster after prolonged natural aging. The formation of large clusters with a uniform Mg/Si ratio is encouraged by pre-aging. It can be concluded that an increase of small clusters with various Mg/Si ratios does not promote the bake-hardening (BH) response, whereas large clusters with a uniform Mg/Si ratio play an important role in hardening during the BH treatment at 443 K (170 °C).

Differential regulation of ParaHox genes by retinoic acid in the invertebrate chordate amphioxus (Branchiostoma floridae).

PubMed

Osborne, Peter W; Benoit, Gérard; Laudet, Vincent; Schubert, Michael; Ferrier, David E K

2009-03-01

The ParaHox cluster is the evolutionary sister to the Hox cluster. Like the Hox cluster, the ParaHox cluster displays spatial and temporal regulation of the component genes along the anterior/posterior axis in a manner that correlates with the gene positions within the cluster (a feature called collinearity). The ParaHox cluster is however a simpler system to study because it is composed of only three genes. We provide a detailed analysis of the amphioxus ParaHox cluster and, for the first time in a single species, examine the regulation of the cluster in response to a single developmental signalling molecule, retinoic acid (RA). Embryos treated with either RA or RA antagonist display altered ParaHox gene expression: AmphiGsx expression shifts in the neural tube, and the endodermal boundary between AmphiXlox and AmphiCdx shifts its anterior/posterior position. We identified several putative retinoic acid response elements and in vitro assays suggest some may participate in RA regulation of the ParaHox genes. By comparison to vertebrate ParaHox gene regulation we explore the evolutionary implications. This work highlights how insights into the regulation and evolution of more complex vertebrate arrangements can be obtained through studies of a simpler, unduplicated amphioxus gene cluster.

Hemodynamic Response to Interictal Epileptiform Discharges Addressed by Personalized EEG-fNIRS Recordings

PubMed Central

Pellegrino, Giovanni; Machado, Alexis; von Ellenrieder, Nicolas; Watanabe, Satsuki; Hall, Jeffery A.; Lina, Jean-Marc; Kobayashi, Eliane; Grova, Christophe

2016-01-01

Objective: We aimed at studying the hemodynamic response (HR) to Interictal Epileptic Discharges (IEDs) using patient-specific and prolonged simultaneous ElectroEncephaloGraphy (EEG) and functional Near InfraRed Spectroscopy (fNIRS) recordings. Methods: The epileptic generator was localized using Magnetoencephalography source imaging. fNIRS montage was tailored for each patient, using an algorithm to optimize the sensitivity to the epileptic generator. Optodes were glued using collodion to achieve prolonged acquisition with high quality signal. fNIRS data analysis was handled with no a priori constraint on HR time course, averaging fNIRS signals to similar IEDs. Cluster-permutation analysis was performed on 3D reconstructed fNIRS data to identify significant spatio-temporal HR clusters. Standard (GLM with fixed HRF) and cluster-permutation EEG-fMRI analyses were performed for comparison purposes. Results: fNIRS detected HR to IEDs for 8/9 patients. It mainly consisted oxy-hemoglobin increases (seven patients), followed by oxy-hemoglobin decreases (six patients). HR was lateralized in six patients and lasted from 8.5 to 30 s. Standard EEG-fMRI analysis detected an HR in 4/9 patients (4/9 without enough IEDs, 1/9 unreliable result). The cluster-permutation EEG-fMRI analysis restricted to the region investigated by fNIRS showed additional strong and non-canonical BOLD responses starting earlier than the IEDs and lasting up to 30 s. Conclusions: (i) EEG-fNIRS is suitable to detect the HR to IEDs and can outperform EEG-fMRI because of prolonged recordings and greater chance to detect IEDs; (ii) cluster-permutation analysis unveils additional HR features underestimated when imposing a canonical HR function (iii) the HR is often bilateral and lasts up to 30 s. PMID:27047325

The spatio-temporal mapping of epileptic networks: Combination of EEG–fMRI and EEG source imaging

PubMed Central

Vulliemoz, S.; Thornton, R.; Rodionov, R.; Carmichael, D.W.; Guye, M.; Lhatoo, S.; McEvoy, A.W.; Spinelli, L.; Michel, C.M.; Duncan, J.S.; Lemieux, L.

2009-01-01

Simultaneous EEG–fMRI acquisitions in patients with epilepsy often reveal distributed patterns of Blood Oxygen Level Dependant (BOLD) change correlated with epileptiform discharges. We investigated if electrical source imaging (ESI) performed on the interictal epileptiform discharges (IED) acquired during fMRI acquisition could be used to study the dynamics of the networks identified by the BOLD effect, thereby avoiding the limitations of combining results from separate recordings. Nine selected patients (13 IED types identified) with focal epilepsy underwent EEG–fMRI. Statistical analysis was performed using SPM5 to create BOLD maps. ESI was performed on the IED recorded during fMRI acquisition using a realistic head model (SMAC) and a distributed linear inverse solution (LAURA). ESI could not be performed in one case. In 10/12 remaining studies, ESI at IED onset (ESIo) was anatomically close to one BOLD cluster. Interestingly, ESIo was closest to the positive BOLD cluster with maximal statistical significance in only 4/12 cases and closest to negative BOLD responses in 4/12 cases. Very small BOLD clusters could also have clinical relevance in some cases. ESI at later time frame (ESIp) showed propagation to remote sources co-localised with other BOLD clusters in half of cases. In concordant cases, the distance between maxima of ESI and the closest EEG–fMRI cluster was less than 33 mm, in agreement with previous studies. We conclude that simultaneous ESI and EEG–fMRI analysis may be able to distinguish areas of BOLD response related to initiation of IED from propagation areas. This combination provides new opportunities for investigating epileptic networks. PMID:19408351

Spatio-temporal pattern clustering for skill assessment of the Korea Operational Oceanographic System

NASA Astrophysics Data System (ADS)

Kim, J.; Park, K.

2016-12-01

In order to evaluate the performance of operational forecast models in the Korea operational oceanographic system (KOOS) which has been developed by Korea Institute of Ocean Science and Technology (KIOST), a skill assessment (SA) tool has developed and provided multiple skill metrics including not only correlation and error skills by comparing predictions and observation but also pattern clustering with numerical models, satellite, and observation. The KOOS has produced 72 hours forecast information on atmospheric and hydrodynamic forecast variables of wind, pressure, current, tide, wave, temperature, and salinity at every 12 hours per day produced by operating numerical models such as WRF, ROMS, MOM5, WW-III, and SWAN and the SA has conducted to evaluate the forecasts. We have been operationally operated several kinds of numerical models such as WRF, ROMS, MOM5, MOHID, WW-III. Quantitative assessment of operational ocean forecast model is very important to provide accurate ocean forecast information not only to general public but also to support ocean-related problems. In this work, we propose a method of pattern clustering using machine learning method and GIS-based spatial analytics to evaluate spatial distribution of numerical models and spatial observation data such as satellite and HF radar. For the clustering, we use 10 or 15 years-long reanalysis data which was computed by the KOOS, ECMWF, and HYCOM to make best matching clusters which are classified physical meaning with time variation and then we compare it with forecast data. Moreover, for evaluating current, we develop extraction method of dominant flow and apply it to hydrodynamic models and HF radar's sea surface current data. By applying pattern clustering method, it allows more accurate and effective assessment of ocean forecast models' performance by comparing not only specific observation positions which are determined by observation stations but also spatio-temporal distribution of whole model areas. We believe that our proposed method will be very useful to examine and evaluate large amount of numerical modeling data as well as satellite data.

Village-based spatio-temporal cluster analysis of the schistosomiasis risk in the Poyang Lake Region, China.

PubMed

Xia, Congcong; Bergquist, Robert; Lynn, Henry; Hu, Fei; Lin, Dandan; Hao, Yuwan; Li, Shizhu; Hu, Yi; Zhang, Zhijie

2017-03-08

The Poyang Lake Region, one of the major epidemic sites of schistosomiasis in China, remains a severe challenge. To improve our understanding of the current endemic status of schistosomiasis and to better control the transmission of the disease in the Poyang Lake Region, it is important to analyse the clustering pattern of schistosomiasis and detect the hotspots of transmission risk. Based on annual surveillance data, at the village level in this region from 2009 to 2014, spatial and temporal cluster analyses were conducted to assess the pattern of schistosomiasis infection risk among humans through purely spatial (Local Moran's I, Kulldorff and Flexible scan statistic) and space-time scan statistics (Kulldorff). A dramatic decline was found in the infection rate during the study period, which was shown to be maintained at a low level. The number of spatial clusters declined over time and were concentrated in counties around Poyang Lake, including Yugan, Yongxiu, Nanchang, Xingzi, Xinjian, De'an as well as Pengze, situated along the Yangtze River and the most serious area found in this study. Space-time analysis revealed that the clustering time frame appeared between 2009 and 2011 and the most likely cluster with the widest range was particularly concentrated in Pengze County. This study detected areas at high risk for schistosomiasis both in space and time at the village level from 2009 to 2014 in Poyang Lake Region. The high-risk areas are now more concentrated and mainly distributed at the river inflows Poyang Lake and along Yangtze River in Pengze County. It was assumed that the water projects including reservoirs and a recently breached dyke in this area were partly to blame. This study points out that attempts to reduce the negative effects of water projects in China should focus on the Poyang Lake Region.

Amyloid and Tau PET Demonstrate Region-Specific Associations in Normal Older People

PubMed Central

Lockhart, Samuel N.; Schöll, Michael; Baker, Suzanne L.; Ayakta, Nagehan; Swinnerton, Kaitlin N.; Bell, Rachel K.; Mellinger, Taylor J.; Shah, Vyoma D.; O’Neil, James P.; Janabi, Mustafa; Jagust, William J.

2017-01-01

β-amyloid (Aβ) and tau pathology become increasingly prevalent with age, however, the spatial relationship between the two pathologies remains unknown. We examined local (same region) and non-local (different region) associations between these 2 aggregated proteins in 46 normal older adults using [18F]AV-1451 (for tau) and [11C]PiB (for Aβ) positron emission tomography (PET) and 1.5T magnetic resonance imaging (MRI) images. While local voxelwise analyses showed associations between PiB and AV-1451 tracer largely in the temporal lobes, k-means clustering revealed that some of these associations were driven by regions with low tracer retention. We followed this up with a whole-brain region-by-region (local and non-local) partial correlational analysis. We calculated each participant’s mean AV-1451 and PiB uptake values within 87 regions of interest (ROI). Pairwise ROI analysis demonstrated many positive PiB—AV-1451 associations. Importantly, strong positive partial correlations (controlling for age, sex, and global gray matter fraction, p < .01) were identified between PiB in multiple regions of association cortex and AV-1451 in temporal cortical ROIs. There were also less frequent and weaker positive associations of regional PiB with frontoparietal AV-1451 uptake. Particularly in temporal lobe ROIs, AV-1451 uptake was strongly predicted by PiB across multiple ROI locations. These data indicate that Aβ and tau pathology show significant local and non-local regional associations among cognitively normal elderly, with increased PiB uptake throughout the cortex correlating with increased temporal lobe AV-1451 uptake. The spatial relationship between Aβ and tau accumulation does not appear to be specific to Aβ location, suggesting a regional vulnerability of temporal brain regions to tau accumulation regardless of where Aβ accumulates. PMID:28232190

Using Clustering to Establish Climate Regimes from PCM Output

NASA Technical Reports Server (NTRS)

Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.

2002-01-01

A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.

Alternative splicing modulates Kv channel clustering through a molecular ball and chain mechanism

NASA Astrophysics Data System (ADS)

Zandany, Nitzan; Marciano, Shir; Magidovich, Elhanan; Frimerman, Teddy; Yehezkel, Rinat; Shem-Ad, Tzilhav; Lewin, Limor; Abdu, Uri; Orr, Irit; Yifrach, Ofer

2015-03-01

Ion channel clustering at the post-synaptic density serves a fundamental role in action potential generation and transmission. Here, we show that interaction between the Shaker Kv channel and the PSD-95 scaffold protein underlying channel clustering is modulated by the length of the intrinsically disordered C terminal channel tail. We further show that this tail functions as an entropic clock that times PSD-95 binding. We thus propose a ‘ball and chain’ mechanism to explain Kv channel binding to scaffold proteins, analogous to the mechanism describing channel fast inactivation. The physiological relevance of this mechanism is demonstrated in that alternative splicing of the Shaker channel gene to produce variants of distinct tail lengths resulted in differential channel cell surface expression levels and clustering metrics that correlate with differences in affinity of the variants for PSD-95. We suggest that modulating channel clustering by specific spatial-temporal spliced variant targeting serves a fundamental role in nervous system development and tuning.

Spatial clustering of average risks and risk trends in Bayesian disease mapping.

PubMed

Anderson, Craig; Lee, Duncan; Dean, Nema

2017-01-01

Spatiotemporal disease mapping focuses on estimating the spatial pattern in disease risk across a set of nonoverlapping areal units over a fixed period of time. The key aim of such research is to identify areas that have a high average level of disease risk or where disease risk is increasing over time, thus allowing public health interventions to be focused on these areas. Such aims are well suited to the statistical approach of clustering, and while much research has been done in this area in a purely spatial setting, only a handful of approaches have focused on spatiotemporal clustering of disease risk. Therefore, this paper outlines a new modeling approach for clustering spatiotemporal disease risk data, by clustering areas based on both their mean risk levels and the behavior of their temporal trends. The efficacy of the methodology is established by a simulation study, and is illustrated by a study of respiratory disease risk in Glasgow, Scotland. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Spatial spread of dengue in a non-endemic tropical city in northern Argentina.

PubMed

Gil, José F; Palacios, Maximiliano; Krolewiecki, Alejandro J; Cortada, Pedro; Flores, Rosana; Jaime, Cesar; Arias, Luis; Villalpando, Carlos; Alberti DÁmato, Anahí M; Nasser, Julio R; Aparicio, Juan P

2016-06-01

After more than eighty years dengue reemerged in Argentina in 1997. Since then, the largest epidemic in terms of geographical extent, magnitude and mortality, was recorded in 2009. In this report we analyzed the DEN-1 epidemic spread in Orán, a mid-size city in a non-endemic tropical area in Northern Argentina, and its correlation with demographic and socioeconomic factors. Cases were diagnosed by ELISA between January and June 2009. We applied a space-time and spatial scan statistic under a Poisson model. Possible association between dengue incidence and socio-economic variables was studied with the Spearman correlation test. The epidemic started from an imported case from Bolivia and space-time analysis detected two clusters: one on February and other in April (in the south and the northeast of the city respectively) with risk ratios of 25.24 and 4.07 (p<0.01). Subsequent cases spread widely around the city without significant space-temporal clustering. Maximum values of the entomological indices were observed in January, at the beginning of the epidemic (B=21.96; LH=8.39). No statistically significant association between socioeconomic variables and dengue incidence was found but positive correlation between population size and the number of cases (p<0.05) was detected. Two mechanisms may explain the observed pattern of epidemic spread in this non-endemic tropical city: a) Short range dispersal of mosquitoes and people generates clusters of cases and b) long-distance (within the city) human movement contributes to a quasi-random distribution of cases. Copyright © 2016 Elsevier B.V. All rights reserved.

Using coordinate-based meta-analyses to explore structural imaging genetics.

PubMed

Janouschek, Hildegard; Eickhoff, Claudia R; Mühleisen, Thomas W; Eickhoff, Simon B; Nickl-Jockschat, Thomas

2018-05-05

Imaging genetics has become a highly popular approach in the field of schizophrenia research. A frequently reported finding is that effects from common genetic variation are associated with a schizophrenia-related structural endophenotype. Genetic contributions to a structural endophenotype may be easier to delineate, when referring to biological rather than diagnostic criteria. We used coordinate-based meta-analyses, namely the anatomical likelihood estimation (ALE) algorithm on 30 schizophrenia-related imaging genetics studies, representing 44 single-nucleotide polymorphisms at 26 gene loci investigated in 4682 subjects. To test whether analyses based on biological information would improve the convergence of results, gene ontology (GO) terms were used to group the findings from the published studies. We did not find any significant results for the main contrast. However, our analysis enrolling studies on genotype × diagnosis interaction yielded two clusters in the left temporal lobe and the medial orbitofrontal cortex. All other subanalyses did not yield any significant results. To gain insight into possible biological relationships between the genes implicated by these clusters, we mapped five of them to GO terms of the category "biological process" (AKT1, CNNM2, DISC1, DTNBP1, VAV3), then five to "cellular component" terms (AKT1, CNNM2, DISC1, DTNBP1, VAV3), and three to "molecular function" terms (AKT1, VAV3, ZNF804A). A subsequent cluster analysis identified representative, non-redundant subsets of semantically similar terms that aided a further interpretation. We regard this approach as a new option to systematically explore the richness of the literature in imaging genetics.

Cluster analysis of water-quality data for Lake Sakakawea, Audubon Lake, and McClusky Canal, central North Dakota, 1990-2003

USGS Publications Warehouse

Ryberg, Karen R.

2006-01-01

As a result of the Dakota Water Resources Act of 2000, the Bureau of Reclamation, U.S. Department of the Interior, identified eight water-supply alternatives (including a no-action alternative) to meet future water needs in portions of the Red River of the North (Red River) Basin. Of those alternatives, four include the interbasin transfer of water from the Missouri River Basin to the Red River Basin. Three of the interbasin transfer alternatives would use the McClusky Canal, located in central North Dakota, to transport the water. Therefore, the water quality of the McClusky Canal and the sources of its water, Lake Sakakawea and Audubon Lake, is of interest to water-quality stakeholders. The Bureau of Reclamation collected water-quality samples at 23 sites on Lake Sakakawea, Audubon Lake, and the McClusky Canal system from 1990 through 2003. Physical properties and water-quality constituents from these samples were summarized and analyzed by the U.S. Geological Survey using hierarchical agglomerative cluster analysis (HACA). HACA separated the samples into related clusters, or groups. These groups were examined for statistical significance and relation to structure of the McClusky Canal system. Statistically, the sample groupings found using HACA were significantly different from each other and appear to result from spatial and temporal water-quality differences corresponding with different sections of the canal and different operational conditions. Future operational changes of the canal system may justify additional water-quality sampling to characterize possible water-quality changes.

An Efficient Data Compression Model Based on Spatial Clustering and Principal Component Analysis in Wireless Sensor Networks.

PubMed

Yin, Yihang; Liu, Fengzheng; Zhou, Xiang; Li, Quanzhong

2015-08-07

Wireless sensor networks (WSNs) have been widely used to monitor the environment, and sensors in WSNs are usually power constrained. Because inner-node communication consumes most of the power, efficient data compression schemes are needed to reduce the data transmission to prolong the lifetime of WSNs. In this paper, we propose an efficient data compression model to aggregate data, which is based on spatial clustering and principal component analysis (PCA). First, sensors with a strong temporal-spatial correlation are grouped into one cluster for further processing with a novel similarity measure metric. Next, sensor data in one cluster are aggregated in the cluster head sensor node, and an efficient adaptive strategy is proposed for the selection of the cluster head to conserve energy. Finally, the proposed model applies principal component analysis with an error bound guarantee to compress the data and retain the definite variance at the same time. Computer simulations show that the proposed model can greatly reduce communication and obtain a lower mean square error than other PCA-based algorithms.

Unsupervised feature relevance analysis applied to improve ECG heartbeat clustering.

PubMed

Rodríguez-Sotelo, J L; Peluffo-Ordoñez, D; Cuesta-Frau, D; Castellanos-Domínguez, G

2012-10-01

The computer-assisted analysis of biomedical records has become an essential tool in clinical settings. However, current devices provide a growing amount of data that often exceeds the processing capacity of normal computers. As this amount of information rises, new demands for more efficient data extracting methods appear. This paper addresses the task of data mining in physiological records using a feature selection scheme. An unsupervised method based on relevance analysis is described. This scheme uses a least-squares optimization of the input feature matrix in a single iteration. The output of the algorithm is a feature weighting vector. The performance of the method was assessed using a heartbeat clustering test on real ECG records. The quantitative cluster validity measures yielded a correctly classified heartbeat rate of 98.69% (specificity), 85.88% (sensitivity) and 95.04% (general clustering performance), which is even higher than the performance achieved by other similar ECG clustering studies. The number of features was reduced on average from 100 to 18, and the temporal cost was a 43% lower than in previous ECG clustering schemes. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Kernel spectral clustering with memory effect

NASA Astrophysics Data System (ADS)

Langone, Rocco; Alzate, Carlos; Suykens, Johan A. K.

2013-05-01

Evolving graphs describe many natural phenomena changing over time, such as social relationships, trade markets, metabolic networks etc. In this framework, performing community detection and analyzing the cluster evolution represents a critical task. Here we propose a new model for this purpose, where the smoothness of the clustering results over time can be considered as a valid prior knowledge. It is based on a constrained optimization formulation typical of Least Squares Support Vector Machines (LS-SVM), where the objective function is designed to explicitly incorporate temporal smoothness. The latter allows the model to cluster the current data well and to be consistent with the recent history. We also propose new model selection criteria in order to carefully choose the hyper-parameters of our model, which is a crucial issue to achieve good performances. We successfully test the model on four toy problems and on a real world network. We also compare our model with Evolutionary Spectral Clustering, which is a state-of-the-art algorithm for community detection of evolving networks, illustrating that the kernel spectral clustering with memory effect can achieve better or equal performances.

Patterns of mortality in a montane mixed-conifer forest in San Diego County, California.

PubMed

Freeman, Mary Pyott; Stow, Douglas A; An, Li

2017-10-01

We examine spatial patterns of conifer tree mortality and their changes over time for the montane mixed-conifer forests of San Diego County. These forest areas have recently experienced extensive tree mortality due to multiple factors. A spatial contextual image processing approach was utilized with high spatial resolution digital airborne imagery to map dead trees for the years 1997, 2000, 2002, and 2005 for three study areas: Palomar, Volcan, and Laguna mountains. Plot-based fieldwork was conducted to further assess mortality patterns. Mean mortality remained static from 1997 to 2002 (4, 2.2, and 4.2 trees/ha for Palomar, Volcan, and Laguna) and then increased by 2005 to 10.3, 9.7, and 5.2 trees/ha, respectively. The increase in mortality between 2002 and 2005 represents the temporal pattern of a discrete disturbance event, attributable to the 2002-2003 drought. Dead trees are significantly clustered for all dates, based on spatial cluster analysis, indicating that they form distinct groups, as opposed to spatially random single dead trees. Other tests indicate no directional shift or spread of mortality over time, but rather an increase in density. While general temporal and spatial mortality processes are uniform across all study areas, the plot-based species and quantity distribution of mortality, and diameter distributions of dead vs. living trees, vary by study area. The results of this study improve our understanding of stand- to landscape-level forest structure and dynamics, particularly by examining them from the multiple perspectives of field and remotely sensed data. © 2017 by the Ecological Society of America.

Spatio-temporal scan statistics for the detection of outbreaks involving common molecular subtypes: using human cases of Escherichia coli O157:H7 provincial PFGE pattern 8 (National Designation ECXAI.0001) in Alberta as an example.

PubMed

So, H C; Pearl, D L; von Königslöw, T; Louie, M; Chui, L; Svenson, L W

2013-08-01

Molecular typing methods have become a common part of the surveillance of foodborne pathogens. In particular, pulsed-field gel electrophoresis (PFGE) has been used successfully to identify outbreaks of Escherichia coli O157:H7 in humans from a variety of food and environmental sources. However, some PFGE patterns appear commonly in surveillance systems, making it more difficult to distinguish between outbreak and sporadic cases based on molecular data alone. In addition, it is unknown whether these common patterns might have unique epidemiological characteristics reflected in their spatial and temporal distributions. Using E. coli O157:H7 surveillance data from Alberta, collected from 2000 to 2002, we investigated whether E. coli O157:H7 with provincial PFGE pattern 8 (national designation ECXAI.0001) clustered in space, time and space-time relative to other PFGE patterns using the spatial scan statistic. Based on our purely spatial and temporal scans using a Bernoulli model, there did not appear to be strong evidence that isolates of E. coli O157:H7 with provincial PFGE pattern 8 are distributed differently from other PFGE patterns. However, we did identify space-time clusters of isolates with PFGE pattern 8, using a Bernoulli model and a space-time permutation model, which included known outbreaks and potentially unrecognized outbreaks or additional outbreak cases. There were differences between the two models in the space-time clusters identified, which suggests that the use of both models could increase the sensitivity of a quantitative surveillance system for identifying outbreaks involving isolates sharing a common PFGE pattern. © 2012 Blackwell Verlag GmbH.

Timing matters: the interval between acute stressors within chronic mild stress modifies behavioral and physiologic stress responses in male rats.

PubMed

Cavigelli, Sonia A; Bao, Alexander D; Bourne, Rebecca A; Caruso, Michael J; Caulfield, Jasmine I; Chen, Mary; Smyth, Joshua M

2018-04-12

Chronic mild stress can lead to negative health outcomes. Frequency, duration, and intensity of acute stressors can affect health-related processes. We tested whether the temporal pattern of daily acute stressors (clustered or dispersed across the day) affects depression-related physiology. We used a rodent model to keep stressor frequency, duration, and intensity constant, and experimentally manipulated the temporal pattern of acute stressors delivered during the active phase of the day. Adult male Sprague-Dawley rats were exposed to one of three chronic mild stress groups: Clustered: stressors that occurred within 1 hour of each other (n = 21), Dispersed: stressors that were spread out across the active phase (n = 21), and Control: no stressors presented (n = 21). Acute mild stressors included noise, strobe lights, novel cage, cage tilt, wet bedding, and water immersion. Depression-related outcomes included: sucrose preference, body weight, circulating glucocorticoid (corticosterone) concentration after a novel acute stressor and during basal morning and evening times, and endotoxin-induced circulating interleukin-6 concentrations. Compared to control rats, those in the Clustered group gained less weight, consumed less sucrose, had a blunted acute corticosterone response, and an accentuated acute interleukin-6 response. Rats in the Dispersed group had an attenuated corticosterone decline during the active period and after an acute stressor compared to the Control group. During a chronic mild stress experience, the temporal distribution of daily acute stressors affected health-related physiologic processes. Regular exposure to daily stressors in rapid succession may predict more depression-related symptoms, whereas exposure to stressors dispersed throughout the day may predict diminished glucocorticoid negative feedback.

Temporal Variability of Oral Microbiota over 10 Months and the Implications for Future Epidemiologic Studies.

PubMed

Vogtmann, Emily; Hua, Xing; Zhou, Liang; Wan, Yunhu; Suman, Shalabh; Zhu, Bin; Dagnall, Casey L; Hutchinson, Amy; Jones, Kristine; Hicks, Belynda D; Sinha, Rashmi; Shi, Jianxin; Abnet, Christian C

2018-05-01

Background: Few studies have prospectively evaluated the association between oral microbiota and health outcomes. Precise estimates of the intrasubject microbial metric stability will allow better study planning. Therefore, we conducted a study to evaluate the temporal variability of oral microbiota. Methods: Forty individuals provided six oral samples using the OMNIgene ORAL kit and Scope mouthwash oral rinses approximately every two months over 10 months. DNA was extracted using the QIAsymphony and the V4 region of the 16S rRNA gene was amplified and sequenced using the MiSeq. To estimate temporal variation, we calculated intraclass correlation coefficients (ICCs) for a variety of metrics and examined stability after clustering samples into distinct community types using Dirichlet multinomial models (DMMs). Results: The ICCs for the alpha diversity measures were high, including for number of observed bacterial species [0.74; 95% confidence interval (CI): 0.65-0.82 and 0.79; 95% CI: 0.75-0.94] from OMNIgene ORAL and Scope mouthwash, respectively. The ICCs for the relative abundance of the top four phyla and beta diversity matrices were lower. Three clusters provided the best model fit for the DMM from the OMNIgene ORAL samples, and the probability of remaining in a specific cluster was high (59.5%-80.7%). Conclusions: The oral microbiota appears to be stable over time for multiple metrics, but some measures, particularly relative abundance, were less stable. Impact: We used this information to calculate stability-adjusted power calculations that will inform future field study protocols and experimental analytic designs. Cancer Epidemiol Biomarkers Prev; 27(5); 594-600. ©2018 AACR . ©2018 American Association for Cancer Research.

Temporal variation of PM10 concentration and properties in Istanbul 2007-2015

NASA Astrophysics Data System (ADS)

Flores, Rosa M.; Kaya, Nefel; Eşer, Övgü; Saltan, Şehnaz

2017-04-01

The study of temporal variation of atmospheric aerosols is essential for a better understanding of sources, transport, and accumulation in the atmosphere. In addition, the study of aerosol properties is important for the understanding of their formation and potential impacts on ecosystems and climate change. Istanbul is a Megacity that often shows exceedance in particulate matter (PM) standard values, especially during the winter season. In this work, temporal variations of hourly ground-level PM10 concentrations, aerosol optical depth (AOD), aerosol index (AI), vertical distribution, and mineral dust loadings were investigated according to air mass trajectory clusters in Istanbul during 2007-2015. Aerosol properties (i.e., AOD, AI, and vertical distribution) and mineral dust loadings were retrieved from satellite observations and the BSC-DREAM8b model, respectively. Air mass backward trajectories and clustering were supplied by NOAA-HYSPLIT model. Mineral dust transport events were characterized according to the exceedance of a dust loading threshold value. The total number of mineral dust transport events ranged from 115 to 183 during the study period. The largest number of mineral dust transport events were observed in 2008 and 2014. However, the highest ground-level PM10 measurements were observed in 2012-2013 with approximately 70% of the daily average concentrations exceeding the air quality standard of 50 µg m-3. Overall, 5-6 air mass trajectory clusters were able to resolve over 85% of the total spatial variance. These trajectories vary in frequency and direction throughout the years, however, the main trajectories favor aerosol transport from N, NE, NNE, and S, and SE. Evaluation of mineral dust loading and PM10 concentrations is helpful for successful development and implementation of air quality management strategies on local levels.

Identification of Dlk1-Dio3 imprinted gene cluster noncoding RNAs as novel candidate biomarkers for liver tumor promotion.

PubMed

Lempiäinen, Harri; Couttet, Philippe; Bolognani, Federico; Müller, Arne; Dubost, Valérie; Luisier, Raphaëlle; Del Rio Espinola, Alberto; Vitry, Veronique; Unterberger, Elif B; Thomson, John P; Treindl, Fridolin; Metzger, Ute; Wrzodek, Clemens; Hahne, Florian; Zollinger, Tulipan; Brasa, Sarah; Kalteis, Magdalena; Marcellin, Magali; Giudicelli, Fanny; Braeuning, Albert; Morawiec, Laurent; Zamurovic, Natasa; Längle, Ulrich; Scheer, Nico; Schübeler, Dirk; Goodman, Jay; Chibout, Salah-Dine; Marlowe, Jennifer; Theil, Diethilde; Heard, David J; Grenet, Olivier; Zell, Andreas; Templin, Markus F; Meehan, Richard R; Wolf, Roland C; Elcombe, Clifford R; Schwarz, Michael; Moulin, Pierre; Terranova, Rémi; Moggs, Jonathan G

2013-02-01

The molecular events during nongenotoxic carcinogenesis and their temporal order are poorly understood but thought to include long-lasting perturbations of gene expression. Here, we have investigated the temporal sequence of molecular and pathological perturbations at early stages of phenobarbital (PB) mediated liver tumor promotion in vivo. Molecular profiling (mRNA, microRNA [miRNA], DNA methylation, and proteins) of mouse liver during 13 weeks of PB treatment revealed progressive increases in hepatic expression of long noncoding RNAs and miRNAs originating from the Dlk1-Dio3 imprinted gene cluster, a locus that has recently been associated with stem cell pluripotency in mice and various neoplasms in humans. PB induction of the Dlk1-Dio3 cluster noncoding RNA (ncRNA) Meg3 was localized to glutamine synthetase-positive hypertrophic perivenous hepatocytes, suggesting a role for β-catenin signaling in the dysregulation of Dlk1-Dio3 ncRNAs. The carcinogenic relevance of Dlk1-Dio3 locus ncRNA induction was further supported by in vivo genetic dependence on constitutive androstane receptor and β-catenin pathways. Our data identify Dlk1-Dio3 ncRNAs as novel candidate early biomarkers for mouse liver tumor promotion and provide new opportunities for assessing the carcinogenic potential of novel compounds.

Affective traits of psychopathy are linked to white-matter abnormalities in impulsive male offenders.

PubMed

Vermeij, Anouk; Kempes, Maaike M; Cima, Maaike J; Mars, Rogier B; Brazil, Inti A

2018-04-26

Psychopathy is a personality disorder typified by lack of empathy and impulsive antisocial behavior. Psychopathic traits may partly relate to disrupted connections between brain regions. The aim of the present study was to link abnormalities in microstructural integrity of white-matter tracts to the severity of different psychopathic traits in 15 male offenders with impulse control problems and 10 without impulse control problems. Psychopathic traits were assessed using the Psychopathy Checklist-revised (PCL-R). Diffusion-weighted MRI was used to examine white-matter tracts. Fractional anisotropy (FA), an index of white-matter integrity, was calculated for each voxel. Clusters of voxels showing a significant relationship with psychopathy severity were submitted to probabilistic tractography. No significant correlations between psychopathy severity and FA were present in the whole group of impulsive and nonimpulsive offenders. In impulsive offenders, interpersonal-affective traits (PCL-R Factor 1) were negatively correlated with FA in the anterior and posterior temporal lobe and orbitofrontal area. Further analyses indicated that elevated affective traits (PCL-R Facet 2) were specifically related to reduced FA in the right temporal lobe. Our findings suggest that white-matter abnormalities in temporal and frontotemporal tracts may be linked to the interpersonal-affective deficits of psychopathy in offenders with relatively severe impulse control problems. Our study offers novel insights into the relationships between the four facets of psychopathy and disrupted structural connectivity, and may provide new leads for further characterization of different subtypes of antisocial populations. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Graph theoretical analysis reveals disrupted topological properties of whole brain functional networks in temporal lobe epilepsy.

PubMed

Wang, Junjing; Qiu, Shijun; Xu, Yong; Liu, Zhenyin; Wen, Xue; Hu, Xiangshu; Zhang, Ruibin; Li, Meng; Wang, Wensheng; Huang, Ruiwang

2014-09-01

Temporal lobe epilepsy (TLE) is one of the most common forms of drug-resistant epilepsy. Previous studies have indicated that the TLE-related impairments existed in extensive local functional networks. However, little is known about the alterations in the topological properties of whole brain functional networks. In this study, we acquired resting-state BOLD-fMRI (rsfMRI) data from 26 TLE patients and 25 healthy controls, constructed their whole brain functional networks, compared the differences in topological parameters between the TLE patients and the controls, and analyzed the correlation between the altered topological properties and the epilepsy duration. The TLE patients showed significant increases in clustering coefficient and characteristic path length, but significant decrease in global efficiency compared to the controls. We also found altered nodal parameters in several regions in the TLE patients, such as the bilateral angular gyri, left middle temporal gyrus, right hippocampus, triangular part of left inferior frontal gyrus, left inferior parietal but supramarginal and angular gyri, and left parahippocampus gyrus. Further correlation analysis showed that the local efficiency of the TLE patients correlated positively with the epilepsy duration. Our results indicated the disrupted topological properties of whole brain functional networks in TLE patients. Our findings indicated the TLE-related impairments in the whole brain functional networks, which may help us to understand the clinical symptoms of TLE patients and offer a clue for the diagnosis and treatment of the TLE patients. Copyright © 2014 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Correlation buildup during recrystallization in three-dimensional dusty plasma clusters

DOE Office of Scientific and Technical Information (OSTI.GOV)

Schella, André; Mulsow, Matthias; Melzer, André

2014-05-15

The recrystallization process of finite three-dimensional dust clouds after laser heating is studied experimentally. The time-dependent Coulomb coupling parameter is presented, showing that the recrystallization starts with an exponential cooling phase where cooling is slower than damping by the neutral gas friction. At later times, the coupling parameter oscillates into equilibrium. It is found that a large fraction of cluster states after recrystallization experiments is in metastable states. The temporal evolution of the correlation buildup shows that correlation occurs on even slower time scale than cooling.

Using Dynamic Time Warping and Data Forensics to Examine Tradeoffs among Land-Energy-Water Networks Across the Conterminous United States

NASA Astrophysics Data System (ADS)

McManamay, R.; Allen, M. R.; Piburn, J.; Sanyal, J.; Stewart, R.; Bhaduri, B. L.

2017-12-01

Characterizing interdependencies among land-energy-water sectors, their vulnerabilities, and tipping points, is challenging, especially if all sectors are simultaneously considered. Because such holistic system behavior is uncertain, largely unmodeled, and in need of testable hypotheses of system drivers, these dynamics are conducive to exploratory analytics of spatiotemporal patterns, powered by tools, such as Dynamic Time Warping (DTW). Here, we conduct a retrospective analysis (1950 - 2010) of temporal trends in land use, energy use, and water use within US counties to identify commonalities in resource consumption and adaptation strategies to resource limitations. We combine existing and derived data from statistical downscaling to synthesize a temporally comprehensive land-energy-water dataset at the US county level and apply DTW and subsequent hierarchical clustering to examine similar temporal trends in resource typologies for land, energy, and water sectors. As expected, we observed tradeoffs among water uses (e.g., public supply vs irrigation) and land uses (e.g., urban vs ag). Strong associations between clusters amongst sectors reveal tight system interdependencies, whereas weak associations suggest unique behaviors and potential for human adaptations towards disruptive technologies and less resource-dependent population growth. Our framework is useful for exploring complex human-environmental system dynamics and generating hypotheses to guide subsequent energy-water-nexus research.

Techniques for spatio-temporal analysis of vegetation fires in the topical belt of Africa

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brivio, P.A.; Ober, G.; Koffi, B.

1995-12-31

Biomass burning of forests and savannas is a phenomenon of continental or even global proportions, capable of causing large scale environmental changes. Satellite space observations, in particular from NOAA-AVHRR GAC data, are the only source of information allowing one to document burning patterns at regional and continental scale and over long periods of time. This paper presents some techniques, such as clustering and rose-diagram, useful in the spatial-temporal analysis of satellite derived fires maps to characterize the evolution of spatial patterns of vegetation fires at regional scale. An automatic clustering approach is presented which enables one to describe and parameterizemore » spatial distribution of fire patterns at different scales. The problem of geographical distribution of vegetation fires with respect to some location of interest, point or line, is also considered and presented. In particular rose-diagrams are used to relate fires patterns to some reference point, as experimental sites of tropospheric chemistry measurements. Different temporal data-sets in the tropical belt of Africa, covering both Northern and Southern Hemisphere dry seasons, using these techniques were analyzed and showed very promising results when compared with data from rain chemistry studies at different sampling sites in the equatorial forest.« less

The influence of natural factors on the spatio-temporal distribution of Oncomelania hupensis.

PubMed

Cheng, Gong; Li, Dan; Zhuang, Dafang; Wang, Yong

2016-12-01

We analyzed the influence of natural factors, such as temperature, rainfall, vegetation and hydrology, on the spatio-temporal distribution of Oncomelania hupensis and explored the leading factors influencing these parameters. The results will provide reference methods and theoretical a basis for the schistosomiasis control. GIS (Geographic Information System) spatial display and analysis were used to describe the spatio-temporal distribution of Oncomelania hupensis in the study area (Dongting Lake in Hunan Province) from 2004 to 2011. Correlation analysis was used to detect the natural factors associated with the spatio-temporal distribution of O. hupensis. Spatial regression analysis was used to quantitatively analyze the effects of related natural factors on the spatio-temporal distribution of snails and explore the dominant factors influencing this parameter. (1) Overall, the spatio-temporal distribution of O. hupensis was governed by the comprehensive effects of natural factors. In the study area, the average density of living snails showed a downward trend, with the exception of a slight rebound in 2009. The density of living snails showed significant spatial clustering, and the degree of aggregation was initially weak but enhanced later. Regions with high snail density and towns with an HH distribution pattern were mostly distributed in the plain areas in the northwestern and inlet and outlet of the lake. (2) There were space-time differences in the influence of natural factors on the spatio-temporal distribution of O. hupensis. Temporally, the comprehensive influence of natural factors on snail distribution increased first and then decreased. Natural factors played an important role in snail distribution in 2005, 2006, 2010 and 2011. Spatially, it decreased from the northeast to the southwest. Snail distributions in more than 20 towns located along the Yuanshui River and on the west side of the Lishui River were less affected by natural factors, whereas relatively larger in areas around the outlet of the lake (Chenglingji) were more affected. (3) The effects of natural factors on the spatio-temporal distribution of O. hupensis were spatio-temporally heterogeneous. Rainfall, land surface temperature, NDVI, and distance from water sources all played an important role in the spatio-temporal distribution of O. hupensis. In addition, due to the effects of the local geographical environment, the direction of the influences the average annual rainfall, land surface temperature, and NDVI had on the spatio-temporal distribution of O. hupensis were all spatio-temporally heterogeneous, and both the distance from water sources and the history of snail distribution always had positive effects on the distribution O. hupensis, but the direction of the influence was spatio-temporally heterogeneous. (4) Of all the natural factors, the leading factors influencing the spatio-temporal distribution of O. hupensis were rainfall and vegetation (NDVI), and the primary factor alternated between these two. The leading role of rainfall decreased year by year, while that of vegetation (NDVI) increased from 2004 to 2011. The spatio-temporal distribution of O. hupensis was significantly influenced by natural factors, and the influences were heterogeneous across space and time. Additionally, the variation in the spatial-temporal distribution of O. hupensis was mainly affected by rainfall and vegetation. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

Three list scheduling temporal partitioning algorithm of time space characteristic analysis and compare for dynamic reconfigurable computing

NASA Astrophysics Data System (ADS)

Chen, Naijin

2013-03-01

Level Based Partitioning (LBP) algorithm, Cluster Based Partitioning (CBP) algorithm and Enhance Static List (ESL) temporal partitioning algorithm based on adjacent matrix and adjacent table are designed and implemented in this paper. Also partitioning time and memory occupation based on three algorithms are compared. Experiment results show LBP partitioning algorithm possesses the least partitioning time and better parallel character, as far as memory occupation and partitioning time are concerned, algorithms based on adjacent table have less partitioning time and less space memory occupation.

Storyline Visualizations of Eye Tracking of Movie Viewing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Balint, John T.; Arendt, Dustin L.; Blaha, Leslie M.

Storyline visualizations offer an approach that promises to capture the spatio-temporal characteristics of individual observers and simultaneously illustrate emerging group behaviors. We develop a visual analytics approach to parsing, aligning, and clustering fixation sequences from eye tracking data. Visualization of the results captures the similarities and differences across a group of observers performing a common task. We apply our storyline approach to visualize gaze patterns of people watching dynamic movie clips. Storylines mitigate some of the shortcomings of existent spatio-temporal visualization techniques and, importantly, continue to highlight individual observer behavioral dynamics.

Measuring local genetic variability in populations of codling moth (Lepidoptera: Tortricidae) across an unmanaged and commercial orchard interface.

PubMed

Fuentes-Contreras, Eduardo; Basoalto, Esteban; Franck, Pierre; Lavandero, Blas; Knight, Alan L; Ramírez, Claudio C

2014-04-01

The genetic structure of adult codling moth, Cydia pomonella (L.), populations was characterized both inside a managed apple, Malus domestica Borkdhausen, orchard and in surrounding unmanaged hosts and nonhost trees in central Chile during 2006-2007. Adult males were collected using an array of sex pheromone-baited traps. Five microsatellite genetic markers were used to study the population genetic structure across both spatial (1-100 ha) and temporal (generations within a season) gradients. Analysis of molecular variance (AMOVA) found a significant, but weak, association in both the spatial and temporal genetic structures. Discriminant analysis also found significant differentiation between the first and second generation for traps located either inside or outside the managed orchard. The Bayesian assignment test detected three genetic clusters during each of the two generations, which corresponded to different areas within the unmanaged and managed apple orchard interface. The lack of a strong spatial structure at a local scale was hypothesized to be because of active adult movement between the managed and unmanaged hosts and the asymmetry in the insecticide selection pressure inside and outside the managed habitats. These data highlight the importance of developing area-wide management programs that incorporate management tactics effective at the landscape level for successful codling moth control.

Temporal Lobe Epilepsy Alters Auditory-motor Integration For Voice Control

PubMed Central

Li, Weifeng; Chen, Ziyi; Yan, Nan; Jones, Jeffery A.; Guo, Zhiqiang; Huang, Xiyan; Chen, Shaozhen; Liu, Peng; Liu, Hanjun

2016-01-01

Temporal lobe epilepsy (TLE) is the most common drug-refractory focal epilepsy in adults. Previous research has shown that patients with TLE exhibit decreased performance in listening to speech sounds and deficits in the cortical processing of auditory information. Whether TLE compromises auditory-motor integration for voice control, however, remains largely unknown. To address this question, event-related potentials (ERPs) and vocal responses to vocal pitch errors (1/2 or 2 semitones upward) heard in auditory feedback were compared across 28 patients with TLE and 28 healthy controls. Patients with TLE produced significantly larger vocal responses but smaller P2 responses than healthy controls. Moreover, patients with TLE exhibited a positive correlation between vocal response magnitude and baseline voice variability and a negative correlation between P2 amplitude and disease duration. Graphical network analyses revealed a disrupted neuronal network for patients with TLE with a significant increase of clustering coefficients and path lengths as compared to healthy controls. These findings provide strong evidence that TLE is associated with an atypical integration of the auditory and motor systems for vocal pitch regulation, and that the functional networks that support the auditory-motor processing of pitch feedback errors differ between patients with TLE and healthy controls. PMID:27356768

Genome-Wide Gene Expression in relation to Age in Large Laboratory Cohorts of Drosophila melanogaster

PubMed Central

Carlson, Kimberly A.; Gardner, Kylee; Pashaj, Anjeza; Carlson, Darby J.; Yu, Fang; Eudy, James D.; Zhang, Chi; Harshman, Lawrence G.

2015-01-01

Aging is a complex process characterized by a steady decline in an organism's ability to perform life-sustaining tasks. In the present study, two cages of approximately 12,000 mated Drosophila melanogaster females were used as a source of RNA from individuals sampled frequently as a function of age. A linear model for microarray data method was used for the microarray analysis to adjust for the box effect; it identified 1,581 candidate aging genes. Cluster analyses using a self-organizing map algorithm on the 1,581 significant genes identified gene expression patterns across different ages. Genes involved in immune system function and regulation, chorion assembly and function, and metabolism were all significantly differentially expressed as a function of age. The temporal pattern of data indicated that gene expression related to aging is affected relatively early in life span. In addition, the temporal variance in gene expression in immune function genes was compared to a random set of genes. There was an increase in the variance of gene expression within each cohort, which was not observed in the set of random genes. This observation is compatible with the hypothesis that D. melanogaster immune function genes lose control of gene expression as flies age. PMID:26090231

The neural correlates of moral decision-making: A systematic review and meta-analysis of moral evaluations and response decision judgements.

PubMed

Garrigan, Beverley; Adlam, Anna L R; Langdon, Peter E

2016-10-01

The aims of this systematic review were to determine: (a) which brain areas are consistently more active when making (i) moral response decisions, defined as choosing a response to a moral dilemma, or deciding whether to accept a proposed solution, or (ii) moral evaluations, defined as judging the appropriateness of another's actions in a moral dilemma, rating moral statements as right or wrong, or identifying important moral issues; and (b) shared and significantly different activation patterns for these two types of moral judgements. A systematic search of the literature returned 28 experiments. Activation likelihood estimate analysis identified the brain areas commonly more active for moral response decisions and for moral evaluations. Conjunction analysis revealed shared activation for both types of moral judgement in the left middle temporal gyrus, cingulate gyrus, and medial frontal gyrus. Contrast analyses found no significant clusters of increased activation for the moral evaluations-moral response decisions contrast, but found that moral response decisions additionally activated the left and right middle temporal gyrus and the right precuneus. Making one's own moral decisions involves different brain areas compared to judging the moral actions of others, implying that these judgements may involve different processes. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.