A new predictive model for the bioconcentration factors of polychlorinated biphenyls (PCBs) based on the molecular electronegativity distance vector (MEDV).

PubMed

Qin, Li-Tang; Liu, Shu-Shen; Liu, Hai-Ling; Ge, Hui-Lin

2008-02-01

Polychlorinated biphenyls (PCBs) are some of the most prevalent pollutants in the total environment and receive more and more concerns as a group of ubiquitous potential persistent organic pollutants. Using the variable selection and modeling based on prediction (VSMP), the molecular electronegativity distance vector (MEDV) derived directly from the molecular topological structures was employed to develop a linear model (MI) between the bioconcentration factors (BCF) and two MEDV descriptors of 58 PCBs. The MI model showed a good estimation ability with a correlation coefficient (r) of 0.9605 and a high stability with a leave-one-out cross-validation correlation coefficient (q) of 0.9564. The MEDV-base model (MI) is easier to use than the splinoid poset method reported by Ivanciuc et al. [Ivanciuc, T., Ivanciuc, O., Klein, D.J., 2006. Modeling the bioconcentration factors and bioaccumulation factors of polychlorinated biphenyls with posetic quatitative super-structure/activity relationships (QSSAR). Mol. Divers. 10, 133-145] and gives a better statistics than molecular connectivity index (MCI)-base model developed by Hu et al. [Hu, H.Y., Xu, F.L., Li, B.G., Cao, J., Dawson, R., Tao, S., 2005. Prediction of the bioconcentration factor of PCBs in fish using the molecular connectivity index and fragment constant models. Water Environ. Res. 77, 87-97]. Main structural factors influencing the BCF of PCBs are the substructures expressed by two atomic groups >C= and -CH=. 58 PCBs were divided into an "odd set" and "even set" in order to ensure the predicted potential of the MI for the external samples. It was shown that three models, MI, MO for "odd set", and ME for "even set", can be used to predict the BCF of remaining 152 PCBs in which the experimental BCFs are not available.

Common neighbours and the local-community-paradigm for topological link prediction in bipartite networks

NASA Astrophysics Data System (ADS)

Daminelli, Simone; Thomas, Josephine Maria; Durán, Claudio; Vittorio Cannistraci, Carlo

2015-11-01

Bipartite networks are powerful descriptions of complex systems characterized by two different classes of nodes and connections allowed only across but not within the two classes. Unveiling physical principles, building theories and suggesting physical models to predict bipartite links such as product-consumer connections in recommendation systems or drug-target interactions in molecular networks can provide priceless information to improve e-commerce or to accelerate pharmaceutical research. The prediction of nonobserved connections starting from those already present in the topology of a network is known as the link-prediction problem. It represents an important subject both in many-body interaction theory in physics and in new algorithms for applied tools in computer science. The rationale is that the existing connectivity structure of a network can suggest where new connections can appear with higher likelihood in an evolving network, or where nonobserved connections are missing in a partially known network. Surprisingly, current complex network theory presents a theoretical bottle-neck: a general framework for local-based link prediction directly in the bipartite domain is missing. Here, we overcome this theoretical obstacle and present a formal definition of common neighbour index and local-community-paradigm (LCP) for bipartite networks. As a consequence, we are able to introduce the first node-neighbourhood-based and LCP-based models for topological link prediction that utilize the bipartite domain. We performed link prediction evaluations in several networks of different size and of disparate origin, including technological, social and biological systems. Our models significantly improve topological prediction in many bipartite networks because they exploit local physical driving-forces that participate in the formation and organization of many real-world bipartite networks. Furthermore, we present a local-based formalism that allows to intuitively implement neighbourhood-based link prediction entirely in the bipartite domain.

Measuring Gap Fraction, Element Clumping Index and LAI in Sierra Forest Stands Using a Full-Waveform Ground-Based Lidar

NASA Technical Reports Server (NTRS)

Zhao, Feng; Strahler, Alan H.; Crystal L. Schaaf; Yao, Tian; Yang, Xiaoyuan; Wang, Zhuosen; Schull, Mitchell A.; Roman, Miguel O.; Woodcock, Curtis E.; Olofsson, Pontus;

Exploiting Synoptic-Scale Climate Processes to Develop Nonstationary, Probabilistic Flood Hazard Projections

NASA Astrophysics Data System (ADS)

Spence, C. M.; Brown, C.; Doss-Gollin, J.

2016-12-01

Climate model projections are commonly used for water resources management and planning under nonstationarity, but they do not reliably reproduce intense short-term precipitation and are instead more skilled at broader spatial scales. To provide a credible estimate of flood trend that reflects climate uncertainty, we present a framework that exploits the connections between synoptic-scale oceanic and atmospheric patterns and local-scale flood-producing meteorological events to develop long-term flood hazard projections. We demonstrate the method for the Iowa River, where high flow episodes have been found to correlate with tropical moisture exports that are associated with a pressure dipole across the eastern continental United States We characterize the relationship between flooding on the Iowa River and this pressure dipole through a nonstationary Pareto-Poisson peaks-over-threshold probability distribution estimated based on the historic record. We then combine the results of a trend analysis of dipole index in the historic record with the results of a trend analysis of the dipole index as simulated by General Circulation Models (GCMs) under climate change conditions through a Bayesian framework. The resulting nonstationary posterior distribution of dipole index, combined with the dipole-conditioned peaks-over-threshold flood frequency model, connects local flood hazard to changes in large-scale atmospheric pressure and circulation patterns that are related to flooding in a process-driven framework. The Iowa River example demonstrates that the resulting nonstationary, probabilistic flood hazard projection may be used to inform risk-based flood adaptation decisions.

Mueller matrix approach for probing multifractality in the underlying anisotropic connective tissue

NASA Astrophysics Data System (ADS)

Das, Nandan Kumar; Dey, Rajib; Ghosh, Nirmalya

2016-09-01

Spatial variation of refractive index (RI) in connective tissues exhibits multifractality, which encodes useful morphological and ultrastructural information about the disease. We present a spectral Mueller matrix (MM)-based approach in combination with multifractal detrended fluctuation analysis (MFDFA) to exclusively pick out the signature of the underlying connective tissue multifractality through the superficial epithelium layer. The method is based on inverse analysis on selected spectral scattering MM elements encoding the birefringence information on the anisotropic connective tissue. The light scattering spectra corresponding to the birefringence carrying MM elements are then subjected to the Born approximation-based Fourier domain preprocessing to extract ultrastructural RI fluctuations of anisotropic tissue. The extracted RI fluctuations are subsequently analyzed via MFDFA to yield the multifractal tissue parameters. The approach was experimentally validated on a simple tissue model comprising of TiO2 as scatterers of the superficial isotropic layer and rat tail collagen as an underlying anisotropic layer. Finally, the method enabled probing of precancer-related subtle alterations in underlying connective tissue ultrastructural multifractality from intact tissues.

[Construction and optimization of ecological network for nature reserves in Fujian Province, China].

PubMed

Gu, Fan; Huang, Yi Xiong; Chen, Chuan Ming; Cheng, Dong Liang; Guo, Jia Lei

2017-03-18

The nature reserve is very important to biodiversity maintenance. However, due to the urbanization, the nature reserve has been fragmented with reduction in area, leading to the loss of species diversity. Establishing ecological network can effectively connect the fragmented habitats and plays an important role in species conversation. In this paper, based on deciding habitat patches and the landscape cost surface in ArcGIS, a minimum cumulative resistance model was used to simulate the potential ecological network of Fujian provincial nature reserves. The connectivity and importance of network were analyzed and evaluated based on comparison of connectivity indices (including the integral index of connectivity and probability of connectivity) and gravity model both before and after the potential ecological network construction. The optimum ecological network optimization measures were proposed. The result demonstrated that woodlands, grasslands and wetlands together made up the important part of the nature reserve ecological network. The habitats with large area had a higher degree of importance in the network. After constructing the network, the connectivity level was significantly improved. Although interaction strength between different patches va-ried greatly, the corridors between patches with large interaction were very important. The research could provide scientific reference and basis for nature protection and planning in Fujian Province.

Seizure-Onset Mapping Based on Time-Variant Multivariate Functional Connectivity Analysis of High-Dimensional Intracranial EEG: A Kalman Filter Approach.

PubMed

Lie, Octavian V; van Mierlo, Pieter

2017-01-01

The visual interpretation of intracranial EEG (iEEG) is the standard method used in complex epilepsy surgery cases to map the regions of seizure onset targeted for resection. Still, visual iEEG analysis is labor-intensive and biased due to interpreter dependency. Multivariate parametric functional connectivity measures using adaptive autoregressive (AR) modeling of the iEEG signals based on the Kalman filter algorithm have been used successfully to localize the electrographic seizure onsets. Due to their high computational cost, these methods have been applied to a limited number of iEEG time-series (<60). The aim of this study was to test two Kalman filter implementations, a well-known multivariate adaptive AR model (Arnold et al. 1998) and a simplified, computationally efficient derivation of it, for their potential application to connectivity analysis of high-dimensional (up to 192 channels) iEEG data. When used on simulated seizures together with a multivariate connectivity estimator, the partial directed coherence, the two AR models were compared for their ability to reconstitute the designed seizure signal connections from noisy data. Next, focal seizures from iEEG recordings (73-113 channels) in three patients rendered seizure-free after surgery were mapped with the outdegree, a graph-theory index of outward directed connectivity. Simulation results indicated high levels of mapping accuracy for the two models in the presence of low-to-moderate noise cross-correlation. Accordingly, both AR models correctly mapped the real seizure onset to the resection volume. This study supports the possibility of conducting fully data-driven multivariate connectivity estimations on high-dimensional iEEG datasets using the Kalman filter approach.

Combination of Alternative Models by Mutual Data Assimilation: Supermodeling With A Suite of Primitive Equation Models

NASA Astrophysics Data System (ADS)

Duane, G. S.; Selten, F.

2016-12-01

Different models of climate and weather commonly give projections/predictions that differ widely in their details. While averaging of model outputs almost always improves results, nonlinearity implies that further improvement can be obtained from model interaction in run time, as has already been demonstrated with toy systems of ODEs and idealized quasigeostrophic models. In the supermodeling scheme, models effectively assimilate data from one another and partially synchronize with one another. Spread among models is manifest as a spread in possible inter-model connection coefficients, so that the models effectively "agree to disagree". Here, we construct a supermodel formed from variants of the SPEEDO model, a primitive-equation atmospheric model (SPEEDY) coupled to ocean and land. A suite of atmospheric models, coupled to the same ocean and land, is chosen to represent typical differences among climate models by varying model parameters. Connections are introduced between all pairs of corresponding independent variables at synoptic-scale intervals. Strengths of the inter-atmospheric connections can be considered to represent inverse inter-model observation error. Connection strengths are adapted based on an established procedure that extends the dynamical equations of a pair of synchronizing systems to synchronize parameters as well. The procedure is applied to synchronize the suite of SPEEDO models with another SPEEDO model regarded as "truth", adapting the inter-model connections along the way. The supermodel with trained connections gives marginally lower error in all fields than any weighted combination of the separate model outputs when used in "weather-prediction mode", i.e. with constant nudging to truth. Stronger results are obtained if a supermodel is used to predict the formation of coherent structures or the frequency of such. Partially synchronized SPEEDO models give a better representation of the blocked-zonal index cycle than does a weighted average of the constituent model outputs. We have thus shown that supermodeling and the synchronization-based procedure to adapt inter-model connections give results superior to output averaging not only with highly nonlinear toy systems, but with smaller nonlinearities as occur in climate models.

Potential Distribution of Mountain Cloud Forest in Michoacán, Mexico: Prioritization for Conservation in the Context of Landscape Connectivity.

PubMed

Correa Ayram, Camilo A; Mendoza, Manuel E; Etter, Andrés; Pérez Salicrup, Diego R

2017-07-01

Landscape connectivity is essential in biodiversity conservation because of its ability to reduce the effect of habitat fragmentation; furthermore is a key property in adapting to climate change. Potential distribution models and landscape connectivity studies have increased with regard to their utility to prioritizing areas for conservation. The objective of this study was to model the potential distribution of Mountain cloud forests in the Transversal Volcanic System, Michoacán and to analyze the role of these areas in maintaining landscape connectivity. Potential distribution was modeled for the Mountain cloud forests based on the maximum entropy approach using 95 occurrence points and 17 ecological variables at 30 m spatial resolution. Potential connectivity was then evaluated by using a probability of connectivity index based on graph theory. The percentage of variation (dPCk) was used to identify the individual contribution of each potential area of Mountain cloud forests in overall connectivity. The different ways in which the potential areas of Mountain cloud forests can contribute to connectivity were evaluated by using the three fractions derived from dPCk (dPCintrak, dPCfluxk, and dPCconnectork). We determined that 37,567 ha of the TVSMich are optimal for the presence of Mountain cloud forests. The contribution of said area in the maintenance of connectivity was low. The conservation of Mountain cloud forests is indispensable, however, in providing or receiving dispersal flows through TVSMich because of its role as a connector element between another habitat types. The knowledge of the potential capacity of Mountain cloud forests to promote structural and functional landscape connectivity is key in the prioritization of conservation areas.

Time-dependence of graph theory metrics in functional connectivity analysis

PubMed Central

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J.; Haneef, Zulfi; Stern, John M.

2016-01-01

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. PMID:26518632

Time-dependence of graph theory metrics in functional connectivity analysis.

PubMed

Chiang, Sharon; Cassese, Alberto; Guindani, Michele; Vannucci, Marina; Yeh, Hsiang J; Haneef, Zulfi; Stern, John M

2016-01-15

Brain graphs provide a useful way to computationally model the network structure of the connectome, and this has led to increasing interest in the use of graph theory to quantitate and investigate the topological characteristics of the healthy brain and brain disorders on the network level. The majority of graph theory investigations of functional connectivity have relied on the assumption of temporal stationarity. However, recent evidence increasingly suggests that functional connectivity fluctuates over the length of the scan. In this study, we investigate the stationarity of brain network topology using a Bayesian hidden Markov model (HMM) approach that estimates the dynamic structure of graph theoretical measures of whole-brain functional connectivity. In addition to extracting the stationary distribution and transition probabilities of commonly employed graph theory measures, we propose two estimators of temporal stationarity: the S-index and N-index. These indexes can be used to quantify different aspects of the temporal stationarity of graph theory measures. We apply the method and proposed estimators to resting-state functional MRI data from healthy controls and patients with temporal lobe epilepsy. Our analysis shows that several graph theory measures, including small-world index, global integration measures, and betweenness centrality, may exhibit greater stationarity over time and therefore be more robust. Additionally, we demonstrate that accounting for subject-level differences in the level of temporal stationarity of network topology may increase discriminatory power in discriminating between disease states. Our results confirm and extend findings from other studies regarding the dynamic nature of functional connectivity, and suggest that using statistical models which explicitly account for the dynamic nature of functional connectivity in graph theory analyses may improve the sensitivity of investigations and consistency across investigations. Copyright © 2015 Elsevier Inc. All rights reserved.

Application of a Cloud Model-Set Pair Analysis in Hazard Assessment for Biomass Gasification Stations.

PubMed

Yan, Fang; Xu, Kaili

2017-01-01

Because a biomass gasification station includes various hazard factors, hazard assessment is needed and significant. In this article, the cloud model (CM) is employed to improve set pair analysis (SPA), and a novel hazard assessment method for a biomass gasification station is proposed based on the cloud model-set pair analysis (CM-SPA). In this method, cloud weight is proposed to be the weight of index. In contrast to the index weight of other methods, cloud weight is shown by cloud descriptors; hence, the randomness and fuzziness of cloud weight will make it effective to reflect the linguistic variables of experts. Then, the cloud connection degree (CCD) is proposed to replace the connection degree (CD); the calculation algorithm of CCD is also worked out. By utilizing the CCD, the hazard assessment results are shown by some normal clouds, and the normal clouds are reflected by cloud descriptors; meanwhile, the hazard grade is confirmed by analyzing the cloud descriptors. After that, two biomass gasification stations undergo hazard assessment via CM-SPA and AHP based SPA, respectively. The comparison of assessment results illustrates that the CM-SPA is suitable and effective for the hazard assessment of a biomass gasification station and that CM-SPA will make the assessment results more reasonable and scientific.

Application of a Cloud Model-Set Pair Analysis in Hazard Assessment for Biomass Gasification Stations

PubMed Central

Yan, Fang; Xu, Kaili

2017-01-01

Because a biomass gasification station includes various hazard factors, hazard assessment is needed and significant. In this article, the cloud model (CM) is employed to improve set pair analysis (SPA), and a novel hazard assessment method for a biomass gasification station is proposed based on the cloud model-set pair analysis (CM-SPA). In this method, cloud weight is proposed to be the weight of index. In contrast to the index weight of other methods, cloud weight is shown by cloud descriptors; hence, the randomness and fuzziness of cloud weight will make it effective to reflect the linguistic variables of experts. Then, the cloud connection degree (CCD) is proposed to replace the connection degree (CD); the calculation algorithm of CCD is also worked out. By utilizing the CCD, the hazard assessment results are shown by some normal clouds, and the normal clouds are reflected by cloud descriptors; meanwhile, the hazard grade is confirmed by analyzing the cloud descriptors. After that, two biomass gasification stations undergo hazard assessment via CM-SPA and AHP based SPA, respectively. The comparison of assessment results illustrates that the CM-SPA is suitable and effective for the hazard assessment of a biomass gasification station and that CM-SPA will make the assessment results more reasonable and scientific. PMID:28076440

Potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal changes in dryland environments

NASA Astrophysics Data System (ADS)

Foerster, Saskia; Wilczok, Charlotte; Brosinsky, Arlena; Kroll, Anja; Segl, Karl; Francke, Till

2014-05-01

Many drylands are characterized by strong erosion in headwater catchments, where connectivity processes play an important role in the redistribution of water and sediments. Sediment connectivity relates to the physical transfer of sediment through a drainage basin (Bracken and Croke 2007). The identification of sediment source areas and the way they connect to the channel network are essential to environmental management (Reid et al. 2007), especially where high erosion and sediment delivery rates occur. Vegetation cover and its spatial and temporal pattern is one of the main factors affecting sediment connectivity. This is particularly true for patchy vegetation covers typical for dryland environments. While many connectivity studies are based on field-derived data, the potential of remotely-sensed data for sediment connectivity analyses has not yet been fully exploited. Recent advances in remote sensing allow for quantitative, spatially explicit, catchment-wide derivation of surface information to be used in connectivity analyses. These advances include a continuous increase in spatial image resolution to comprise processes at the plot to hillslope to catchment scale, an increase in the temporal resolution to cover seasonal and long-term changes and an increase in the spectral resolution enabling the discrimination of dry and green vegetation fractions from soil surfaces in heterogeneous dryland landscapes. The utilization of remotely-sensed data for connectivity studies raises questions on what type of information is required, how scale of sediment flux and image resolution match, how the connectivity information can be incorporated into water and sediment transport models and how this improves model predictions. The objective of this study is to demonstrate the potential of remotely-sensed data for mapping sediment connectivity pathways and their seasonal change at the example of a mesoscale dryland catchment in the Spanish Pyrenees. Here, sediment connectivity pathways have been mapped for two adjacent sub-catchments (approx. 70 km²) of the Isábena River in different seasons using a quantitative connectivity index based on fractional vegetation cover and topography data. Fractional cover of green and dry vegetation, bare soil and rock were derived by applying a Multiple Endmember Spectral Mixture Analysis approach applied to a hyperspectral image dataset. Sediment connectivity was mapped using the Index of Connectivity (Borselli et al. 2008), in which the effect of land cover on runoff and sediment fluxes is expressed by a spatially distributed weighing factor (in this study, the cover and management factor of the RUSLE). The resulting connectivity maps show that areas behave very differently with regard to connectivity, depending on the land cover but also on the spatial distribution of vegetation abundances and topographic barriers. Most parts of the catchment show higher connectivity values in summer than in spring. The studied sub-catchments show a slightly different connectivity behaviour reflecting the different land cover proportions and their spatial configuration. Future work includes the incorporation of sediment connectivity information into a hydrological model (WASA-SED, Mueller et al. 2010) to better reflect connectivity processes and testing the sensitivity of the model to different input data.

Process-based tolerance assessment of connecting rod machining process

NASA Astrophysics Data System (ADS)

Sharma, G. V. S. S.; Rao, P. Srinivasa; Surendra Babu, B.

2016-06-01

Process tolerancing based on the process capability studies is the optimistic and pragmatic approach of determining the manufacturing process tolerances. On adopting the define-measure-analyze-improve-control approach, the process potential capability index ( C p) and the process performance capability index ( C pk) values of identified process characteristics of connecting rod machining process are achieved to be greater than the industry benchmark of 1.33, i.e., four sigma level. The tolerance chain diagram methodology is applied to the connecting rod in order to verify the manufacturing process tolerances at various operations of the connecting rod manufacturing process. This paper bridges the gap between the existing dimensional tolerances obtained via tolerance charting and process capability studies of the connecting rod component. Finally, the process tolerancing comparison has been done by adopting a tolerance capability expert software.

Risk assessment of flood disaster and forewarning model at different spatial-temporal scales

NASA Astrophysics Data System (ADS)

Zhao, Jun; Jin, Juliang; Xu, Jinchao; Guo, Qizhong; Hang, Qingfeng; Chen, Yaqian

2018-05-01

Aiming at reducing losses from flood disaster, risk assessment of flood disaster and forewarning model is studied. The model is built upon risk indices in flood disaster system, proceeding from the whole structure and its parts at different spatial-temporal scales. In this study, on the one hand, it mainly establishes the long-term forewarning model for the surface area with three levels of prediction, evaluation, and forewarning. The method of structure-adaptive back-propagation neural network on peak identification is used to simulate indices in prediction sub-model. Set pair analysis is employed to calculate the connection degrees of a single index, comprehensive index, and systematic risk through the multivariate connection number, and the comprehensive assessment is made by assessment matrixes in evaluation sub-model. The comparison judging method is adopted to divide warning degree of flood disaster on risk assessment comprehensive index with forewarning standards in forewarning sub-model and then the long-term local conditions for proposing planning schemes. On the other hand, it mainly sets up the real-time forewarning model for the spot, which introduces the real-time correction technique of Kalman filter based on hydrological model with forewarning index, and then the real-time local conditions for presenting an emergency plan. This study takes Tunxi area, Huangshan City of China, as an example. After risk assessment and forewarning model establishment and application for flood disaster at different spatial-temporal scales between the actual and simulated data from 1989 to 2008, forewarning results show that the development trend for flood disaster risk remains a decline on the whole from 2009 to 2013, despite the rise in 2011. At the macroscopic level, project and non-project measures are advanced, while at the microcosmic level, the time, place, and method are listed. It suggests that the proposed model is feasible with theory and application, thus offering a way for assessing and forewarning flood disaster risk.

Selection of test paths for solder joint intermittent connection faults under DC stimulus

NASA Astrophysics Data System (ADS)

Huakang, Li; Kehong, Lv; Jing, Qiu; Guanjun, Liu; Bailiang, Chen

2018-06-01

The test path of solder joint intermittent connection faults under direct-current stimulus is examined in this paper. According to the physical structure of the circuit, a network model is established first. A network node is utilised to represent the test node. The path edge refers to the number of intermittent connection faults in the path. Then, the selection criteria of the test path based on the node degree index are proposed and the solder joint intermittent connection faults are covered using fewer test paths. Finally, three circuits are selected to verify the method. To test if the intermittent fault is covered by the test paths, the intermittent fault is simulated by a switch. The results show that the proposed method can detect the solder joint intermittent connection fault using fewer test paths. Additionally, the number of detection steps is greatly reduced without compromising fault coverage.

Modelling non-Euclidean movement and landscape connectivity in highly structured ecological networks

USGS Publications Warehouse

Sutherland, Christopher; Fuller, Angela K.; Royle, J. Andrew

2015-01-01

The ecological distance SCR model uses spatially indexed capture-recapture data to estimate how activity patterns are influenced by landscape structure. As well as reducing bias in estimates of abundance, this approach provides biologically realistic representations of home range geometry, and direct information about species-landscape interactions. The incorporation of both structural (landscape) and functional (movement) components of connectivity provides a direct measure of species-specific landscape connectivity.

Artificialized land characteristics and sediment connectivity explain muddy flood hazard in Wallonia

NASA Astrophysics Data System (ADS)

de Walque, Baptiste; Bielders, Charles; Degré, Aurore; Maugnard, Alexandre

2017-04-01

Muddy flood occurrence is an off-site erosion problem of growing interest in Europe and in particular in the loess belt and Condroz regions of Wallonia (Belgium). In order to assess the probability of occurrence of muddy floods in specific places, a muddy flood hazard prediction model has been built. It was used to test 11 different explanatory variables in simple and multiple logistic regressions approaches. A database of 442 muddy flood-affected sites and an equal number of homologous non flooded sites was used. For each site, relief, land use, sediment production and sediment connectivity of the contributing area were extracted. To assess the prediction quality of the model, we proceeded to a validation using 48 new pairs of homologous sites. Based on Akaïke Information Criterion (AIC), we determined that the best muddy flood hazard assessment model requires a total of 6 explanatory variable as inputs: the spatial aggregation of the artificialized land, the sediment connectivity, the artificialized land proximity to the outlet, the proportion of artificialized land, the mean slope and the Gravelius index of compactness of the contributive area. The artificialized land properties listed above showed to improve substantially the model quality (p-values from 10e-10 to 10e-4). All of the 3 properties showed negative correlation with the muddy flood hazard. These results highlight the importance of considering the artificialized land characteristics in the sediment transport assessment models. Indeed, artificialized land such as roads may dramatically deviate flows and influence the connectivity in the landscape. Besides the artificialized land properties, the sediment connectivity showed significant explanatory power (p-value of 10e-11). A positive correlation between the sediment connectivity and the muddy flood hazard was found, ranging from 0.3 to 0.45 depending on the sediment connectivity index. Several studies already have highlighted the importance of this parameter in the sediment transport characterization in the landscape. Using the best muddy flood probability of occurrence threshold value of 0.49, the validation of the best multiple logistic regression resulted in a prediction quality of 75.6% (original dataset) and 81.2% (secondary dataset). The developed statistical model could be used as a reliable tool to target muddy floods mitigation measures in sites resulting with the highest muddy floods hazard.

Design-for-manufacture of gradient-index optical systems using time-varying boundary condition diffusion

NASA Astrophysics Data System (ADS)

Harkrider, Curtis Jason

2000-08-01

The incorporation of gradient-index (GRIN) material into optical systems offers novel and practical solutions to lens design problems. However, widespread use of gradient-index optics has been limited by poor correlation between gradient-index designs and the refractive index profiles produced by ion exchange between glass and molten salt. Previously, a design-for- manufacture model was introduced that connected the design and fabrication processes through use of diffusion modeling linked with lens design software. This project extends the design-for-manufacture model into a time- varying boundary condition (TVBC) diffusion model. TVBC incorporates the time-dependent phenomenon of melt poisoning and introduces a new index profile control method, multiple-step diffusion. The ions displaced from the glass during the ion exchange fabrication process can reduce the total change in refractive index (Δn). Chemical equilibrium is used to model this melt poisoning process. Equilibrium experiments are performed in a titania silicate glass and chemically analyzed. The equilibrium model is fit to ion concentration data that is used to calculate ion exchange boundary conditions. The boundary conditions are changed purposely to control the refractive index profile in multiple-step TVBC diffusion. The glass sample is alternated between ion exchange with a molten salt bath and annealing. The time of each diffusion step can be used to exert control on the index profile. The TVBC computer model is experimentally verified and incorporated into the design- for-manufacture subroutine that runs in lens design software. The TVBC design-for-manufacture model is useful for fabrication-based tolerance analysis of gradient-index lenses and for the design of manufactureable GRIN lenses. Several optical elements are designed and fabricated using multiple-step diffusion, verifying the accuracy of the model. The strength of multiple-step diffusion process lies in its versatility. An axicon, imaging lens, and curved radial lens, all with different index profile requirements, are designed out of a single glass composition.

[Topological models of retention index of thin-layer chromatogram for chiral organic acids].

PubMed

Li, Mingjian; Wang, Yuxiao; Feng, Hui; Feng, Changjun

2014-03-01

On the basis of Kier's molecular connectivity indices and conjugated matrix, novel molecular connectivity indices ((m) G(t)(v)) were defined and calculated for 18 chiral hydroxyl acids and amino acids. The chiral connectivity indices ((m)C(t)(v)) were introduced by extending (m)G(t)(v): (m)C(t)(v) = (m)G(t)(v) x w(j), where w(j) is the chiral index. The quantitative structure-retention index relationship (QSRR) between the retention index (R(M)) of thin-layer chromatogram for the chiral organic acids and (m)C(t)(v) was studied by multivariate statistical regression. By leaps-and-bounds regression analysis, the best four-parameter QSRR model was set up, and the traditional correlation coefficient (R2) and the cross-validation correlation coefficient (Q2) of leave-one-out (LOO) were 0.973 and 0.950, respectively. The results demonstrated that the model was highly reliable and had good predictive ability from the point of view of statistics. From the four parameters (0C(p)(v), 2C(p)(v), C(ch),(v), 5C(p)(v)) of the model, it is known that the dominant influence factors of the retention index were the molecular structure characteristics of two-dimensional and the space factors: the chiral characteristics, the flexibility and the puckered degree of molecules for the chiral organic acids. The results showed that the new parameter mC(t)(v) had good rationality and efficiency for the retention indices of the chiral organic acids. Therefore, an effective method was provided to predict the retention indices of the chiral organic acids.

Resting-State Seed-Based Analysis: An Alternative to Task-Based Language fMRI and Its Laterality Index.

PubMed

Smitha, K A; Arun, K M; Rajesh, P G; Thomas, B; Kesavadas, C

2017-06-01

Language is a cardinal function that makes human unique. Preservation of language function poses a great challenge for surgeons during resection. The aim of the study was to assess the efficacy of resting-state fMRI in the lateralization of language function in healthy subjects to permit its further testing in patients who are unable to perform task-based fMRI. Eighteen healthy right-handed volunteers were prospectively evaluated with resting-state fMRI and task-based fMRI to assess language networks. The laterality indices of Broca and Wernicke areas were calculated by using task-based fMRI via a voxel-value approach. We adopted seed-based resting-state fMRI connectivity analysis together with parameters such as amplitude of low-frequency fluctuation and fractional amplitude of low-frequency fluctuation (fALFF). Resting-state fMRI connectivity maps for language networks were obtained from Broca and Wernicke areas in both hemispheres. We performed correlation analysis between the laterality index and the z scores of functional connectivity, amplitude of low-frequency fluctuation, and fALFF. Pearson correlation analysis between signals obtained from the z score of fALFF and the laterality index yielded a correlation coefficient of 0.849 ( P < .05). Regression analysis of the fALFF with the laterality index yielded an R 2 value of 0.721, indicating that 72.1% of the variance in the laterality index of task-based fMRI could be predicted from the fALFF of resting-state fMRI. The present study demonstrates that fALFF can be used as an alternative to task-based fMRI for assessing language laterality. There was a strong positive correlation between the fALFF of the Broca area of resting-state fMRI with the laterality index of task-based fMRI. Furthermore, we demonstrated the efficacy of fALFF for predicting the laterality of task-based fMRI. © 2017 by American Journal of Neuroradiology.

Connecting Atlantic temperature variability and biological cycling in two earth system models

NASA Astrophysics Data System (ADS)

Gnanadesikan, Anand; Dunne, John P.; Msadek, Rym

2014-05-01

Connections between the interdecadal variability in North Atlantic temperatures and biological cycling have been widely hypothesized. However, it is unclear whether such connections are due to small changes in basin-averaged temperatures indicated by the Atlantic Multidecadal Oscillation (AMO) Index, or whether both biological cycling and the AMO index are causally linked to changes in the Atlantic Meridional Overturning Circulation (AMOC). We examine interdecadal variability in the annual and month-by-month diatom biomass in two Earth System Models with the same formulations of atmospheric, land, sea ice and ocean biogeochemical dynamics but different formulations of ocean physics and thus different AMOC structures and variability. In the isopycnal-layered ESM2G, strong interdecadal changes in surface salinity associated with changes in AMOC produce spatially heterogeneous variability in convection, nutrient supply and thus diatom biomass. These changes also produce changes in ice cover, shortwave absorption and temperature and hence the AMO Index. Off West Greenland, these changes are consistent with observed changes in fisheries and support climate as a causal driver. In the level-coordinate ESM2M, nutrient supply is much higher and interdecadal changes in diatom biomass are much smaller in amplitude and not strongly linked to the AMO index.

Evaluating atmospheric blocking in the global climate model EC-Earth

NASA Astrophysics Data System (ADS)

Hartung, Kerstin; Hense, Andreas; Kjellström, Erik

2013-04-01

Atmospheric blocking is a phenomenon of the midlatitudal troposphere, which plays an important role in climate variability. Therefore a correct representation of blocking in climate models is necessary, especially for evaluating the results of climate projections. In my master's thesis a validation of blocking in the coupled climate model EC-Earth is performed. Blocking events are detected based on the Tibaldi-Molteni Index. At first, a comparison with the reanalysis dataset ERA-Interim is conducted. The blocking frequency depending on longitude shows a small general underestimation of blocking in the model - a well known problem. Scaife et al. (2011) proposed the correction of model bias as a way to solve this problem. However, applying the correction to the higher resolution EC-Earth model does not yield any improvement. Composite maps show a link between blocking events and surface variables. One example is the formation of a positive surface temperature anomaly north and a negative anomaly south of the blocking anticyclone. In winter the surface temperature in EC-Earth can be reproduced quite well, but in summer a cold bias over the inner-European ocean is present. Using generalized linear models (GLMs) I want to study the connection between regional blocking and global atmospheric variables further. GLMs have the advantage of being applicable to non-Gaussian variables. Therefore the blocking index at each longitude, which is Bernoulli distributed, can be analysed statistically with GLMs. I applied a logistic regression between the blocking index and the geopotential height at 500 hPa to study the teleconnection of blocking events at midlatitudes with global geopotential height. GLMs also offer the possibility of quantifying the connections shown in composite maps. The implementation of the logistic regression can even be expanded to a search for trends in blocking frequency, for example in the scenario simulations.

Some connectivity indices and zagreb index of polyhex nanotubes.

PubMed

Farahani, Mohammad Reza

2012-12-01

Several topological indices are investigated in polyhex nanotubes: Randić connectivity index, sum-connectivity index, atom-bond connectivity index, geometric-arithmetic index, First and Second Zagreb indices and Zagreb polynomials. Formulas for calculating the above topological descriptors in polyhex zigzag TUZC6[m,n] and armchair TUAC6[m,n] nanotube families are given.

Development of a novel walkability index for London, United Kingdom: cross-sectional application to the Whitehall II Study.

PubMed

Stockton, Jemima C; Duke-Williams, Oliver; Stamatakis, Emmanuel; Mindell, Jennifer S; Brunner, Eric J; Shelton, Nicola J

2016-05-18

Physical activity is essential for health; walking is the easiest way to incorporate activity into everyday life. Previous studies report positive associations between neighbourhood walkability and walking but most focused on cities in North America and Australasia. Urban form with respect to street connectivity, residential density and land use mix-common components of walkability indices-differs in European cities. The objective of this study was to develop a walkability index for London and test the index using walking data from the Whitehall II Study. A neighbourhood walkability index for London was constructed, comprising factors associated with walking behaviours: residential dwelling density, street connectivity and land use mix. Three models were produced that differed in the land uses included. Neighbourhoods were operationalised at three levels of administrative geography: (i) 21,140 output areas, (ii) 633 wards and (iii) 33 local authorities. A neighbourhood walkability score was assigned to each London-dwelling Whitehall II Study participant (2003-04, N = 3020, mean ± SD age = 61.0 years ± 6.0) based on residential postcode. The effect of changing the model specification and the units of enumeration on spatial variation in walkability was examined. There was a radial decay in walkability from the centre to the periphery of London. There was high inter-model correlation in walkability scores for any given neighbourhood operationalisation (0.92-0.98), and moderate-high correlation between neighbourhood operationalisations for any given model (0.39-0.70). After adjustment for individual level factors and area deprivation, individuals in the most walkable neighbourhoods operationalised as wards were more likely to walk >6 h/week (OR = 1.4; 95 % CI: 1.1-1.9) than those in the least walkable. Walkability was associated with walking time in adults. This walkability index could help urban planners identify and design neighbourhoods in London with characteristics more supportive of walking, thereby promoting public health.

Knowledge synthesis with maps of neural connectivity.

PubMed

Tallis, Marcelo; Thompson, Richard; Russ, Thomas A; Burns, Gully A P C

2011-01-01

This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called "Knowledge Engineering from Experimental Design" (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features.

Molecular structure and gas chromatographic retention behavior of the components of Ylang-Ylang oil.

PubMed

Olivero, J; Gracia, T; Payares, P; Vivas, R; Díaz, D; Daza, E; Geerlings, P

1997-05-01

Using quantitative structure-retention relationships (QSRR) methodologies the Kovats gas chromatographic retention indices for both apolar (DB-1) and polar (DB-Wax) columns for 48 compounds from Ylang-Ylang essential oil were empirically predicted from calculated and experimental data on molecular structure. Topological, geometric, and electronic descriptors were obtained for model generation. Relationships between descriptors and the retention data reported were established by linear multiple regression, giving equations that can be used to predict the Kovats indices for compounds present in essential oils, both in DB-1 and DB-Wax columns. Factor analysis was performed to interpret the meaning of the descriptors included in the models. The prediction model for the DB-1 column includes descriptors such as Randic's first-order connectivity index (1X), the molecular surface (MSA), the sum of the atomic charge on all the hydrogens (QH), Randic's third-order connectivity index (3X) and the molecular electronegativity (chi). The prediction model for the DB-Wax column includes the first three descriptors mentioned for the DB-1 column (1X, MSA and QH) and the most negative charge (MNC), the global softness (S), and the difference between Randic's and Kier and Hall's third-order connectivity indexes (3X-3XV).

Structural and Functional Connectivity from Unmanned-Aerial System Data

NASA Astrophysics Data System (ADS)

Masselink, Rens; Heckmann, Tobias; Casalí, Javier; Giménez, Rafael; Cerdá, Artemi; Keesstra, Saskia

2017-04-01

Over the past decade there has been an increase in both connectivity research and research involving Unmanned-Aerial systems (UASs). In some studies, UASs were successfully used for the assessment of connectivity, but not yet to their full potential. We present several ways to use data obtained from UASs to measure variables related to connectivity, and use these to assess both structural and functional connectivity. These assessments of connectivity can aid us in obtaining a better understanding of the dynamics of e.g. sediment and nutrient transport. We identify three sources of data obtained from a consumer camera mounted on a fixed-wing UAS, which can be used separately or combined: Visual and near-infrared imagery, point clouds, and digital elevation models (DEMs). Imagery (or: orthophotos) can be used for (automatic) mapping of connectivity features like rills, gullies and soil and water conservation measures using supervised or unsupervised classification methods with e.g. Object-Based Image Analysis. Furthermore, patterns of soil moisture in the top layers can be extracted from visual and near-infrared imagery. Point clouds can be analysed for vegetation height and density, and soil surface roughness. Lastly, DEMs can be used in combination with imagery for a number of tasks, including raster-based (e.g. DEM derivatives) and object-based (e.g., feature detection) analysis: Flow routing algorithms can be used to analyse potential pathways of surface runoff and sediment transport. This allows for the assessment of structural connectivity through indices that are based, for example, on morphometric and other properties of surfaces, contributing areas, and pathways. Third, erosion and deposition can be measured by calculating elevation changes from repeat surveys. From these "intermediate" variables like roughness, vegetation density and soil moisture, structural connectivity and functional connectivity can be assessed by combining them into a dynamic index of connectivity, use them in connectivity modelling (Masselink et al., 2016b) or be combined with measured data of water and sediment fluxes (Masselink et al., 2016a). References Masselink, R.J.H., Heckmann, T., Temme, A.J.A.M., Anders, N.S., Gooren, H.P.A., Keesstra, S.D., 2016a. A network theory approach for a better understanding of overland flow connectivity. Hydrol. Process. doi:10.1002/hyp.10993 Masselink, R.J.H., Keesstra, S.D., Temme, A.J.A.M., Seeger, M., Giménez, R., Casalí, J., 2016b. Modelling Discharge and Sediment Yield at Catchment Scale Using Connectivity Components. Land Degrad. Dev. 27, 933-945. doi:10.1002/ldr.2512

Empirical Examination of Fundamental Indexation in the German Market

NASA Astrophysics Data System (ADS)

Mihm, Max; Locarek-Junge, Hermann

Index Funds, Exchange Traded Funds and Derivatives give investors easy access to well diversified index portfolios. These index-based investment products exhibit low fees, which make them an attractive alternative to actively managed funds. Against this background, a new class of stock indices has been established based on the concept of “Fundamental Indexation”. The selection and weighting of index constituents is conducted by means of fundamental criteria like total assets, book value or number of employees. This paper examines the performance of fundamental indices in the German equity market. For this purpose, a backtest of five fundamental indices is conducted over the last 20 years. Furthermore the index returns are analysed under the assumption of an efficient as well as an inefficient market. Index returns in efficient markets are explained by applying the three factor model for stock returns of Fama and French (J Financ Econ 33(1):3-56, 1993). The results show that the outperformance of fundamental indices is partly due to a higher risk exposure, particularly to companies with a low price to book ratio. By relaxing the assumption of market efficiency, a return drag of capitalisation weighted indices can be deduced. Given a mean-reverting movement of prices, a direct connection between market capitalisation and index weighting leads to inferior returns.

The influence of floodplain geomorphology and hydrologic connectivity on alligator gar (Atractosteus spatula) habitat along the embanked floodplain of the Lower Mississippi River

NASA Astrophysics Data System (ADS)

van der Most, Merel; Hudson, Paul F.

2018-02-01

The floodplain geomorphology of large lowland rivers is intricately related to aquatic ecosystems dependent upon flood pulse dynamics. The alligator gar (Atractosteus spatula) is native to the Lower Mississippi River and dependent upon floodplain backwater areas for spawning. In this study we utilize a geospatial approach to develop a habitat suitability index for alligator gar that explicitly considers hydrologic connectivity and the floodplain geomorphology along a frequently inundated segment of the Lower Mississippi River. The data sets include Landsat imagery, a high-resolution LiDAR digital elevation model (DEM), National Hydrography Dataset (NHD), and hydrologic and geomorphic data. A habitat suitability index is created based on the extent and frequency of inundation, water depth, temperature, and vegetation. A comparison between the remote sensing approach and the NHD revealed substantial differences in the area and location of water bodies available for alligator gar spawning. The final habitat suitability index indicates that a modest proportion (19%) of the overall embanked floodplain is available for alligator gar spawning. Opportunities exist for management efforts to utilize engineered and natural geomorphic features to facilitate hydrologic connectivity at flow levels below flood stage that would expand the habitat of alligator gar across the floodplain. The study results have direct implications regarding environmental restoration of the Lower Mississippi, an iconic example of an embanked meandering river floodplain.

Connectivity from source to sink in a lowland area: the Loire river basin (France)

NASA Astrophysics Data System (ADS)

Gay, Aurore; Cerdan, Olivier; Degan, Francesca; Salvador, Sebastien

2014-05-01

Sediment connectivity relates to the transfer of sediments from sources to sinks via runoff and in channel transport. It is highly dependent on spatial variability of landscape properties such as differences in morphology, land use and infiltration/runoff characteristics but may also vary in time due to differences in rainfall amount/intensity and changes in vegetation cover throughout the year. In the Loire river basin, we found that sediment fluxes displayed strong variations in space but also at the interannual and seasonnal time scales (Gay et al. 2013). In this context, our goal is to better understand and quantify hillslope sediment redistributions within this lowland area thanks to the use of semi distributed connectivity approach. To this aim, Borselli's index of connectivity (IC, Borselli et al., 2008) is selected to assess hillslope connectivity at annual and seasonal time scales. Several improvements are proposed to take into account the coupling of the structural landscape connectivity and its hydrosedimentary response. Parameters such as rainfall intensity and differences in seasonal land cover are integrated into the model to account for landscape variations through time. Infiltration and runoff indices were also tested. Preliminary results confirm the variability of landscape connectivity throughout the year. The integration of the index of infiltration and runoff properties of landscape (IDPR) as defined by Mardhel et al. 2004 seems to improve the IC model outputs. From this first step, in-stream sediment connectivity index should be developed for a better understanding and assessment of sediment redistributions at the entire catchment scale. L. Borselli L., Cassi P., Torri D. Prolegomena to sediment and flow connectivity in the landscape: a GIS and field numerical assessment. Catena, 75 (2008), pp. 268-277 Gay A., Cerdan O., Delmas M., Desmet M., Variability of sediment yields in the Loire river basin (France): the role of small scale catchments (under review). Mardhel V., Frantar P., Uhan J., Mio A. Index of development and persistence of the river networks as a component of regional groundwater vulnerability assessment in Slovenia.Int. Conf. groundwater vulnerability assessment and mapping. Ustron, Poland, 15-18 June 2004.

Mid-term fire danger index based on satellite imagery and ancillary geographic data

NASA Astrophysics Data System (ADS)

Stefanidou, A.; Dragozi, E.; Tompoulidou, M.; Stepanidou, L.; Grigoriadis, D.; Katagis, T.; Stavrakoudis, D.; Gitas, I.

2017-09-01

Fire danger forecast constitutes one of the most important components of integrated fire management since it provides crucial information for efficient pre-fire planning, alertness and timely response to a possible fire event. The aim of this work is to develop an index that has the capability of predicting accurately fire danger on a mid-term basis. The methodology that is currently under development is based on an innovative approach that employs dry fuel spatial connectivity as well as biophysical and topological variables for the reliable prediction of fire danger. More specifically, the estimation of the dry fuel connectivity is based on a previously proposed automated procedure implemented in R software that uses Moderate Resolution Imaging Spectrometer (MODIS) time series data. Dry fuel connectivity estimates are then combined with other ancillary data such as fuel type and proximity to roads in order to result in the generation of the proposed mid-term fire danger index. The innovation of the proposed index—which will be evaluated by comparison to historical fire data—lies in the fact that its calculation is almost solely affected by the availability of satellite data. Finally, it should be noted that the index is developed within the framework of the National Observatory of Forest Fires (NOFFi) project.

[Characteristics of supramolecular imprinting template on liver meridian tropism of traditional Chinese medicine based on molecular connectivity index].

PubMed

Fan, Shi-Qi; Li, Sen; Liu, Jin-Ling; Yang, Jiao; Hu, Chao; Zhu, Jun-Ping; Xiao, Xiao-Qin; Liu, Wen-Long; He, Fu-Yuan

2017-01-01

The molecular connectivity index was adopted to explore the characteristics of supramolecular imprinting template of herbs distributed to liver meridian, in order to provide scientific basis for traditional Chinese medicines(TCMs) distributed to liver meridian. In this paper, with "12th five-year plan" national planning textbooks Science of Traditional Chinese Medicine and Chemistry of Traditional Chinese Medicine as the blueprint, literatures and TCMSP sub-databases in TCM pharmacology of northwest science and technology university of agriculture and forestry were retrieved to collect and summarize active constituents of TCM distributed to liver meridian, and calculate the molecular connectivity index. The average molecular connectivity index of ingredients distributed to liver meridian was 9.47, which was close to flavonoid glycosides' (9.17±2.11) and terpenes (9.30±3.62). Therefore, it is inferred that template molecule of liver meridian is similar to physicochemical property of flavonoid glycosides and terpenes, which could be best matched with imprinting template of liver meridian. Copyright© by the Chinese Pharmaceutical Association.

Dynamic biological exposure indexes for n-hexane and 2,5-hexanedione, suggested by a physiologically based pharmacokinetic model

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

Perbellini, L.; Mozzo, P.; Olivato, D.

Biological exposure index (BEI) of n-hexane was studied for accuracy using a physiologically based pharmacokinetic (PB-PK) model. The kinetics of n-hexane in alveolar air, blood, urine, and other tissues were simulated for different values of alveolar ventilations and also for constant and variable exposures. The kinetics of 2,5-hexanedione, the toxic n-hexane metabolite, were also simulated. The ranges of n-hexane concentrations in biological media and the urinary concentrations of 2,5-hexanedione are discussed in connection with a mean n-hexane exposure of 180 mg/m3 (50 ppm) (threshold limit value (TLV) suggested by American Conference of Governmental Industrial Hygienists (ACGIH) for 1988-89). The experimentalmore » and field data as well as those predicted by simulation with the PB-PK model were comparable. The physiological-pharmacokinetic simulations are used to propose the dynamic BEIs of n-hexane and 2,5-hexanedione. The use of simulation with PB-PK models enables a better understanding of the limits, advantages, and issues associated with biological monitoring of exposures to industrial solvents.« less

Is there any connection between the network morphology and the fluctuations of the stock market index?

NASA Astrophysics Data System (ADS)

Stefan, F. M.; Atman, A. P. F.

2015-02-01

Models which consider behavioral aspects of the investors have attracted increasing interest in the Finance and Econophysics literature in the last years. Different behavioral profiles (imitation, anti-imitation, indifference) were proposed for the investors, which take their decision based on their trust network (neighborhood). Results from agent-based models have shown that most of the features observed in actual stock market indices can be replicated in simulations. Here, we present a deeper investigation of an agent based model considering different network morphologies (regular, random, small-world) for the investors' trust network, in an attempt to answer the question raised in the title. We study the model by considering four scenarios for the investors and different initial conditions to analyze their influence in the stock market fluctuations. We have characterized the stationary limit for each scenario tested, focusing on the changes introduced when complex networks were used, and calculated the Hurst exponent in some cases. Simulations showed interesting results suggesting that the fluctuations of the stock market index are strongly affected by the network morphology, a remarkable result which we believe was never reported or predicted before.

Spatial assessment of landscape ecological connectivity in different urban gradient.

PubMed

Park, Sohyun

2015-07-01

Urbanization has resulted in remnant natural patches within cities that often have no connectivity among themselves and to natural reserves outside the urban area. Protecting ecological connectivity in fragmented urban areas is becoming crucial in maintaining urban biodiversity and securing critical habitat levels and configurations under continual development pressures. Nevertheless, few studies have been undertaken for urban landscapes. This study aims to assess ecological connectivity for a group of species that represent the urban desert landscape in the Phoenix metropolitan area and to compare the connectivity values along the different urban gradient. A GIS-based landscape connectivity model which relies upon ecological connectivity index (ECI) was developed and applied to this region. A GIS-based concentric buffering technique was employed to delineate conceptual boundaries for urban, suburban, and rural zones. The research findings demonstrated that urban habitats and potential habitat patches would be significantly influenced by future urban development. Particularly, the largest loss of higher connectivity would likely to be anticipated in the "in-between areas" where urban, suburban, and rural zones overlap one another. The connectivity maps would be useful to provide spatial identification regarding connectivity patterns and vulnerability for urban and suburban activities in this area. This study provides planners and landscape architects with a spatial guidance to minimize ecological fragmentation, which ultimately leads to urban landscape sustainability. This study suggests that conventional planning practices which disregard the ecological processes in urban landscapes need to integrate landscape ecology into planning and design strategies.

Studying the Relationship between High-Latitude Geomagnetic Activity and Parameters of Interplanetary Magnetic Clouds with the Use of Artificial Neural Networks

NASA Astrophysics Data System (ADS)

Barkhatov, N. A.; Revunov, S. E.; Vorobjev, V. G.; Yagodkina, O. I.

2018-03-01

The cause-and-effect relations of the dynamics of high-latitude geomagnetic activity (in terms of the AL index) and the type of the magnetic cloud of the solar wind are studied with the use of artificial neural networks. A recurrent neural network model has been created based on the search for the optimal physically coupled input and output parameters characterizing the action of a plasma flux belonging to a certain magnetic cloud type on the magnetosphere. It has been shown that, with IMF components as input parameters of neural networks with allowance for a 90-min prehistory, it is possible to retrieve the AL sequence with an accuracy to 80%. The successful retrieval of the AL dynamics by the used data indicates the presence of a close nonlinear connection of the AL index with cloud parameters. The created neural network models can be applied with high efficiency to retrieve the AL index, both in periods of isolated magnetospheric substorms and in periods of the interaction between the Earth's magnetosphere and magnetic clouds of different types. The developed model of AL index retrieval can be used to detect magnetic clouds.

Observation and Modeling of Clear Air Turbulence (CAT) over Europe

NASA Astrophysics Data System (ADS)

Sprenger, M.; Mayoraz, L.; Stauch, V.; Sharman, B.; Polymeris, J.

2012-04-01

CAT represents a very relevant phenomenon for aviation safety. It can lead to passenger injuries, causes an increase in fuel consumption and, under severe intensity, can involve structural damages to the aircraft. The physical processes causing CAT remain at present not fully understood. Moreover, because of its small scale, CAT cannot be represented in numerical weather prediction (NWP) models. In this study, the physical processes related to CAT and its representation in NWP models is further investigated. First, 134 CAT events over Europe are extracted from a flight monitoring data base (FDM), run by the SWISS airline and containing over 100'000 flights. The location, time, and meteorological parameters along the turbulent spots are analysed. Furthermore, the 7-km NWP model run by the Swiss National Weather Service (Meteoswiss) is used to calculate model-based CAT indices, e.g. Richardson number, Ellrod & Knapp turbulence index and a complex/combined CAT index developed at NCAR. The CAT indices simulated with COSMO-7 is then compared to the observed CAT spots, hence allowing to assess the model's performance, and potential use in a CAT warning system. In a second step, the meteorological conditions associated with CAT are investigated. To this aim, CAT events are defined as coherent structures in space and in time, i.e. their dimension and life cycle is studied, in connection with jet streams and upper-level fronts. Finally, in a third step the predictability of CAT is assessed, by comparing CAT index predictions based on different lead times of the NWP model COSMO-7

Predicting survival across chronic interstitial lung disease: the ILD-GAP model.

PubMed

Ryerson, Christopher J; Vittinghoff, Eric; Ley, Brett; Lee, Joyce S; Mooney, Joshua J; Jones, Kirk D; Elicker, Brett M; Wolters, Paul J; Koth, Laura L; King, Talmadge E; Collard, Harold R

2014-04-01

Risk prediction is challenging in chronic interstitial lung disease (ILD) because of heterogeneity in disease-specific and patient-specific variables. Our objective was to determine whether mortality is accurately predicted in patients with chronic ILD using the GAP model, a clinical prediction model based on sex, age, and lung physiology, that was previously validated in patients with idiopathic pulmonary fibrosis. Patients with idiopathic pulmonary fibrosis (n=307), chronic hypersensitivity pneumonitis (n=206), connective tissue disease-associated ILD (n=281), idiopathic nonspecific interstitial pneumonia (n=45), or unclassifiable ILD (n=173) were selected from an ongoing database (N=1,012). Performance of the previously validated GAP model was compared with novel prediction models in each ILD subtype and the combined cohort. Patients with follow-up pulmonary function data were used for longitudinal model validation. The GAP model had good performance in all ILD subtypes (c-index, 74.6 in the combined cohort), which was maintained at all stages of disease severity and during follow-up evaluation. The GAP model had similar performance compared with alternative prediction models. A modified ILD-GAP Index was developed for application across all ILD subtypes to provide disease-specific survival estimates using a single risk prediction model. This was done by adding a disease subtype variable that accounted for better adjusted survival in connective tissue disease-associated ILD, chronic hypersensitivity pneumonitis, and idiopathic nonspecific interstitial pneumonia. The GAP model accurately predicts risk of death in chronic ILD. The ILD-GAP model accurately predicts mortality in major chronic ILD subtypes and at all stages of disease.

Knowledge Synthesis with Maps of Neural Connectivity

PubMed Central

Tallis, Marcelo; Thompson, Richard; Russ, Thomas A.; Burns, Gully A. P. C.

2011-01-01

This paper describes software for neuroanatomical knowledge synthesis based on neural connectivity data. This software supports a mature methodology developed since the early 1990s. Over this time, the Swanson laboratory at USC has generated an account of the neural connectivity of the sub-structures of the hypothalamus, amygdala, septum, hippocampus, and bed nucleus of the stria terminalis. This is based on neuroanatomical data maps drawn into a standard brain atlas by experts. In earlier work, we presented an application for visualizing and comparing anatomical macro connections using the Swanson third edition atlas as a framework for accurate registration. Here we describe major improvements to the NeuARt application based on the incorporation of a knowledge representation of experimental design. We also present improvements in the interface and features of the data mapping components within a unified web-application. As a step toward developing an accurate sub-regional account of neural connectivity, we provide navigational access between the data maps and a semantic representation of area-to-area connections that they support. We do so based on an approach called “Knowledge Engineering from Experimental Design” (KEfED) model that is based on experimental variables. We have extended the underlying KEfED representation of tract-tracing experiments by incorporating the definition of a neuronanatomical data map as a measurement variable in the study design. This paper describes the software design of a web-application that allows anatomical data sets to be described within a standard experimental context and thus indexed by non-spatial experimental design features. PMID:22053155

Integration of the Eventlndex with other ATLAS systems

NASA Astrophysics Data System (ADS)

Barberis, D.; Cárdenas Zárate, S. E.; Gallas, E. J.; Prokoshin, F.

2015-12-01

The ATLAS EventIndex System, developed for use in LHC Run 2, is designed to index every processed event in ATLAS, replacing the TAG System used in Run 1. Its storage infrastructure, based on Hadoop open-source software framework, necessitates revamping how information in this system relates to other ATLAS systems. It will store more indexes since the fundamental mechanisms for retrieving these indexes will be better integrated into all stages of data processing, allowing more events from later stages of processing to be indexed than was possible with the previous system. Connections with other systems (conditions database, monitoring) are fundamentally critical to assess dataset completeness, identify data duplication, and check data integrity, and also enhance access to information in EventIndex by user and system interfaces. This paper gives an overview of the ATLAS systems involved, the relevant metadata, and describe the technologies we are deploying to complete these connections.

Examining longitudinal train dynamics in ore car tipplers

NASA Astrophysics Data System (ADS)

Cole, Colin; Spiryagin, Maksym; Bosomworth, Chris

2017-04-01

Train simulation has been adapted in this paper to model the behaviour of indexing operations in ore car tippler operations. An important consideration in simulations at these low speeds (less than 4 km/h) is the increased rolling resistance transitioning from stationary conditions to motion. Most formulations of rolling resistance equations do not include this range although there are empirical values in some railway standards. The indexer control utilised here has a target trapezoidal velocity profile. The indexer to train connection was modelled as a stiff linear spring, a damper and a gap element. A sensitivity analysis was completed considering variations in wagon connections including wedge static friction, preload, coupling slack and tippler slack. Track topography including downhill grades of 0.1% and 0.2% and a valley profile were also investigated. Results showed high sensitivity to draft gear parameters of static friction and preload, but minimal benefit from downhill grades and changes in coupling slack.

Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks

PubMed Central

Samia, Yasmine; Lutscher, Frithjof; Hastings, Alan

2015-01-01

The movement of fish in watersheds is frequently inhibited by human-made migration barriers such as dams or culverts. The resulting lack of connectivity of spatial subpopulations is often cited as a cause for observed population decline. We formulate a matrix model for a spatially distributed fish population in a watershed, and we investigate how location and other characteristics of a single movement barrier impact the asymptotic growth rate of the population. We find that while population growth rate often decreases with the introduction of a movement obstacle, it may also increase due to a ‘retention effect’. Furthermore, obstacle mortality greatly affects population growth rate. In practice, different connectivity indices are used to predict population effects of migration barriers, but the relation of these indices to population growth rates in demographic models is often unclear. When comparing our results with the dentritic connectivity index, we see that the index captures neither the retention effect nor the influences of obstacle mortality. We argue that structural indices cannot entirely replace more detailed demographic models to understand questions of persistence and extinction. We advocate the development of novel functional indices and characteristics. PMID:26311313

Connectivity, passability and heterogeneity interact to determine fish population persistence in river networks.

PubMed

Samia, Yasmine; Lutscher, Frithjof; Hastings, Alan

2015-09-06

The movement of fish in watersheds is frequently inhibited by human-made migration barriers such as dams or culverts. The resulting lack of connectivity of spatial subpopulations is often cited as a cause for observed population decline. We formulate a matrix model for a spatially distributed fish population in a watershed, and we investigate how location and other characteristics of a single movement barrier impact the asymptotic growth rate of the population. We find that while population growth rate often decreases with the introduction of a movement obstacle, it may also increase due to a 'retention effect'. Furthermore, obstacle mortality greatly affects population growth rate. In practice, different connectivity indices are used to predict population effects of migration barriers, but the relation of these indices to population growth rates in demographic models is often unclear. When comparing our results with the dentritic connectivity index, we see that the index captures neither the retention effect nor the influences of obstacle mortality. We argue that structural indices cannot entirely replace more detailed demographic models to understand questions of persistence and extinction. We advocate the development of novel functional indices and characteristics. © 2015 The Author(s).

[Structure and function of Fenshuijiang Reservoir ecosystem based on the analysis with Ecopath model].

PubMed

Wu, Zhen; Jia, Pei-Qiao; Hu, Zhong-Jun; Chen, Li-Qiao; Gu, Zhi-Min; Liu, Qi-Gen

2012-03-01

Based on the 2008-2009 survey data of fishery resources and eco-environment of Fenshuijiang Reservoir, a mass balance model for the Reservoir ecosystem was constructed by Ecopath with Ecosim software. The model was composed of 14 functional groups, including silver carp, bighead carp, Hemibarbus maculates, Cutler alburnus, Microlepis and other fishes, Oligochaeta, aquatic insect, zooplankton, phytoplankton, and organic detritus, etc. , being able to better simulate Fenshuijiang Reservoir ecosystem. In this ecosystem, there were five trophic levels (TLs), and the nutrient flow mainly occurred in the first three TLs. Grazing and detritus food chains were the main energy flows in the ecosystem, but the food web was simpler and susceptible to be disturbed by outer environment. The transfer efficiency at lower TLs was relatively low, indicating that the ecosystem had a lower capability in energy utilization, and the excessive stock of nutrients in the ecosystem could lead to eutrophication. The lower connectance index, system omnivory index, Finn' s cycled index, and Finn's mean path length demonstrated that the ecosystem was unstable, while the high ecosystem property indices such as Pp/R and Pp/B showed that the ecosystem was immature and highly productive. It was suggested that Fenshuijiang Reservoir was still a developing new reservoir ecosystem, with a very short history and comparatively high primary productivity.

The effect of road network patterns on pedestrian safety: A zone-based Bayesian spatial modeling approach.

PubMed

Guo, Qiang; Xu, Pengpeng; Pei, Xin; Wong, S C; Yao, Danya

2017-02-01

Pedestrian safety is increasingly recognized as a major public health concern. Extensive safety studies have been conducted to examine the influence of multiple variables on the occurrence of pedestrian-vehicle crashes. However, the explicit relationship between pedestrian safety and road network characteristics remains unknown. This study particularly focused on the role of different road network patterns on the occurrence of crashes involving pedestrians. A global integration index via space syntax was introduced to quantify the topological structures of road networks. The Bayesian Poisson-lognormal (PLN) models with conditional autoregressive (CAR) prior were then developed via three different proximity structures: contiguity, geometry-centroid distance, and road network connectivity. The models were also compared with the PLN counterpart without spatial correlation effects. The analysis was based on a comprehensive crash dataset from 131 selected traffic analysis zones in Hong Kong. The results indicated that higher global integration was associated with more pedestrian-vehicle crashes; the irregular pattern network was proved to be safest in terms of pedestrian crash occurrences, whereas the grid pattern was the least safe; the CAR model with a neighborhood structure based on road network connectivity was found to outperform in model goodness-of-fit, implying the importance of accurately accounting for spatial correlation when modeling spatially aggregated crash data. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Dynamic evaluation on landscape connectivity of ecological land: a case study of Shenzhen, Guangdong Province of South China].

PubMed

Wu, Jian-Sheng; Liu, Hong-Meng; Huang, Xiu-Lan; Feng, Zhe

2012-09-01

Ecological land is the most crucial and sensitive land use type in rapidly urbanizing areas. Landscape connectivity can help us to better understand the interactions between landscape structure and landscape function. By using the land use data of Shenzhen from 1996 to 2008 and the graph theory- based integral index of connectivity (IIC), probability index of connectivity (PC), and importance value of patches (dPC), a dynamic evaluation on the landscape connectivity of ecological land in the City was conducted, and a spatial assessment was made to identify the most important patches for maintaining overall landscape connectivity. In combining with the basic ecological controlling line in Shenzhen, the variations of the landscape connectivity of the ecological land inside and outside the basic ecological controlling line were evaluated. From 1996 to 2008, the overall landscape connectivity of the ecological land in Shenzhen displayed a downward trend, the importance and the spatial distribution of the important patches for maintaining the overall landscape connectivity changed, and the basic ecological controlling line played definite roles in maintaining the landscape connectivity of ecological land inside the line.

Theoretical optimum of implant positional index design.

PubMed

Semper, W; Kraft, S; Krüger, T; Nelson, K

2009-08-01

Rotational freedom of the implant-abutment connection influences its screw joint stability; for optimization, influential factors need to be evaluated based on a previously developed closed formula. The underlying hypothesis is that the manufacturing tolerances, geometric pattern, and dimensions of the index do not influence positional stability. We used the dimensions of 5 commonly used implant systems with a clearance of 20 microm to calculate the extent of rotational freedom; a 3D simulation (SolidWorks) validated the analytical findings. Polygonal positional indices showed the highest degrees of rotational freedom. The polygonal profile displayed higher positional stability than the polygons, but less positional accuracy than the cam-groove connection. Features of a maximal rotation-safe positional index were determined. The analytical calculation of rotational freedom of implant positional indices is possible. Rotational freedom is dependent on the geometric design of the index and may be decreased by incorporating specific aspects into the positional index design.

Ventral and Dorsal Striatum Networks in Obesity: Link to Food Craving and Weight Gain.

PubMed

Contreras-Rodríguez, Oren; Martín-Pérez, Cristina; Vilar-López, Raquel; Verdejo-Garcia, Antonio

2017-05-01

The food addiction model proposes that obesity overlaps with addiction in terms of neurobiological alterations in the striatum and related clinical manifestations (i.e., craving and persistence of unhealthy habits). Therefore, we aimed to examine the functional connectivity of the striatum in excess-weight versus normal-weight subjects and to determine the extent of the association between striatum connectivity and individual differences in food craving and changes in body mass index (BMI). Forty-two excess-weight participants (BMI > 25) and 39 normal-weight participants enrolled in the study. Functional connectivity in the ventral and dorsal striatum was indicated by seed-based analyses on resting-state data. Food craving was indicated with subjective ratings of visual cues of high-calorie food. Changes in BMI between baseline and 12 weeks follow-up were assessed in 28 excess-weight participants. Measures of connectivity in the ventral striatum and dorsal striatum were compared between groups and correlated with craving and BMI change. Participants with excess weight displayed increased functional connectivity between the ventral striatum and the medial prefrontal and parietal cortices and between the dorsal striatum and the somatosensory cortex. Dorsal striatum connectivity correlated with food craving and predicted BMI gains. Obesity is linked to alterations in the functional connectivity of dorsal striatal networks relevant to food craving and weight gain. These neural alterations are associated with habit learning and thus compatible with the food addiction model of obesity. Copyright © 2016 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

Stochastic effects in a discretized kinetic model of economic exchange

NASA Astrophysics Data System (ADS)

Bertotti, M. L.; Chattopadhyay, A. K.; Modanese, G.

2017-04-01

Linear stochastic models and discretized kinetic theory are two complementary analytical techniques used for the investigation of complex systems of economic interactions. The former employ Langevin equations, with an emphasis on stock trade; the latter is based on systems of ordinary differential equations and is better suited for the description of binary interactions, taxation and welfare redistribution. We propose a new framework which establishes a connection between the two approaches by introducing random fluctuations into the kinetic model based on Langevin and Fokker-Planck formalisms. Numerical simulations of the resulting model indicate positive correlations between the Gini index and the total wealth, that suggest a growing inequality with increasing income. Further analysis shows, in the presence of a conserved total wealth, a simultaneous decrease in inequality as social mobility increases, in conformity with economic data.

Probing multi-scale self-similarity of tissue structures using light scattering spectroscopy: prospects in pre-cancer detection

NASA Astrophysics Data System (ADS)

Chatterjee, Subhasri; Das, Nandan K.; Kumar, Satish; Mohapatra, Sonali; Pradhan, Asima; Panigrahi, Prasanta K.; Ghosh, Nirmalya

2013-02-01

Multi-resolution analysis on the spatial refractive index inhomogeneities in the connective tissue regions of human cervix reveals clear signature of multifractality. We have thus developed an inverse analysis strategy for extraction and quantification of the multifractality of spatial refractive index fluctuations from the recorded light scattering signal. The method is based on Fourier domain pre-processing of light scattering data using Born approximation, and its subsequent analysis through Multifractal Detrended Fluctuation Analysis model. The method has been validated on several mono- and multi-fractal scattering objects whose self-similar properties are user controlled and known a-priori. Following successful validation, this approach has initially been explored for differentiating between different grades of precancerous human cervical tissues.

Equation-based model for the stock market

NASA Astrophysics Data System (ADS)

Xavier, Paloma O. C.; Atman, A. P. F.; de Magalhães, A. R. Bosco

2017-09-01

We propose a stock market model which is investigated in the forms of difference and differential equations whose variables correspond to the demand or supply of each agent and to the price. In the model, agents are driven by the behavior of their trust contact network as well by fundamental analysis. By means of the deterministic version of the model, the connection between such drive mechanisms and the price is analyzed: imitation behavior promotes market instability, finitude of resources is associated to stock index stability, and high sensitivity to the fair price provokes price oscillations. Long-range correlations in the price temporal series and heavy-tailed distribution of returns are observed for the version of the model which considers different proposals for stochasticity of microeconomic and macroeconomic origins.

[RS estimation of inventory parameters and carbon storage of moso bamboo forest based on synergistic use of object-based image analysis and decision tree].

PubMed

Du, Hua Qiang; Sun, Xiao Yan; Han, Ning; Mao, Fang Jie

2017-10-01

By synergistically using the object-based image analysis (OBIA) and the classification and regression tree (CART) methods, the distribution information, the indexes (including diameter at breast, tree height, and crown closure), and the aboveground carbon storage (AGC) of moso bamboo forest in Shanchuan Town, Anji County, Zhejiang Province were investigated. The results showed that the moso bamboo forest could be accurately delineated by integrating the multi-scale ima ge segmentation in OBIA technique and CART, which connected the image objects at various scales, with a pretty good producer's accuracy of 89.1%. The investigation of indexes estimated by regression tree model that was constructed based on the features extracted from the image objects reached normal or better accuracy, in which the crown closure model archived the best estimating accuracy of 67.9%. The estimating accuracy of diameter at breast and tree height was relatively low, which was consistent with conclusion that estimating diameter at breast and tree height using optical remote sensing could not achieve satisfactory results. Estimation of AGC reached relatively high accuracy, and accuracy of the region of high value achieved above 80%.

Improvement of a free software tool for the assessment of sediment connectivity

NASA Astrophysics Data System (ADS)

Crema, Stefano; Lanni, Cristiano; Goldin, Beatrice; Marchi, Lorenzo; Cavalli, Marco

2015-04-01

Sediment connectivity expresses the degree of linkage that controls sediment fluxes throughout landscape, in particular between sediment sources and downstream areas. The assessment of sediment connectivity becomes a key issue when dealing with risk mitigation and priorities of intervention in the territory. In this work, the authors report the improvements made to an open source and stand-alone application (SedInConnect, http://www.sedalp.eu/download/tools.shtml), along with extensive applications to alpine catchments. SedInConnect calculates a sediment connectivity index as expressed in Cavalli et al. (2013); the software improvements consisted primarily in the introduction of the sink feature, i.e. areas that act as traps for sediment produced upstream (e.g., lakes, sediment traps). Based on user-defined sinks, the software decouples those parts of the catchment that do not deliver sediment to a selected target of interest (e.g., fan apex, main drainage network). In this way the assessment of sediment connectivity is achieved by taking in consideration effective sediment contributing areas. Sediment connectivity analysis has been carried out on several catchments in the South Tyrol alpine area (Northern Italy) with the goal of achieving a fast and objective characterization of the topographic control on sediment transfer. In addition to depicting the variability of sediment connectivity inside each basin, the index of connectivity has proved to be a valuable indicator of the dominant process characterizing the basin sediment dynamics (debris flow, bedload, mixed behavior). The characterization of the dominant process is of great importance for the hazard and risk assessment in mountain areas, and for choice and design of structural and non-structural intervention measures. The recognition of the dominant sediment transport process by the index of connectivity is in agreement with evidences arising from post-event field surveys and with the application of morphometric indexes, such as the Melton ruggedness number, commonly used for discriminating debris-flow catchments from bedload catchments. References: Cavalli, M., Trevisani, S., Comiti, F., Marchi, L., 2013. Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology 188,31-41. doi:10.1016/j.geomorph.2012.05.007

Hydrologic Connectivity Estimated throughout the Nation's River Corridors

NASA Astrophysics Data System (ADS)

Hunt, R.; Borchardt, M. A.; Bradbury, K. R.

2014-12-01

Hydrologic connectivity is a key concept that integrates longitudinal transport in rivers with vertical and lateral exchanges between rivers and hyporheic zones, riparian wetlands, floodplains, and ponded aquatic ecosystems. Desirable levels of connectivity are thought to be associated with rivers that are well-connected longitudinally while also being well connected vertically and laterally with marginal waters where carbon and nutrients are efficiently transformed, and where aquatic organisms feed, or are reared, or take refuge during floods. But what is the proper balance between longitudinal and vertical and lateral connectivity? We took a step towards quantifying hydrologic connectivity using the model NEXSS (Gomez-Velez and Harvey, 2014, GRL) applied throughout the nation's rivers. NEXSS simulates vertical and lateral connectivity and compares it with longitudinal transport along the river's main axis. It uses as inputs measured network topology for first to eighth order channels, river hydraulic geometry, sediment grain size, bedform types and sizes, estimated hydraulic conductivity of sediments, and estimates of reaction rates such as denitrification. Results indicate that hyporheic flow is large enough to exchange a river's entire volume many times within a river network, which increases biogeochemical opportunities for nutrient processing and attenuation of contaminants. Also, the analysis demonstrated why and where (i.e., in which physiographic regions of the nation) are hyporheic flow and solute reactions the greatest. The cumulative influence of hydrologic connectivity on water quality is expressed by a dimensionless index of reaction significance. Our quantification of hydrologic connectivity adds a physical basis that supports water quality modeling, and also supports scientifically based prioritization of management actions (e.g. stream restoration) and may support other types of actions (e.g. legislative actions) to help conserve healthy functional rivers with proper levels of stream metabolism and diverse food webs. The NEXSS model will be modified to account for variable flow (baseflow to bankfull) and to account for exchange that occurs with overbank flooding of riparian wetlands and floodplains.

Hydrologic Connectivity Estimated throughout the Nation's River Corridors

NASA Astrophysics Data System (ADS)

Harvey, J. W.; Gomez-Velez, J. D.

2015-12-01

Hydrologic connectivity is a key concept that integrates longitudinal transport in rivers with vertical and lateral exchanges between rivers and hyporheic zones, riparian wetlands, floodplains, and ponded aquatic ecosystems. Desirable levels of connectivity are thought to be associated with rivers that are well-connected longitudinally while also being well connected vertically and laterally with marginal waters where carbon and nutrients are efficiently transformed, and where aquatic organisms feed, or are reared, or take refuge during floods. But what is the proper balance between longitudinal and vertical and lateral connectivity? We took a step towards quantifying hydrologic connectivity using the model NEXSS (Gomez-Velez and Harvey, 2014, GRL) applied throughout the nation's rivers. NEXSS simulates vertical and lateral connectivity and compares it with longitudinal transport along the river's main axis. It uses as inputs measured network topology for first to eighth order channels, river hydraulic geometry, sediment grain size, bedform types and sizes, estimated hydraulic conductivity of sediments, and estimates of reaction rates such as denitrification. Results indicate that hyporheic flow is large enough to exchange a river's entire volume many times within a river network, which increases biogeochemical opportunities for nutrient processing and attenuation of contaminants. Also, the analysis demonstrated why and where (i.e., in which physiographic regions of the nation) are hyporheic flow and solute reactions the greatest. The cumulative influence of hydrologic connectivity on water quality is expressed by a dimensionless index of reaction significance. Our quantification of hydrologic connectivity adds a physical basis that supports water quality modeling, and also supports scientifically based prioritization of management actions (e.g. stream restoration) and may support other types of actions (e.g. legislative actions) to help conserve healthy functional rivers with proper levels of stream metabolism and diverse food webs. The NEXSS model will be modified to account for variable flow (baseflow to bankfull) and to account for exchange that occurs with overbank flooding of riparian wetlands and floodplains.

On the history of the connectivity index: from the connectivity index to the exact solution of the protein alignment problem.

PubMed

Randić, M

2015-01-01

We briefly review the history of the connectivity index from 1975 to date. We hope to throw some light on why this unique, by its design, graph theoretical molecular descriptor continues to be of interest in QSAR, having wide use in applications in structure-property and structure-activity studies. We will elaborate on its generalizations and the insights it offered on applications in Multiple Regression Analysis (MRA). Going beyond the connectivity index we will outline several related developments in the development of molecular descriptors used in MRA, including molecular ID numbers (1986), the variable connectivity index (1991), orthogonal regression (1991), irrelevance of co-linearity of descriptors (1997), anti-connectivity (2006), and high discriminatory descriptors characterizing molecular similarity (2015). We will comment on beauty in QSAR and recent progress in searching for similarity of DNA, proteins and the proteome. This review reports on several results which are little known to the structure-property-activity community, the significance of which may surprise those unfamiliar with the application of discrete mathematics to chemistry. It tells the reader many unknown stories about the connectivity index, which may help the reader to better understand the meaning of this index. Readers are not required to be familiar with graph theory.

Global and regional cortical connectivity maturation index (CCMI) of developmental human brain with quantification of short-range association tracts

NASA Astrophysics Data System (ADS)

Ouyang, Minhui; Jeon, Tina; Mishra, Virendra; Du, Haixiao; Wang, Yu; Peng, Yun; Huang, Hao

2016-03-01

From early childhood to adulthood, synaptogenesis and synaptic pruning continuously reshape the structural architecture and neural connection in developmental human brains. Disturbance of the precisely balanced strengthening of certain axons and pruning of others may cause mental disorders such as autism and schizophrenia. To characterize this balance, we proposed a novel measurement based on cortical parcellation and diffusion MRI (dMRI) tractography, a cortical connectivity maturation index (CCMI). To evaluate the spatiotemporal sensitivity of CCMI as a potential biomarker, dMRI and T1 weighted datasets of 21 healthy subjects 2-25 years were acquired. Brain cortex was parcellated into 68 gyral labels using T1 weighted images, then transformed into dMRI space to serve as the seed region of interest for dMRI-based tractography. Cortico-cortical association fibers initiated from each gyrus were categorized into long- and short-range ones, based on the other end of fiber terminating in non-adjacent or adjacent gyri of the seed gyrus, respectively. The regional CCMI was defined as the ratio between number of short-range association tracts and that of all association tracts traced from one of 68 parcellated gyri. The developmental trajectory of the whole brain CCMI follows a quadratic model with initial decreases from 2 to 16 years followed by later increases after 16 years. Regional CCMI is heterogeneous among different cortical gyri with CCMI dropping to the lowest value earlier in primary somatosensory cortex and visual cortex while later in the prefrontal cortex. The proposed CCMI may serve as sensitive biomarker for brain development under normal or pathological conditions.

High reliability solid refractive index matching materials for field installable connections in FTTH network

NASA Astrophysics Data System (ADS)

Saito, Kotaro; Kihara, Mitsuru; Shimizu, Tomoya; Yoneda, Keisuke; Kurashima, Toshio

2015-06-01

We performed environmental and accelerated aging tests to ensure the long-term reliability of solid type refractive index matching material at a splice point. Stable optical characteristics were confirmed in environmental tests based on an IEC standard. In an accelerated aging test at 140 °C, which is very much higher than the specification test temperature, the index matching material itself and spliced fibers passing through it had steady optical characteristics. Then we performed an accelerated aging test on an index matching material attached to a built-in fiber before splicing it in the worst condition, which is different from the normal use configuration. As a result, we confirmed that the repeated insertion and removal of fiber for splicing resulted in failure. We consider that the repetition of adhesion between index matching material and fibers causes the splice to degrade. With this result, we used the Arrhenius model to estimate a median lifetime of about 68 years in a high temperature environment of 60 °C. Thus solid type index matching material at a splice point is highly reliable over long periods under normal conditions of use.

Safety models incorporating graph theory based transit indicators.

PubMed

Quintero, Liliana; Sayed, Tarek; Wahba, Mohamed M

2013-01-01

There is a considerable need for tools to enable the evaluation of the safety of transit networks at the planning stage. One interesting approach for the planning of public transportation systems is the study of networks. Network techniques involve the analysis of systems by viewing them as a graph composed of a set of vertices (nodes) and edges (links). Once the transport system is visualized as a graph, various network properties can be evaluated based on the relationships between the network elements. Several indicators can be calculated including connectivity, coverage, directness and complexity, among others. The main objective of this study is to investigate the relationship between network-based transit indicators and safety. The study develops macro-level collision prediction models that explicitly incorporate transit physical and operational elements and transit network indicators as explanatory variables. Several macro-level (zonal) collision prediction models were developed using a generalized linear regression technique, assuming a negative binomial error structure. The models were grouped into four main themes: transit infrastructure, transit network topology, transit route design, and transit performance and operations. The safety models showed that collisions were significantly associated with transit network properties such as: connectivity, coverage, overlapping degree and the Local Index of Transit Availability. As well, the models showed a significant relationship between collisions and some transit physical and operational attributes such as the number of routes, frequency of routes, bus density, length of bus and 3+ priority lanes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Right Heart End-Systolic Remodeling Index Strongly Predicts Outcomes in Pulmonary Arterial Hypertension: Comparison With Validated Models.

PubMed

Amsallem, Myriam; Sweatt, Andrew J; Aymami, Marie C; Kuznetsova, Tatiana; Selej, Mona; Lu, HongQuan; Mercier, Olaf; Fadel, Elie; Schnittger, Ingela; McConnell, Michael V; Rabinovitch, Marlene; Zamanian, Roham T; Haddad, Francois

2017-06-01

Right ventricular (RV) end-systolic dimensions provide information on both size and function. We investigated whether an internally scaled index of end-systolic dimension is incremental to well-validated prognostic scores in pulmonary arterial hypertension. From 2005 to 2014, 228 patients with pulmonary arterial hypertension were prospectively enrolled. RV end-systolic remodeling index (RVESRI) was defined by lateral length divided by septal height. The incremental values of RV free wall longitudinal strain and RVESRI to risk scores were determined. Mean age was 49±14 years, 78% were female, 33% had connective tissue disease, 52% were in New York Heart Association class ≥III, and mean pulmonary vascular resistance was 11.2±6.4 WU. RVESRI and right atrial area were strongly connected to the other right heart metrics. Three zones of adaptation (adapted, maladapted, and severely maladapted) were identified based on the RVESRI to RV systolic pressure relationship. During a mean follow-up of 3.9±2.4 years, the primary end point of death, transplant, or admission for heart failure was reached in 88 patients. RVESRI was incremental to risk prediction scores in pulmonary arterial hypertension, including the Registry to Evaluate Early and Long-Term PAH Disease Management score, the Pulmonary Hypertension Connection equation, and the Mayo Clinic model. Using multivariable analysis, New York Heart Association class III/IV, RVESRI, and log NT-proBNP (N-Terminal Pro-B-Type Natriuretic Peptide) were retained (χ 2 , 62.2; P <0.0001). Changes in RVESRI at 1 year (n=203) were predictive of outcome; patients initiated on prostanoid therapy showed the greatest improvement in RVESRI. Among right heart metrics, RVESRI demonstrated the best test-retest characteristics. RVESRI is a simple reproducible prognostic marker in patients with pulmonary arterial hypertension. © 2017 American Heart Association, Inc.

Self-organized criticality in a network of economic agents with finite consumption

NASA Astrophysics Data System (ADS)

da Cruz, João P.; Lind, Pedro G.

2012-02-01

We introduce a minimal agent model to explain the emergence of heavy-tailed return distributions as a result of self-organized criticality. The model assumes that agents trade their economic outputs with each other composing a complex network of agents and connections. Further, the incoming degree of an agent is proportional to the demand on its goods, while its outgoing degree is proportional to the supply. The model considers a collection of economic agents which are attracted to establish connections among them to make an exchange at a price formed by supply and demand. With our model we are able to reproduce the evolution of the return of macroscopic quantities (indices) and to correctly retrieve the non-trivial exponent value characterizing the amplitude of drops in several indices in financial markets, relating it to the underlying topology of connections. The distribution of drops in empirical data is obtained by counting the number of successive time-steps for which a decrease in the index value is observed. All eight financial indexes show an exponent m˜5/2. Finally, we present mean-field calculations of the critical exponents, and of the scaling relation m=3/2 γ-1 between the exponent m for the distribution of drops and the topological exponent γ for the degree distribution.

Network diffusion-based analysis of high-throughput data for the detection of differentially enriched modules

PubMed Central

Bersanelli, Matteo; Mosca, Ettore; Remondini, Daniel; Castellani, Gastone; Milanesi, Luciano

2016-01-01

A relation exists between network proximity of molecular entities in interaction networks, functional similarity and association with diseases. The identification of network regions associated with biological functions and pathologies is a major goal in systems biology. We describe a network diffusion-based pipeline for the interpretation of different types of omics in the context of molecular interaction networks. We introduce the network smoothing index, a network-based quantity that allows to jointly quantify the amount of omics information in genes and in their network neighbourhood, using network diffusion to define network proximity. The approach is applicable to both descriptive and inferential statistics calculated on omics data. We also show that network resampling, applied to gene lists ranked by quantities derived from the network smoothing index, indicates the presence of significantly connected genes. As a proof of principle, we identified gene modules enriched in somatic mutations and transcriptional variations observed in samples of prostate adenocarcinoma (PRAD). In line with the local hypothesis, network smoothing index and network resampling underlined the existence of a connected component of genes harbouring molecular alterations in PRAD. PMID:27731320

Performance evaluation method of electric energy data acquire system based on combination of subjective and objective weights

NASA Astrophysics Data System (ADS)

Gao, Chen; Ding, Zhongan; Deng, Bofa; Yan, Shengteng

2017-10-01

According to the characteristics of electric energy data acquire system (EEDAS), considering the availability of each index data and the connection between the index integrity, establishing the performance evaluation index system of electric energy data acquire system from three aspects as master station system, communication channel, terminal equipment. To determine the comprehensive weight of each index based on triangular fuzzy number analytic hierarchy process with entropy weight method, and both subjective preference and objective attribute are taken into consideration, thus realize the performance comprehensive evaluation more reasonable and reliable. Example analysis shows that, by combination with analytic hierarchy process (AHP) and triangle fuzzy numbers (TFN) to establish comprehensive index evaluation system based on entropy method, the evaluation results not only convenient and practical, but also more objective and accurate.

Fuzzy comprehensive evaluation for grid-connected performance of integrated distributed PV-ES systems

NASA Astrophysics Data System (ADS)

Lv, Z. H.; Li, Q.; Huang, R. W.; Liu, H. M.; Liu, D.

2016-08-01

Based on the discussion about topology structure of integrated distributed photovoltaic (PV) power generation system and energy storage (ES) in single or mixed type, this paper focuses on analyzing grid-connected performance of integrated distributed photovoltaic and energy storage (PV-ES) systems, and proposes a comprehensive evaluation index system. Then a multi-level fuzzy comprehensive evaluation method based on grey correlation degree is proposed, and the calculations for weight matrix and fuzzy matrix are presented step by step. Finally, a distributed integrated PV-ES power generation system connected to a 380 V low voltage distribution network is taken as the example, and some suggestions are made based on the evaluation results.

Digital image analysis to quantify carbide networks in ultrahigh carbon steels

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

Hecht, Matthew D.; Webler, Bryan A.; Picard, Yoosuf N., E-mail: ypicard@cmu.edu

A method has been developed and demonstrated to quantify the degree of carbide network connectivity in ultrahigh carbon steels through digital image processing and analysis of experimental micrographs. It was shown that the network connectivity and carbon content can be correlated to toughness for various ultrahigh carbon steel specimens. The image analysis approach first involved segmenting the carbide network and pearlite matrix into binary contrast representations via a grayscale intensity thresholding operation. Next, the carbide network pixels were skeletonized and parceled into braches and nodes, allowing the determination of a connectivity index for the carbide network. Intermediate image processing stepsmore » to remove noise and fill voids in the network are also detailed. The connectivity indexes of scanning electron micrographs were consistent in both secondary and backscattered electron imaging modes, as well as across two different (50 × and 100 ×) magnifications. Results from ultrahigh carbon steels reported here along with other results from the literature generally showed lower connectivity indexes correlated with higher Charpy impact energy (toughness). A deviation from this trend was observed at higher connectivity indexes, consistent with a percolation threshold for crack propagation across the carbide network. - Highlights: • A method for carbide network analysis in steels is proposed and demonstrated. • ImageJ method extracts a network connectivity index from micrographs. • Connectivity index consistent in different imaging conditions and magnifications. • Impact energy may plateau when a critical network connectivity is exceeded.« less

A simplified GIS-based model for large wood recruitment and connectivity in mountain basins

NASA Astrophysics Data System (ADS)

Lucía, Ana; Antonello, Andrea; Campana, Daniela; Cavalli, Marco; Crema, Stefano; Franceschi, Silvia; Marchese, Enrico; Niedrist, Martin; Schneiderbauer, Stefan; Comiti, Francesco

2014-05-01

The mobilization of large wood (LW) elements in mountain rivers channels during floods may increase their hazard potential, especially by clogging narrow sections such as bridges. However, the prediction of LW transport magnitude during flood events is a challenging topic. Although some models on LW transport have been recently developed, the objective of this work was to generate a simplified GIS-based model to identify along the channel network the most likely LW-related critical sections during high-magnitude flood events in forested mountain basins. Potential LW contribution generated by landsliding occurring on hillslopes is assessed using SHALSTAB stability model coupled to a GIS-based connectivity index, developed as a modification of the index proposed by Cavalli et al (2013). Connected slope-derived LW volumes are then summed at each raster cell to LW volumes generated by bank erosion along the erodibile part of river corridors, where bank erosion processes are estimated based on user-defined channel widening ratios stemming from observations following recent extreme events in mountain basins. LW volume in the channel is then routed through the stream network applying simple Boolean rules meant to capture the most important limiting transport condition in these high-energy systems at flood stage, i.e. flow width relative to log length. In addition, the role of bridges and retention check-dams in blocking floating logs is accounted for in the model, in particular bridge length and height are used to characterize their clogging susceptibility for different levels of expected LW volumes and size. The model has been tested in the Rienz and Ahr basins (about 630 km2 each), located in the Eastern Italian Alps. Sixty percent of the basin area is forested, and elevations range from 811 m a.s.l. to 3488 m a.s.l.. We used a 2.5 m resolution DTM and DSM, and their difference was used to calculate the canopy height. Data from 35 plots of the National Forest Inventory were used to estimate forest stand volume by a semi-empirical model. Ddatabase on shallow landslides along with precipitation depth was utilized to calibrate the parameters for the SHALSTAB model. Orthophotos (0.5 m pixel resolution) and existing technical maps were used to delimitate the channel banks, which were used to calculate automatically channel width for each grid cell. The model output provided information about the expected volume and mean size of LW recruited and transported during a 300 yr flood event in the test basins, as well as the location of the most probable clogged sections (mostly related to infrastructures) along the channel network. The model thus shows the capability to assist river managers in identifying the most critical sections of river networks and to assess the effectiveness and location of different mitigation options such as wood retention structures or forest management practices.

Understanding Existing Salmonid Habitat Availability and Connectivity to Improve River Management

NASA Astrophysics Data System (ADS)

Duffin, J.; Yager, E.; Tonina, D.; Benjankar, R. M.

2017-12-01

In the Pacific Northwest river restoration is common for salmon conservation. Mangers need methods to help target restoration to problem areas in rivers to create habitat that meets a species' needs. Hydraulic models and habitat suitability curves provide basic information on habitat availability and overall quality, but these analyses need to be expanded to address habitat quality based on the accessibility of habitats required for multiple life stages. Scientists are starting to use connectivity measurements to understand the longitudinal proximity of habitat patches, which can be used to address the habitat variability of a reach. By evaluating the availability and quality of habitat and calculating the connectivity between complementary habitats, such as spawning and rearing habitats, we aim to identify areas that should be targeted for restoration. To meet these goals, we assessed Chinook salmon habitat on the Lemhi River in Idaho. The depth and velocity outputs from a 2D hydraulic model are used in conjunction with locally created habitat suitability curves to evaluate the availability and quality of habitat for multiple Chinook salmon life stages. To assess the variability of the habitat, connectivity between habitat patches necessary for different life stages is calculated with a proximity index. A spatial representation of existing habitat quality and connectivity between complimentary habitats can be linked to river morphology by the evaluation of local geomorphic characteristics, including sinuosity and channel units. The understanding of the current habitat availability for multiple life stage needs, the connectivity between these habitat patches, and their relationship with channel morphology can help managers better identify restoration needs and direct their limited resources.

Adaptation of Sediment Connectivity Index for Swedish catchments and application for flood prediction of roads

NASA Astrophysics Data System (ADS)

Cantone, Carolina; Kalantari, Zahra; Cavalli, Marco; Crema, Stefano

2016-04-01

Climate changes are predicted to increase precipitation intensities and occurrence of extreme rainfall events in the near future. Scandinavia has been identified as one of the most sensitive regions in Europe to such changes; therefore, an increase in the risk for flooding, landslides and soil erosion is to be expected also in Sweden. An increase in the occurrence of extreme weather events will impose greater strain on the built environment and major transport infrastructures such as roads and railways. This research aimed to identify the risk of flooding at the road-stream intersections, crucial locations where water and debris can accumulate and cause failures of the existing drainage facilities. Two regions in southwest of Sweden affected by an extreme rainfall event in August 2014, were used for calibrating and testing a statistical flood prediction model. A set of Physical Catchment Descriptors (PCDs) including road and catchment characteristics was identified for the modelling. Moreover, a GIS-based topographic Index of Sediment Connectivity (IC) was used as PCD. The novelty of this study relies on the adaptation of IC for describing sediment connectivity in lowland areas taking into account contribution of soil type, land use and different patterns of precipitation during the event. A weighting factor for IC was calculated by estimating runoff calculated with SCS Curve Number method, assuming a constant value of precipitation for a given time period, corresponding to the critical event. The Digital Elevation Model of the study site was reconditioned at the drainage facilities locations to consider the real flow path in the analysis. These modifications led to highlight the role of rainfall patterns and surface runoff for modelling sediment delivery in lowland areas. Moreover, it was observed that integrating IC into the statistic prediction model increased its accuracy and performance. After the calibration procedure in one of the study areas, the model was validated in the other study area, located in the central part of Sweden, since this experienced flooding in relation to the same triggering event.

Landscape genetics of high mountain frog metapopulations

USGS Publications Warehouse

Murphy, M.A.; Dezzani, R.; Pilliod, D.S.; Storfer, A.

2010-01-01

Explaining functional connectivity among occupied habitats is crucial for understanding metapopulation dynamics and species ecology. Landscape genetics has primarily focused on elucidating how ecological features between observations influence gene flow. Functional connectivity, however, may be the result of both these between-site (landscape resistance) landscape characteristics and at-site (patch quality) landscape processes that can be captured using network based models. We test hypotheses of functional connectivity that include both between-site and at-site landscape processes in metapopulations of Columbia spotted frogs (Rana luteiventris) by employing a novel justification of gravity models for landscape genetics (eight microsatellite loci, 37 sites, n = 441). Primarily used in transportation and economic geography, gravity models are a unique approach as flow (e.g. gene flow) is explained as a function of three basic components: distance between sites, production/attraction (e.g. at-site landscape process) and resistance (e.g. between-site landscape process). The study system contains a network of nutrient poor high mountain lakes where we hypothesized a short growing season and complex topography between sites limit R. luteiventris gene flow. In addition, we hypothesized production of offspring is limited by breeding site characteristics such as the introduction of predatory fish and inherent site productivity. We found that R. luteiventris connectivity was negatively correlated with distance between sites, presence of predatory fish (at-site) and topographic complexity (between-site). Conversely, site productivity (as measured by heat load index, at-site) and growing season (as measured by frost-free period between-sites) were positively correlated with gene flow. The negative effect of predation and positive effect of site productivity, in concert with bottleneck tests, support the presence of source-sink dynamics. In conclusion, gravity models provide a powerful new modelling approach for examining a wide range of both basic and applied questions in landscape genetics.

Street connectivity and obesity in Glasgow, Scotland: impact of age, sex and socioeconomic position.

PubMed

Ball, Kylie; Lamb, Karen; Travaglini, Noemi; Ellaway, Anne

2012-11-01

This study investigated associations of street connectivity with body mass index (BMI), and whether these associations varied by sex, age and socioeconomic position, amongst adults in Glasgow, Scotland. Data on socio-demographic variables, height and weight were collected from 1062 participants in the Greater Glasgow Health and Well-being Study, and linked with neighbourhood-level census and geo-referenced data on area level deprivation and street connectivity. Results of multilevel models showed that, after adjustment for individual level covariates, street connectivity was not significantly associated with either BMI or BMI category; nor were there any significant interactions between age, sex or socioeconomic position and street connectivity. Copyright © 2012 Elsevier Ltd. All rights reserved.

East Java Maritime Connectivity and Its Regional Development Support

NASA Astrophysics Data System (ADS)

Purboyo, H.; Ibad, M. Z.

2017-07-01

The study presents an evolution of maritime connectivity index of East Java which is associated with accessibility and mobility index of regions in East Java. The findings show that East Java increased connectivity more than three times from 1996 to 2011. Initially, the East Java is importer but then become exporter to national territory. For accessibility, the inland regions of East Java in general is higher than the coastal areas. And for mobility, inland regions initially have a small index, but in subsequent years its index is greater than the coastal areas.

On Atom-Bond Connectivity Index

NASA Astrophysics Data System (ADS)

Zhou, Bo; Xing, Rundan

2011-02-01

The atom-bond connectivity (ABC) index, introduced by Estrada et al. in 1998, displays an excellent correlation with the formation heat of alkanes. We give upper bounds for this graph invariant using the number of vertices, the number of edges, the Randíc connectivity indices, and the first Zagreb index. We determine the unique tree with the maximum ABC index among trees with given numbers of vertices and pendant vertices, and the n-vertex trees with the maximum, and the second, the third, and the fourth maximum ABC indices for n ≥ 6.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference.

PubMed

Widdows, Dominic; Cohen, Trevor

2015-10-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.

Reasoning with Vectors: A Continuous Model for Fast Robust Inference

PubMed Central

Widdows, Dominic; Cohen, Trevor

2015-01-01

This paper describes the use of continuous vector space models for reasoning with a formal knowledge base. The practical significance of these models is that they support fast, approximate but robust inference and hypothesis generation, which is complementary to the slow, exact, but sometimes brittle behavior of more traditional deduction engines such as theorem provers. The paper explains the way logical connectives can be used in semantic vector models, and summarizes the development of Predication-based Semantic Indexing, which involves the use of Vector Symbolic Architectures to represent the concepts and relationships from a knowledge base of subject-predicate-object triples. Experiments show that the use of continuous models for formal reasoning is not only possible, but already demonstrably effective for some recognized informatics tasks, and showing promise in other traditional problem areas. Examples described in this paper include: predicting new uses for existing drugs in biomedical informatics; removing unwanted meanings from search results in information retrieval and concept navigation; type-inference from attributes; comparing words based on their orthography; and representing tabular data, including modelling numerical values. The algorithms and techniques described in this paper are all publicly released and freely available in the Semantic Vectors open-source software package.1 PMID:26582967

Increased overall cortical connectivity with syndrome specific local decreases suggested by atypical sleep-EEG synchronization in Williams syndrome.

PubMed

Gombos, Ferenc; Bódizs, Róbert; Kovács, Ilona

2017-07-21

Williams syndrome (7q11.23 microdeletion) is characterized by specific alterations in neurocognitive architecture and functioning, as well as disordered sleep. Here we analyze the region, sleep state and frequency-specific EEG synchronization of whole night sleep recordings of 21 Williams syndrome and 21 typically developing age- and gender-matched subjects by calculating weighted phase lag indexes. We found broadband increases in inter- and intrahemispheric neural connectivity for both NREM and REM sleep EEG of Williams syndrome subjects. These effects consisted of increased theta, high sigma, and beta/low gamma synchronization, whereas alpha synchronization was characterized by a peculiar Williams syndrome-specific decrease during NREM states (intra- and interhemispheric centro-temporal) and REM phases of sleep (occipital intra-area synchronization). We also found a decrease in short range, occipital connectivity of NREM sleep EEG theta activity. The striking increased overall synchronization of sleep EEG in Williams syndrome subjects is consistent with the recently reported increase in synaptic and dendritic density in stem-cell based Williams syndrome models, whereas decreased alpha and occipital connectivity might reflect and underpin the altered microarchitecture of primary visual cortex and disordered visuospatial functioning of Williams syndrome subjects.

On the Hosoya index of a family of deterministic recursive trees

NASA Astrophysics Data System (ADS)

Chen, Xufeng; Zhang, Jingyuan; Sun, Weigang

2017-01-01

In this paper, we calculate the Hosoya index in a family of deterministic recursive trees with a special feature that includes new nodes which are connected to existing nodes with a certain rule. We then obtain a recursive solution of the Hosoya index based on the operations of a determinant. The computational complexity of our proposed algorithm is O(log2 n) with n being the network size, which is lower than that of the existing numerical methods. Finally, we give a weighted tree shrinking method as a graphical interpretation of the recurrence formula for the Hosoya index.

Highlighting landslides and other geomorphological features using sediment connectivity maps

NASA Astrophysics Data System (ADS)

Bossi, Giulia; Crema, Stefano; Cavalli, Marco; Marcato, Gianluca; Pasuto, Alessandro

2016-04-01

Landslide identification is usually made through interpreting geomorphological features in the field or with remote sensing imagery. In recent years, airborne laser scanning (LiDAR) has enhanced the potentiality of geomorphological investigations by providing a detailed and diffuse representation of the land surface. The development of algorithms for geomorphological analysis based on LiDAR derived high-resolution Digital Terrain Models (DTMs) is increasing. Among them, the sediment connectivity index (IC) has been used to quantify sediment dynamics in alpine catchments. In this work, maps of the sediment connectivity index are used for detecting geomorphological features and processes not exclusively related to water-laden processes or debris flows. The test area is located in the upper Passer Valley in South Tyrol (Italy). Here a 4 km2 Deep-seated Gravitational Slope Deformation (DGSD) with several secondary phenomena has been studied for years. The connectivity index was applied to a well-known study area in order to evaluate its effectiveness as an interpretative layer to assist geomorphological analysis. Results were cross checked with evidence previously identified by means of in situ investigations, photointerpretation and monitoring data. IC was applied to a 2.5 m LiDAR derived DTM using two different scenarios in order to test their effectiveness: i) IC derived on the hydrologically correct DTM; ii) IC derived on the original DTM. In the resulting maps a cluster of low-connectivity areas appears as the deformation of the DGSD induce a convexity in the central part of the phenomenon. The double crests, product of the sagging of the landslide, are extremely evident since in those areas the flow directions diverge from the general drainage pattern, which is directed towards the valley river. In the crown area a rock-slab that shows clear evidence of incumbent detachment is clearly highlighted since the maps emphasize the presence of traction trenches and reverse slope. In the second scenario, rockfall activity is more evident since the collapse path induces scars in the slope that locally are identified as flow paths, moreover the presence of the block remnants creates an obstruction (i.e., a sink) for the algorithm. On the other hand, the presence of a smaller rotational landslide at the toe of the DGSD is more detectable in the map derived from the first scenario that shows a rapid change in slope together with a high drainage concentration. An integrated approach that assists the geomorphologic analysis based on aerial images and shaded relief maps with an IC map has proven to be a valuable tool as it allows to highlight different gravitational processes.

Improved predictability of droughts over southern Africa using the standardized precipitation evapotranspiration index and ENSO

NASA Astrophysics Data System (ADS)

Manatsa, Desmond; Mushore, Terrence; Lenouo, Andre

2017-01-01

The provision of timely and reliable climate information on which to base management decisions remains a critical component in drought planning for southern Africa. In this observational study, we have not only proposed a forecasting scheme which caters for timeliness and reliability but improved relevance of the climate information by using a novel drought index called the standardised precipitation evapotranspiration index (SPEI), instead of the traditional precipitation only based index, the standardised precipitation index (SPI). The SPEI which includes temperature and other climatic factors in its construction has a more robust connection to ENSO than the SPI. Consequently, the developed ENSO-SPEI prediction scheme can provide quantitative information about the spatial extent and severity of predicted drought conditions in a way that reflects more closely the level of risk in the global warming context of the sub region. However, it is established that the ENSO significant regional impact is restricted only to the period December-March, implying a revisit to the traditional ENSO-based forecast scheme which essentially divides the rainfall season into the two periods, October to December and January to March. Although the prediction of ENSO events has increased with the refinement of numerical models, this work has demonstrated that the prediction of drought impacts related to ENSO is also a reality based only on observations. A large temporal lag is observed between the development of ENSO phenomena (typically in May of the previous year) and the identification of regional SPEI defined drought conditions. It has been shown that using the Southern Africa Regional Climate Outlook Forum's (SARCOF) traditional 3-month averaged Nino 3.4 SST index (June to August) as a predictor does not have an added advantage over using only the May SST index values. In this regard, the extended lead time and improved skill demonstrated in this study could immensely benefit regional decision makers.

Sediment connectivity evolution on an alpine catchment undergoing glacier retreat

NASA Astrophysics Data System (ADS)

Goldin, Beatrice; Rudaz, Benjamin; Bardou, Eric

2014-05-01

Climate changes can result in a wide range of variations of natural environment including retreating glaciers. Melting from glaciers will have a significant impact on the sediment transport characteristics of glacierized alpine catchments that can affect downstream channel network. Sediment connectivity assessment, i.e. the degree of connections that controls sediment fluxes between different segments of a landscape, can be useful in order to address management activity on sediment fluxes changes of alpine streams. Through the spatial characterization of the connectivity patterns of a catchment and its potential evolution it is possible to both define sediment transport pathways and estimate different contributions of the sub-catchment as sediment sources. In this study, a topography based index (Cavalli et al., 2013) has been applied to assess spatial sediment connectivity in the Navisence catchment (35 km2), an alpine basin located in the southern Walliser Alps (Switzerland) characterized by a complex glacier system with well-developed lateral moraines on glacier margins already crossed by several lateral channels. Glacier retreat of the main glacial edifice will provide a new connectivity pattern. At present the glacier disconnects lateral slopes from the main talweg: it is expected that its retreat will experience an increased connectivity. In order to study this evolution, two high resolution (2 m) digital terrain models (DTMs) describing respectively the terrain before and after glacier retreat have been analyzed. The current DTM was obtained from high resolution photogrammetry (2 m resolution). The future DTM was derived from application of the sloping local base level (SLBL) routine (Jaboyedoff et al., 2004) on the current glacier system, allowing to remove the ice body by reconstituting a U-shaped polynomial bedrock surface. From this new surface a coherent river network was drawn and slight random noise was added. Finally the river network was burned into the rough surface of the SLBL results. The impact of sediment dynamic changes on the study catchment due to glacier retreat has been assessed by comparing predictions deriving from model application on different scenarios. Simulations allowed the analysis of sediment connectivity evolution over decade scales suggesting an increase of potential sediment transfer and connections in areas close to the main channel network. References: Cavalli, M., Trevisani, S., Comiti, F., Marchi, L., 2013. Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology 188, 31-41. Jaboyedoff M., Bardou E., Derron M.-H. 2004. Sloping local base level: a tool to estimate potential erodible volume and infilling alluvial sediment of glacial valleys. Swiss Geo-Scientists meeting, November 2004, Lausanne.

SETI@home

Science.gov Websites

experiment, based at UC Berkeley, that uses Internet-connected computers in the Search for Extraterrestrial several hours to be sure. If that didn't solve the problem, it probably means the index the server uses to

The Kirchhoff index and the matching number

NASA Astrophysics Data System (ADS)

Zhou, Bo; Trinajstić, Nenad

The Kirchhoff index of a connected (molecular) graph is the sum of the resistance-distances between all unordered pairs of vertices and may also be expressed by its Laplacian eigenvalues. We determine the minimum Kirchhoff index of connected (molecular) graphs in terms of the number of vertices and matching number and characterize the unique extremal graph. The results on the Kirchhoff index are compared with the corresponding results on the Wiener index.

Establishment of key grid-connected performance index system for integrated PV-ES system

NASA Astrophysics Data System (ADS)

Li, Q.; Yuan, X. D.; Qi, Q.; Liu, H. M.

2016-08-01

In order to further promote integrated optimization operation of distributed new energy/ energy storage/ active load, this paper studies the integrated photovoltaic-energy storage (PV-ES) system which is connected with the distribution network, and analyzes typical structure and configuration selection for integrated PV-ES generation system. By combining practical grid- connected characteristics requirements and technology standard specification of photovoltaic generation system, this paper takes full account of energy storage system, and then proposes several new grid-connected performance indexes such as paralleled current sharing characteristic, parallel response consistency, adjusting characteristic, virtual moment of inertia characteristic, on- grid/off-grid switch characteristic, and so on. A comprehensive and feasible grid-connected performance index system is then established to support grid-connected performance testing on integrated PV-ES system.

Watershed Dynamics, with focus on connectivity index and management of water related impacts on road infrastructure

NASA Astrophysics Data System (ADS)

Kalantari, Z.

2015-12-01

In Sweden, spatially explicit approaches have been applied in various disciplines such as landslide modelling based on soil type data and flood risk modelling for large rivers. Regarding flood mapping, most previous studies have focused on complex hydrological modelling on a small scale whereas just a few studies have used a robust GIS-based approach integrating most physical catchment descriptor (PCD) aspects on a larger scale. This study was built on a conceptual framework for looking at SedInConnect model, topography, land use, soil data and other PCDs and climate change in an integrated way to pave the way for more integrated policy making. The aim of the present study was to develop methodology for predicting the spatial probability of flooding on a general large scale. This framework can provide a region with an effective tool to inform a broad range of watershed planning activities within a region. Regional planners, decision-makers, etc. can utilize this tool to identify the most vulnerable points in a watershed and along roads to plan for interventions and actions to alter impacts of high flows and other extreme weather events on roads construction. The application of the model over a large scale can give a realistic spatial characterization of sediment connectivity for the optimal management of debris flow to road structures. The ability of the model to capture flooding probability was determined for different watersheds in central Sweden. Using data from this initial investigation, a method to subtract spatial data for multiple catchments and to produce soft data for statistical analysis was developed. It allowed flood probability to be predicted from spatially sparse data without compromising the significant hydrological features on the landscape. This in turn allowed objective quantification of the probability of floods at the field scale for future model development and watershed management.

Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling

PubMed Central

Huang, Hui; Wan Mohamed Radzi, Che Wan Jasimah bt; Salarzadeh Jenatabadi, Hashem

2017-01-01

The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child’s food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM) concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China) were considered. The framework includes two categories of data comprising the normal body mass index (BMI) range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment. PMID:28208833

Family Environment and Childhood Obesity: A New Framework with Structural Equation Modeling.

PubMed

Huang, Hui; Wan Mohamed Radzi, Che Wan Jasimah Bt; Salarzadeh Jenatabadi, Hashem

2017-02-13

The main purpose of the current article is to introduce a framework of the complexity of childhood obesity based on the family environment. A conceptual model that quantifies the relationships and interactions among parental socioeconomic status, family food security level, child's food intake and certain aspects of parental feeding behaviour is presented using the structural equation modeling (SEM) concept. Structural models are analysed in terms of the direct and indirect connections among latent and measurement variables that lead to the child weight indicator. To illustrate the accuracy, fit, reliability and validity of the introduced framework, real data collected from 630 families from Urumqi (Xinjiang, China) were considered. The framework includes two categories of data comprising the normal body mass index (BMI) range and obesity data. The comparison analysis between two models provides some evidence that in obesity modeling, obesity data must be extracted from the dataset and analysis must be done separately from the normal BMI range. This study may be helpful for researchers interested in childhood obesity modeling based on family environment.

Road Risk Modeling and Cloud-Aided Safety-Based Route Planning.

PubMed

Li, Zhaojian; Kolmanovsky, Ilya; Atkins, Ella; Lu, Jianbo; Filev, Dimitar P; Michelini, John

2016-11-01

This paper presents a safety-based route planner that exploits vehicle-to-cloud-to-vehicle (V2C2V) connectivity. Time and road risk index (RRI) are considered as metrics to be balanced based on user preference. To evaluate road segment risk, a road and accident database from the highway safety information system is mined with a hybrid neural network model to predict RRI. Real-time factors such as time of day, day of the week, and weather are included as correction factors to the static RRI prediction. With real-time RRI and expected travel time, route planning is formulated as a multiobjective network flow problem and further reduced to a mixed-integer programming problem. A V2C2V implementation of our safety-based route planning approach is proposed to facilitate access to real-time information and computing resources. A real-world case study, route planning through the city of Columbus, Ohio, is presented. Several scenarios illustrate how the "best" route can be adjusted to favor time versus safety metrics.

Impact of soil protection measures based on topographical variations through connectivity indices in two agricultural catchments in Spain

NASA Astrophysics Data System (ADS)

Taguas, Encarnación; Mesas, F. Javier; García-Ferrer, Alfonso; Marín-Moreno, Víctor; Mateos, Luciano

2017-04-01

Physiographic attributes of the catchments (spatial organization and internal connectivity) determine sediment production, transport and delivery to river channels downstream. Understanding the hydrological connectivity allows identifying runoff and sediment contribution from overland flow pathways, rills and gullies at the upper parts of the catchments to sink areas (Borselli et al., 2008). Currently, the design of orchards and row crops plantations is driven by traffic and machinery management criteria, meaning significant simplification of the landscape. Topographic alterations may reduce the connectivity and maximize the retention of water and sediments in catchments by increasing travel times and infiltration (Gay et al., 2016). There are connectivity indices based on topography and land use information (Borselli et al., 2008) and travel times (Chow et al., 1988) which may help to identify measures to reduce water and sediment transfer. In this work, connectivity indices derived from digital elevation models (DEM) of two small agricultural catchments where topographic measures to interrupt the connectivity had been implemented were analyzed. The topographical details of the tree row ridges in a young almond orchard catchment and half-moons (individual terraces) in an olive grove catchment were obtained using Unmanned Aerial Vehicles (UAVs) flights. The aim was to evaluate the benefits of ridges and half-moons by comparing spatial patterns of connectivity indices before and after the topographical modifications in the catchments. The catchments were flown in December 2016. The original DEMs were generated based on previous topographical information and a filter based on minimum heights. The statistics and the maps generated will be presented as results of our study and its interpretation will provide an analysis to preliminarily explore effective and economical measures for erosion control and improved water harvesting. REFERENCES Gay, O. Cerdan, V. Mardhel, M. Desmet. 2016. Application of an index of sediment connectivity in a lowland area. J Soils Sediments (2016) 16:280-293 Borselli, L., Cassi, P., Torri D. 2008. Prolegomena to sediment and flow connectivity in the landscape: A GIS and field numerical assessment. Catena 75, 268-277 Ven Te Chow, D. R., Maidment, L., Mays W. 1988. Applied Hydrology McGraw-Hill, 572 pp. ACKNOWLEDGMENT This study was supported by the project CGL2015-64284-C2-2-R (Spanish Ministry of Economy and Competitiveness).

SedInConnect: a stand-alone, free and open source tool for the assessment of sediment connectivity

NASA Astrophysics Data System (ADS)

Crema, Stefano; Cavalli, Marco

2018-02-01

There is a growing call, within the scientific community, for solid theoretic frameworks and usable indices/models to assess sediment connectivity. Connectivity plays a significant role in characterizing structural properties of the landscape and, when considered in combination with forcing processes (e.g., rainfall-runoff modelling), can represent a valuable analysis for an improved landscape management. In this work, the authors present the development and application of SedInConnect: a free, open source and stand-alone application for the computation of the Index of Connectivity (IC), as expressed in Cavalli et al. (2013) with the addition of specific innovative features. The tool is intended to have a wide variety of users, both from the scientific community and from the authorities involved in the environmental planning. Thanks to its open source nature, the tool can be adapted and/or integrated according to the users' requirements. Furthermore, presenting an easy-to-use interface and being a stand-alone application, the tool can help management experts in the quantitative assessment of sediment connectivity in the context of hazard and risk assessment. An application to a sample dataset and an overview on up-to-date applications of the approach and of the tool shows the development potential of such analyses. The modelled connectivity, in fact, appears suitable not only to characterize sediment dynamics at the catchment scale but also to integrate prediction models and as a tool for helping geomorphological interpretation.

Development of a lumbar EMG-based coactivation index for the assessment of complex dynamic tasks.

PubMed

Le, Peter; Aurand, Alexander; Walter, Benjamin A; Best, Thomas M; Khan, Safdar N; Mendel, Ehud; Marras, William S

2018-03-01

The objective of this study was to develop and test an EMG-based coactivation index and compare it to a coactivation index defined by a biologically assisted lumbar spine model to differentiate between tasks. The purpose was to provide a universal approach to assess coactivation of a multi-muscle system when a computational model is not accessible. The EMG-based index developed utilised anthropometric-defined muscle characteristics driven by torso kinematics and EMG. Muscles were classified as agonists/antagonists based upon 'simulated' moments of the muscles relative to the total 'simulated' moment. Different tasks were used to test the range of the index including lifting, pushing and Valsalva. Results showed that the EMG-based index was comparable to the index defined by a biologically assisted model (r 2  = 0.78). Overall, the EMG-based index provides a universal, usable method to assess the neuromuscular effort associated with coactivation for complex dynamic tasks when the benefit of a biomechanical model is not available. Practitioner Summary: A universal coactivation index for the lumbar spine was developed to assess complex dynamic tasks. This method was validated relative to a model-based index for use when a high-end computational model is not available. Its simplicity allows for fewer inputs and usability for assessment of task ergonomics and rehabilitation.

Declining functional connectivity and changing hub locations in Alzheimer's disease: an EEG study.

PubMed

Engels, Marjolein M A; Stam, Cornelis J; van der Flier, Wiesje M; Scheltens, Philip; de Waal, Hanneke; van Straaten, Elisabeth C W

2015-08-20

EEG studies have shown that patients with Alzheimer's disease (AD) have weaker functional connectivity than controls, especially in higher frequency bands. Furthermore, active regions seem more prone to AD pathology. How functional connectivity is affected in AD subgroups of disease severity and how network hubs (highly connected brain areas) change is not known. We compared AD patients with different disease severity and controls in terms of functional connections, hub strength and hub location. We studied routine 21-channel resting-state electroencephalography (EEG) of 318 AD patients (divided into tertiles based on disease severity: mild, moderate and severe AD) and 133 age-matched controls. Functional connectivity between EEG channels was estimated with the Phase Lag Index (PLI). From the PLI-based connectivity matrix, the minimum spanning tree (MST) was derived. For each node (EEG channel) in the MST, the betweenness centrality (BC) was computed, a measure to quantify the relative importance of a node within the network. Then we derived color-coded head plots based on BC values and calculated the center of mass (the exact middle had x and y values of 0). A shifting of the hub locations was defined as a shift of the center of mass on the y-axis across groups. Multivariate general linear models with PLI or BC values as dependent variables and the groups as continuous variables were used in the five conventional frequency bands. We found that functional connectivity decreases with increasing disease severity in the alpha band. All, except for posterior, regions showed increasing BC values with increasing disease severity. The center of mass shifted from posterior to more anterior regions with increasing disease severity in the higher frequency bands, indicating a loss of relative functional importance of the posterior brain regions. In conclusion, we observed decreasing functional connectivity in the posterior regions, together with a shifted hub location from posterior to central regions with increasing AD severity. Relative hub strength decreases in posterior regions while other regions show a relative rise with increasing AD severity, which is in accordance with the activity-dependent degeneration theory. Our results indicate that hubs are disproportionally affected in AD.

Identifying Seizure Onset Zone From the Causal Connectivity Inferred Using Directed Information

NASA Astrophysics Data System (ADS)

Malladi, Rakesh; Kalamangalam, Giridhar; Tandon, Nitin; Aazhang, Behnaam

2016-10-01

In this paper, we developed a model-based and a data-driven estimator for directed information (DI) to infer the causal connectivity graph between electrocorticographic (ECoG) signals recorded from brain and to identify the seizure onset zone (SOZ) in epileptic patients. Directed information, an information theoretic quantity, is a general metric to infer causal connectivity between time-series and is not restricted to a particular class of models unlike the popular metrics based on Granger causality or transfer entropy. The proposed estimators are shown to be almost surely convergent. Causal connectivity between ECoG electrodes in five epileptic patients is inferred using the proposed DI estimators, after validating their performance on simulated data. We then proposed a model-based and a data-driven SOZ identification algorithm to identify SOZ from the causal connectivity inferred using model-based and data-driven DI estimators respectively. The data-driven SOZ identification outperforms the model-based SOZ identification algorithm when benchmarked against visual analysis by neurologist, the current clinical gold standard. The causal connectivity analysis presented here is the first step towards developing novel non-surgical treatments for epilepsy.

Determination of the aerosol size distribution by analytic inversion of the extinction spectrum in the complex anomalous diffraction approximation.

PubMed

Franssens, G; De Maziére, M; Fonteyn, D

2000-08-20

A new derivation is presented for the analytical inversion of aerosol spectral extinction data to size distributions. It is based on the complex analytic extension of the anomalous diffraction approximation (ADA). We derive inverse formulas that are applicable to homogeneous nonabsorbing and absorbing spherical particles. Our method simplifies, generalizes, and unifies a number of results obtained previously in the literature. In particular, we clarify the connection between the ADA transform and the Fourier and Laplace transforms. Also, the effect of the particle refractive-index dispersion on the inversion is examined. It is shown that, when Lorentz's model is used for this dispersion, the continuous ADA inverse transform is mathematically well posed, whereas with a constant refractive index it is ill posed. Further, a condition is given, in terms of Lorentz parameters, for which the continuous inverse operator does not amplify the error.

A method to relate chemical accident properties and expert judgements in order to derive useful information for the development of Environment-Accident Index.

PubMed

Scott Andersson, Asa; Tysklind, Mats; Fängmark, Ingrid

2007-08-17

The environment consists of a variety of different compartments and processes that act together in a complex system that complicate the environmental risk assessment after a chemical accident. The Environment-Accident Index (EAI) is an example of a tool based on a strategy to join the properties of a chemical with site-specific properties to facilitate this assessment and to be used in the planning process. In the development of the EAI it is necessary to make an unbiased judgement of relevant variables to include in the formula and to estimate their relative importance. The development of EAI has so far included the assimilation of chemical accidents, selection of a representative set of chemical accidents, and response values (representing effects in the environment after a chemical accident) have been developed by means of an expert panel. The developed responses were then related to the chemical and site-specific properties, through a mathematical model based on multivariate modelling (PLS), to create an improved EAI model. This resulted in EAI(new), a PLS based EAI model connected to a new classification scale. The advantages of EAI(new) compared to the old EAI (EAI(old)) is that it can be calculated without the use of tables, it can estimate the effects for all included responses and make a rough classification of chemical accidents according to the new classification scale. Finally EAI(new) is a more stable model than EAI(old), built on a valid base of accident scenarios which makes it more reliable to use for a variety of chemicals and situations as it covers a broader spectra of accident scenarios. EAI(new) can be expressed as a regression model to facilitate the calculation of the index for persons that do not have access to PLS. Future work can be; an external validation of EAI(new); to complete the formula structure; to adjust the classification scale; and to make a real life evaluation of EAI(new).

A Quantitative Structure-Property Relationship (QSPR) Study of Aliphatic Alcohols by the Method of Dividing the Molecular Structure into Substructure

PubMed Central

Liu, Fengping; Cao, Chenzhong; Cheng, Bin

2011-01-01

A quantitative structure–property relationship (QSPR) analysis of aliphatic alcohols is presented. Four physicochemical properties were studied: boiling point (BP), n-octanol–water partition coefficient (lg POW), water solubility (lg W) and the chromatographic retention indices (RI) on different polar stationary phases. In order to investigate the quantitative structure–property relationship of aliphatic alcohols, the molecular structure ROH is divided into two parts, R and OH to generate structural parameter. It was proposed that the property is affected by three main factors for aliphatic alcohols, alkyl group R, substituted group OH, and interaction between R and OH. On the basis of the polarizability effect index (PEI), previously developed by Cao, the novel molecular polarizability effect index (MPEI) combined with odd-even index (OEI), the sum eigenvalues of bond-connecting matrix (SX1CH) previously developed in our team, were used to predict the property of aliphatic alcohols. The sets of molecular descriptors were derived directly from the structure of the compounds based on graph theory. QSPR models were generated using only calculated descriptors and multiple linear regression techniques. These QSPR models showed high values of multiple correlation coefficient (R > 0.99) and Fisher-ratio statistics. The leave-one-out cross-validation demonstrated the final models to be statistically significant and reliable. PMID:21731451

Landscape assessment of spatial Cs-137 connectivity patterns in arable land with gray loamy soils in the Bryansk Region (landscapes of the Opolje)

NASA Astrophysics Data System (ADS)

Linnik, Vitaly; Sokolov, Alexander; Saveliev, Anatoly; Mironenko, Iya

2017-04-01

As a result of the Chernobyl accident in 1986 landscapes of the Bryansk Region (Russia) were contaminated by Cs-137. In 1993 air-gamma survey with 100 m resolution was done in contaminated areas of the region, which revealed significant spatial heterogeneity of Cs-137 contamination. The initial "spotting" of contamination Cs-137, which in the spring of 1986 represented multi-scale complex patterns of contamination, was substantially transformed by 1993 as a result of erosion processes of various intensity. The purpose of this research was to obtain estimates of the transformation of initial Cs-137 patterns as influenced by different landscape factors. The study is based on the concept of sediment and hydrological connectivity. We apply GIS-based models considering lateral soil migration to analyze sediment cascade system. The study area is a test plot that has grey loamy soils (landscapes of the Opolje) with a size 10x16 km in the central part of the Bryansk Region, with more than 80% of the area under cultivation. Elevation levels are in the range of 140-210 m. Because of plowing, intense erosion processes have taken place. The slope angles in the lower parts of slopes reach 2-3 degrees. Maximum slopes in gullies reach 11,5 degrees. Cs-137 levels of contamination vary from 3,6 kBq/m2 to 35 3,6 kBq/m2. Over the past few decades the Cs-137 technique has been applied to determine net soil redistribution rates. It is applicable for medium long term (30 to 40 years) soil redistribution estimates. In this technique, the anthropogenic radionuclide Cs-137 is used as a sediment tracer from upland erosion studies to catchment sediment budgets, as well as to depositional areas in colluvial positions, valleys, river terraces, floodplains. The soil movement is primarily driven by water flow due to the gravity. The effect of gravity can be easily approximated using DEM derivatives. Cs-137 patterns have been investigated to estimate landscape connectivity and soil redistribution rates in different slope positions. In addition to the Cs-137 contamination, DEM parameters, such as slope angle, aspect, and different landscape indexes (wetness index etc.) have been estimated. Potential Cs-137 connectivity of hillslopes - floodplain or hillslopes -valley is characterized by lateral contributing area. To assess the relationship of Cs-137 with various landscape factors we used different statistical models. Analysis of the lateral redistribution of Cs-137 in the landscape is based on the assumption of primordial density in nonuniformity of Cs-137 deposition in different landscape positions. Relationship of Cs-137 connectivity for various landscape positions is presented. Fundamental differences of Cs-137 connectivity for slopes of southern and northern exposure are demonstrated.

A consensus-based dynamics for market volumes

NASA Astrophysics Data System (ADS)

Sabatelli, Lorenzo; Richmond, Peter

2004-12-01

We develop a model of trading orders based on opinion dynamics. The agents may be thought as the share holders of a major mutual fund rather than as direct traders. The balance between their buy and sell orders determines the size of the fund order (volume) and has an impact on prices and indexes. We assume agents interact simultaneously to each other through a Sznajd-like interaction. Their degree of connection is determined by the probability of changing opinion independently of what their neighbours are doing. We assume that such a probability may change randomly, after each transaction, of an amount proportional to the relative difference between the volatility then measured and a benchmark that we assume to be an exponential moving average of the past volume values. We show how this simple model is compatible with some of the main statistical features observed for the asset volumes in financial markets.

A probabilistic framework to infer brain functional connectivity from anatomical connections.

PubMed

Deligianni, Fani; Varoquaux, Gael; Thirion, Bertrand; Robinson, Emma; Sharp, David J; Edwards, A David; Rueckert, Daniel

2011-01-01

We present a novel probabilistic framework to learn across several subjects a mapping from brain anatomical connectivity to functional connectivity, i.e. the covariance structure of brain activity. This prediction problem must be formulated as a structured-output learning task, as the predicted parameters are strongly correlated. We introduce a model selection framework based on cross-validation with a parametrization-independent loss function suitable to the manifold of covariance matrices. Our model is based on constraining the conditional independence structure of functional activity by the anatomical connectivity. Subsequently, we learn a linear predictor of a stationary multivariate autoregressive model. This natural parameterization of functional connectivity also enforces the positive-definiteness of the predicted covariance and thus matches the structure of the output space. Our results show that functional connectivity can be explained by anatomical connectivity on a rigorous statistical basis, and that a proper model of functional connectivity is essential to assess this link.

A brain-region-based meta-analysis method utilizing the Apriori algorithm.

PubMed

Niu, Zhendong; Nie, Yaoxin; Zhou, Qian; Zhu, Linlin; Wei, Jieyao

2016-05-18

Brain network connectivity modeling is a crucial method for studying the brain's cognitive functions. Meta-analyses can unearth reliable results from individual studies. Meta-analytic connectivity modeling is a connectivity analysis method based on regions of interest (ROIs) which showed that meta-analyses could be used to discover brain network connectivity. In this paper, we propose a new meta-analysis method that can be used to find network connectivity models based on the Apriori algorithm, which has the potential to derive brain network connectivity models from activation information in the literature, without requiring ROIs. This method first extracts activation information from experimental studies that use cognitive tasks of the same category, and then maps the activation information to corresponding brain areas by using the automatic anatomical label atlas, after which the activation rate of these brain areas is calculated. Finally, using these brain areas, a potential brain network connectivity model is calculated based on the Apriori algorithm. The present study used this method to conduct a mining analysis on the citations in a language review article by Price (Neuroimage 62(2):816-847, 2012). The results showed that the obtained network connectivity model was consistent with that reported by Price. The proposed method is helpful to find brain network connectivity by mining the co-activation relationships among brain regions. Furthermore, results of the co-activation relationship analysis can be used as a priori knowledge for the corresponding dynamic causal modeling analysis, possibly achieving a significant dimension-reducing effect, thus increasing the efficiency of the dynamic causal modeling analysis.

Dependent scattering and absorption by densely packed discrete spherical particles: Effects of complex refractive index

NASA Astrophysics Data System (ADS)

Ma, L. X.; Tan, J. Y.; Zhao, J. M.; Wang, F. Q.; Wang, C. A.; Wang, Y. Y.

2017-07-01

Due to the dependent scattering and absorption effects, the radiative transfer equation (RTE) may not be suitable for dealing with radiative transfer in dense discrete random media. This paper continues previous research on multiple and dependent scattering in densely packed discrete particle systems, and puts emphasis on the effects of particle complex refractive index. The Mueller matrix elements of the scattering system with different complex refractive indexes are obtained by both electromagnetic method and radiative transfer method. The Maxwell equations are directly solved based on the superposition T-matrix method, while the RTE is solved by the Monte Carlo method combined with the hard sphere model in the Percus-Yevick approximation (HSPYA) to consider the dependent scattering effects. The results show that for densely packed discrete random media composed of medium size parameter particles (equals 6.964 in this study), the demarcation line between independent and dependent scattering has remarkable connections with the particle complex refractive index. With the particle volume fraction increase to a certain value, densely packed discrete particles with higher refractive index contrasts between the particles and host medium and higher particle absorption indexes are more likely to show stronger dependent characteristics. Due to the failure of the extended Rayleigh-Debye scattering condition, the HSPYA has weak effect on the dependent scattering correction at large phase shift parameters.

Channel plasmon-polariton guiding by subwavelength metal grooves.

PubMed

Bozhevolnyi, Sergey I; Volkov, Valentyn S; Devaux, Eloïse; Ebbesen, Thomas W

2005-07-22

We report on realization of channel plasmon-polariton (CPP) propagation along a subwavelength metal groove. Using imaging with a near-field microscope and end-fire coupling with a tapered fiber connected to a tunable laser at telecommunication wavelengths (1425-1620 nm), we demonstrate low-loss (propagation length approximately 100 microm) and well-confined (mode width approximately 1.1 microm) CPP guiding along a triangular 0.6 microm-wide and 1 microm-deep groove in gold. We develop a simple model based on the effective-index method that accounts for the main features of CPP guiding and provides a clear physical picture of this phenomenon.

Interrelationships Between Walkability, Air Pollution, Greenness, and Body Mass Index.

PubMed

James, Peter; Kioumourtzoglou, Marianthi-Anna; Hart, Jaime E; Banay, Rachel F; Kloog, Itai; Laden, Francine

2017-11-01

Recent studies have linked urban environmental factors and body mass index (BMI); however, such factors are often examined in isolation, ignoring correlations across exposures. Using data on Nurses' Health Study participants living in the Northeastern United States in 2006, we estimated associations between neighborhood walkability (a composite of population density, street connectivity, and business access), greenness (from satellite imagery), and ambient air pollution (from satellite-based spatiotemporally resolved PM2.5 predictions and weighted monthly average concentrations of NO2 from up to five nearest monitors) and self-reported BMI using generalized additive models, allowing for deviations from linearity using penalized splines. Among 23,435 women aged 60-87 years, we observed nonlinear associations between walkability and BMI and between PM2.5 and BMI in single-exposure models adjusted for age, race, and individual- and area-level socioeconomic status. When modeling all exposures simultaneously, only the association between walkability and BMI remained nonlinear and nonmonotonic. Increasing walkability was associated with increasing BMI at lower levels of walkability (walkability index <1.8), while increasing walkability was linked to lower BMI in areas of higher walkability (walkability index >1.8). A 10 percentile increase in walkability, right above 1.8 was associated with a 0.84% decrease in log BMI. The relationship between walkability and BMI existed only among younger participants (<71 years old). Neighborhood walkability was nonlinearly linked to lower BMI independent of air pollution and greenness. Our findings highlight the importance of accounting for nonlinear confounding by interrelated urban environmental factors when investigating associations between the environment and BMI.

Supermodeling by Synchronization of Alternative SPEEDO Models

NASA Astrophysics Data System (ADS)

Duane, Gregory; Selten, Frank

2016-04-01

The supermodeling approach, wherein different imperfect models of the same objective process are dynamically combined in run-time to reduce systematic error, is tested using SPEEDO - a primitive equation atmospheric model coupled to the CLIO ocean model. Three versions of SPEEDO are defined by parameters that differ in a range that arguably mimics differences among state-of-the-art climate models. A fourth model is taken to represent truth. The "true" ocean drives all three model atmospheres. The three models are also connected to one another at every level, with spatially uniform nudging coefficients that are trained so that the three models, which synchronize with one another, also synchronize with truth when data is continuously assimilated, as in weather prediction. The SPEEDO supermodel is evaluated in weather-prediction mode, with nudging to truth. It is found that the supemodel performs better than any of the three models and marginally better than the best weighted average of the outputs of the three models run separately. To evaluate the utility for climate projection, parameters corresponding to green house gas levels are changed in truth and in the three models. The supermodel formed with inter-model connections from the present-CO2 runs no longer give the optimal configuration for the supermodel in the doubled-CO2 realm, but the supermodel with the previously trained connections is still useful as compared to the separate models or averages of their outputs. In ongoing work, a training algorithm is examined that attempts to match the blocked-zonal index cycle of the SPEEDO model atmosphere to truth, rather than simply minimizing the RMS error in the various fields. Such an approach comes closer to matching the model attractor to the true attractor - the desired effect in climate projection - rather than matching instantaneous states. Gradient descent in a cost function defined over a finite temporal window can indeed be done efficiently. Preliminary results are presented for a crudely defined index cycle.

Trigonometrical sums connected with the chiral Potts model, Verlinde dimension formula, two-dimensional resistor network, and number theory

NASA Astrophysics Data System (ADS)

Chair, Noureddine

2014-02-01

We have recently developed methods for obtaining exact two-point resistance of the complete graph minus N edges. We use these methods to obtain closed formulas of certain trigonometrical sums that arise in connection with one-dimensional lattice, in proving Scott's conjecture on permanent of Cauchy matrix, and in the perturbative chiral Potts model. The generalized trigonometrical sums of the chiral Potts model are shown to satisfy recursion formulas that are transparent and direct, and differ from those of Gervois and Mehta. By making a change of variables in these recursion formulas, the dimension of the space of conformal blocks of SU(2) and SO(3) WZW models may be computed recursively. Our methods are then extended to compute the corner-to-corner resistance, and the Kirchhoff index of the first non-trivial two-dimensional resistor network, 2×N. Finally, we obtain new closed formulas for variant of trigonometrical sums, some of which appear in connection with number theory.

A prediction model for cognitive performance in health ageing using diffusion tensor imaging with graph theory.

PubMed

Yun, Ruijuan; Lin, Chung-Chih; Wu, Shuicai; Huang, Chu-Chung; Lin, Ching-Po; Chao, Yi-Ping

2013-01-01

In this study, we employed diffusion tensor imaging (DTI) to construct brain structural network and then derive the connection matrices from 96 healthy elderly subjects. The correlation analysis between these topological properties of network based on graph theory and the Cognitive Abilities Screening Instrument (CASI) index were processed to extract the significant network characteristics. These characteristics were then integrated to estimate the models by various machine-learning algorithms to predict user's cognitive performance. From the results, linear regression model and Gaussian processes model showed presented better abilities with lower mean absolute errors of 5.8120 and 6.25 to predict the cognitive performance respectively. Moreover, these extracted topological properties of brain structural network derived from DTI also could be regarded as the bio-signatures for further evaluation of brain degeneration in healthy aged and early diagnosis of mild cognitive impairment (MCI).

Higher body mass index is associated with reduced posterior default mode connectivity in older adults.

PubMed

Beyer, Frauke; Kharabian Masouleh, Sharzhad; Huntenburg, Julia M; Lampe, Leonie; Luck, Tobias; Riedel-Heller, Steffi G; Loeffler, Markus; Schroeter, Matthias L; Stumvoll, Michael; Villringer, Arno; Witte, A Veronica

2017-04-11

Obesity is a complex neurobehavioral disorder that has been linked to changes in brain structure and function. However, the impact of obesity on functional connectivity and cognition in aging humans is largely unknown. Therefore, the association of body mass index (BMI), resting-state network connectivity, and cognitive performance in 712 healthy, well-characterized older adults of the Leipzig Research Center for Civilization Diseases (LIFE) cohort (60-80 years old, mean BMI 27.6 kg/m 2  ± 4.2 SD, main sample: n = 521, replication sample: n = 191) was determined. Statistical analyses included a multivariate model selection approach followed by univariate analyses to adjust for possible confounders. Results showed that a higher BMI was significantly associated with lower default mode functional connectivity in the posterior cingulate cortex and precuneus. The effect remained stable after controlling for age, sex, head motion, registration quality, cardiovascular, and genetic factors as well as in replication analyses. Lower functional connectivity in BMI-associated areas correlated with worse executive function. In addition, higher BMI correlated with stronger head motion. Using 3T neuroimaging in a large cohort of healthy older adults, independent negative associations of obesity and functional connectivity in the posterior default mode network were observed. In addition, a subtle link between lower resting-state connectivity in BMI-associated regions and cognitive function was found. The findings might indicate that obesity is associated with patterns of decreased default mode connectivity similar to those seen in populations at risk for Alzheimer's disease. Hum Brain Mapp, 2017. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis).

PubMed

Allen, Corrie H; Parrott, Lael; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning.

An individual-based modelling approach to estimate landscape connectivity for bighorn sheep (Ovis canadensis)

PubMed Central

Allen, Corrie H.; Kyle, Catherine

2016-01-01

Background. Preserving connectivity, or the ability of a landscape to support species movement, is among the most commonly recommended strategies to reduce the negative effects of climate change and human land use development on species. Connectivity analyses have traditionally used a corridor-based approach and rely heavily on least cost path modeling and circuit theory to delineate corridors. Individual-based models are gaining popularity as a potentially more ecologically realistic method of estimating landscape connectivity. However, this remains a relatively unexplored approach. We sought to explore the utility of a simple, individual-based model as a land-use management support tool in identifying and implementing landscape connectivity. Methods. We created an individual-based model of bighorn sheep (Ovis canadensis) that simulates a bighorn sheep traversing a landscape by following simple movement rules. The model was calibrated for bighorn sheep in the Okanagan Valley, British Columbia, Canada, a region containing isolated herds that are vital to conservation of the species in its northern range. Simulations were run to determine baseline connectivity between subpopulations in the study area. We then applied the model to explore two land management scenarios on simulated connectivity: restoring natural fire regimes and identifying appropriate sites for interventions that would increase road permeability for bighorn sheep. Results. This model suggests there are no continuous areas of good habitat between current subpopulations of sheep in the study area; however, a series of stepping-stones or circuitous routes could facilitate movement between subpopulations and into currently unoccupied, yet suitable, bighorn habitat. Restoring natural fire regimes or mimicking fire with prescribed burns and tree removal could considerably increase bighorn connectivity in this area. Moreover, several key road crossing sites that could benefit from wildlife overpasses were identified. Discussion. By linking individual-scale movement rules to landscape-scale outcomes, our individual-based model of bighorn sheep allows for the exploration of how on-the-ground management or conservation scenarios may increase functional connectivity for the species in the study area. More generally, this study highlights the usefulness of individual-based models to identify how a species makes broad use of a landscape for movement. Application of this approach can provide effective quantitative support for decision makers seeking to incorporate wildlife conservation and connectivity into land use planning. PMID:27168997

Graph theoretic analysis of structural connectivity across the spectrum of Alzheimer's disease: The importance of graph creation methods

PubMed Central

Phillips, David J.; McGlaughlin, Alec; Ruth, David; Jager, Leah R.; Soldan, Anja

2015-01-01

Graph theory is increasingly being used to study brain connectivity across the spectrum of Alzheimer's disease (AD), but prior findings have been inconsistent, likely reflecting methodological differences. We systematically investigated how methods of graph creation (i.e., type of correlation matrix and edge weighting) affect structural network properties and group differences. We estimated the structural connectivity of brain networks based on correlation maps of cortical thickness obtained from MRI. Four groups were compared: 126 cognitively normal older adults, 103 individuals with Mild Cognitive Impairment (MCI) who retained MCI status for at least 3 years (stable MCI), 108 individuals with MCI who progressed to AD-dementia within 3 years (progressive MCI), and 105 individuals with AD-dementia. Small-world measures of connectivity (characteristic path length and clustering coefficient) differed across groups, consistent with prior studies. Groups were best discriminated by the Randić index, which measures the degree to which highly connected nodes connect to other highly connected nodes. The Randić index differentiated the stable and progressive MCI groups, suggesting that it might be useful for tracking and predicting the progression of AD. Notably, however, the magnitude and direction of group differences in all three measures were dependent on the method of graph creation, indicating that it is crucial to take into account how graphs are constructed when interpreting differences across diagnostic groups and studies. The algebraic connectivity measures showed few group differences, independent of the method of graph construction, suggesting that global connectivity as it relates to node degree is not altered in early AD. PMID:25984446

Changes of glacier, glacier-fed rivers and lakes in Altai Tavan Bogd National Park, Western Mongolia, based on multispectral satellite data from 1990 to 2017

NASA Astrophysics Data System (ADS)

Batsaikhan, B.; Lkhamjav, O.; Batsaikhan, N.

2017-12-01

Impacts on glaciers and water resource management have been altering through climate changes in Mongolia territory characterized by dry and semi-arid climate with low precipitation. Melting glaciers are early indicators of climate change unlike the response of the forests which is slower and takes place over a long period of time. Mountain glaciers are important environmental components of local, regional, and global hydrological cycles. The study calculates an overview of changes for glacier, glacier-fed rivers and lakes in Altai Tavan Bogd mountain, the Western Mongolia, based on the indexes of multispectral data and the methods typically applied in glacier studies. Were utilized an integrated approach of Normalized Difference Snow Index (NDSI) and Normalized Difference Water Index (NDWI) to combine Landsat, MODIS imagery and digital elevation model, to identify glacier cover are and quantify water storage change in lakes, and compared that with and climate parameters including precipitation, land surface temperature, evaporation, moisture. Our results show that melts of glacier at the study area has contributed to significantly increase of water storage of lakes in valley of The Altai Tavan Bogd mountain. There is hydrologic connection that lake basin is directly fed by glacier meltwater.

Spatial capture-recapture models for jointly estimating population density and landscape connectivity

USGS Publications Warehouse

Royle, J. Andrew; Chandler, Richard B.; Gazenski, Kimberly D.; Graves, Tabitha A.

2013-01-01

Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture–recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on “ecological distance,” i.e., the least-cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least-cost path models into a likelihood-based estimation scheme for spatial capture–recapture models in order to estimate population density and parameters of the least-cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture–recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.

Spatial capture--recapture models for jointly estimating population density and landscape connectivity.

PubMed

Royle, J Andrew; Chandler, Richard B; Gazenski, Kimberly D; Graves, Tabitha A

2013-02-01

Population size and landscape connectivity are key determinants of population viability, yet no methods exist for simultaneously estimating density and connectivity parameters. Recently developed spatial capture--recapture (SCR) models provide a framework for estimating density of animal populations but thus far have not been used to study connectivity. Rather, all applications of SCR models have used encounter probability models based on the Euclidean distance between traps and animal activity centers, which implies that home ranges are stationary, symmetric, and unaffected by landscape structure. In this paper we devise encounter probability models based on "ecological distance," i.e., the least-cost path between traps and activity centers, which is a function of both Euclidean distance and animal movement behavior in resistant landscapes. We integrate least-cost path models into a likelihood-based estimation scheme for spatial capture-recapture models in order to estimate population density and parameters of the least-cost encounter probability model. Therefore, it is possible to make explicit inferences about animal density, distribution, and landscape connectivity as it relates to animal movement from standard capture-recapture data. Furthermore, a simulation study demonstrated that ignoring landscape connectivity can result in negatively biased density estimators under the naive SCR model.

Study of cumulative fatigue damage detection for used parts with nonlinear output frequency response functions based on NARMAX modelling

NASA Astrophysics Data System (ADS)

Huang, Honglan; Mao, Hanying; Mao, Hanling; Zheng, Weixue; Huang, Zhenfeng; Li, Xinxin; Wang, Xianghong

2017-12-01

Cumulative fatigue damage detection for used parts plays a key role in the process of remanufacturing engineering and is related to the service safety of the remanufactured parts. In light of the nonlinear properties of used parts caused by cumulative fatigue damage, the based nonlinear output frequency response functions detection approach offers a breakthrough to solve this key problem. First, a modified PSO-adaptive lasso algorithm is introduced to improve the accuracy of the NARMAX model under impulse hammer excitation, and then, an effective new algorithm is derived to estimate the nonlinear output frequency response functions under rectangular pulse excitation, and a based nonlinear output frequency response functions index is introduced to detect the cumulative fatigue damage in used parts. Then, a novel damage detection approach that integrates the NARMAX model and the rectangular pulse is proposed for nonlinear output frequency response functions identification and cumulative fatigue damage detection of used parts. Finally, experimental studies of fatigued plate specimens and used connecting rod parts are conducted to verify the validity of the novel approach. The obtained results reveal that the new approach can detect cumulative fatigue damages of used parts effectively and efficiently and that the various values of the based nonlinear output frequency response functions index can be used to detect the different fatigue damages or working time. Since the proposed new approach can extract nonlinear properties of systems by only a single excitation of the inspected system, it shows great promise for use in remanufacturing engineering applications.

Predicting seizure by modeling synaptic plasticity based on EEG signals - a case study of inherited epilepsy

NASA Astrophysics Data System (ADS)

Zhang, Honghui; Su, Jianzhong; Wang, Qingyun; Liu, Yueming; Good, Levi; Pascual, Juan M.

2018-03-01

This paper explores the internal dynamical mechanisms of epileptic seizures through quantitative modeling based on full brain electroencephalogram (EEG) signals. Our goal is to provide seizure prediction and facilitate treatment for epileptic patients. Motivated by an earlier mathematical model with incorporated synaptic plasticity, we studied the nonlinear dynamics of inherited seizures through a differential equation model. First, driven by a set of clinical inherited electroencephalogram data recorded from a patient with diagnosed Glucose Transporter Deficiency, we developed a dynamic seizure model on a system of ordinary differential equations. The model was reduced in complexity after considering and removing redundancy of each EEG channel. Then we verified that the proposed model produces qualitatively relevant behavior which matches the basic experimental observations of inherited seizure, including synchronization index and frequency. Meanwhile, the rationality of the connectivity structure hypothesis in the modeling process was verified. Further, through varying the threshold condition and excitation strength of synaptic plasticity, we elucidated the effect of synaptic plasticity to our seizure model. Results suggest that synaptic plasticity has great effect on the duration of seizure activities, which support the plausibility of therapeutic interventions for seizure control.

Glutamatergic Signaling Drives Ketamine-Mediated Response in Depression: Evidence from Dynamic Causal Modeling.

PubMed

Gilbert, Jessica R; Yarrington, Julia S; Wills, Kathleen E; Nugent, Allison C; Zarate, Carlos A

2018-04-13

The glutamatergic modulator ketamine has rapid antidepressant effects in individuals with major depressive disorder (MDD) and bipolar depression. Thus, modulating glutamatergic transmission may be critical to effectively treating depression, though the mechanisms by which this occurs are not fully understood. This double-blind, crossover, placebo-controlled study analyzed data from 18 drug-free MDD subjects and 18 heathy controls who received a single intravenous infusion of ketamine hydrochloride (0.5 mg/kg) as well as an intravenous saline placebo. Magnetoencephalographic (MEG) recordings were collected prior to the first infusion and six to nine hours after both ketamine and placebo infusions. During scanning, participants passively received tactile stimulation to the right index finger. Antidepressant response was assessed across timepoints using the Montgomery-Asberg Depression Rating Scale (MADRS). Dynamic causal modeling (DCM) was used to measure changes in -amino-3-hydroxy-5-methyl-4-isoxazole propionic acid (AMPA)- and N-methyl-D-aspartate (NMDA)-mediated connectivity estimates in MDD subjects and controls using a simple model of somatosensory evoked responses. Both MDD and healthy subjects showed ketamine-mediated NMDA-blockade sensitization, with MDD subjects showing enhanced NMDA connectivity estimates in backward connections, and controls showing enhanced NMDA connectivity estimates in forward connections in our model. Within our MDD subject group, ketamine efficacy-as measured by improved mood ratings-correlated with reduced NMDA and AMPA connectivity estimates in discrete extrinsic connections within the somatosensory cortical network. These findings suggest that AMPA- and NMDA-mediated glutamatergic signaling play a key role in antidepressant response to ketamine and, further, that DCM is a powerful tool for modeling AMPA- and NMDA-mediated connectivity in vivo. NCT#00088699.

Modeling the heterogeneous traffic correlations in urban road systems using traffic-enhanced community detection approach

NASA Astrophysics Data System (ADS)

Lu, Feng; Liu, Kang; Duan, Yingying; Cheng, Shifen; Du, Fei

2018-07-01

A better characterization of the traffic influence among urban roads is crucial for traffic control and traffic forecasting. The existence of spatial heterogeneity imposes great influence on modeling the extent and degree of road traffic correlation, which is usually neglected by the traditional distance based method. In this paper, we propose a traffic-enhanced community detection approach to spatially reveal the traffic correlation in city road networks. First, the road network is modeled as a traffic-enhanced dual graph with the closeness between two road segments determined not only by their topological connection, but also by the traffic correlation between them. Then a flow-based community detection algorithm called Infomap is utilized to identify the road segment clusters. Evaluated by Moran's I, Calinski-Harabaz Index and the traffic interpolation application, we find that compared to the distance based method and the community based method, our proposed traffic-enhanced community based method behaves better in capturing the extent of traffic relevance as both the topological structure of the road network and the traffic correlations among urban roads are considered. It can be used in more traffic-related applications, such as traffic forecasting, traffic control and guidance.

From Connectivity Models to Region Labels: Identifying Foci of a Neurological Disorder

PubMed Central

Venkataraman, Archana; Kubicki, Marek; Golland, Polina

2014-01-01

We propose a novel approach to identify the foci of a neurological disorder based on anatomical and functional connectivity information. Specifically, we formulate a generative model that characterizes the network of abnormal functional connectivity emanating from the affected foci. This allows us to aggregate pairwise connectivity changes into a region-based representation of the disease. We employ the variational expectation-maximization algorithm to fit the model and subsequently identify both the afflicted regions and the differences in connectivity induced by the disorder. We demonstrate our method on a population study of schizophrenia. PMID:23864168

A note on Kirchhoff index

NASA Astrophysics Data System (ADS)

Zhou, Bo; Trinajstić, Nenad

2008-03-01

We report lower bounds for the Kirchhoff index of a connected (molecular) graph in terms of its structural parameters such as the number of vertices (atoms), the number of edges (bonds), maximum vertex degree (valency), connectivity and chromatic number.

Air pollution tolerance index and heavy metal bioaccumulation in selected plant species from urban biotopes.

PubMed

Nadgórska-Socha, Aleksandra; Kandziora-Ciupa, Marta; Trzęsicki, Michał; Barczyk, Gabriela

2017-09-01

This research was carried out on plants Taraxacum officinale, Plantago lanceolata, Betula pendula and Robinia pseudoacacia growing in urban biotopes with different levels of heavy metal contamination in the city of Dąbrowa Górnicza (southern Poland). Based on the pollution index, the highest heavy metal contamination was determined in the site 4 (connected with industry emitters) and 6 (high traffic). The metal accumulation index (MAI) values ranged within the biotopes in Dąbrowa Górnicza between 7.3 and 20.6 for R. pseudoacacia, 4.71-23.1 for P. lanceolata, 4.68-28.1 for T. officinale and 10.5-27.2 for B. pendula. Increasing tendency in proline content in biotopes connected with high traffic was found in the leaves of investigated plants (except R. pseudoacacia). Similar tendency was observed for ascorbic acid content in the foliage of the plants as well as in T. officinalle in stands connected industrial emission. Non-protein thiols content increased especially in the leaves of R. pseudoacacia in biotopes with high traffic emissions as well as in T. officinale in stands connected with industry. The mean values of APTI (Air Pollution Tolerance Index) within the city of Dąbrowa Górnicza for investigated plants were found in the following ascending order P. lanceolata < R. pseudoacacia < B. pendula < T. officinale. Among the investigated plants B. pendula and T. officinale may be postulated as appropriate plants in urban areas with considerable soil and air contamination, especially with heavy metals. The results indicate that species deemed tolerant according to APTI are suitable plants in barriers areas to combat atmospheric pollution. Copyright © 2017 Elsevier Ltd. All rights reserved.

Minimum spanning tree analysis of the human connectome

PubMed Central

Sommer, Iris E.; Bohlken, Marc M.; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A.; Douw, Linda; Otte, Willem M.; Mandl, René C.W.; Stam, Cornelis J.

2018-01-01

Abstract One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion‐weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null‐model. The MST of individual subjects matched this reference MST for a mean 58%–88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so‐called rich club nodes (a subset of high‐degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical–subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. PMID:29468769

[Spatial characteristics analysis of Huizhou-Styled Village based on ideal ecosystem model and 3D landscape indices: A case in Chengkan, China].

PubMed

Yao, Meng Yuan; Yan, Shi Jiang; Wu, Yan Lan

2016-12-01

Huizhou-Styled Village is a typical representative of the traditional Chinese ancient villages. It preserves plentiful information of the regional culture and ecological connotation. The Huizhou-Style is the apotheosis of harmony between the Chinese ancient people and nature. The research and protection of Huizhou-Styled Village plays a very important role in fields of ecology, geography, architecture and esthetics. This paper took Chengkan Village of Anhui Province as an exa-mple, and proposed a new model of ideal ecosystem oriented in theories of Feng-shui and psychological field. The new method of characterizing 3D landscape index was introduced to explore the spatial patterns of Huizhou-Styled Village and the functionality of the composited landscape components in a quantitative way. The results indicated that, Chengkan Village showed a spatially composited pattern of "mountain-forest-village-river-forest". It formed an ideal settlement ring structure with human architecture in the center and natural landscape around in the horizontal and vertical horizons. The traditional method based on the projection distance caused the deviation of the landscape index, such as underestimating the area and distance of landscape patch. The 3D landscape index of average patch area was 6.7% higher than the 2D landscape index. The increasing rate ofarea proportion in 3D index was 1.0% higher than that of 2D index in forest lands. Area proportion of the other landscapes decreased, especially the artificial landscapes like construction and cropland landscapes. The area and perimeter metric were underestimated, whereas the shape metric and the diversity metric were overestimated. This caused the underestimation of the dominance of natural patches was underestimated and the overestimation of the dominance of artificial patches during the analysis of landscape pattern. The 3D landscape index showed that the natural elements and their combination in Chengkan Village ecosystem reflected better ecological function, the key elements and the composited landscape ecosystem preserved higher stability, connectivity and aggregation. The quantitative confirmation showed that the Huizhou-Styled Village represented by Chengkan Village is an ideal ecosystem.

On the connection between the 3HE-enrichment and spectral index of solar energetic particles

NASA Technical Reports Server (NTRS)

Kocharov, L. G.; Dvoryanchikov, Y. V.

1985-01-01

A model is presented which explains the observed tendency of events with large 3He/4He ratios to have steeper spectra. In this model preferential injection of 3He, acceleration by Alfven waves and Coulomb deceleration of ions are considered simultaneously. The observed tendency may be obtained as a result of competition between injection and acceleration processes.

Diuretics and Gout: What's the Connection?

MedlinePlus

... Limiting beverages that are sugar sweetened and limiting foods and beverages that contain high fructose corn syrup Losing weight and maintaining a healthy weight based on your body mass index To ... also limit your intake of foods rich in the compound purine, which form uric ...

On the interconnection of stable protein complexes: inter-complex hubs and their conservation in Saccharomyces cerevisiae and Homo sapiens networks.

PubMed

Guerra, Concettina

2015-01-01

Protein complexes are key molecular entities that perform a variety of essential cellular functions. The connectivity of proteins within a complex has been widely investigated with both experimental and computational techniques. We developed a computational approach to identify and characterise proteins that play a role in interconnecting complexes. We computed a measure of inter-complex centrality, the crossroad index, based on disjoint paths connecting proteins in distinct complexes and identified inter-complex hubs as proteins with a high value of the crossroad index. We applied the approach to a set of stable complexes in Saccharomyces cerevisiae and in Homo sapiens. Just as done for hubs, we evaluated the topological and biological properties of inter-complex hubs addressing the following questions. Do inter-complex hubs tend to be evolutionary conserved? What is the relation between crossroad index and essentiality? We found a good correlation between inter-complex hubs and both evolutionary conservation and essentiality.

Waterbodies Extraction from LANDSAT8-OLI Imagery Using Awater Indexs-Guied Stochastic Fully-Connected Conditional Random Field Model and the Support Vector Machine

NASA Astrophysics Data System (ADS)

Wang, X.; Xu, L.

2018-04-01

One of the most important applications of remote sensing classification is water extraction. The water index (WI) based on Landsat images is one of the most common ways to distinguish water bodies from other land surface features. But conventional WI methods take into account spectral information only form a limited number of bands, and therefore the accuracy of those WI methods may be constrained in some areas which are covered with snow/ice, clouds, etc. An accurate and robust water extraction method is the key to the study at present. The support vector machine (SVM) using all bands spectral information can reduce for these classification error to some extent. Nevertheless, SVM which barely considers spatial information is relatively sensitive to noise in local regions. Conditional random field (CRF) which considers both spatial information and spectral information has proven to be able to compensate for these limitations. Hence, in this paper, we develop a systematic water extraction method by taking advantage of the complementarity between the SVM and a water index-guided stochastic fully-connected conditional random field (SVM-WIGSFCRF) to address the above issues. In addition, we comprehensively evaluate the reliability and accuracy of the proposed method using Landsat-8 operational land imager (OLI) images of one test site. We assess the method's performance by calculating the following accuracy metrics: Omission Errors (OE) and Commission Errors (CE); Kappa coefficient (KP) and Total Error (TE). Experimental results show that the new method can improve target detection accuracy under complex and changeable environments.

Application of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index

NASA Astrophysics Data System (ADS)

Majasalmi, Titta; Korhonen, Lauri; Korpela, Ilkka; Vauhkonen, Jari

2017-07-01

We propose 3D triangulations of airborne Laser Scanning (ALS) point clouds as a new approach to derive 3D canopy structures and to estimate forest canopy effective LAI (LAIe). Computational geometry and topological connectivity were employed to filter the triangulations to yield a quasi-optimal relationship with the field measured LAIe. The optimal filtering parameters were predicted based on ALS height metrics, emulating the production of maps of LAIe and canopy volume for large areas. The LAIe from triangulations was validated with field measured LAIe and compared with a reference LAIe calculated from ALS data using logarithmic model based on Beer's law. Canopy transmittance was estimated using All Echo Cover Index (ACI), and the mean projection of unit foliage area (β) was obtained using no-intercept regression with field measured LAIe. We investigated the influence species and season on the triangulated LAIe and demonstrated the relationship between triangulated LAIe and canopy volume. Our data is from 115 forest plots located at the southern boreal forest area in Finland and for each plot three different ALS datasets were available to apply the triangulations. The triangulation approach was found applicable for both leaf-on and leaf-off datasets after initial calibration. Results showed the Root Mean Square Errors (RMSEs) between LAIe from triangulations and field measured values agreed the most using the highest pulse density data (RMSE = 0.63, the coefficient of determination (R2) = 0.53). Yet, the LAIe calculated using ACI-index agreed better with the field measured LAIe (RMSE = 0.53 and R2 = 0.70). The best models to predict the optimal alpha value contained the ACI-index, which indicates that within-crown transmittance is accounted by the triangulation approach. The cover indices may be recommended for retrieving LAIe only, but for applications which require more sophisticated information on canopy shape and volume, such as radiative transfer models, the triangulation approach may be preferred.

Resistance-surface-based wildlife conservation connectivity modeling: Summary of efforts in the United States and guide for practitioners

Treesearch

Alisa A. Wade; Kevin S. McKelvey; Michael K. Schwartz

2015-01-01

Resistance-surface-based connectivity modeling has become a widespread tool for conservation planning. The current ease with which connectivity models can be created, however, masks the numerous untested assumptions underlying both the rules that produce the resistance surface and the algorithms used to locate low-cost paths across the target landscape. Here we present...

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Science.gov Websites

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Structural habitat predicts functional dispersal habitat of a large carnivore: how leopards change spots.

PubMed

Fattebert, Julien; Robinson, Hugh S; Balme, Guy; Slotow, Rob; Hunter, Luke

2015-10-01

Natal dispersal promotes inter-population linkage, and is key to spatial distribution of populations. Degradation of suitable landscape structures beyond the specific threshold of an individual's ability to disperse can therefore lead to disruption of functional landscape connectivity and impact metapopulation function. Because it ignores behavioral responses of individuals, structural connectivity is easier to assess than functional connectivity and is often used as a surrogate for landscape connectivity modeling. However using structural resource selection models as surrogate for modeling functional connectivity through dispersal could be erroneous. We tested how well a second-order resource selection function (RSF) models (structural connectivity), based on GPS telemetry data from resident adult leopard (Panthera pardus L.), could predict subadult habitat use during dispersal (functional connectivity). We created eight non-exclusive subsets of the subadult data based on differing definitions of dispersal to assess the predictive ability of our adult-based RSF model extrapolated over a broader landscape. Dispersing leopards used habitats in accordance with adult selection patterns, regardless of the definition of dispersal considered. We demonstrate that, for a wide-ranging apex carnivore, functional connectivity through natal dispersal corresponds to structural connectivity as modeled by a second-order RSF. Mapping of the adult-based habitat classes provides direct visualization of the potential linkages between populations, without the need to model paths between a priori starting and destination points. The use of such landscape scale RSFs may provide insight into predicting suitable dispersal habitat peninsulas in human-dominated landscapes where mitigation of human-wildlife conflict should be focused. We recommend the use of second-order RSFs for landscape conservation planning and propose a similar approach to the conservation of other wide-ranging large carnivore species where landscape-scale resource selection data already exist.

PCPA protects against monocrotaline-induced pulmonary arterial remodeling in rats: potential roles of connective tissue growth factor.

PubMed

Bai, Yang; Li, Zhong-Xia; Zhao, Yue-Tong; Liu, Mo; Wang, Yun; Lian, Guo-Chao; Zhao, Qi; Wang, Huai-Liang

2017-12-19

The purpose of this study was to investigate the mechanism of monocrotaline (MCT)-induced pulmonary artery hypertension (PAH) and determine whether 4-chloro-DL-phenylalanine (PCPA) could inhibit pulmonary arterial remodeling associated with connective tissue growth factor (CTGF) expression and downstream signal pathway. MCT was administered to forty Sprague Dawley rats to establish the PAH model. PCPA was administered at doses of 50 and 100 mg/kg once daily for 3 weeks via intraperitoneal injection. On day 22, the pulmonary arterial pressure (PAP), right ventricle hypertrophy index (RVI) and pulmonary artery morphology were assessed and the serotonin receptor-1B (SR-1B), CTGF, p-ERK/ERK were measured by western blot or immunohistochemistry. The concentration of serotonin in plasma was checked by ELISA. Apoptosis and apoptosis-related indexes were detected by TUNEL and western blot. In the MCT-induced PAH models, the PAP, RVI, pulmonary vascular remodeling, SR-1B index, CTGF index, anti-apoptotic factors bcl-xl and bcl-2, serotonin concentration in plasma were all increased and the pro-apoptotic factor caspase-3 was reduced. PCPA significantly ameliorated pulmonary arterial remodeling induced by MCT, and this action was associated with accelerated apoptosis and down-regulation of CTGF, SR-1B and p-ERK/ERK. The present study suggests that PCPA protects against the pathogenesis of PAH by suppressing remodeling and inducing apoptosis, which are likely associated with CTGF and downstream ERK signaling pathway in rats.

An Associative Index Model for the Results List Based on Vannevar Bush's Selection Concept

ERIC Educational Resources Information Center

Cole, Charles; Julien, Charles-Antoine; Leide, John E.

2010-01-01

Introduction: We define the results list problem in information search and suggest the "associative index model", an ad-hoc, user-derived indexing solution based on Vannevar Bush's description of an associative indexing approach for his memex machine. We further define what selection means in indexing terms with reference to Charles…

Quantifying landscape pattern and connectivity in a Mediterranean coastal settlement: the case of the Urla district, Turkey.

PubMed

Coskun Hepcan, Cigdem

2013-01-01

This study was aimed at analyzing and interpreting changes in landscape pattern and connectivity in the Urla district, Turkey using core landscape metrics based on a 42-year data derived from 1963 CORONA and 2005 ASTER satellite images and ten 1/25,000 topographical maps (1963-2005). The district represents a distinctive example of re-emerged suburbanization in the Izmir metropolitan area. In order to explore landscape characteristics of the study area, nine landscape composition and configuration metrics were chosen as follows: class area, percentage of landscape, number of patches, patch density, largest patch index, landscape shape index, mean patch size, perimeter area fractal dimension, and connectance index. The landscape configurations in the Urla district changed significantly by 2005 in that the process of (sub-)urbanization in the study area evolved from a rural, monocentric urban typology to a more suburban, polycentric morphology. Agricultural, maquis-phrygana, and forest areas decreased, while the built-up, olive plantation and phrygana areas increased. There was nearly a fivefold increase in the built-up areas during the study period, and the connectivity of the natural landscape declined. To prevent further fragmentation, it is important to keep the existing natural land cover types and agricultural areas intact. More importantly, a sustainable development scenario is required that contains a green infrastructure, or an ecological network planning for conservation and rehabilitation of the vital natural resources in the study area.

Multimodal MR-imaging reveals large-scale structural and functional connectivity changes in profound early blindness

PubMed Central

Bauer, Corinna M.; Hirsch, Gabriella V.; Zajac, Lauren; Koo, Bang-Bon; Collignon, Olivier

2017-01-01

In the setting of profound ocular blindness, numerous lines of evidence demonstrate the existence of dramatic anatomical and functional changes within the brain. However, previous studies based on a variety of distinct measures have often provided inconsistent findings. To help reconcile this issue, we used a multimodal magnetic resonance (MR)-based imaging approach to provide complementary structural and functional information regarding this neuroplastic reorganization. This included gray matter structural morphometry, high angular resolution diffusion imaging (HARDI) of white matter connectivity and integrity, and resting state functional connectivity MRI (rsfcMRI) analysis. When comparing the brains of early blind individuals to sighted controls, we found evidence of co-occurring decreases in cortical volume and cortical thickness within visual processing areas of the occipital and temporal cortices respectively. Increases in cortical volume in the early blind were evident within regions of parietal cortex. Investigating white matter connections using HARDI revealed patterns of increased and decreased connectivity when comparing both groups. In the blind, increased white matter connectivity (indexed by increased fiber number) was predominantly left-lateralized, including between frontal and temporal areas implicated with language processing. Decreases in structural connectivity were evident involving frontal and somatosensory regions as well as between occipital and cingulate cortices. Differences in white matter integrity (as indexed by quantitative anisotropy, or QA) were also in general agreement with observed pattern changes in the number of white matter fibers. Analysis of resting state sequences showed evidence of both increased and decreased functional connectivity in the blind compared to sighted controls. Specifically, increased connectivity was evident between temporal and inferior frontal areas. Decreases in functional connectivity were observed between occipital and frontal and somatosensory-motor areas and between temporal (mainly fusiform and parahippocampus) and parietal, frontal, and other temporal areas. Correlations in white matter connectivity and functional connectivity observed between early blind and sighted controls showed an overall high degree of association. However, comparing the relative changes in white matter and functional connectivity between early blind and sighted controls did not show a significant correlation. In summary, these findings provide complimentary evidence, as well as highlight potential contradictions, regarding the nature of regional and large scale neuroplastic reorganization resulting from early onset blindness. PMID:28328939

Assessing Variation in Permanence/Pragmatism Orientations: Implications for Marital Stability.

ERIC Educational Resources Information Center

Morgan, Mary Y.; Scanzoni, John

1987-01-01

Traces history of construct known as "permanent availability,""universal availability," and "permanence/pragmatism." Connects latter with emerging research tradition labeled "causes and consequences of divorce." Based on data collected from college students, constructed an index of permanence/pragmatism in close relationship. (Author)

Persistence and diversity of directional landscape connectivity improves biomass pulsing in expanding and contracting wetlands

USGS Publications Warehouse

Yurek, Simeon; DeAngelis, Donald L.; Trexler, Joel C.; Klassen, Stephen; Larsen, Laurel G.

2016-01-01

In flood-pulsed ecosystems, hydrology and landscape structure mediate transfers of energy up the food chain by expanding and contracting in area, enabling spatial expansion and growth of fish populations during rising water levels, and subsequent concentration during the drying phase. Connectivity of flooded areas is dynamic as waters rise and fall, and is largely determined by landscape geomorphology and anisotropy. We developed a methodology for simulating fish dispersal and concentration on spatially-explicit, dynamic floodplain wetlands with pulsed food web dynamics, to evaluate how changes in connectivity through time contribute to the concentration of fish biomass that is essential for higher trophic levels. The model also tracks a connectivity index (DCI) over different compass directions to see if fish biomass dynamics can be related in a simple way to topographic pattern. We demonstrate the model for a seasonally flood-pulsed, oligotrophic system, the Everglades, where flow regimes have been greatly altered. Three dispersing populations of functional fish groups were simulated with empirically-based dispersal rules on two landscapes, and two twelve-year time series of managed water levels for those areas were applied. The topographies of the simulations represented intact and degraded ridge-and-slough landscapes (RSL). Simulation results showed large pulses of biomass concentration forming during the onset of the drying phase, when water levels were falling and fish began to converge into the sloughs. As water levels fell below the ridges, DCI declined over different directions, closing down dispersal lanes, and fish density spiked. Persistence of intermediate levels of connectivity on the intact RSL enabled persistent concentration events throughout the drying phase. The intact landscape also buffered effects of wet season population growth. Water level reversals on both landscapes negatively affected fish densities by depleting fish populations without allowing enough time for them to regenerate. Testable, spatiotemporal predictions of the timing, location, duration, and magnitude of fish concentration pulses were produced by the model, and can be applied to restoration planning.

Demonstration of a conceptual model for using LiDAR to improve the estimation of floodwater mitigation potential of Prairie Pothole Region wetlands

USGS Publications Warehouse

Huang, S.; Young, Caitlin; Feng, M.; Heidemann, Hans Karl; Cushing, Matthew; Mushet, D.M.; Liu, S.

2011-01-01

Recent flood events in the Prairie Pothole Region of North America have stimulated interest in modeling water storage capacities of wetlands and their surrounding catchments to facilitate flood mitigation efforts. Accurate estimates of basin storage capacities have been hampered by a lack of high-resolution elevation data. In this paper, we developed a 0.5 m bare-earth model from Light Detection And Ranging (LiDAR) data and, in combination with National Wetlands Inventory data, delineated wetland catchments and their spilling points within a 196 km2 study area. We then calculated the maximum water storage capacity of individual basins and modeled the connectivity among these basins. When compared to field survey results, catchment and spilling point delineations from the LiDAR bare-earth model captured subtle landscape features very well. Of the 11 modeled spilling points, 10 matched field survey spilling points. The comparison between observed and modeled maximum water storage had an R2 of 0.87 with mean absolute error of 5564 m3. Since maximum water storage capacity of basins does not translate into floodwater regulation capability, we further developed a Basin Floodwater Regulation Index. Based upon this index, the absolute and relative water that could be held by wetlands over a landscape could be modeled. This conceptual model of floodwater downstream contribution was demonstrated with water level data from 17 May 2008.

A robust holographic autofocusing criterion based on edge sparsity: comparison of Gini index and Tamura coefficient for holographic autofocusing based on the edge sparsity of the complex optical wavefront

NASA Astrophysics Data System (ADS)

Tamamitsu, Miu; Zhang, Yibo; Wang, Hongda; Wu, Yichen; Ozcan, Aydogan

2018-02-01

The Sparsity of the Gradient (SoG) is a robust autofocusing criterion for holography, where the gradient modulus of the complex refocused hologram is calculated, on which a sparsity metric is applied. Here, we compare two different choices of sparsity metrics used in SoG, specifically, the Gini index (GI) and the Tamura coefficient (TC), for holographic autofocusing on dense/connected or sparse samples. We provide a theoretical analysis predicting that for uniformly distributed image data, TC and GI exhibit similar behavior, while for naturally sparse images containing few high-valued signal entries and many low-valued noisy background pixels, TC is more sensitive to distribution changes in the signal and more resistive to background noise. These predictions are also confirmed by experimental results using SoG-based holographic autofocusing on dense and connected samples (such as stained breast tissue sections) as well as highly sparse samples (such as isolated Giardia lamblia cysts). Through these experiments, we found that ToG and GoG offer almost identical autofocusing performance on dense and connected samples, whereas for naturally sparse samples, GoG should be calculated on a relatively small region of interest (ROI) closely surrounding the object, while ToG offers more flexibility in choosing a larger ROI containing more background pixels.

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

Diefenderfer, Heida L.; Johnson, Gary E.; Sather, Nichole K.

This report describes the 2010 research conducted under the U.S. Army Corps of Engineers (USACE) project EST-P-09-1, titled Evaluation of Life History Diversity, Habitat Connectivity, and Survival Benefits Associated with Habitat Restoration Actions in the Lower Columbia River and Estuary, and known as the 'Salmon Benefits' study. The primary goal of the study is to establish scientific methods to quantify habitat restoration benefits to listed salmon and trout in the lower Columbia River and estuary (LCRE) in three required areas: habitat connectivity, early life history diversity, and survival (Figure ES.1). The general study approach was to first evaluate the statemore » of the science regarding the ability to quantify benefits to listed salmon and trout from habitat restoration actions in the LCRE in the 2009 project year, and then, if feasible, in subsequent project years to develop quantitative indices of habitat connectivity, early life history diversity, and survival. Based on the 2009 literature review, the following definitions are used in this study. Habitat connectivity is defined as a landscape descriptor concerning the ability of organisms to move among habitat patches, including the spatial arrangement of habitats (structural connectivity) and how the perception and behavior of salmon affect the potential for movement among habitats (functional connectivity). Life history is defined as the combination of traits exhibited by an organism throughout its life cycle, and for the purposes of this investigation, a life history strategy refers to the body size and temporal patterns of estuarine usage exhibited by migrating juvenile salmon. Survival is defined as the probability of fish remaining alive over a defined amount of space and/or time. The objectives of the 4-year study are as follows: (1) develop and test a quantitative index of juvenile salmon habitat connectivity in the LCRE incorporating structural, functional, and hydrologic components; (2) develop and test a quantitative index of the early life history diversity of juvenile salmon in the LCRE; (3) assess and, if feasible, develop and test a quantitative index of the survival benefits of tidal wetland habitat restoration (hydrologic reconnection) in the LCRE; and (4) synthesize the results of investigations into the indices for habitat connectivity, early life history diversity, and survival benefits.« less

A strategy to load balancing for non-connectivity MapReduce job

NASA Astrophysics Data System (ADS)

Zhou, Huaping; Liu, Guangzong; Gui, Haixia

2017-09-01

MapReduce has been widely used in large scale and complex datasets as a kind of distributed programming model. Original Hash partitioning function in MapReduce often results the problem of data skew when data distribution is uneven. To solve the imbalance of data partitioning, we proposes a strategy to change the remaining partitioning index when data is skewed. In Map phase, we count the amount of data which will be distributed to each reducer, then Job Tracker monitor the global partitioning information and dynamically modify the original partitioning function according to the data skew model, so the Partitioner can change the index of these partitioning which will cause data skew to the other reducer that has less load in the next partitioning process, and can eventually balance the load of each node. Finally, we experimentally compare our method with existing methods on both synthetic and real datasets, the experimental results show our strategy can solve the problem of data skew with better stability and efficiency than Hash method and Sampling method for non-connectivity MapReduce task.

The influence of changes in land use and landscape patterns on soil erosion in a watershed.

PubMed

Zhang, Shanghong; Fan, Weiwei; Li, Yueqiang; Yi, Yujun

2017-01-01

It is very important to have a good understanding of the relation between soil erosion and landscape patterns so that soil and water conservation in river basins can be optimized. In this study, this relationship was explored, using the Liusha River Watershed, China, as a case study. A distributed water and sediment model based on the Soil and Water Assessment Tool (SWAT) was developed to simulate soil erosion from different land use types in each sub-basin of the Liusha River Watershed. Observed runoff and sediment data from 1985 to 2005 and land use maps from 1986, 1995, and 2000 were used to calibrate and validate the model. The erosion modulus for each sub-basin was calculated from SWAT model results using the different land use maps and 12 landscape indices were chosen and calculated to describe the land use in each sub-basin for the different years. The variations in instead of the absolute amounts of the erosion modulus and the landscape indices for each sub-basin were used as the dependent and independent variables, respectively, for the regression equations derived from multiple linear regression. The results indicated that the variations in the erosion modulus were closely related to changes in the large patch index, patch cohesion index, modified Simpson's evenness index, and the aggregation index. From the regression equation and the corresponding landscape indices, it was found that watershed erosion can be reduced by decreasing the physical connectivity between patches, improving the evenness of the landscape patch types, enriching landscape types, and enhancing the degree of aggregation between the landscape patches. These findings will be useful for water and soil conservation and for optimizing the management of watershed landscapes. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation of environment-related properties of chemicals for design of sustainable processes: development of group-contribution+ (GC+) property models and uncertainty analysis.

PubMed

Hukkerikar, Amol Shivajirao; Kalakul, Sawitree; Sarup, Bent; Young, Douglas M; Sin, Gürkan; Gani, Rafiqul

2012-11-26

The aim of this work is to develop group-contribution(+) (GC(+)) method (combined group-contribution (GC) method and atom connectivity index (CI) method) based property models to provide reliable estimations of environment-related properties of organic chemicals together with uncertainties of estimated property values. For this purpose, a systematic methodology for property modeling and uncertainty analysis is used. The methodology includes a parameter estimation step to determine parameters of property models and an uncertainty analysis step to establish statistical information about the quality of parameter estimation, such as the parameter covariance, the standard errors in predicted properties, and the confidence intervals. For parameter estimation, large data sets of experimentally measured property values of a wide range of chemicals (hydrocarbons, oxygenated chemicals, nitrogenated chemicals, poly functional chemicals, etc.) taken from the database of the US Environmental Protection Agency (EPA) and from the database of USEtox is used. For property modeling and uncertainty analysis, the Marrero and Gani GC method and atom connectivity index method have been considered. In total, 22 environment-related properties, which include the fathead minnow 96-h LC(50), Daphnia magna 48-h LC(50), oral rat LD(50), aqueous solubility, bioconcentration factor, permissible exposure limit (OSHA-TWA), photochemical oxidation potential, global warming potential, ozone depletion potential, acidification potential, emission to urban air (carcinogenic and noncarcinogenic), emission to continental rural air (carcinogenic and noncarcinogenic), emission to continental fresh water (carcinogenic and noncarcinogenic), emission to continental seawater (carcinogenic and noncarcinogenic), emission to continental natural soil (carcinogenic and noncarcinogenic), and emission to continental agricultural soil (carcinogenic and noncarcinogenic) have been modeled and analyzed. The application of the developed property models for the estimation of environment-related properties and uncertainties of the estimated property values is highlighted through an illustrative example. The developed property models provide reliable estimates of environment-related properties needed to perform process synthesis, design, and analysis of sustainable chemical processes and allow one to evaluate the effect of uncertainties of estimated property values on the calculated performance of processes giving useful insights into quality and reliability of the design of sustainable processes.

a Framework of Change Detection Based on Combined Morphologica Features and Multi-Index Classification

NASA Astrophysics Data System (ADS)

Li, S.; Zhang, S.; Yang, D.

2017-09-01

Remote sensing images are particularly well suited for analysis of land cover change. In this paper, we present a new framework for detection of changing land cover using satellite imagery. Morphological features and a multi-index are used to extract typical objects from the imagery, including vegetation, water, bare land, buildings, and roads. Our method, based on connected domains, is different from traditional methods; it uses image segmentation to extract morphological features, while the enhanced vegetation index (EVI), the differential water index (NDWI) are used to extract vegetation and water, and a fragmentation index is used to the correct extraction results of water. HSV transformation and threshold segmentation extract and remove the effects of shadows on extraction results. Change detection is performed on these results. One of the advantages of the proposed framework is that semantic information is extracted automatically using low-level morphological features and indexes. Another advantage is that the proposed method detects specific types of change without any training samples. A test on ZY-3 images demonstrates that our framework has a promising capability to detect change.

Minimum spanning tree analysis of the human connectome.

PubMed

van Dellen, Edwin; Sommer, Iris E; Bohlken, Marc M; Tewarie, Prejaas; Draaisma, Laurijn; Zalesky, Andrew; Di Biase, Maria; Brown, Jesse A; Douw, Linda; Otte, Willem M; Mandl, René C W; Stam, Cornelis J

2018-06-01

One of the challenges of brain network analysis is to directly compare network organization between subjects, irrespective of the number or strength of connections. In this study, we used minimum spanning tree (MST; a unique, acyclic subnetwork with a fixed number of connections) analysis to characterize the human brain network to create an empirical reference network. Such a reference network could be used as a null model of connections that form the backbone structure of the human brain. We analyzed the MST in three diffusion-weighted imaging datasets of healthy adults. The MST of the group mean connectivity matrix was used as the empirical null-model. The MST of individual subjects matched this reference MST for a mean 58%-88% of connections, depending on the analysis pipeline. Hub nodes in the MST matched with previously reported locations of hub regions, including the so-called rich club nodes (a subset of high-degree, highly interconnected nodes). Although most brain network studies have focused primarily on cortical connections, cortical-subcortical connections were consistently present in the MST across subjects. Brain network efficiency was higher when these connections were included in the analysis, suggesting that these tracts may be utilized as the major neural communication routes. Finally, we confirmed that MST characteristics index the effects of brain aging. We conclude that the MST provides an elegant and straightforward approach to analyze structural brain networks, and to test network topological features of individual subjects in comparison to empirical null models. © 2018 The Authors Human Brain Mapping Published by Wiley Periodicals, Inc.

Stress assessment based on EEG univariate features and functional connectivity measures.

PubMed

Alonso, J F; Romero, S; Ballester, M R; Antonijoan, R M; Mañanas, M A

2015-07-01

The biological response to stress originates in the brain but involves different biochemical and physiological effects. Many common clinical methods to assess stress are based on the presence of specific hormones and on features extracted from different signals, including electrocardiogram, blood pressure, skin temperature, or galvanic skin response. The aim of this paper was to assess stress using EEG-based variables obtained from univariate analysis and functional connectivity evaluation. Two different stressors, the Stroop test and sleep deprivation, were applied to 30 volunteers to find common EEG patterns related to stress effects. Results showed a decrease of the high alpha power (11 to 12 Hz), an increase in the high beta band (23 to 36 Hz, considered a busy brain indicator), and a decrease in the approximate entropy. Moreover, connectivity showed that the high beta coherence and the interhemispheric nonlinear couplings, measured by the cross mutual information function, increased significantly for both stressors, suggesting that useful stress indexes may be obtained from EEG-based features.

Neurophysiological Basis of Multi-Scale Entropy of Brain Complexity and Its Relationship With Functional Connectivity.

PubMed

Wang, Danny J J; Jann, Kay; Fan, Chang; Qiao, Yang; Zang, Yu-Feng; Lu, Hanbing; Yang, Yihong

2018-01-01

Recently, non-linear statistical measures such as multi-scale entropy (MSE) have been introduced as indices of the complexity of electrophysiology and fMRI time-series across multiple time scales. In this work, we investigated the neurophysiological underpinnings of complexity (MSE) of electrophysiology and fMRI signals and their relations to functional connectivity (FC). MSE and FC analyses were performed on simulated data using neural mass model based brain network model with the Brain Dynamics Toolbox, on animal models with concurrent recording of fMRI and electrophysiology in conjunction with pharmacological manipulations, and on resting-state fMRI data from the Human Connectome Project. Our results show that the complexity of regional electrophysiology and fMRI signals is positively correlated with network FC. The associations between MSE and FC are dependent on the temporal scales or frequencies, with higher associations between MSE and FC at lower temporal frequencies. Our results from theoretical modeling, animal experiment and human fMRI indicate that (1) Regional neural complexity and network FC may be two related aspects of brain's information processing: the more complex regional neural activity, the higher FC this region has with other brain regions; (2) MSE at high and low frequencies may represent local and distributed information processing across brain regions. Based on literature and our data, we propose that the complexity of regional neural signals may serve as an index of the brain's capacity of information processing-increased complexity may indicate greater transition or exploration between different states of brain networks, thereby a greater propensity for information processing.

Multiscale solute transport upscaling for a three-dimensional hierarchical porous medium

NASA Astrophysics Data System (ADS)

Zhang, Mingkan; Zhang, Ye

2015-03-01

A laboratory-generated hierarchical, fully heterogeneous aquifer model (FHM) provides a reference for developing and testing an upscaling approach that integrates large-scale connectivity mapping with flow and transport modeling. Based on the FHM, three hydrostratigraphic models (HSMs) that capture lithological (static) connectivity at different resolutions are created, each corresponding to a sedimentary hierarchy. Under increasing system lnK variances (0.1, 1.0, 4.5), flow upscaling is first conducted to calculate equivalent hydraulic conductivity for individual connectivity (or unit) of the HSMs. Given the computed flow fields, an instantaneous, conservative tracer test is simulated by all models. For the HSMs, two upscaling formulations are tested based on the advection-dispersion equation (ADE), implementing space versus time-dependent macrodispersivity. Comparing flow and transport predictions of the HSMs against those of the reference model, HSMs capturing connectivity at increasing resolutions are more accurate, although upscaling errors increase with system variance. Results suggest: (1) by explicitly modeling connectivity, an enhanced degree of freedom in representing dispersion can improve the ADE-based upscaled models by capturing non-Fickian transport of the FHM; (2) when connectivity is sufficiently resolved, the type of data conditioning used to model transport becomes less critical. Data conditioning, however, is influenced by the prediction goal; (3) when aquifer is weakly-to-moderately heterogeneous, the upscaled models adequately capture the transport simulation of the FHM, despite the existence of hierarchical heterogeneity at smaller scales. When aquifer is strongly heterogeneous, the upscaled models become less accurate because lithological connectivity cannot adequately capture preferential flows; (4) three-dimensional transport connectivities of the hierarchical aquifer differ quantitatively from those analyzed for two-dimensional systems. This article was corrected on 7 MAY 2015. See the end of the full text for details.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results.

PubMed

Humada, Ali M; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M; Ahmed, Mushtaq N

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results

PubMed Central

Humada, Ali M.; Hojabri, Mojgan; Sulaiman, Mohd Herwan Bin; Hamada, Hussein M.; Ahmed, Mushtaq N.

2016-01-01

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions. PMID:27035575

Do Not Only Connect

NASA Astrophysics Data System (ADS)

Kirkby, M. J.

2012-04-01

Although the concept of connectivity has been increasingly canvassed in the last 10 years, there have been relatively few, and sometimes contradictory operational definitions. Connectivity can be reasonably associated with water flow, sediment transport and ecological habitats, and either generally or along specific pathways, for example in hyporheic exchanges, and inherits a legacy from concepts such as contributing area and hydraulic routing. Here we focus on a single mode, for overland flow, but there remain a bewildering range of operational definitions. Connectivity between two points A and B, on a flow line, can be described as a nominal variable (presence or absence of connection), as a scalar (time delay or breakthrough volume), or as increasingly complex vectors (hydrograph at B for given input at A), even at steady state for a conservative system. Detailed descriptions of dynamic connectivity between adjacent points across an area form one critical ingredient of fine scale process-based models, such as CRUM or MAHLERAN. In this way, connectivity provides a valuable way of conceptualizing the local persistence and continuity of overland flow, particularly in semi-arid areas with short bursts of rainfall and patchy surface properties. For time-spans over which the soils and topography can respond, the division between structural and functional connectivity is also valuable; structure providing a necessary pre-condition for functional connection, and function a necessary condition for change in structure. Beyond the strictly local scale, we would like to collapse the detail of overland flow connectivity into summary index variables, providing one or a few parameters that, for example, scale the response of a hillslope or small catchment to storm rainfall. Candidate indices include average travel times from runoff generating cells, average residence times and contributing areas, all potentially time-varying in response to catchment condition and storm rainfall. However, no magic bullet has yet emerged to summarize the complexity of catchment response.

A Theory of Term Importance in Automatic Text Analysis.

ERIC Educational Resources Information Center

Salton, G.; And Others

Most existing automatic content analysis and indexing techniques are based on work frequency characteristics applied largely in an ad hoc manner. Contradictory requirements arise in this connection, in that terms exhibiting high occurrence frequencies in individual documents are often useful for high recall performance (to retrieve many relevant…

System dynamic modelling of industrial growth and landscape ecology in China.

PubMed

Xu, Jian; Kang, Jian; Shao, Long; Zhao, Tianyu

2015-09-15

With the rapid development of large industrial corridors in China, the landscape ecology of the country is currently being affected. Therefore, in this study, a system dynamic model with multi-dimensional nonlinear dynamic prediction function that considers industrial growth and landscape ecology is developed and verified to allow for more sustainable development. Firstly, relationships between industrial development and landscape ecology in China are examined, and five subsystems are then established: industry, population, urban economy, environment and landscape ecology. The main influencing factors are then examined for each subsystem to establish flow charts connecting those factors. Consequently, by connecting the subsystems, an overall industry growth and landscape ecology model is established. Using actual data and landscape index calculated based on GIS of the Ha-Da-Qi industrial corridor, a typical industrial corridor in China, over the period 2005-2009, the model is validated in terms of historical behaviour, logical structure and future prediction, where for 84.8% of the factors, the error rate of the model is less than 5%, the mean error rate of all factors is 2.96% and the error of the simulation test for the landscape ecology subsystem is less than 2%. Moreover, a model application has been made to consider the changes in landscape indices under four industrial development modes, and the optimal industrial growth plan has been examined for landscape ecological protection through the simulation prediction results over 2015-2020. Copyright © 2015 Elsevier Ltd. All rights reserved.

Data-Driven Sequence of Changes to Anatomical Brain Connectivity in Sporadic Alzheimer's Disease.

PubMed

Oxtoby, Neil P; Garbarino, Sara; Firth, Nicholas C; Warren, Jason D; Schott, Jonathan M; Alexander, Daniel C

2017-01-01

Model-based investigations of transneuronal spreading mechanisms in neurodegenerative diseases relate the pattern of pathology severity to the brain's connectivity matrix, which reveals information about how pathology propagates through the connectivity network. Such network models typically use networks based on functional or structural connectivity in young and healthy individuals, and only end-stage patterns of pathology, thereby ignoring/excluding the effects of normal aging and disease progression. Here, we examine the sequence of changes in the elderly brain's anatomical connectivity over the course of a neurodegenerative disease. We do this in a data-driven manner that is not dependent upon clinical disease stage, by using event-based disease progression modeling. Using data from the Alzheimer's Disease Neuroimaging Initiative dataset, we sequence the progressive decline of anatomical connectivity, as quantified by graph-theory metrics, in the Alzheimer's disease brain. Ours is the first single model to contribute to understanding all three of the nature, the location, and the sequence of changes to anatomical connectivity in the human brain due to Alzheimer's disease. Our experimental results reveal new insights into Alzheimer's disease: that degeneration of anatomical connectivity in the brain may be a viable, even early, biomarker and should be considered when studying such neurodegenerative diseases.

Assessing habitat connectivity for ground-dwelling animals in an urban environment.

PubMed

Braaker, S; Moretti, M; Boesch, R; Ghazoul, J; Obrist, M K; Bontadina, F

To ensure viable species populations in fragmented landscapes, individuals must be able to move between suitable habitat patches. Despite the increased interest in biodiversity assessment in urban environments, the ecological relevance of habitat connectivity in highly fragmented landscapes remains largely unknown. The first step to understanding the role of habitat connectivity in urban ecology is the challenging task of assessing connectivity in the complex patchwork of contrasting habitats that is found in cities. We developed a data-based framework, minimizing the use of subjective assumptions, to assess habitat connectivity that consists of the following sequential steps: (1) identification of habitat preference based on empirical habitat-use data; (2) derivation of habitat resistance surfaces evaluating various transformation functions; (3) modeling of different connectivity maps with electrical circuit theory (Circuitscape), a method considering all possible pathways across the landscape simultaneously; and (4) identification of the best connectivity map with information-theoretic model selection. We applied this analytical framework to assess habitat connectivity for the European hedgehog Erinaceus europaeus, a model species for ground-dwelling animals, in the city of Zurich, Switzerland, using GPS track points from 40 individuals. The best model revealed spatially explicit connectivity “pinch points,” as well as multiple habitat connections. Cross-validation indicated the general validity of the selected connectivity model. The results show that both habitat connectivity and habitat quality affect the movement of urban hedgehogs (relative importance of the two variables was 19.2% and 80.8%, respectively), and are thus both relevant for predicting urban animal movements. Our study demonstrates that even in the complex habitat patchwork of cities, habitat connectivity plays a major role for ground-dwelling animal movement. Data-based habitat connectivity maps can thus serve as an important tool for city planners to identify habitat corridors and plan appropriate management and conservation measures for urban animals. The analytical framework we describe to model such connectivity maps is generally applicable to different types of habitat-use data and can be adapted to the movement scale of the focal species. It also allows evaluation of the impact of future landscape changes or management scenarios on habitat connectivity in urban landscapes.

Combining demographic and genetic factors to assess population vulnerability in stream species

USGS Publications Warehouse

Erin L, Landguth; Muhlfeld, Clint C.; Jones, Leslie W.; Waples, Robin S.; Whited, Diane; Lowe, Winsor H.; Lucotch, John; Neville, Helen; Luikart, Gordon

2014-01-01

Accelerating climate change and other cumulative stressors create an urgent need to understand the influence of environmental variation and landscape features on the connectivity and vulnerability of freshwater species. Here, we introduce a novel modeling framework for aquatic systems that integrates spatially explicit, individual-based, demographic and genetic (demogenetic) assessments with environmental variables. To show its potential utility, we simulated a hypothetical network of 19 migratory riverine populations (e.g., salmonids) using a riverscape connectivity and demogenetic model (CDFISH). We assessed how stream resistance to movement (a function of water temperature, fluvial distance, and physical barriers) might influence demogenetic connectivity, and hence, population vulnerability. We present demographic metrics (abundance, immigration, and change in abundance) and genetic metrics (diversity, differentiation, and change in differentiation), and combine them into a single vulnerability index for identifying populations at risk of extirpation. We considered four realistic scenarios that illustrate the relative sensitivity of these metrics for early detection of reduced connectivity: (1) maximum resistance due to high water temperatures throughout the network, (2) minimum resistance due to low water temperatures throughout the network, (3) increased resistance at a tributary junction caused by a partial barrier, and (4) complete isolation of a tributary, leaving resident individuals only. We then applied this demogenetic framework using empirical data for a bull trout (Salvelinus confluentus) metapopulation in the upper Flathead River system, Canada and USA, to assess how current and predicted future stream warming may influence population vulnerability. Results suggest that warmer water temperatures and associated barriers to movement (e.g., low flows, dewatering) are predicted to fragment suitable habitat for migratory salmonids, resulting in the loss of genetic diversity and reduced numbers in certain vulnerable populations. This demogenetic simulation framework, which is illustrated in a web-based interactive mapping prototype, should be useful for evaluating population vulnerability in a wide variety of dendritic and fragmented riverscapes, helping to guide conservation and management efforts for freshwater species.

Network organization is globally atypical in autism: A graph theory study of intrinsic functional connectivity.

PubMed

Keown, Christopher L; Datko, Michael C; Chen, Colleen P; Maximo, José Omar; Jahedi, Afrooz; Müller, Ralph-Axel

2017-01-01

Despite abundant evidence of brain network anomalies in autism spectrum disorder (ASD), findings have varied from broad functional underconnectivity to broad overconnectivity. Rather than pursuing overly simplifying general hypotheses ('under' vs. 'over'), we tested the hypothesis of atypical network distribution in ASD (i.e., participation of unusual loci in distributed functional networks). We used a selective high-quality data subset from the ABIDE datashare (including 111 ASD and 174 typically developing [TD] participants) and several graph theory metrics. Resting state functional MRI data were preprocessed and analyzed for detection of low-frequency intrinsic signal correlations. Groups were tightly matched for available demographics and head motion. As hypothesized, the Rand Index (reflecting how similar network organization was to a normative set of networks) was significantly lower in ASD than TD participants. This was accounted for by globally reduced cohesion and density, but increased dispersion of networks. While differences in hub architecture did not survive correction, rich club connectivity (among the hubs) was increased in the ASD group. Our findings support the model of reduced network integration (connectivity with networks) and differentiation (or segregation; based on connectivity outside network boundaries) in ASD. While the findings applied at the global level, they were not equally robust across all networks and in one case (greater cohesion within ventral attention network in ASD) even reversed.

Simulation Study on Fit Indexes in CFA Based on Data with Slightly Distorted Simple Structure

ERIC Educational Resources Information Center

Beauducel, Andre; Wittmann, Werner W.

2005-01-01

Fit indexes were compared with respect to a specific type of model misspecification. Simple structure was violated with some secondary loadings that were present in the true models that were not specified in the estimated models. The c2 test, Comparative Fit Index, Goodness-of-Fit Index, Incremental Fit Index, Nonnormed Fit Index, root mean…

GIS-based approach for quantifying landscape connectivity of Javan Hawk-Eagle habitat

NASA Astrophysics Data System (ADS)

Nurfatimah, C.; Syartinilia; Mulyani, Y. A.

2018-05-01

Javan Hawk-Eagle (Nisaetus bartelsi; JHE) is a law-protected endemic raptor which currently faced the decreased in number and size of habitat patches that will lead to patch isolation and species extinction. This study assessed the degree of connectivity between remnant habitat patches in central part of Java by utilizing Conefor Sensinode software as an additional tool for ArcGIS. The connectivity index was determined by three fractions which are infra, flux and connector. Using connectivity indices successfully identified 4 patches as core habitat, 9 patches as stepping-stone habitat and 6 patches as isolated habitat were derived from those connectivity indices. Those patches then being validated with land cover map derived from Landsat 8 of August 2014. 36% of core habitat covered by natural forest, meanwhile stepping stone habitat has 55% natural forest and isolated habitat covered by 59% natural forest. Isolated patches were caused by zero connectivity (PCcon = 0) and the patch size which too small to support viable JHE population. Yet, the condition of natural forest and the surrounding matrix landscape in isolated patches actually support the habitat need. Thus, it is very important to conduct the right conservation management system based on the condition of each patches.

Connection to Nature: Children's Affective Attitude toward Nature

ERIC Educational Resources Information Center

Cheng, Judith Chen-Hsuan; Monroe, Martha C.

2012-01-01

A connection to nature index was developed and tested to measure children's affective attitude toward the natural environment. The index was employed through a survey that investigates students' attitude toward Lagoon Quest, a mandatory environmental education program for all fourth-grade, public school students in Brevard County, Florida. Factor…

The Influence of Water Conservancy Projects on River Network Connectivity, A Case of Luanhe River Basin

NASA Astrophysics Data System (ADS)

Li, Z.; Li, C.

2017-12-01

Connectivity is one of the most important characteristics of a river, which is derived from the natural water cycle and determine the renewability of river water. The water conservancy project can change the connectivity of natural river networks, and directly threaten the health and stability of the river ecosystem. Based on the method of Dendritic Connectivity Index (DCI), the impacts from sluices and dams on the connectivity of river network are deeply discussed herein. DCI quantitatively evaluate the connectivity of river networks based on the number of water conservancy facilities, the connectivity of fish and geographical location. The results show that the number of water conservancy facilities and their location in the river basin have a great influence on the connectivity of the river network. With the increase of the number of sluices and dams, DCI is decreasing gradually, but its decreasing range is becoming smaller and smaller. The dam located in the middle of the river network cuts the upper and lower parts of the whole river network, and destroys the connectivity of the river network more seriously. Therefore, this method can be widely applied to the comparison of different alternatives during planning of river basins and then provide a reference for the site selection and design of the water conservancy project and facility concerned.

Watershed erosion modeling using the probability of sediment connectivity in a gently rolling system

NASA Astrophysics Data System (ADS)

Mahoney, David Tyler; Fox, James Forrest; Al Aamery, Nabil

2018-06-01

Sediment connectivity has been shown in recent years to explain how the watershed configuration controls sediment transport. However, we find no studies develop a watershed erosion modeling framework based on sediment connectivity, and few, if any, studies have quantified sediment connectivity for gently rolling systems. We develop a new predictive sediment connectivity model that relies on the intersecting probabilities for sediment supply, detachment, transport, and buffers to sediment transport, which is integrated in a watershed erosion model framework. The model predicts sediment flux temporally and spatially across a watershed using field reconnaissance results, a high-resolution digital elevation models, a hydrologic model, and shear-based erosion formulae. Model results validate the capability of the model to predict erosion pathways causing sediment connectivity. More notably, disconnectivity dominates the gently rolling watershed across all morphologic levels of the uplands, including, microtopography from low energy undulating surfaces across the landscape, swales and gullies only active in the highest events, karst sinkholes that disconnect drainage areas, and floodplains that de-couple the hillslopes from the stream corridor. Results show that sediment connectivity is predicted for about 2% or more the watershed's area 37 days of the year, with the remaining days showing very little or no connectivity. Only 12.8 ± 0.7% of the gently rolling watershed shows sediment connectivity on the wettest day of the study year. Results also highlight the importance of urban/suburban sediment pathways in gently rolling watersheds, and dynamic and longitudinal distributions of sediment connectivity might be further investigated in future work. We suggest the method herein provides the modeler with an added tool to account for sediment transport criteria and has the potential to reduce computational costs in watershed erosion modeling.

Eccentric connectivity index of chemical trees

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

Haoer, R. S., E-mail: raadsehen@gmail.com; Department of Mathematics, Faculty of Computer Sciences and Mathematics, University Of Kufa, Najaf; Atan, K. A., E-mail: kamel@upm.edu.my

Let G = (V, E) be a simple connected molecular graph. In such a simple molecular graph, vertices and edges are depicted atoms and chemical bonds respectively, we refer to the sets of vertices by V (G) and edges by E (G). If d(u, v) be distance between two vertices u, v ∈ V(G) and can be defined as the length of a shortest path joining them. Then, the eccentricity connectivity index (ECI) of a molecular graph G is ξ(G) = ∑{sub v∈V(G)} d(v) ec(v), where d(v) is degree of a vertex v ∈ V(G). ec(v) is the length ofmore » a greatest path linking to another vertex of v. In this study, we focus the general formula for the eccentricity connectivity index (ECI) of some chemical trees as alkenes.« less

A comparative study of theoretical graph models for characterizing structural networks of human brain.

PubMed

Li, Xiaojin; Hu, Xintao; Jin, Changfeng; Han, Junwei; Liu, Tianming; Guo, Lei; Hao, Wei; Li, Lingjiang

2013-01-01

Previous studies have investigated both structural and functional brain networks via graph-theoretical methods. However, there is an important issue that has not been adequately discussed before: what is the optimal theoretical graph model for describing the structural networks of human brain? In this paper, we perform a comparative study to address this problem. Firstly, large-scale cortical regions of interest (ROIs) are localized by recently developed and validated brain reference system named Dense Individualized Common Connectivity-based Cortical Landmarks (DICCCOL) to address the limitations in the identification of the brain network ROIs in previous studies. Then, we construct structural brain networks based on diffusion tensor imaging (DTI) data. Afterwards, the global and local graph properties of the constructed structural brain networks are measured using the state-of-the-art graph analysis algorithms and tools and are further compared with seven popular theoretical graph models. In addition, we compare the topological properties between two graph models, namely, stickiness-index-based model (STICKY) and scale-free gene duplication model (SF-GD), that have higher similarity with the real structural brain networks in terms of global and local graph properties. Our experimental results suggest that among the seven theoretical graph models compared in this study, STICKY and SF-GD models have better performances in characterizing the structural human brain network.

Performance of the Enhanced Vegetation Index to Detect Inner-annual Dry Season and Drought Impacts on Amazon Forest Canopies

NASA Astrophysics Data System (ADS)

Brede, B.; Verbesselt, J.; Dutrieux, L.; Herold, M.

2015-04-01

The Amazon rainforests represent the largest connected forested area in the tropics and play an integral role in the global carbon cycle. In the last years the discussion about their phenology and response to drought has intensified. A recent study argued that seasonality in greenness expressed as Enhanced Vegetation Index (EVI) is an artifact of variations in sun-sensor geometry throughout the year. We aimed to reproduce these results with the Moderate-Resolution Imaging Spectroradiometer (MODIS) MCD43 product suite, which allows modeling the Bidirectional Reflectance Distribution Function (BRDF) and keeping sun-sensor geometry constant. The derived BRDF-adjusted EVI was spatially aggregated over large areas of central Amazon forests. The resulting time series of EVI spanning the 2000-2013 period contained distinct seasonal patterns with peak values at the onset of the dry season, but also followed the same pattern of sun geometry expressed as Solar Zenith Angle (SZA). Additionally, we assessed EVI's sensitivity to precipitation anomalies. For that we compared BRDF-adjusted EVI dry season anomalies to two drought indices (Maximum Cumulative Water Deficit, Standardized Precipitation Index). This analysis covered the whole of Amazonia and data from the years 2000 to 2013. The results showed no meaningful connection between EVI anomalies and drought. This is in contrast to other studies that investigate the drought impact on EVI and forest photosynthetic capacity. The results from both sub-analyses question the predictive power of EVI for large scale assessments of forest ecosystem functioning in Amazonia. Based on the presented results, we recommend a careful evaluation of the EVI for applications in tropical forests, including rigorous validation supported by ground plots.

On Certain Topological Indices of Boron Triangular Nanotubes

NASA Astrophysics Data System (ADS)

Aslam, Adnan; Ahmad, Safyan; Gao, Wei

2017-08-01

The topological index gives information about the whole structure of a chemical graph, especially degree-based topological indices that are very useful. Boron triangular nanotubes are now replacing usual carbon nanotubes due to their excellent properties. We have computed general Randić (Rα), first Zagreb (M1) and second Zagreb (M2), atom-bond connectivity (ABC), and geometric-arithmetic (GA) indices of boron triangular nanotubes. Also, we have computed the fourth version of atom-bond connectivity (ABC4) and the fifth version of geometric-arithmetic (GA5) indices of boron triangular nanotubes.

Sparse Multivariate Autoregressive Modeling for Mild Cognitive Impairment Classification

PubMed Central

Li, Yang; Wee, Chong-Yaw; Jie, Biao; Peng, Ziwen

2014-01-01

Brain connectivity network derived from functional magnetic resonance imaging (fMRI) is becoming increasingly prevalent in the researches related to cognitive and perceptual processes. The capability to detect causal or effective connectivity is highly desirable for understanding the cooperative nature of brain network, particularly when the ultimate goal is to obtain good performance of control-patient classification with biological meaningful interpretations. Understanding directed functional interactions between brain regions via brain connectivity network is a challenging task. Since many genetic and biomedical networks are intrinsically sparse, incorporating sparsity property into connectivity modeling can make the derived models more biologically plausible. Accordingly, we propose an effective connectivity modeling of resting-state fMRI data based on the multivariate autoregressive (MAR) modeling technique, which is widely used to characterize temporal information of dynamic systems. This MAR modeling technique allows for the identification of effective connectivity using the Granger causality concept and reducing the spurious causality connectivity in assessment of directed functional interaction from fMRI data. A forward orthogonal least squares (OLS) regression algorithm is further used to construct a sparse MAR model. By applying the proposed modeling to mild cognitive impairment (MCI) classification, we identify several most discriminative regions, including middle cingulate gyrus, posterior cingulate gyrus, lingual gyrus and caudate regions, in line with results reported in previous findings. A relatively high classification accuracy of 91.89 % is also achieved, with an increment of 5.4 % compared to the fully-connected, non-directional Pearson-correlation-based functional connectivity approach. PMID:24595922

Resting-state global functional connectivity as a biomarker of cognitive reserve in mild cognitive impairment.

PubMed

Franzmeier, N; Caballero, M Á Araque; Taylor, A N W; Simon-Vermot, L; Buerger, K; Ertl-Wagner, B; Mueller, C; Catak, C; Janowitz, D; Baykara, E; Gesierich, B; Duering, M; Ewers, M

2017-04-01

Cognitive reserve (CR) shows protective effects in Alzheimer's disease (AD) and reduces the risk of dementia. Despite the clinical significance of CR, a clinically useful diagnostic biomarker of brain changes underlying CR in AD is not available yet. Our aim was to develop a fully-automated approach applied to fMRI to produce a biomarker associated with CR in subjects at increased risk of AD. We computed resting-state global functional connectivity (GFC), i.e. the average connectivity strength, for each voxel within the cognitive control network, which may sustain CR due to its central role in higher cognitive function. In a training sample including 43 mild cognitive impairment (MCI) subjects and 24 healthy controls (HC), we found that MCI subjects with high CR (> median of years of education, CR+) showed increased frequency of high GFC values compared to MCI-CR- and HC. A summary index capturing such a surplus frequency of high GFC was computed (called GFC reserve (GFC-R) index). GFC-R discriminated MCI-CR+ vs. MCI-CR-, with the area under the ROC = 0.84. Cross-validation in an independently recruited test sample of 23 MCI subjects showed that higher levels of the GFC-R index predicted higher years of education and an alternative questionnaire-based proxy of CR, controlled for memory performance, gray matter of the cognitive control network, white matter hyperintensities, age, and gender. In conclusion, the GFC-R index that captures GFC changes within the cognitive control network provides a biomarker candidate of functional brain changes of CR in patients at increased risk of AD.

Using circuit theory to model connectivity in ecology, evolution, and conservation.

PubMed

McRae, Brad H; Dickson, Brett G; Keitt, Timothy H; Shah, Viral B

2008-10-01

Connectivity among populations and habitats is important for a wide range of ecological processes. Understanding, preserving, and restoring connectivity in complex landscapes requires connectivity models and metrics that are reliable, efficient, and process based. We introduce a new class of ecological connectivity models based in electrical circuit theory. Although they have been applied in other disciplines, circuit-theoretic connectivity models are new to ecology. They offer distinct advantages over common analytic connectivity models, including a theoretical basis in random walk theory and an ability to evaluate contributions of multiple dispersal pathways. Resistance, current, and voltage calculated across graphs or raster grids can be related to ecological processes (such as individual movement and gene flow) that occur across large population networks or landscapes. Efficient algorithms can quickly solve networks with millions of nodes, or landscapes with millions of raster cells. Here we review basic circuit theory, discuss relationships between circuit and random walk theories, and describe applications in ecology, evolution, and conservation. We provide examples of how circuit models can be used to predict movement patterns and fates of random walkers in complex landscapes and to identify important habitat patches and movement corridors for conservation planning.

Cortical parcellation based on structural connectivity: A case for generative models.

PubMed

Tittgemeyer, Marc; Rigoux, Lionel; Knösche, Thomas R

2018-06-01

One of the major challenges in systems neuroscience is to identify brain networks and unravel their significance for brain function -this has led to the concept of the 'connectome'. Connectomes are currently extensively studied in large-scale international efforts at multiple scales, and follow different definitions with respect to their connections as well as their elements. Perhaps the most promising avenue for defining the elements of connectomes originates from the notion that individual brain areas maintain distinct (long-range) connection profiles. These connectivity patterns determine the areas' functional properties and also allow for their anatomical delineation and mapping. This rationale has motivated the concept of connectivity-based cortex parcellation. In the past ten years, non-invasive mapping of human brain connectivity has led to immense advances in the development of parcellation techniques and their applications. Unfortunately, many of these approaches primarily aim for confirmation of well-known, existing architectonic maps and, to that end, unsuitably incorporate prior knowledge and frequently build on circular argumentation. Often, current approaches also tend to disregard the specific apertures of connectivity measurements, as well as the anatomical specificities of cortical areas, such as spatial compactness, regional heterogeneity, inter-subject variability, the multi-scaling nature of connectivity information, and potential hierarchical organisation. From a methodological perspective, however, a useful framework that regards all of these aspects in an unbiased way is technically demanding. In this commentary, we first outline the concept of connectivity-based cortex parcellation and discuss its prospects and limitations in particular with respect to structural connectivity. To improve reliability and efficiency, we then strongly advocate for connectivity-based cortex parcellation as a modelling approach; that is, an approximation of the data based on (model) parameter inference. As such, a parcellation algorithm can be formally tested for robustness -the precision of its predictions can be quantified and statistics about potential generalization of the results can be derived. Such a framework also allows the question of model constraints to be reformulated in terms of hypothesis testing through model selection and offers a formative way to integrate anatomical knowledge in terms of prior distributions. Copyright © 2018 Elsevier Inc. All rights reserved.

Maximum covariance analysis to identify intraseasonal oscillations over tropical Brazil

NASA Astrophysics Data System (ADS)

Barreto, Naurinete J. C.; Mesquita, Michel d. S.; Mendes, David; Spyrides, Maria H. C.; Pedra, George U.; Lucio, Paulo S.

2017-09-01

A reliable prognosis of extreme precipitation events in the tropics is arguably challenging to obtain due to the interaction of meteorological systems at various time scales. A pivotal component of the global climate variability is the so-called intraseasonal oscillations, phenomena that occur between 20 and 100 days. The Madden-Julian Oscillation (MJO), which is directly related to the modulation of convective precipitation in the equatorial belt, is considered the primary oscillation in the tropical region. The aim of this study is to diagnose the connection between the MJO signal and the regional intraseasonal rainfall variability over tropical Brazil. This is achieved through the development of an index called Multivariate Intraseasonal Index for Tropical Brazil (MITB). This index is based on Maximum Covariance Analysis (MCA) applied to the filtered daily anomalies of rainfall data over tropical Brazil against a group of covariates consisting of: outgoing longwave radiation and the zonal component u of the wind at 850 and 200 hPa. The first two MCA modes, which were used to create the { MITB}_1 and { MITB}_2 indices, represent 65 and 16 % of the explained variance, respectively. The combined multivariate index was able to satisfactorily represent the pattern of intraseasonal variability over tropical Brazil, showing that there are periods of activation and inhibition of precipitation connected with the pattern of MJO propagation. The MITB index could potentially be used as a diagnostic tool for intraseasonal forecasting.

Using Rasch Measurement to Develop a Computer Modeling-Based Instrument to Assess Students' Conceptual Understanding of Matter

ERIC Educational Resources Information Center

Wei, Silin; Liu, Xiufeng; Wang, Zuhao; Wang, Xingqiao

2012-01-01

Research suggests that difficulty in making connections among three levels of chemical representations--macroscopic, submicroscopic, and symbolic--is a primary reason for student alternative conceptions of chemistry concepts, and computer modeling is promising to help students make the connections. However, no computer modeling-based assessment…

Stock market index prediction using neural networks

NASA Astrophysics Data System (ADS)

Komo, Darmadi; Chang, Chein-I.; Ko, Hanseok

1994-03-01

A neural network approach to stock market index prediction is presented. Actual data of the Wall Street Journal's Dow Jones Industrial Index has been used for a benchmark in our experiments where Radial Basis Function based neural networks have been designed to model these indices over the period from January 1988 to Dec 1992. A notable success has been achieved with the proposed model producing over 90% prediction accuracies observed based on monthly Dow Jones Industrial Index predictions. The model has also captured both moderate and heavy index fluctuations. The experiments conducted in this study demonstrated that the Radial Basis Function neural network represents an excellent candidate to predict stock market index.

Conflicting hydropower development and aquatic ecosystem conservation in Bhutan

NASA Astrophysics Data System (ADS)

Wi, S.; Yang, Y. C. E.

2017-12-01

Hydropower is one of the clean energy sources that many Himalayan countries are eager to develop to solve their domestic energy deficit issue such as India, Nepal and Pakistan. Like other Himalayan countries, Bhutan also has a great potential for hydropower development. However, Bhutan is one of few countries that has a domestic energy surplus and export its hydropower generation to neighboring countries (mainly to India). Exporting hydropower is one of the major economic sources in Bhutan. However, constructions of dams and reservoirs for hydropower development inevitably involve habitat fragmentation, causing a conflict of interest with the pursuit of value in aquatic ecosystem conservation. The objectives of this study is to 1) develop a distributed hydrologic model with snow and glacier module to simulate the hydrologic regimes of seven major watersheds in Bhutan; 2) apply the hydrologic model to compute hydropower generation for all existing and potential dams; 3) evaluate cascade impacts of each individual dam on downstream regions by employing three hydro-ecological indicators: the River Connectivity Index (RCI), Dendritic Connectivity Index (DCI), total affected river stretch (ARS), and 4) analyze the tradeoffs between hydropower generation and river connectivity at the national scale by means of a multiple objective genetic algorithm. Modeling results of three Pareto Fronts between ecological indicators and hydropower generation accompany with future energy export targets from the government can inform dam selections that maximizing hydropower generation while minimizing the impact on the aquatic ecosystem (Figure 1a). The impacts of climate change on these Pareto front are also explored to identify robust dam selection under changing temperature and precipitation (Figure 1b).

Ecological connectivity networks in rapidly expanding cities.

PubMed

Nor, Amal Najihah M; Corstanje, Ron; Harris, Jim A; Grafius, Darren R; Siriwardena, Gavin M

2017-06-01

Urban expansion increases fragmentation of the landscape. In effect, fragmentation decreases connectivity, causes green space loss and impacts upon the ecology and function of green space. Restoration of the functionality of green space often requires restoring the ecological connectivity of this green space within the city matrix. However, identifying ecological corridors that integrate different structural and functional connectivity of green space remains vague. Assessing connectivity for developing an ecological network by using efficient models is essential to improve these networks under rapid urban expansion. This paper presents a novel methodological approach to assess and model connectivity for the Eurasian tree sparrow ( Passer montanus ) and Yellow-vented bulbul ( Pycnonotus goiavier ) in three cities (Kuala Lumpur, Malaysia; Jakarta, Indonesia and Metro Manila, Philippines). The approach identifies potential priority corridors for ecological connectivity networks. The study combined circuit models, connectivity analysis and least-cost models to identify potential corridors by integrating structure and function of green space patches to provide reliable ecological connectivity network models in the cities. Relevant parameters such as landscape resistance and green space structure (vegetation density, patch size and patch distance) were derived from an expert and literature-based approach based on the preference of bird behaviour. The integrated models allowed the assessment of connectivity for both species using different measures of green space structure revealing the potential corridors and least-cost pathways for both bird species at the patch sites. The implementation of improvements to the identified corridors could increase the connectivity of green space. This study provides examples of how combining models can contribute to the improvement of ecological networks in rapidly expanding cities and demonstrates the usefulness of such models for biodiversity conservation and urban planning.

No Association between Cortical Gyrification or Intrinsic Curvature and Attention-deficit/Hyperactivity Disorder in Adolescents and Young Adults.

PubMed

Forde, Natalie J; Ronan, Lisa; Zwiers, Marcel P; Alexander-Bloch, Aaron F; Faraone, Stephen V; Oosterlaan, Jaap; Heslenfeld, Dirk J; Hartman, Catharina A; Buitelaar, Jan K; Hoekstra, Pieter J

2017-01-01

Magnetic resonance imaging (MRI) studies have highlighted subcortical, cortical, and structural connectivity abnormalities associated with attention-deficit/hyperactivity disorder (ADHD). Gyrification investigations of the cortex have been inconsistent and largely negative, potentially due to a lack of sensitivity of the previously used morphological parameters. The innovative approach of applying intrinsic curvature analysis, which is predictive of gyrification pattern, to the cortical surface applied herein allowed us greater sensitivity to determine whether the structural connectivity abnormalities thus far identified at a centimeter scale also occur at a millimeter scale within the cortical surface. This could help identify neurodevelopmental processes that contribute to ADHD. Structural MRI datasets from the NeuroIMAGE project were used [ n = 306 ADHD, n = 164 controls, and n = 148 healthy siblings of individuals with ADHD (age in years, mean(sd); 17.2 (3.4), 16.8 (3.2), and 17.7 (3.8), respectively)]. Reconstructions of the cortical surfaces were computed with FreeSurfer. Intrinsic curvature (taken as a marker of millimeter-scale surface connectivity) and local gyrification index were calculated for each point on the surface (vertex) with Caret and FreeSurfer, respectively. Intrinsic curvature skew and mean local gyrification index were extracted per region; frontal, parietal, temporal, occipital, cingulate, and insula. A generalized additive model was used to compare the trajectory of these measures between groups over age, with sex, scanner site, total surface area of hemisphere, and familiality accounted for. After correcting for sex, scanner site, and total surface area no group differences were found in the developmental trajectory of intrinsic curvature or local gyrification index. Despite the increased sensitivity of intrinsic curvature, compared to gyrification measures, to subtle morphological abnormalities of the cortical surface we found no milimeter-scale connectivity abnormalities associated with ADHD.

Resting-state theta band connectivity and graph analysis in generalized social anxiety disorder.

PubMed

Xing, Mengqi; Tadayonnejad, Reza; MacNamara, Annmarie; Ajilore, Olusola; DiGangi, Julia; Phan, K Luan; Leow, Alex; Klumpp, Heide

2017-01-01

Functional magnetic resonance imaging (fMRI) resting-state studies show generalized social anxiety disorder (gSAD) is associated with disturbances in networks involved in emotion regulation, emotion processing, and perceptual functions, suggesting a network framework is integral to elucidating the pathophysiology of gSAD. However, fMRI does not measure the fast dynamic interconnections of functional networks. Therefore, we examined whole-brain functional connectomics with electroencephalogram (EEG) during resting-state. Resting-state EEG data was recorded for 32 patients with gSAD and 32 demographically-matched healthy controls (HC). Sensor-level connectivity analysis was applied on EEG data by using Weighted Phase Lag Index (WPLI) and graph analysis based on WPLI was used to determine clustering coefficient and characteristic path length to estimate local integration and global segregation of networks. WPLI results showed increased oscillatory midline coherence in the theta frequency band indicating higher connectivity in the gSAD relative to HC group during rest. Additionally, WPLI values positively correlated with state anxiety levels within the gSAD group but not the HC group. Our graph theory based connectomics analysis demonstrated increased clustering coefficient and decreased characteristic path length in theta-based whole brain functional organization in subjects with gSAD compared to HC. Theta-dependent interconnectivity was associated with state anxiety in gSAD and an increase in information processing efficiency in gSAD (compared to controls). Results may represent enhanced baseline self-focused attention, which is consistent with cognitive models of gSAD and fMRI studies implicating emotion dysregulation and disturbances in task negative networks (e.g., default mode network) in gSAD.

Connectivity inference from neural recording data: Challenges, mathematical bases and research directions.

PubMed

Magrans de Abril, Ildefons; Yoshimoto, Junichiro; Doya, Kenji

2018-06-01

This article presents a review of computational methods for connectivity inference from neural activity data derived from multi-electrode recordings or fluorescence imaging. We first identify biophysical and technical challenges in connectivity inference along the data processing pipeline. We then review connectivity inference methods based on two major mathematical foundations, namely, descriptive model-free approaches and generative model-based approaches. We investigate representative studies in both categories and clarify which challenges have been addressed by which method. We further identify critical open issues and possible research directions. Copyright © 2018 The Author(s). Published by Elsevier Ltd.. All rights reserved.

Quantitative analysis of multiple biokinetic models using a dynamic water phantom: A feasibility study

PubMed Central

Chiang, Fu-Tsai; Li, Pei-Jung; Chung, Shih-Ping; Pan, Lung-Fa; Pan, Lung-Kwang

2016-01-01

ABSTRACT This study analyzed multiple biokinetic models using a dynamic water phantom. The phantom was custom-made with acrylic materials to model metabolic mechanisms in the human body. It had 4 spherical chambers of different sizes, connected by 8 ditches to form a complex and adjustable water loop. One infusion and drain pole connected the chambers to an auxiliary silicon-based hose, respectively. The radio-active compound solution (TC-99m-MDP labeled) formed a sealed and static water loop inside the phantom. As clean feed water was infused to replace the original solution, the system mimicked metabolic mechanisms for data acquisition. Five cases with different water loop settings were tested and analyzed, with case settings changed by controlling valve poles located in the ditches. The phantom could also be changed from model A to model B by transferring its vertical configuration. The phantom was surveyed with a clinical gamma camera to determine the time-dependent intensity of every chamber. The recorded counts per pixel in each chamber were analyzed and normalized to compare with theoretical estimations from the MATLAB program. Every preset case was represented by uniquely defined, time-dependent, simultaneous differential equations, and a corresponding MATLAB program optimized the solutions by comparing theoretical calculations and practical measurements. A dimensionless agreement (AT) index was recommended to evaluate the comparison in each case. ATs varied from 5.6 to 48.7 over the 5 cases, indicating that this work presented an acceptable feasibility study. PMID:27286096

Algorithmic complexity of real financial markets

NASA Astrophysics Data System (ADS)

Mansilla, R.

2001-12-01

A new approach to the understanding of complex behavior of financial markets index using tools from thermodynamics and statistical physics is developed. Physical complexity, a quantity rooted in the Kolmogorov-Chaitin theory is applied to binary sequences built up from real time series of financial markets indexes. The study is based on NASDAQ and Mexican IPC data. Different behaviors of this quantity are shown when applied to the intervals of series placed before crashes and to intervals when no financial turbulence is observed. The connection between our results and the efficient market hypothesis is discussed.

Hydrodynamic modeling of hydrologic surface connectivity within a coastal river-floodplain system

NASA Astrophysics Data System (ADS)

Castillo, C. R.; Guneralp, I.

2017-12-01

Hydrologic surface connectivity (HSC) within river-floodplain environments is a useful indicator of the overall health of riparian habitats because it allows connections amongst components/landforms of the riverine landscape system to be quantified. Overbank flows have traditionally been the focus for analyses concerned with river-floodplain connectivity, but recent works have identified the large significance from sub-bankfull streamflows. Through the use of morphometric analysis and a digital elevation model that is relative to the river water surface, we previously determined that >50% of the floodplain for Mission River on the Coastal Bend of Texas becomes connected to the river at streamflows well-below bankfull conditions. Guided by streamflow records, field-based inundation data, and morphometric analysis; we develop a two-dimensional hydrodynamic model for lower portions of Mission River Floodplain system. This model not only allows us to analyze connections induced by surface water inundation, but also other aspects of the hydrologic connectivity concept such as exchanges of sediment and energy between the river and its floodplain. We also aggregate hydrodynamic model outputs to an object/landform level in order to analyze HSC and associated attributes using measures from graph/network theory. Combining physically-based hydrodynamic models with object-based and graph theoretical analyses allow river-floodplain connectivity to be quantified in a consistent manner with measures/indicators commonly used in landscape analysis. Analyzes similar to ours build towards the establishment of a formal framework for analyzing river-floodplain interaction that will ultimately serve to inform the management of riverine/floodplain environments.

Information Retrieval Using UMLS-based Structured Queries

PubMed Central

Fagan, Lawrence M.; Berrios, Daniel C.; Chan, Albert; Cucina, Russell; Datta, Anupam; Shah, Maulik; Surendran, Sujith

2001-01-01

During the last three years, we have developed and described components of ELBook, a semantically based information-retrieval system [1-4]. Using these components, domain experts can specify a query model, indexers can use the query model to index documents, and end-users can search these documents for instances of indexed queries.

Fragmentation alters stream fish community structure in dendritic ecological networks.

PubMed

Perkin, Joshuah S; Gido, Keith B

2012-12-01

Effects of fragmentation on the ecology of organisms occupying dendritic ecological networks (DENs) have recently been described through both conceptual and mathematical models, but few hypotheses have been tested in complex, real-world ecosystems. Stream fishes provide a model system for assessing effects of fragmentation on the structure of communities occurring within DENs, including how fragmentation alters metacommunity dynamics and biodiversity. A recently developed habitat-availability measure, the "dendritic connectivity index" (DCI), allows for assigning quantitative measures of connectivity in DENs regardless of network extent or complexity, and might be used to predict fish community response to fragmentation. We characterized stream fish community structure in 12 DENs in the Great Plains, USA, during periods of dynamic (summer) and muted (fall) discharge regimes to test the DCI as a predictive model of fish community response to fragmentation imposed by road crossings. Results indicated that fish communities in stream segments isolated by road crossings had reduced species richness (alpha diversity) relative to communities that maintained connectivity with the surrounding DEN during summer and fall. Furthermore, isolated communities had greater dissimilarity (beta diversity) to downstream sites notisolated by road crossings during summer and fall. Finally, dissimilarity among communities within DENs decreased as a function of increased habitat connectivity (measured using the DCI) for summer and fall, suggesting that communities within highly connected DENs tend to be more homogeneous. Our results indicate that the DCI is sensitive to community effects of fragmentation in riverscapes and might be used by managers to predict ecological responses to changes in habitat connectivity. Moreover, our findings illustrate that relating structural connectivity of riverscapes to functional connectivity among communities might aid in maintaining metacommunity dynamics and biodiversity in complex dendritic ecosystems.

Wetland Hydrologic Connectivity to Downstream Waters: A Classification Approach and National Assessment

NASA Astrophysics Data System (ADS)

Leibowitz, S. G.; Hill, R. A.; Weber, M.; Jones, C., Jr.; Rains, M. C.; Creed, I. F.; Christensen, J.

2017-12-01

Connectivity has become a major focus of hydrological and ecological studies. Connectivity enhances fluxes among landscape features, whereas isolation eliminates or reduces such flows. Thus connectivity can be an important characteristic controlling ecosystem services. Hydrologic connectivity is particularly significant, since chemical and biological flows are often associated with water movement. Wetlands have many important functions, and the degree to which they are hydrologically connected influences the effect they have on downstream waters. Wetlands with high connectivity can serve as sources (e.g., net exporters of dissolved organic carbon), while those with low connectivity can function as sinks (e.g., net importers of suspended sediments). We developed a system to classify wetlands based on type, magnitude, and frequency of hydrologic connectivity with downstream waters. We determined type (riparian, non-riparian surface, and non-riparian subsurface) by considering soil and bedrock permeability. For magnitude, we developed indices to represent travel time based on Manning's kinematic and Darcy's equations. We used soil drainage class as an indicator of frequency. We also included an index that assesses relative level of anthropogenic impacts to connectivity (e.g., presence of canals and ditches and impervious surfaces). The classification system was designed to be applied at various spatial scales using available data. The system was applied to 4.7 million wetlands in the conterminous United States, using the National Land Cover Dataset and other nationally available geospatial data, and the resulting maps were assessed for patterns in wetland connectivity. While wetland connectivity was dominated by fast, frequent riparian connections nationally, distributions of connectivity were characteristic for each region. Consideration of these distributions of connectivity should promote better management of watershed functions such as flood control and water quality improvement.

Planar polymer and glass graded index waveguides for data center applications

NASA Astrophysics Data System (ADS)

Pitwon, Richard; Yamauchi, Akira; Brusberg, Lars; Wang, Kai; Ishigure, Takaaki; Schröder, Henning; Neitz, Marcel; Worrall, Alex

2016-03-01

Embedded optical waveguide technology for optical printed circuit boards (OPCBs) has advanced considerably over the past decade both in terms of materials and achievable waveguide structures. Two distinct classes of planar graded index multimode waveguide have recently emerged based on polymer and glass materials. We report on the suitability of graded index polymer waveguides, fabricated using the Mosquito method, and graded index glass waveguides, fabricated using ion diffusion on thin glass foils, for deployment within future data center environments as part of an optically disaggregated architecture. To this end, we first characterize the wavelength dependent performance of different waveguide types to assess their suitability with respect to two dominant emerging multimode transceiver classes based on directly modulated 850 nm VCSELs and 1310 silicon photonics devices. Furthermore we connect the different waveguide types into an optically disaggregated data storage system and characterize their performance with respect to different common high speed data protocols used at the intra and inter rack level including 10 Gb Ethernet and Serial Attached SCSI.

Emergence of small-world structure in networks of spiking neurons through STDP plasticity.

PubMed

Basalyga, Gleb; Gleiser, Pablo M; Wennekers, Thomas

2011-01-01

In this work, we use a complex network approach to investigate how a neural network structure changes under synaptic plasticity. In particular, we consider a network of conductance-based, single-compartment integrate-and-fire excitatory and inhibitory neurons. Initially the neurons are connected randomly with uniformly distributed synaptic weights. The weights of excitatory connections can be strengthened or weakened during spiking activity by the mechanism known as spike-timing-dependent plasticity (STDP). We extract a binary directed connection matrix by thresholding the weights of the excitatory connections at every simulation step and calculate its major topological characteristics such as the network clustering coefficient, characteristic path length and small-world index. We numerically demonstrate that, under certain conditions, a nontrivial small-world structure can emerge from a random initial network subject to STDP learning.

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

Massaro, F.; D’Abrusco, R.

Using data from the Wide-field Infrared Survey Explorer ( WISE ) all-sky survey, we discovered that the nonthermal infrared (IR) emission of blazars, the largest known population of extragalactic γ -ray sources, has peculiar spectral properties. In this work, we confirm and strengthen our previous analyses using the latest available releases of both the WISE and the Fermi source catalogs. We also show that there is a tight correlation between the mid-IR colors and the γ -ray spectral index of Fermi blazars. We name this correlation the infrared– γ -ray connection. We discuss how this connection links both the emittedmore » powers and the spectral shapes of particles accelerated in jets arising from blazars over 10 decades in energy. Based on this evidence, we argue that the infrared– γ -ray connection is stronger than the well-known radio– γ -ray connection.« less

Effect of DEM resolution and comparison between different weighting factors for hydrologic connectivity index

NASA Astrophysics Data System (ADS)

Cantreul, Vincent; Cavalli, Marco; Degré, Aurore

2016-04-01

The emerging concept of hydrological connectivity is difficult to quantify. Some indices have been proposed. The most cited is Borselli's one. It mainly uses the DEM as input. The pixel size may strongly impacts the result of the calculation. It has not been studied yet in silty areas. Another important aspect is the choice of the weighting factor which strongly influences the index value. The objective of this poster is so to compare 8 different DEM's resolutions (12, 24, 48, 72, 96, 204, 504 and 996cm) and 3 different weighting factors (factor C of Wischmeier, Manning's factor and rugosity index) in the Borselli's index calculation. The IC was calculated in a 124ha catchment (Hevillers), in the loess belt, in Belgium. The DEM used is coming from a UAV with a maximum resolution of 12 cm. Permanent covered surfaces are not considered in order to avoid artefact due to the vegetation (2% of the surface). Regarding the DEM pixel size, the IC increases for a given pixel when the pixel size decreases. That confirms some results observed in the Alpine region by Cavalli (2014). The mean difference between 12 cm and 10 m resolution is 35% with higher values up to 100% for higher connectivity zones (flow paths). Another result is the lower impact of connections in the watershed (grass strips…) at lower pixel sizes. This is linked to the small width of some connections which are sometimes comparing to cell size. Furthermore, a great loss of precision is observed from the 500 cm pixel size and upper. That remark is quite intuitive. Finally, some very well disconnected zones appear for the highest resolutions. Regarding the weighting factor, IC values calculated using C factor are lower than with the rugosity index which is only a topographic factor. With very high resolution DEM, it permits to represent the fine topography. For the C factor, the zones up to very well disconnected areas (grass strips, wood…) are well represented with lower index values than downstream zones. On the contrary, areas up to very well connected zones (roads, paths…) are higher and much more connected than downstream areas. For the Manning's factor, the values are very low and not very well contrasted. This factor is not enough discriminant for this study. In conclusion, high resolution DEM (1 meter or higher) is needed for the IC calculation (precison, impact of connections…). Very high resolution permits to identify very well disconnected areas but it multiplies the calculation time. For the weighting factor, rugosity index and C factor have each some advantages. It is planned to test other approaches for the IC calculation. Key-words: hydrological connectivity index, DEM, resolution, weighting factor, comparison

New model performance index for engineering design of control systems

NASA Technical Reports Server (NTRS)

1970-01-01

Performance index includes a model representing linear control-system design specifications. Based on a geometric criterion for approximation of the model by the actual system, the index can be interpreted directly in terms of the desired system response model without actually having the model's time response.

Model-based estimators of density and connectivity to inform conservation of spatially structured populations

USGS Publications Warehouse

Morin, Dana J.; Fuller, Angela K.; Royle, J. Andrew; Sutherland, Chris

2017-01-01

Conservation and management of spatially structured populations is challenging because solutions must consider where individuals are located, but also differential individual space use as a result of landscape heterogeneity. A recent extension of spatial capture–recapture (SCR) models, the ecological distance model, uses spatial encounter histories of individuals (e.g., a record of where individuals are detected across space, often sequenced over multiple sampling occasions), to estimate the relationship between space use and characteristics of a landscape, allowing simultaneous estimation of both local densities of individuals across space and connectivity at the scale of individual movement. We developed two model-based estimators derived from the SCR ecological distance model to quantify connectivity over a continuous surface: (1) potential connectivity—a metric of the connectivity of areas based on resistance to individual movement; and (2) density-weighted connectivity (DWC)—potential connectivity weighted by estimated density. Estimates of potential connectivity and DWC can provide spatial representations of areas that are most important for the conservation of threatened species, or management of abundant populations (i.e., areas with high density and landscape connectivity), and thus generate predictions that have great potential to inform conservation and management actions. We used a simulation study with a stationary trap design across a range of landscape resistance scenarios to evaluate how well our model estimates resistance, potential connectivity, and DWC. Correlation between true and estimated potential connectivity was high, and there was positive correlation and high spatial accuracy between estimated DWC and true DWC. We applied our approach to data collected from a population of black bears in New York, and found that forested areas represented low levels of resistance for black bears. We demonstrate that formal inference about measures of landscape connectivity can be achieved from standard methods of studying animal populations which yield individual encounter history data such as camera trapping. Resulting biological parameters including resistance, potential connectivity, and DWC estimate the spatial distribution and connectivity of the population within a statistical framework, and we outline applications to many possible conservation and management problems.

Stellar Population Properties of Ultracompact Dwarfs in M87: A Mass–Metallicity Correlation Connecting Low-metallicity Globular Clusters and Compact Ellipticals

NASA Astrophysics Data System (ADS)

Zhang, Hong-Xin; Puzia, Thomas H.; Peng, Eric W.; Liu, Chengze; Côté, Patrick; Ferrarese, Laura; Duc, Pierre-Alain; Eigenthaler, Paul; Lim, Sungsoon; Lançon, Ariane; Muñoz, Roberto P.; Roediger, Joel; Sánchez-Janssen, Ruben; Taylor, Matthew A.; Yu, Jincheng

2018-05-01

We derive stellar population parameters for a representative sample of ultracompact dwarfs (UCDs) and a large sample of massive globular clusters (GCs) with stellar masses ≳ 106 M ⊙ in the central galaxy M87 of the Virgo galaxy cluster, based on model fitting to the Lick-index measurements from both the literature and new observations. After necessary spectral stacking of the relatively faint objects in our initial sample of 40 UCDs and 118 GCs, we obtain 30 sets of Lick-index measurements for UCDs and 80 for GCs. The M87 UCDs have ages ≳ 8 Gyr and [α/Fe] ≃ 0.4 dex, in agreement with previous studies based on smaller samples. The literature UCDs, located in lower-density environments than M87, extend to younger ages and smaller [α/Fe] (at given metallicities) than M87 UCDs, resembling the environmental dependence of the stellar nuclei of dwarf elliptical galaxies (dEs) in the Virgo cluster. The UCDs exhibit a positive mass–metallicity relation (MZR), which flattens and connects compact ellipticals at stellar masses ≳ 108 M ⊙. The Virgo dE nuclei largely follow the average MZR of UCDs, whereas most of the M87 GCs are offset toward higher metallicities for given stellar masses. The difference between the mass–metallicity distributions of UCDs and GCs may be qualitatively understood as a result of their different physical sizes at birth in a self-enrichment scenario or of galactic nuclear cluster star formation efficiency being relatively low in a tidal stripping scenario for UCD formation. The existing observations provide the necessary but not sufficient evidence for tidally stripped dE nuclei being the dominant contributors to the M87 UCDs.

From Points to Patterns - Functional Relations between Groundwater Connectivity and Catchment-scale Streamflow Response

NASA Astrophysics Data System (ADS)

Rinderer, M.; McGlynn, B. L.; van Meerveld, I. H. J.

2016-12-01

Groundwater measurements can help us to improve our understanding of runoff generation at the catchment-scale but typically only provide point-scale data. These measurements, therefore, need to be interpolated or upscaled in order to obtain information about catchment scale groundwater dynamics. Our approach used data from 51 spatially distributed groundwater monitoring sites in a Swiss pre-alpine catchment and time series clustering to define six groundwater response clusters. Each of the clusters was characterized by distinctly different site characteristics (i.e., Topographic Wetness Index and curvature), which allowed us to assign all unmonitored locations to one of these clusters. Time series modeling and the definition of response thresholds (i.e., the depth of more transmissive soil layers) allowed us to derive maps of the spatial distribution of active (i.e., responding) locations across the catchment at 15 min time intervals. Connectivity between all active locations and the stream network was determined using a graph theory approach. The extent of the active and connected areas differed during events and suggests that not all active locations directly contributed to streamflow. Gate keeper sites prevented connectivity of upslope locations to the channel network. Streamflow dynamics at the catchment outlet were correlated to catchment average connectivity dynamics. In a sensitivity analysis we tested six different groundwater levels for a site to be considered "active", which showed that the definition of the threshold did not significantly influence the conclusions drawn from our analysis. This study is the first one to derive patterns of groundwater dynamics based on empirical data (rather than interpolation) and provides insight into the spatio-temporal evolution of the active and connected runoff source areas at the catchment-scale that is critical to understanding the dynamics of water quantity and quality in streams.

Safety pilot model deployment : lessons learned and recommendations for future connected vehicle activities.

DOT National Transportation Integrated Search

2015-09-01

The Connected Vehicle Safety Pilot was a research program that demonstrated the readiness of DSRC-based connected vehicle safety applications for nationwide deployment. The vision of the Connected Vehicle Safety Pilot Program was to test connected ve...

Research on potential user identification model for electric energy substitution

NASA Astrophysics Data System (ADS)

Xia, Huaijian; Chen, Meiling; Lin, Haiying; Yang, Shuo; Miao, Bo; Zhu, Xinzhi

2018-01-01

The implementation of energy substitution plays an important role in promoting the development of energy conservation and emission reduction in china. Energy service management platform of alternative energy users based on the data in the enterprise production value, product output, coal and other energy consumption as a potential evaluation index, using principal component analysis model to simplify the formation of characteristic index, comprehensive index contains the original variables, and using fuzzy clustering model for the same industry user’s flexible classification. The comprehensive index number and user clustering classification based on constructed particle optimization neural network classification model based on the user, user can replace electric potential prediction. The results of an example show that the model can effectively predict the potential of users’ energy potential.

Support vector methods for survival analysis: a comparison between ranking and regression approaches.

PubMed

Van Belle, Vanya; Pelckmans, Kristiaan; Van Huffel, Sabine; Suykens, Johan A K

2011-10-01

To compare and evaluate ranking, regression and combined machine learning approaches for the analysis of survival data. The literature describes two approaches based on support vector machines to deal with censored observations. In the first approach the key idea is to rephrase the task as a ranking problem via the concordance index, a problem which can be solved efficiently in a context of structural risk minimization and convex optimization techniques. In a second approach, one uses a regression approach, dealing with censoring by means of inequality constraints. The goal of this paper is then twofold: (i) introducing a new model combining the ranking and regression strategy, which retains the link with existing survival models such as the proportional hazards model via transformation models; and (ii) comparison of the three techniques on 6 clinical and 3 high-dimensional datasets and discussing the relevance of these techniques over classical approaches fur survival data. We compare svm-based survival models based on ranking constraints, based on regression constraints and models based on both ranking and regression constraints. The performance of the models is compared by means of three different measures: (i) the concordance index, measuring the model's discriminating ability; (ii) the logrank test statistic, indicating whether patients with a prognostic index lower than the median prognostic index have a significant different survival than patients with a prognostic index higher than the median; and (iii) the hazard ratio after normalization to restrict the prognostic index between 0 and 1. Our results indicate a significantly better performance for models including regression constraints above models only based on ranking constraints. This work gives empirical evidence that svm-based models using regression constraints perform significantly better than svm-based models based on ranking constraints. Our experiments show a comparable performance for methods including only regression or both regression and ranking constraints on clinical data. On high dimensional data, the former model performs better. However, this approach does not have a theoretical link with standard statistical models for survival data. This link can be made by means of transformation models when ranking constraints are included. Copyright © 2011 Elsevier B.V. All rights reserved.

The Influence of Life History Variability on Population Connectivity: Development and Application of a Trait-Based Biophysical Model of Individuals

NASA Astrophysics Data System (ADS)

Wong-Ala, J.; Neuheimer, A. B.; Hixon, M.; Powell, B.

2016-02-01

Connectivity estimates, which measure the exchange of individuals among populations, are necessary to create effective reserves for marine life. Connectivity can be influenced by a combination of biology (e.g. spawning time) and physics (e.g. currents). In the past a dispersal model was created in an effort to explain connectivity for the highly sought after reef fish Lau`ipala (Yellow Tang, Zebrasoma flavescens) around Hawai`i Island using physics alone, but this was shown to be insufficient. Here we created an individual based model (IBM) to describe Lau`ipala life history and behavior forced with ocean currents and temperature (via coupling to a physical model) to examine biophysical interactions. The IBM allows for tracking of individual fish from spawning to settlement, and individual variability in modeled processes. We first examined the influence of different reproductive (e.g. batch vs. constant spawners), developmental (e.g. pelagic larval duration), and behavioral (e.g. active vs. passive buoyancy control) traits on modeled connectivity estimates for larval reef fish around Hawai`i Island and compared results to genetic observations of parent-offspring pair distribution. Our model is trait-based which allows individuals to vary in life history strategies enabling mechanistic links between predictions and underlying traits and straightforward applications to other species and sites.

Micromechanical modeling of rate-dependent behavior of Connective tissues.

PubMed

Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

2017-03-07

In this paper, a constitutive and micromechanical model for prediction of rate-dependent behavior of connective tissues (CTs) is presented. Connective tissues are considered as nonlinear viscoelastic material. The rate-dependent behavior of CTs is incorporated into model using the well-known quasi-linear viscoelasticity (QLV) theory. A planar wavy representative volume element (RVE) is considered based on the tissue microstructure histological evidences. The presented model parameters are identified based on the available experiments in the literature. The presented constitutive model introduced to ABAQUS by means of UMAT subroutine. Results show that, monotonic uniaxial test predictions of the presented model at different strain rates for rat tail tendon (RTT) and human patellar tendon (HPT) are in good agreement with experimental data. Results of incremental stress-relaxation test are also presented to investigate both instantaneous and viscoelastic behavior of connective tissues. Copyright © 2017 Elsevier Ltd. All rights reserved.

Human Pose Estimation from Monocular Images: A Comprehensive Survey

PubMed Central

Gong, Wenjuan; Zhang, Xuena; Gonzàlez, Jordi; Sobral, Andrews; Bouwmans, Thierry; Tu, Changhe; Zahzah, El-hadi

2016-01-01

Human pose estimation refers to the estimation of the location of body parts and how they are connected in an image. Human pose estimation from monocular images has wide applications (e.g., image indexing). Several surveys on human pose estimation can be found in the literature, but they focus on a certain category; for example, model-based approaches or human motion analysis, etc. As far as we know, an overall review of this problem domain has yet to be provided. Furthermore, recent advancements based on deep learning have brought novel algorithms for this problem. In this paper, a comprehensive survey of human pose estimation from monocular images is carried out including milestone works and recent advancements. Based on one standard pipeline for the solution of computer vision problems, this survey splits the problem into several modules: feature extraction and description, human body models, and modeling methods. Problem modeling methods are approached based on two means of categorization in this survey. One way to categorize includes top-down and bottom-up methods, and another way includes generative and discriminative methods. Considering the fact that one direct application of human pose estimation is to provide initialization for automatic video surveillance, there are additional sections for motion-related methods in all modules: motion features, motion models, and motion-based methods. Finally, the paper also collects 26 publicly available data sets for validation and provides error measurement methods that are frequently used. PMID:27898003

Geospace environment modeling 2008--2009 challenge: Dst index

USGS Publications Warehouse

Rastätter, L.; Kuznetsova, M.M.; Glocer, A.; Welling, D.; Meng, X.; Raeder, J.; Wittberger, M.; Jordanova, V.K.; Yu, Y.; Zaharia, S.; Weigel, R.S.; Sazykin, S.; Boynton, R.; Wei, H.; Eccles, V.; Horton, W.; Mays, M.L.; Gannon, J.

2013-01-01

This paper reports the metrics-based results of the Dst index part of the 2008–2009 GEM Metrics Challenge. The 2008–2009 GEM Metrics Challenge asked modelers to submit results for four geomagnetic storm events and five different types of observations that can be modeled by statistical, climatological or physics-based models of the magnetosphere-ionosphere system. We present the results of 30 model settings that were run at the Community Coordinated Modeling Center and at the institutions of various modelers for these events. To measure the performance of each of the models against the observations, we use comparisons of 1 hour averaged model data with the Dst index issued by the World Data Center for Geomagnetism, Kyoto, Japan, and direct comparison of 1 minute model data with the 1 minute Dst index calculated by the United States Geological Survey. The latter index can be used to calculate spectral variability of model outputs in comparison to the index. We find that model rankings vary widely by skill score used. None of the models consistently perform best for all events. We find that empirical models perform well in general. Magnetohydrodynamics-based models of the global magnetosphere with inner magnetosphere physics (ring current model) included and stand-alone ring current models with properly defined boundary conditions perform well and are able to match or surpass results from empirical models. Unlike in similar studies, the statistical models used in this study found their challenge in the weakest events rather than the strongest events.

Quantification of the impact of a confounding variable on functional connectivity confirms anti-correlated networks in the resting-state.

PubMed

Carbonell, F; Bellec, P; Shmuel, A

2014-02-01

The effect of regressing out the global average signal (GAS) in resting state fMRI data has become a concern for interpreting functional connectivity analyses. It is not clear whether the reported anti-correlations between the Default Mode and the Dorsal Attention Networks are intrinsic to the brain, or are artificially created by regressing out the GAS. Here we introduce a concept, Impact of the Global Average on Functional Connectivity (IGAFC), for quantifying the sensitivity of seed-based correlation analyses to the regression of the GAS. This voxel-wise IGAFC index is defined as the product of two correlation coefficients: the correlation between the GAS and the fMRI time course of a voxel, times the correlation between the GAS and the seed time course. This definition enables the calculation of a threshold at which the impact of regressing-out the GAS would be large enough to introduce spurious negative correlations. It also yields a post-hoc impact correction procedure via thresholding, which eliminates spurious correlations introduced by regressing out the GAS. In addition, we introduce an Artificial Negative Correlation Index (ANCI), defined as the absolute difference between the IGAFC index and the impact threshold. The ANCI allows a graded confidence scale for ranking voxels according to their likelihood of showing artificial correlations. By applying this method, we observed regions in the Default Mode and Dorsal Attention Networks that were anti-correlated. These findings confirm that the previously reported negative correlations between the Dorsal Attention and Default Mode Networks are intrinsic to the brain and not the result of statistical manipulations. Our proposed quantification of the impact that a confound may have on functional connectivity can be generalized to global effect estimators other than the GAS. It can be readily applied to other confounds, such as systemic physiological or head movement interferences, in order to quantify their impact on functional connectivity in the resting state. © 2013.

Agent-based model for the h-index - exact solution

NASA Astrophysics Data System (ADS)

Żogała-Siudem, Barbara; Siudem, Grzegorz; Cena, Anna; Gagolewski, Marek

2016-01-01

Hirsch's h-index is perhaps the most popular citation-based measure of scientific excellence. In 2013, Ionescu and Chopard proposed an agent-based model describing a process for generating publications and citations in an abstract scientific community [G. Ionescu, B. Chopard, Eur. Phys. J. B 86, 426 (2013)]. Within such a framework, one may simulate a scientist's activity, and - by extension - investigate the whole community of researchers. Even though the Ionescu and Chopard model predicts the h-index quite well, the authors provided a solution based solely on simulations. In this paper, we complete their results with exact, analytic formulas. What is more, by considering a simplified version of the Ionescu-Chopard model, we obtained a compact, easy to compute formula for the h-index. The derived approximate and exact solutions are investigated on a simulated and real-world data sets.

Refractive index sensor based on lateral-offset of coreless silica interferometer

NASA Astrophysics Data System (ADS)

Baharin, Nur Faizzah; Azmi, Asrul Izam; Abdullah, Ahmad Sharmi; Mohd Noor, Muhammad Yusof

2018-02-01

A compact, cost-effective and high sensitivity fiber interferometer refractive index (RI) sensor based on symmetrical offset coreless silica fiber (CSF) configuration is proposed, optimized and demonstrated. The sensor is formed by splicing a section of CSF between two CSF sections in an offset manner. Thus, two distinct optical paths are created with large index difference, the first path through the connecting CSF sections and the second path is outside the CSF through the surrounding media. RI sensing is established from direct interaction of light with surrounding media, hence high sensitivity can be achieved with a relatively compact sensor length. In the experimental work, a 1.5 mm sensor demonstrates RI sensitivity of 750 nm/RIU for RI range between 1.33 and 1.345. With the main attributes of high sensitivity and compact size, the proposed sensor can be further developed for related applications including blood diagnosis, water quality control and food industries.

48 CFR 1252.211-70 - Index for specifications.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 5 2010-10-01 2010-10-01 false Index for specifications... Index for specifications. As prescribed in (TAR) 48 CFR 1211.204-70, insert the following clause: Index for Specifications (APR 2005) If an index or table of contents is furnished in connection with...

Granger causal time-dependent source connectivity in the somatosensory network

NASA Astrophysics Data System (ADS)

Gao, Lin; Sommerlade, Linda; Coffman, Brian; Zhang, Tongsheng; Stephen, Julia M.; Li, Dichen; Wang, Jue; Grebogi, Celso; Schelter, Bjoern

2015-05-01

Exploration of transient Granger causal interactions in neural sources of electrophysiological activities provides deeper insights into brain information processing mechanisms. However, the underlying neural patterns are confounded by time-dependent dynamics, non-stationarity and observational noise contamination. Here we investigate transient Granger causal interactions using source time-series of somatosensory evoked magnetoencephalographic (MEG) elicited by air puff stimulation of right index finger and recorded using 306-channel MEG from 21 healthy subjects. A new time-varying connectivity approach, combining renormalised partial directed coherence with state space modelling, is employed to estimate fast changing information flow among the sources. Source analysis confirmed that somatosensory evoked MEG was mainly generated from the contralateral primary somatosensory cortex (SI) and bilateral secondary somatosensory cortices (SII). Transient Granger causality shows a serial processing of somatosensory information, 1) from contralateral SI to contralateral SII, 2) from contralateral SI to ipsilateral SII, 3) from contralateral SII to contralateral SI, and 4) from contralateral SII to ipsilateral SII. These results are consistent with established anatomical connectivity between somatosensory regions and previous source modeling results, thereby providing empirical validation of the time-varying connectivity analysis. We argue that the suggested approach provides novel information regarding transient cortical dynamic connectivity, which previous approaches could not assess.

Experimental characterization of powered Fontan hemodynamics in an idealized total cavopulmonary connection model

NASA Astrophysics Data System (ADS)

Kerlo, Anna-Elodie M.; Delorme, Yann T.; Xu, Duo; Frankel, Steven H.; Giridharan, Guruprasad A.; Rodefeld, Mark D.; Chen, Jun

2013-08-01

A viscous impeller pump (VIP) based on the Von Karman viscous pump is specifically designed to provide cavopulmonary assist in a univentricular Fontan circulation. The technology will make it possible to biventricularize the univentricular Fontan circulation. Ideally, it will reduce the number of surgeries required for Fontan conversion from three to one early in life, while simultaneously improving physiological conditions. Later in life, it will provide a currently unavailable means of chronic support for adolescent and adult patients with failing Fontan circulations. Computational fluid dynamics simulations demonstrate that the VIP can satisfactorily augment cavopulmonary blood flow in an idealized total cavopulmonary connection (TCPC). When the VIP is deployed at the TCPC intersection as a static device, it stabilizes the four-way flow pattern and is not obstructive to the flow. Experimental studies are carried out to assess performance, hemodynamic characteristics, and flow structures of the VIP in an idealized TCPC model. Stereoscopic particle image velocimetry is applied using index-matched blood analog. Results show excellent performance of the VIP without cavitation and with reduction of the energy losses. The non-rotating VIP smoothes and accelerates flow, and decreases stresses and turbulence in the TCPC. The rotating VIP generates the desired low-pressure Fontan flow augmentation (0-10 mmHg) while maintaining acceptable stress thresholds.

Fast and efficient indexing approach for object recognition

NASA Astrophysics Data System (ADS)

Hefnawy, Alaa; Mashali, Samia A.; Rashwan, Mohsen; Fikri, Magdi

1999-08-01

This paper introduces a fast and efficient indexing approach for both 2D and 3D model-based object recognition in the presence of rotation, translation, and scale variations of objects. The indexing entries are computed after preprocessing the data by Haar wavelet decomposition. The scheme is based on a unified image feature detection approach based on Zernike moments. A set of low level features, e.g. high precision edges, gray level corners, are estimated by a set of orthogonal Zernike moments, calculated locally around every image point. A high dimensional, highly descriptive indexing entries are then calculated based on the correlation of these local features and employed for fast access to the model database to generate hypotheses. A list of the most candidate models is then presented by evaluating the hypotheses. Experimental results are included to demonstrate the effectiveness of the proposed indexing approach.

Retrieving hydrological connectivity from empirical causality in karst systems

NASA Astrophysics Data System (ADS)

Delforge, Damien; Vanclooster, Marnik; Van Camp, Michel; Poulain, Amaël; Watlet, Arnaud; Hallet, Vincent; Kaufmann, Olivier; Francis, Olivier

2017-04-01

Because of their complexity, karst systems exhibit nonlinear dynamics. Moreover, if one attempts to model a karst, the hidden behavior complicates the choice of the most suitable model. Therefore, both intense investigation methods and nonlinear data analysis are needed to reveal the underlying hydrological connectivity as a prior for a consistent physically based modelling approach. Convergent Cross Mapping (CCM), a recent method, promises to identify causal relationships between time series belonging to the same dynamical systems. The method is based on phase space reconstruction and is suitable for nonlinear dynamics. As an empirical causation detection method, it could be used to highlight the hidden complexity of a karst system by revealing its inner hydrological and dynamical connectivity. Hence, if one can link causal relationships to physical processes, the method should show great potential to support physically based model structure selection. We present the results of numerical experiments using karst model blocks combined in different structures to generate time series from actual rainfall series. CCM is applied between the time series to investigate if the empirical causation detection is consistent with the hydrological connectivity suggested by the karst model.

Dimensional Model for Estimating Factors influencing Childhood Obesity: Path Analysis Based Modeling

PubMed Central

Kheirollahpour, Maryam; Shohaimi, Shamarina

2014-01-01

The main objective of this study is to identify and develop a comprehensive model which estimates and evaluates the overall relations among the factors that lead to weight gain in children by using structural equation modeling. The proposed models in this study explore the connection among the socioeconomic status of the family, parental feeding practice, and physical activity. Six structural models were tested to identify the direct and indirect relationship between the socioeconomic status and parental feeding practice general level of physical activity, and weight status of children. Finally, a comprehensive model was devised to show how these factors relate to each other as well as to the body mass index (BMI) of the children simultaneously. Concerning the methodology of the current study, confirmatory factor analysis (CFA) was applied to reveal the hidden (secondary) effect of socioeconomic factors on feeding practice and ultimately on the weight status of the children and also to determine the degree of model fit. The comprehensive structural model tested in this study suggested that there are significant direct and indirect relationships among variables of interest. Moreover, the results suggest that parental feeding practice and physical activity are mediators in the structural model. PMID:25097878

[Delineation of ecological security pattern based on ecological network].

PubMed

Fu, Qiang; Gu, Chao Lin

2017-03-18

Ecological network can be used to describe and assess the relationship between spatial organization of landscapes and species survival under the condition of the habitat fragmentation. Taking Qingdao City as the research area, woodland and wetland ecological networks in 2005 were simulated based on least cost path method, and the ecological networks were classified by their corridors' cumulative cost value. We made importance distinction of ecological network structure elements such as patches and corridors using betweenness centrality index and correlation length-percentage of importance of omitted patches index, and then created the structure system of ecological network. Considering the effects brought by the newly-added construction land from 2005 to 2013, we proposed the ecological security pattern for construction land change of Qingdao City. The results showed that based on ecological network framework, graph theory based methods could be used to quantify both attributes of specific ecological land (e.g., the area of an ecological network patch) and functional connection between ecological lands. Between 2005 and 2013, large area of wetlands had been destroyed by newly-added construction land, while the role of specific woodland and wetland played in the connection of the whole network had not been considered. The delineation of ecological security pattern based on ecological network could optimize regional ecological basis, provide accurate spatial explicit decision for ecological conservation and restoration, and meanwhile provide scientific and reasonable space guidance for urban spatial expansion.

Connecting Formal and Content Schemata: Some Results of Recent Work in Semiotics.

ERIC Educational Resources Information Center

Oller, John W., Jr.

This paper expands on schematic theory through a review of recent work in the field of semiotics. Content and formal schemata are shown to be grounded respectively in perceptual (abductive) and indexical (inductive) strategies of inference. A third kind of schemata is based on deductive generalization and referred to as abstract schemata. All…

A copula-multifractal volatility hedging model for CSI 300 index futures

NASA Astrophysics Data System (ADS)

Wei, Yu; Wang, Yudong; Huang, Dengshi

2011-11-01

In this paper, we propose a new hedging model combining the newly introduced multifractal volatility (MFV) model and the dynamic copula functions. Using high-frequency intraday quotes of the spot Shanghai Stock Exchange Composite Index (SSEC), spot China Securities Index 300 (CSI 300), and CSI 300 index futures, we compare the direct and cross hedging effectiveness of the copula-MFV model with several popular copula-GARCH models. The main empirical results show that the proposed copula-MFV model obtains better hedging effectiveness than the copula-GARCH-type models in general. Furthermore, the hedge operating strategy based MFV hedging model involves fewer transaction costs than those based on the GARCH-type models. The finding of this paper indicates that multifractal analysis may offer a new way of quantitative hedging model design using financial futures.

QSAR modeling based on structure-information for properties of interest in human health.

PubMed

Hall, L H; Hall, L M

2005-01-01

The development of QSAR models based on topological structure description is presented for problems in human health. These models are based on the structure-information approach to quantitative biological modeling and prediction, in contrast to the mechanism-based approach. The structure-information approach is outlined, starting with basic structure information developed from the chemical graph (connection table). Information explicit in the connection table (element identity and skeletal connections) leads to significant (implicit) structure information that is useful for establishing sound models of a wide range of properties of interest in drug design. Valence state definition leads to relationships for valence state electronegativity and atom/group molar volume. Based on these important aspects of molecules, together with skeletal branching patterns, both the electrotopological state (E-state) and molecular connectivity (chi indices) structure descriptors are developed and described. A summary of four QSAR models indicates the wide range of applicability of these structure descriptors and the predictive quality of QSAR models based on them: aqueous solubility (5535 chemically diverse compounds, 938 in external validation), percent oral absorption (%OA, 417 therapeutic drugs, 195 drugs in external validation testing), AMES mutagenicity (2963 compounds including 290 therapeutic drugs, 400 in external validation), fish toxicity (92 substituted phenols, anilines and substituted aromatics). These models are established independent of explicit three-dimensional (3-D) structure information and are directly interpretable in terms of the implicit structure information useful to the drug design process.

The Oceanic Contribution to Atlantic Multi-Decadal Variability

NASA Astrophysics Data System (ADS)

Wills, R. C.; Armour, K.; Battisti, D. S.; Hartmann, D. L.

2017-12-01

Atlantic multi-decadal variability (AMV) is typically associated with variability in ocean heat transport (OHT) by the Atlantic Meridional Overturning Circulation (AMOC). However, recent work has cast doubt on this connection by showing that slab-ocean climate models, in which OHT cannot vary, exhibit similar variability. Here, we apply low-frequency component analysis to isolate the variability of Atlantic sea-surface temperatures (SSTs) that occurs on decadal and longer time scales. In observations and in pre-industrial control simulations of comprehensive climate models, we find that AMV is confined to the extratropics, with the strongest temperature anomalies in the North Atlantic subpolar gyre. We show that warm subpolar temperatures are associated with a strengthened AMOC, increased poleward OHT, and local heat fluxes from the ocean into the atmosphere. In contrast, the traditional index of AMV based on the basin-averaged SST anomaly shows warm temperatures preceded by heat fluxes from the atmosphere into the ocean, consistent with the atmosphere driving this variability, and shows a weak relationship with AMOC. The autocorrelation time of the basin-averaged SST index is 1 year compared to an autocorrelation time of 5 years for the variability of subpolar temperatures. This shows that multi-decadal variability of Atlantic SSTs is sustained by OHT variability associated with AMOC, while atmosphere-driven SST variability, such as exists in slab-ocean models, contributes primarily on interannual time scales.

Uncertainty Model for Total Solar Irradiance Estimation on Australian Rooftops

NASA Astrophysics Data System (ADS)

Al-Saadi, Hassan; Zivanovic, Rastko; Al-Sarawi, Said

2017-11-01

The installations of solar panels on Australian rooftops have been in rise for the last few years, especially in the urban areas. This motivates academic researchers, distribution network operators and engineers to accurately address the level of uncertainty resulting from grid-connected solar panels. The main source of uncertainty is the intermittent nature of radiation, therefore, this paper presents a new model to estimate the total radiation incident on a tilted solar panel. Where a probability distribution factorizes clearness index, the model is driven upon clearness index with special attention being paid for Australia with the utilization of best-fit-correlation for diffuse fraction. The assessment of the model validity is achieved with the adoption of four goodness-of-fit techniques. In addition, the Quasi Monte Carlo and sparse grid methods are used as sampling and uncertainty computation tools, respectively. High resolution data resolution of solar irradiations for Adelaide city were used for this assessment, with an outcome indicating a satisfactory agreement between actual data variation and model.

Brain substrates of unhealthy versus healthy food choices: influence of homeostatic status and body mass index.

PubMed

Harding, I H; Andrews, Z B; Mata, F; Orlandea, S; Martínez-Zalacaín, I; Soriano-Mas, C; Stice, E; Verdejo-Garcia, A

2018-03-01

Unhealthy dietary choices are a major contributor to harmful weight gain and obesity. This study interrogated the brain substrates of unhealthy versus healthy food choices in vivo, and evaluated the influence of hunger state and body mass index (BMI) on brain activation and connectivity. Thirty adults (BMI: 18-38 kg m -2 ) performed a food-choice task involving preference-based selection between beverage pairs consisting of high-calorie (unhealthy) or low-calorie (healthy) options, concurrent with functional magnetic resonance imaging (fMRI). Selected food stimuli were delivered to participants using an MRI-compatible gustometer. fMRI scans were performed both after 10-h fasting and when sated. Brain activation and hypothalamic functional connectivity were assessed when selecting between unhealthy-healthy beverage pairings, relative to unhealthy-unhealthy and healthy-healthy options. Results were considered significant at cluster-based family-wise error corrected P<0.05. Selecting between unhealthy and healthy foods elicited significant activation in the hypothalamus, the medial and dorsolateral prefrontal cortices, the anterior insula and the posterior cingulate. Hunger was associated with higher activation within the ventromedial and dorsolateral prefrontal cortices, as well as lower connectivity between the hypothalamus and both the ventromedial prefrontal cortex and dorsal striatum. Critically, people with higher BMI showed lower activation of the hypothalamus-regardless of hunger state-and higher activation of the ventromedial prefrontal cortex when hungry. People who are overweight and obese have weaker activation of brain regions involved in energy regulation and greater activation of reward valuation regions while making choices between unhealthy and healthy foods. These results provide evidence for a shift towards hedonic-based, and away from energy-based, food selection in obesity.

Highly diverse, massive organic data as explored by a composite QSPR strategy: an advanced study of boiling point.

PubMed

Ivanova, A A; Ivanov, A A; Oliferenko, A A; Palyulin, V A; Zefirov, N S

2005-06-01

An improved strategy of quantitative structure-property relationship (QSPR) studies of diverse and inhomogeneous organic datasets has been proposed. A molecular connectivity term was successively corrected for different structural features encoded in fragmental descriptors. The so-called solvation index 1chis (a weighted Randic index) was used as a "leading" variable and standardized molecular fragments were employed as "corrective" class-specific variables. Performance of the new approach was illustrated by modelling a dataset of experimental normal boiling points of 833 organic compounds belonging to 20 structural classes. Firstly, separate QSPR models were derived for each class and for eight groups of structurally similar classes. Finally, a general model formed by combining all the classes together was derived (r2=0.957, s=12.9degreesC). The strategy outlined can find application in QSPR analyses of massive, highly diverse databases of organic compounds.

Comparison of self-written waveguide techniques and bulk index matching for low-loss polymer waveguide interconnects

NASA Astrophysics Data System (ADS)

Burrell, Derek; Middlebrook, Christopher

2016-03-01

Polymer waveguides (PWGs) are used within photonic interconnects as inexpensive and versatile substitutes for traditional optical fibers. The PWGs are typically aligned to silica-based optical fibers for coupling. An epoxide elastomer is then applied and cured at the interface for index matching and rigid attachment. Self-written waveguides (SWWs) are proposed as an alternative to further reduce connection insertion loss (IL) and alleviate marginal misalignment issues. Elastomer material is deposited after the initial alignment, and SWWs are formed by injecting ultraviolet (UV) light into the fiber or waveguide. The coupled UV light cures a channel between the two differing structures. A suitable cladding layer can be applied after development. Such factors as longitudinal gap distance, UV cure time, input power level, polymer material selection and choice of solvent affect the resulting SWWs. Experimental data are compared between purely index-matched samples and those with SWWs at the fiber-PWG interface. It is shown that < 1 dB IL per connection can be achieved by either method and results indicate lowest potential losses associated with a fine-tuned self-writing process. Successfully fabricated SWWs reduce overall processing time and enable an effectively continuous low-loss rigid interconnect.

Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression

PubMed Central

Posner, Jonathan; Cha, Jiook; Wang, Zhishun; Talati, Ardesheer; Warner, Virginia; Gerber, Andrew; Peterson, Bradley S; Weissman, Myrna

2016-01-01

Research into the pathophysiology of major depressive disorder (MDD) has focused largely on individuals already affected by MDD. Studies have thus been limited in their ability to disentangle effects that arise as a result of MDD from precursors of the disorder. By studying individuals at high familial risk for MDD, we aimed to identify potential biomarkers indexing risk for developing MDD, a critical step toward advancing prevention and early intervention. Using resting-state functional connectivity MRI (rs-fcMRI) and diffusion MRI (tractography), we examined connectivity within the default mode network (DMN) and between the DMN and the central executive network (CEN) in 111 individuals, aged 11–60 years, at high and low familial risk for depression. Study participants were part of a three-generation longitudinal, cohort study of familial depression. Based on rs-fcMRI, individuals at high vs low familial risk for depression showed increased DMN connectivity, as well as decreased DMN-CEN-negative connectivity. These findings remained significant after excluding individuals with a current or lifetime history of depression. Diffusion MRI measures based on tractography supported the findings of decreased DMN-CEN-negative connectivity. Path analyses indicated that decreased DMN-CEN-negative connectivity mediated a relationship between familial risk and a neuropsychological measure of impulsivity. Our findings suggest that DMN and DMN-CEN connectivity differ in those at high vs low risk for depression and thus suggest potential biomarkers for identifying individuals at risk for developing MDD. PMID:26593265

Increased Default Mode Network Connectivity in Individuals at High Familial Risk for Depression.

PubMed

Posner, Jonathan; Cha, Jiook; Wang, Zhishun; Talati, Ardesheer; Warner, Virginia; Gerber, Andrew; Peterson, Bradley S; Weissman, Myrna

2016-06-01

Research into the pathophysiology of major depressive disorder (MDD) has focused largely on individuals already affected by MDD. Studies have thus been limited in their ability to disentangle effects that arise as a result of MDD from precursors of the disorder. By studying individuals at high familial risk for MDD, we aimed to identify potential biomarkers indexing risk for developing MDD, a critical step toward advancing prevention and early intervention. Using resting-state functional connectivity MRI (rs-fcMRI) and diffusion MRI (tractography), we examined connectivity within the default mode network (DMN) and between the DMN and the central executive network (CEN) in 111 individuals, aged 11-60 years, at high and low familial risk for depression. Study participants were part of a three-generation longitudinal, cohort study of familial depression. Based on rs-fcMRI, individuals at high vs low familial risk for depression showed increased DMN connectivity, as well as decreased DMN-CEN-negative connectivity. These findings remained significant after excluding individuals with a current or lifetime history of depression. Diffusion MRI measures based on tractography supported the findings of decreased DMN-CEN-negative connectivity. Path analyses indicated that decreased DMN-CEN-negative connectivity mediated a relationship between familial risk and a neuropsychological measure of impulsivity. Our findings suggest that DMN and DMN-CEN connectivity differ in those at high vs low risk for depression and thus suggest potential biomarkers for identifying individuals at risk for developing MDD.

A Spatially-Registered, Massively Parallelised Data Structure for Interacting with Large, Integrated Geodatasets

NASA Astrophysics Data System (ADS)

Irving, D. H.; Rasheed, M.; O'Doherty, N.

2010-12-01

The efficient storage, retrieval and interactive use of subsurface data present great challenges in geodata management. Data volumes are typically massive, complex and poorly indexed with inadequate metadata. Derived geomodels and interpretations are often tightly bound in application-centric and proprietary formats; open standards for long-term stewardship are poorly developed. Consequently current data storage is a combination of: complex Logical Data Models (LDMs) based on file storage formats; 2D GIS tree-based indexing of spatial data; and translations of serialised memory-based storage techniques into disk-based storage. Whilst adequate for working at the mesoscale over a short timeframes, these approaches all possess technical and operational shortcomings: data model complexity; anisotropy of access; scalability to large and complex datasets; and weak implementation and integration of metadata. High performance hardware such as parallelised storage and Relational Database Management System (RDBMS) have long been exploited in many solutions but the underlying data structure must provide commensurate efficiencies to allow multi-user, multi-application and near-realtime data interaction. We present an open Spatially-Registered Data Structure (SRDS) built on Massively Parallel Processing (MPP) database architecture implemented by a ANSI SQL 2008 compliant RDBMS. We propose a LDM comprising a 3D Earth model that is decomposed such that each increasing Level of Detail (LoD) is achieved by recursively halving the bin size until it is less than the error in each spatial dimension for that data point. The value of an attribute at that point is stored as a property of that point and at that LoD. It is key to the numerical efficiency of the SRDS that it is under-pinned by a power-of-two relationship thus precluding the need for computationally intensive floating point arithmetic. Our approach employed a tightly clustered MPP array with small clusters of storage, processors and memory communicating over a high-speed network inter-connect. This is a shared-nothing architecture where resources are managed within each cluster unlike most other RDBMSs. Data are accessed on this architecture by their primary index values which utilises the hashing algorithm for point-to-point access. The hashing algorithm’s main role is the efficient distribution of data across the clusters based on the primary index. In this study we used 3D seismic volumes, 2D seismic profiles and borehole logs to demonstrate application in both (x,y,TWT) and (x,y,z)-space. In the SRDS the primary index is a composite column index of (x,y) to avoid invoking time-consuming full table scans as is the case in tree-based systems. This means that data access is isotropic. A query for data in a specified spatial range permits retrieval recursively by point-to-point queries within each nested LoD yielding true linear performance up to the Petabyte scale with hardware scaling presenting the primary limiting factor. Our architecture and LDM promotes: realtime interaction with massive data volumes; streaming of result sets and server-rendered 2D/3D imagery; rigorous workflow control and auditing; and in-database algorithms run directly against data as a HPC cloud service.

An evaluation method of power quality about electrified railways connected to power grid based on PSCAD/EMTDC

NASA Astrophysics Data System (ADS)

Liang, Weibin; Ouyang, Sen; Huang, Xiang; Su, Weijian

2017-05-01

The existing modeling process of power quality about electrified railways connected to power grid is complicated and the simulation scene is incomplete, so this paper puts forward a novel evaluation method of power quality based on PSCAD/ETMDC. Firstly, a model of power quality about electrified railways connected to power grid is established, which is based on testing report or measured data. The equivalent model of electrified locomotive contains power characteristic and harmonic characteristic, which are substituted by load and harmonic source. Secondly, in order to make evaluation more complete, an analysis scheme has been put forward. The scheme uses a combination of three-dimensions of electrified locomotive, which contains types, working conditions and quantity. At last, Shenmao Railway is taken as example to evaluate the power quality at different scenes, and the result shows electrified railways connected to power grid have significant effect on power quality.

A left cerebellar pathway mediates language in prematurely-born young adults

PubMed Central

Constable, R. Todd; Vohr, Betty R.; Scheinost, Dustin; Benjamin, Jennifer R.; Fulbright, Robert K.; Lacadie, Cheryl; Schneider, Karen C.; Katz, Karol H.; Zhang, Heping; Papademetris, Xenophon; Ment, Laura R.

2012-01-01

Preterm (PT) subjects are at risk for developmental delay, and task-based studies suggest that developmental disorders may be due to alterations in neural connectivity. Since emerging data imply the importance of right cerebellar function for language acquisition in typical development, we hypothesized that PT subjects would have alternate areas of cerebellar connectivity, and that these areas would be responsible for differences in cognitive outcomes between PT subjects and term controls at age 20 years. Nineteen PT and 19 term control young adults were prospectively studied using resting-state functional MRI (fMRI) to create voxel-based contrast maps reflecting the functional connectivity of each tissue element in the grey matter through analysis of the intrinsic connectivity contrast degree (ICC-d). Left cerebellar ICC-d differences between subjects identified a region of interest that was used for subsequent seed-based connectivity analyses. Subjects underwent standardized language testing, and correlations with cognitive outcomes were assessed. There were no differences in gender, hand preference, maternal education, age at study, or Peabody Picture Vocabulary Test (PPVT) scores. Functional connectivity (FcMRI) demonstrated increased tissue connectivity in the biventer, simple and quadrangular lobules of the L cerebellum (p<0.05) in PTs compared to term controls; seed-based analyses from these regions demonstrated alterations in connectivity from L cerebellum to both R and L inferior frontal gyri (IFG) in PTs compared to term controls. For PTs but not term controls, there were significant positive correlations between these connections and PPVT scores (R IFG: r=0.555, p=0.01; L IFG: r=0.454, p=0.05), as well as Verbal Comprehension Index (VCI) scores (R IFG: r=0.472, p=0.04). These data suggest the presence of a left cerebellar language circuit in PT subjects at young adulthood. These findings may represent either a delay in maturation or the engagement of alternative neural pathways for language in the developing PT brain. PMID:22982585

IVGTT-based simple assessment of glucose tolerance in the Zucker fatty rat: Validation against minimal models.

PubMed

Morettini, Micaela; Faelli, Emanuela; Perasso, Luisa; Fioretti, Sandro; Burattini, Laura; Ruggeri, Piero; Di Nardo, Francesco

2017-01-01

For the assessment of glucose tolerance from IVGTT data in Zucker rat, minimal model methodology is reliable but time- and money-consuming. This study aimed to validate for the first time in Zucker rat, simple surrogate indexes of insulin sensitivity and secretion against the glucose-minimal-model insulin sensitivity index (SI) and against first- (Φ1) and second-phase (Φ2) β-cell responsiveness indexes provided by C-peptide minimal model. Validation of the surrogate insulin sensitivity index (ISI) and of two sets of coupled insulin-based indexes for insulin secretion, differing from the cut-off point between phases (FPIR3-SPIR3, t = 3 min and FPIR5-SPIR5, t = 5 min), was carried out in a population of ten Zucker fatty rats (ZFR) and ten Zucker lean rats (ZLR). Considering the whole rat population (ZLR+ZFR), ISI showed a significant strong correlation with SI (Spearman's correlation coefficient, r = 0.88; P<0.001). Both FPIR3 and FPIR5 showed a significant (P<0.001) strong correlation with Φ1 (r = 0.76 and r = 0.75, respectively). Both SPIR3 and SPIR5 showed a significant (P<0.001) strong correlation with Φ2 (r = 0.85 and r = 0.83, respectively). ISI is able to detect (P<0.001) the well-recognized reduction in insulin sensitivity in ZFRs, compared to ZLRs. The insulin-based indexes of insulin secretion are able to detect in ZFRs (P<0.001) the compensatory increase of first- and second-phase secretion, associated to the insulin-resistant state. The ability of the surrogate indexes in describing glucose tolerance in the ZFRs was confirmed by the Disposition Index analysis. The model-based validation performed in the present study supports the utilization of low-cost, insulin-based indexes for the assessment of glucose tolerance in Zucker rat, reliable animal model of human metabolic syndrome.

Predicting links based on knowledge dissemination in complex network

NASA Astrophysics Data System (ADS)

Zhou, Wen; Jia, Yifan

2017-04-01

Link prediction is the task of mining the missing links in networks or predicting the next vertex pair to be connected by a link. A lot of link prediction methods were inspired by evolutionary processes of networks. In this paper, a new mechanism for the formation of complex networks called knowledge dissemination (KD) is proposed with the assumption of knowledge disseminating through the paths of a network. Accordingly, a new link prediction method-knowledge dissemination based link prediction (KDLP)-is proposed to test KD. KDLP characterizes vertex similarity based on knowledge quantity (KQ) which measures the importance of a vertex through H-index. Extensive numerical simulations on six real-world networks demonstrate that KDLP is a strong link prediction method which performs at a higher prediction accuracy than four well-known similarity measures including common neighbors, local path index, average commute time and matrix forest index. Furthermore, based on the common conclusion that an excellent link prediction method reveals a good evolving mechanism, the experiment results suggest that KD is a considerable network evolving mechanism for the formation of complex networks.

Structural-functional relationships between eye orbital imaging biomarkers and clinical visual assessments

NASA Astrophysics Data System (ADS)

Yao, Xiuya; Chaganti, Shikha; Nabar, Kunal P.; Nelson, Katrina; Plassard, Andrew; Harrigan, Rob L.; Mawn, Louise A.; Landman, Bennett A.

2017-02-01

Eye diseases and visual impairment affect millions of Americans and induce billions of dollars in annual economic burdens. Expounding upon existing knowledge of eye diseases could lead to improved treatment and disease prevention. This research investigated the relationship between structural metrics of the eye orbit and visual function measurements in a cohort of 470 patients from a retrospective study of ophthalmology records for patients (with thyroid eye disease, orbital inflammation, optic nerve edema, glaucoma, intrinsic optic nerve disease), clinical imaging, and visual function assessments. Orbital magnetic resonance imaging (MRI) and computed tomography (CT) images were retrieved and labeled in 3D using multi-atlas label fusion. Based on the 3D structures, both traditional radiology measures (e.g., Barrett index, volumetric crowding index, optic nerve length) and novel volumetric metrics were computed. Using stepwise regression, the associations between structural metrics and visual field scores (visual acuity, functional acuity, visual field, functional field, and functional vision) were assessed. Across all models, the explained variance was reasonable (R2 0.1-0.2) but highly significant (p < 0.001). Instead of analyzing a specific pathology, this study aimed to analyze data across a variety of pathologies. This approach yielded a general model for the connection between orbital structural imaging biomarkers and visual function.

Graph-based analysis of connectivity in spatially-explicit population models: HexSim and the Connectivity Analysis Toolkit

EPA Science Inventory

Background / Question / Methods Planning for the recovery of threatened species is increasingly informed by spatially-explicit population models. However, using simulation model results to guide land management decisions can be difficult due to the volume and complexity of model...

Blocking probability in the hose-model optical VPN with different number of wavelengths

NASA Astrophysics Data System (ADS)

Roslyakov, Alexander V.

2017-04-01

Connection setup with guaranteed quality of service (QoS) in the optical virtual private network (OVPN) is a major goal for the network providers. In order to support this we propose a QoS based OVPN connection set up mechanism over WDM network to the end customer. The proposed WDM network model can be specified in terms of QoS parameter such as blocking probability. We estimated this QoS parameter based on the hose-model OVPN. In this mechanism the OVPN connections also can be created or deleted according to the availability of the wavelengths in the optical path. In this paper we have considered the impact of the number of wavelengths on the computation of blocking probability. The goal of the work is to dynamically provide a best OVPN connection during frequent arrival of connection requests with QoS requirements.

Tracer-aided modelling to explore non-linearities in flow paths, hydrological connectivity and faecal contamination risk

NASA Astrophysics Data System (ADS)

Neill, A. J.; Tetzlaff, D.; Strachan, N.; Soulsby, C.

2016-12-01

The non-linearities of runoff generation processes are strongly influenced by the connectivity of hillslopes and channel networks, particularly where overland flow is an important runoff mechanism. Despite major advances in understanding hydrological connectivity and runoff generation, the role of connectivity in the contamination of potable water supplies by faecal pathogens from grazing animals remains unclear. This is a water quality issue with serious implications for public health. Here, we sought to understand the dynamics of hydrological connectivity, flow paths and linked faecal pathogen transport in a montane catchment in Scotland with high deer populations. We firstly calibrated, within an uncertainty framework, a parsimonious tracer-aided hydrological model to daily discharge and stream isotope data. The model, developed on the basis of past empirical and tracer studies, conceptualises the catchment as three interacting hydrological source areas (dynamic saturation zone, dynamic hillslope, and groundwater) for which water fluxes, water ages and storage-based connectivity can be simulated. We next coupled several faecal indicator organism (FIO; a common indicator of faecal pathogen contamination) behaviour and transport schemes to the robust hydrological models. A further calibration was then undertaken based on the ability of each coupled model to simulate daily FIO concentrations. This gave us a final set of coupled behavioural models from which we explored how in-stream FIO dynamics could be related to the changing connectivity between the three hydrological source areas, flow paths, water ages and consequent dominant runoff generation processes. We found that high levels of FIOs were transient and episodic, and strongly correlated with periods of high connectivity through overland flow. This non-linearity in connectivity and FIO flux was successfully captured within our dynamic, tracer-aided hydrological model.

[Selection of distance thresholds of urban forest landscape connectivity in Shenyang City].

PubMed

Liu, Chang-fu; Zhou, Bin; He, Xing-yuan; Chen, Wei

2010-10-01

By using the QuickBird remote sensing image interpretation data of urban forests in Shenyang City in 2006, and with the help of geographical information system, this paper analyzed the landscape patches of the urban forests in the area inside the third ring-road of Shenyang. Based on the habitat availability and the dispersal potential of animal and plant species, 8 distance thresholds (50, 100, 200, 400, 600, 800, 1000, and 1200 m) were selected to compute the integral index of connectivity, probability of connectivity, and important value of the landscape patches, and the computed values were used for analyzing and screening the distance thresholds of urban forest landscape connectivity in the City. The results showed that the appropriate distance thresholds of the urban forest landscape connectivity in Shenyang City in 2006 ranged from 100 to 400 m, with 200 m being most appropriate. It was suggested that the distance thresholds should be increased or decreased according to the performability of urban forest landscape connectivity and the different demands for landscape levels.

Anisotropic connectivity implements motion-based prediction in a spiking neural network.

PubMed

Kaplan, Bernhard A; Lansner, Anders; Masson, Guillaume S; Perrinet, Laurent U

2013-01-01

Predictive coding hypothesizes that the brain explicitly infers upcoming sensory input to establish a coherent representation of the world. Although it is becoming generally accepted, it is not clear on which level spiking neural networks may implement predictive coding and what function their connectivity may have. We present a network model of conductance-based integrate-and-fire neurons inspired by the architecture of retinotopic cortical areas that assumes predictive coding is implemented through network connectivity, namely in the connection delays and in selectiveness for the tuning properties of source and target cells. We show that the applied connection pattern leads to motion-based prediction in an experiment tracking a moving dot. In contrast to our proposed model, a network with random or isotropic connectivity fails to predict the path when the moving dot disappears. Furthermore, we show that a simple linear decoding approach is sufficient to transform neuronal spiking activity into a probabilistic estimate for reading out the target trajectory.

Prediction of individual brain maturity using fMRI.

PubMed

Dosenbach, Nico U F; Nardos, Binyam; Cohen, Alexander L; Fair, Damien A; Power, Jonathan D; Church, Jessica A; Nelson, Steven M; Wig, Gagan S; Vogel, Alecia C; Lessov-Schlaggar, Christina N; Barnes, Kelly Anne; Dubis, Joseph W; Feczko, Eric; Coalson, Rebecca S; Pruett, John R; Barch, Deanna M; Petersen, Steven E; Schlaggar, Bradley L

2010-09-10

Group functional connectivity magnetic resonance imaging (fcMRI) studies have documented reliable changes in human functional brain maturity over development. Here we show that support vector machine-based multivariate pattern analysis extracts sufficient information from fcMRI data to make accurate predictions about individuals' brain maturity across development. The use of only 5 minutes of resting-state fcMRI data from 238 scans of typically developing volunteers (ages 7 to 30 years) allowed prediction of individual brain maturity as a functional connectivity maturation index. The resultant functional maturation curve accounted for 55% of the sample variance and followed a nonlinear asymptotic growth curve shape. The greatest relative contribution to predicting individual brain maturity was made by the weakening of short-range functional connections between the adult brain's major functional networks.

On Topological Indices of Certain Families of Nanostar Dendrimers.

PubMed

Husin, Mohamad Nazri; Hasni, Roslan; Arif, Nabeel Ezzulddin; Imran, Muhammad

2016-06-24

A topological index of graph G is a numerical parameter related to G which characterizes its molecular topology and is usually graph invariant. In the field of quantitative structure-activity (QSAR)/quantitative structure-activity structure-property (QSPR) research, theoretical properties of the chemical compounds and their molecular topological indices such as the Randić connectivity index, atom-bond connectivity (ABC) index and geometric-arithmetic (GA) index are used to predict the bioactivity of different chemical compounds. A dendrimer is an artificially manufactured or synthesized molecule built up from the branched units called monomers. In this paper, the fourth version of ABC index and the fifth version of GA index of certain families of nanostar dendrimers are investigated. We derive the analytical closed formulas for these families of nanostar dendrimers. The obtained results can be of use in molecular data mining, particularly in researching the uniqueness of tested (hyper-branched) molecular graphs.

Factoring the brain signatures of anesthesia concentration and level of arousal across individuals.

PubMed

Barttfeld, Pablo; Bekinschtein, Tristan A; Salles, Alejo; Stamatakis, Emmanuel A; Adapa, Ram; Menon, David K; Sigman, Mariano

2015-01-01

Combining resting-state functional magnetic resonance imaging (fMRI) connectivity and behavioral analysis during sedation, we factored out general effects of the anesthetic drug propofol and a specific index of conscious report, participants' level of responsiveness. The factorial analysis shows that increasing concentration of propofol in blood specifically decreases the connectivity strength of fronto-parietal cortical loops. In contrast, loss of responsiveness is indexed by a functional disconnection between the thalamus and the frontal cortex, balanced by an increase in connectivity strength of the thalamus to the occipital and temporal regions of the cortex.

Factoring the brain signatures of anesthesia concentration and level of arousal across individuals

PubMed Central

Barttfeld, Pablo; Bekinschtein, Tristan A.; Salles, Alejo; Stamatakis, Emmanuel A.; Adapa, Ram; Menon, David K.; Sigman, Mariano

2015-01-01

Combining resting-state functional magnetic resonance imaging (fMRI) connectivity and behavioral analysis during sedation, we factored out general effects of the anesthetic drug propofol and a specific index of conscious report, participants’ level of responsiveness. The factorial analysis shows that increasing concentration of propofol in blood specifically decreases the connectivity strength of fronto-parietal cortical loops. In contrast, loss of responsiveness is indexed by a functional disconnection between the thalamus and the frontal cortex, balanced by an increase in connectivity strength of the thalamus to the occipital and temporal regions of the cortex. PMID:26509121

Multi- and monofractal indices of short-term heart rate variability.

PubMed

Fischer, R; Akay, M; Castiglioni, P; Di Rienzo, M

2003-09-01

Indices of heart rate variability (HRV) based on fractal signal models have recently been shown to possess value as predictors of mortality in specific patient populations. To develop more powerful clinical indices of HRV based on a fractal signal model, the study investigated two HRV indices based on a monofractal signal model called fractional Brownian motion and an index based on a multifractal signal model called multifractional Brownian motion. The performance of the indices was compared with an HRV index in common clinical use. To compare the indices, 18 normal subjects were subjected to postural changes, and the indices were compared on their ability to respond to the resulting autonomic events in HRV recordings. The magnitude of the response to postural change (normalised by the measurement variability) was assessed by analysis of variance and multiple comparison testing. Four HRV indices were investigated for this study: the standard deviation of all normal R-R intervals; an HRV index commonly used in the clinic; detrended fluctuation analysis, an HRV index found to be the most powerful predictor of mortality in a study of patients with depressed left ventricular function; an HRV index developed using the maximum likelihood estimation (MLE) technique for a monofractal signal model; and an HRV index developed for the analysis of multifractional Brownian motion signals. The HRV index based on the MLE technique was found to respond most strongly to the induced postural changes (95% CI). The magnitude of its response (normalised by the measurement variability) was at least 25% greater than any of the other indices tested.

A spatial-temporal system for dynamic cadastral management.

PubMed

Nan, Liu; Renyi, Liu; Guangliang, Zhu; Jiong, Xie

2006-03-01

A practical spatio-temporal database (STDB) technique for dynamic urban land management is presented. One of the STDB models, the expanded model of Base State with Amendments (BSA), is selected as the basis for developing the dynamic cadastral management technique. Two approaches, the Section Fast Indexing (SFI) and the Storage Factors of Variable Granularity (SFVG), are used to improve the efficiency of the BSA model. Both spatial graphic data and attribute data, through a succinct engine, are stored in standard relational database management systems (RDBMS) for the actual implementation of the BSA model. The spatio-temporal database is divided into three interdependent sub-databases: present DB, history DB and the procedures-tracing DB. The efficiency of database operation is improved by the database connection in the bottom layer of the Microsoft SQL Server. The spatio-temporal system can be provided at a low-cost while satisfying the basic needs of urban land management in China. The approaches presented in this paper may also be of significance to countries where land patterns change frequently or to agencies where financial resources are limited.

A fuzzy-logic based decision-making approach for identification of groundwater quality based on groundwater quality indices.

PubMed

Vadiati, M; Asghari-Moghaddam, A; Nakhaei, M; Adamowski, J; Akbarzadeh, A H

2016-12-15

Due to inherent uncertainties in measurement and analysis, groundwater quality assessment is a difficult task. Artificial intelligence techniques, specifically fuzzy inference systems, have proven useful in evaluating groundwater quality in uncertain and complex hydrogeological systems. In the present study, a Mamdani fuzzy-logic-based decision-making approach was developed to assess groundwater quality based on relevant indices. In an effort to develop a set of new hybrid fuzzy indices for groundwater quality assessment, a Mamdani fuzzy inference model was developed with widely-accepted groundwater quality indices: the Groundwater Quality Index (GQI), the Water Quality Index (WQI), and the Ground Water Quality Index (GWQI). In an effort to present generalized hybrid fuzzy indices a significant effort was made to employ well-known groundwater quality index acceptability ranges as fuzzy model output ranges rather than employing expert knowledge in the fuzzification of output parameters. The proposed approach was evaluated for its ability to assess the drinking water quality of 49 samples collected seasonally from groundwater resources in Iran's Sarab Plain during 2013-2014. Input membership functions were defined as "desirable", "acceptable" and "unacceptable" based on expert knowledge and the standard and permissible limits prescribed by the World Health Organization. Output data were categorized into multiple categories based on the GQI (5 categories), WQI (5 categories), and GWQI (3 categories). Given the potential of fuzzy models to minimize uncertainties, hybrid fuzzy-based indices produce significantly more accurate assessments of groundwater quality than traditional indices. The developed models' accuracy was assessed and a comparison of the performance indices demonstrated the Fuzzy Groundwater Quality Index model to be more accurate than both the Fuzzy Water Quality Index and Fuzzy Ground Water Quality Index models. This suggests that the new hybrid fuzzy indices developed in this research are reliable and flexible when used in groundwater quality assessment for drinking purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Adherence to Rivaroxaban Compared with Other Oral Anticoagulant Agents Among Patients with Nonvalvular Atrial Fibrillation.

PubMed

McHorney, Colleen A; Ashton, Veronica; Laliberté, François; Germain, Guillaume; Wynant, Willy; Crivera, Concetta; Schein, Jeffrey R; Lefebvre, Patrick; Peterson, Eric D

2017-09-01

Adherence to oral anticoagulant (OAC) agents is important for patients with nonvalvular atrial fibrillation (NVAF) to prevent potentially severe adverse events. To compare real-world adherence rates and time to discontinuation for rivaroxaban versus other OACs (apixaban, dabigatran, and warfarin) among patients with NVAF using claims-based data. Health care claims from the IMS Health Real-World Data Adjudicated Claims database (July 2012-June 2015) were analyzed. Adherence rate was defined as the percentage of patients with proportion of days covered (PDC) ≥ 0.80 and ≥ 0.90. Discontinuation was defined as a gap of more than 30 days between the end of a dispensing days of supply and the start date of the next fill, if any. Patients were included if they had ≥ 2 dispensings of rivaroxaban, apixaban, dabigatran, or warfarin at least 180 days apart (the first was considered the index date), had > 60 days of supply, had ≥ 6 months of pre-index eligibility, had ≥ 1 atrial fibrillation (AF) diagnosis pre-index or at index date, and had no valvular involvement. A logistic regression model was used to evaluate adherence to OAC therapy, while a Cox model was used to compare time to discontinuation; both models adjusted for baseline confounders. A total of 13,645 rivaroxaban, 6,304 apixaban, 3,360 dabigatran, and 13,366 warfarin patients were identified. A significantly higher proportion of rivaroxaban users (80.1%) was adherent to therapy (PDC ≥ 0.80 at 6 months) versus apixaban (75.8%), dabigatran (69.2%), and warfarin users (64.5%). After adjustment, the proportion of patients adherent to therapy remained significantly higher for rivaroxaban users versus apixaban (absolute difference [AD] = 5.8%), dabigatran (AD = 9.5%), and warfarin users (AD = 13.6%; all P < 0.001). More pronounced differences were found with a PDC ≥0.90. In addition, rivaroxaban users were significantly less likely to discontinue therapy compared with other OACs after adjustments (all P < 0.05). Among NVAF patients, rivaroxaban was associated with significantly higher adherence rates relative to other OACs whether using either a PDC of > 0.80 or > 0.90. Such differences in adherence could translate into improved patient outcomes and lower health care costs. This research was funded by Janssen Scientific Affairs. Ashton, Crivera, and Schein are employees and stockholders of Janssen Scientific Affairs. Laliberté, Germain, Wynant, and Lefebvre are employees of Analysis Group, a consulting company that received research grants from Janssen Scientific Affairs in connection with this study. McHorney is an employee of Evidera, a consulting company that received research grants from Janssen Scientific Affairs in connection with this study. Peterson received research grants from Janssen Scientific Affairs in connection with this study. All authors contributed to concept and design. The data were collected by Germain, Wynant, Laliberté, and Lefebvre and interpreted primarily by McHorney and Peterson, with the assistance of Lefebvre, Laliberté, Ashton, Crivera, and Schein. The manuscript was written primarily by Laliberté, Germain, and Lefebvre, with the assistance of Wynant. Revisions were made primarily by Ashton, Crivera, McHorney, Schein, and Peterson.

Micromechanics and constitutive modeling of connective soft tissues.

PubMed

Fallah, A; Ahmadian, M T; Firozbakhsh, K; Aghdam, M M

2016-07-01

In this paper, a micromechanical model for connective soft tissues based on the available histological evidences is developed. The proposed model constituents i.e. collagen fibers and ground matrix are considered as hyperelastic materials. The matrix material is assumed to be isotropic Neo-Hookean while the collagen fibers are considered to be transversely isotropic hyperelastic. In order to take into account the effects of tissue structure in lower scales on the macroscopic behavior of tissue, a strain energy density function (SEDF) is developed for collagen fibers based on tissue hierarchical structure. Macroscopic response and properties of tissue are obtained using the numerical homogenization method with the help of ABAQUS software. The periodic boundary conditions and the proposed constitutive models are implemented into ABAQUS using the DISP and the UMAT subroutines, respectively. The existence of the solution and stable material behavior of proposed constitutive model for collagen fibers are investigated based on the poly-convexity condition. Results of the presented micromechanics model for connective tissues are compared and validated with available experimental data. Effects of geometrical and material parameters variation at microscale on macroscopic mechanical behavior of tissues are investigated. The results show that decrease in collagen content of the connective tissues like the tendon due to diseases leads 20% more stretch than healthy tissue under the same load which can results in connective tissue malfunction and hypermobility in joints. Copyright © 2016 Elsevier Ltd. All rights reserved.

Financial networks based on Granger causality: A case study

NASA Astrophysics Data System (ADS)

Papana, Angeliki; Kyrtsou, Catherine; Kugiumtzis, Dimitris; Diks, Cees

2017-09-01

Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to specify the direction of the interrelationships among the international stock indexes and portray the links of the resulting networks, by the presence of direct couplings between variables exploiting all available information. However, their differences are assessed due to the presence of nonlinearity. The weighted networks formed with respect to the causality measures are transformed to binary ones using a significance test. The financial networks are formed on sliding windows in order to examine the network characteristics and trace changes in the connectivity structure. Subsequently, two statistical network quantities are calculated; the average degree and the average shortest path length. The empirical findings reveal interesting time-varying properties of the constructed network, which are clearly dependent on the nature of the financial cycle.

Volatility Behaviors of Financial Time Series by Percolation System on Sierpinski Carpet Lattice

NASA Astrophysics Data System (ADS)

Pei, Anqi; Wang, Jun

2015-01-01

The financial time series is simulated and investigated by the percolation system on the Sierpinski carpet lattice, where percolation is usually employed to describe the behavior of connected clusters in a random graph, and the Sierpinski carpet lattice is a graph which corresponds the fractal — Sierpinski carpet. To study the fluctuation behavior of returns for the financial model and the Shanghai Composite Index, we establish a daily volatility measure — multifractal volatility (MFV) measure to obtain MFV series, which have long-range cross-correlations with squared daily return series. The autoregressive fractionally integrated moving average (ARFIMA) model is used to analyze the MFV series, which performs better when compared to other volatility series. By a comparative study of the multifractality and volatility analysis of the data, the simulation data of the proposed model exhibits very similar behaviors to those of the real stock index, which indicates somewhat rationality of the model to the market application.

Cityscape genetics: structural vs. functional connectivity of an urban lizard population.

PubMed

Beninde, Joscha; Feldmeier, Stephan; Werner, Maike; Peroverde, Daniel; Schulte, Ulrich; Hochkirch, Axel; Veith, Michael

2016-10-01

Functional connectivity is essential for the long-term persistence of populations. However, many studies assess connectivity with a focus on structural connectivity only. Cityscapes, namely urban landscapes, are particularly dynamic and include numerous potential anthropogenic barriers to animal movements, such as roads, traffic or buildings. To assess and compare structural connectivity of habitats and functional connectivity of gene flow of an urban lizard, we here combined species distribution models (SDMs) with an individual-based landscape genetic optimization procedure. The most important environmental factors of the SDMs are structural diversity and substrate type, with high and medium levels of structural diversity as well as open and rocky/gravel substrates contributing most to structural connectivity. By contrast, water cover was the best model of all environmental factors following landscape genetic optimization. The river is thus a major barrier to gene flow, while of the typical anthropogenic factors only buildings showed an effect. Nonetheless, using SDMs as a basis for landscape genetic optimization provided the highest ranked model for functional connectivity. Optimizing SDMs in this way can provide a sound basis for models of gene flow of the cityscape, and elsewhere, while presence-only and presence-absence modelling approaches showed differences in performance. Additionally, interpretation of results based on SDM factor importance can be misleading, dictating more thorough analyses following optimization of SDMs. Such approaches can be adopted for management strategies, for example aiming to connect native common wall lizard populations or disconnect them from non-native introduced populations, which are currently spreading in many cities in Central Europe. © 2016 John Wiley & Sons Ltd.

Identifying appropriate spatial scales for marine conservation and management using a larval dispersal model: The case of Concholepas concholepas (loco) in Chile

NASA Astrophysics Data System (ADS)

Garavelli, Lysel; Kaplan, David Michael; Colas, François; Stotz, Wolfgang; Yannicelli, Beatriz; Lett, Christophe

2014-05-01

Along the coast of Chile, fisheries targeting the marine gastropod Concholepas concholepas, commonly named “loco”, were highly valuable until the end of the 80s when catches declined significantly. Since the late 90s, a management plan based on territorial-user-rights areas has been implemented, with limited effect on stock recovery. More effective loco conservation and management is impeded by lack of information regarding connectivity via larval dispersal between these individually-managed areas. To develop a regional view of loco connectivity, we integrate loco life history information into a biophysical, individual-based larval dispersal model. This model is used to evaluate scales of loco connectivity and seasonality in connectivity patterns, as well as to partition the coast into largely disconnected subpopulations using a recently developed connectivity-matrix clustering algorithm. We find mean dispersal distances ranging from 170 to 220 km depending on release depth of larvae and planktonic larval duration. Settlement success levels depend quantitatively on the physical and biological processes included in the model, but connectivity patterns remain qualitatively similar. Model estimates of settlement success peak for larval release dates in late austral autumn, consistent with field results and with favorable conditions for larval coastal retention due to weak upwelling during austral autumn. Despite the relatively homogeneous Chilean coastline, distinct subpopulations with minimal connectivity between them are readily identifiable. Barriers to connectivity that are robust to changes in model configuration exist at 23°S and 29°S latitudes. These zones are all associated with important headlands and embayments of the Chilean coast.

Estimation of effective connectivity via data-driven neural modeling

PubMed Central

Freestone, Dean R.; Karoly, Philippa J.; Nešić, Dragan; Aram, Parham; Cook, Mark J.; Grayden, David B.

2014-01-01

This research introduces a new method for functional brain imaging via a process of model inversion. By estimating parameters of a computational model, we are able to track effective connectivity and mean membrane potential dynamics that cannot be directly measured using electrophysiological measurements alone. The ability to track the hidden aspects of neurophysiology will have a profound impact on the way we understand and treat epilepsy. For example, under the assumption the model captures the key features of the cortical circuits of interest, the framework will provide insights into seizure initiation and termination on a patient-specific basis. It will enable investigation into the effect a particular drug has on specific neural populations and connectivity structures using minimally invasive measurements. The method is based on approximating brain networks using an interconnected neural population model. The neural population model is based on a neural mass model that describes the functional activity of the brain, capturing the mesoscopic biophysics and anatomical structure. The model is made subject-specific by estimating the strength of intra-cortical connections within a region and inter-cortical connections between regions using a novel Kalman filtering method. We demonstrate through simulation how the framework can be used to track the mechanisms involved in seizure initiation and termination. PMID:25506315

An index-based framework for assessing patterns and trends in river fragmentation and flow regulation by global dams at multiple scales

NASA Astrophysics Data System (ADS)

Grill, Günther; Lehner, Bernhard; Lumsdon, Alexander E.; MacDonald, Graham K.; Zarfl, Christiane; Reidy Liermann, Catherine

2015-01-01

The global number of dam constructions has increased dramatically over the past six decades and is forecast to continue to rise, particularly in less industrialized regions. Identifying development pathways that can deliver the benefits of new infrastructure while also maintaining healthy and productive river systems is a great challenge that requires understanding the multifaceted impacts of dams at a range of scales. New approaches and advanced methodologies are needed to improve predictions of how future dam construction will affect biodiversity, ecosystem functioning, and fluvial geomorphology worldwide, helping to frame a global strategy to achieve sustainable dam development. Here, we respond to this need by applying a graph-based river routing model to simultaneously assess flow regulation and fragmentation by dams at multiple scales using data at high spatial resolution. We calculated the cumulative impact of a set of 6374 large existing dams and 3377 planned or proposed dams on river connectivity and river flow at basin and subbasin scales by fusing two novel indicators to create a holistic dam impact matrix for the period 1930-2030. Static network descriptors such as basin area or channel length are of limited use in hierarchically nested and dynamic river systems, so we developed the river fragmentation index and the river regulation index, which are based on river volume. These indicators are less sensitive to the effects of network configuration, offering increased comparability among studies with disparate hydrographies as well as across scales. Our results indicate that, on a global basis, 48% of river volume is moderately to severely impacted by either flow regulation, fragmentation, or both. Assuming completion of all dams planned and under construction in our future scenario, this number would nearly double to 93%, largely due to major dam construction in the Amazon Basin. We provide evidence for the importance of considering small to medium sized dams and for the need to include waterfalls to establish a baseline of natural fragmentation. Our versatile framework can serve as a component of river fragmentation and connectivity assessments; as a standardized, easily replicable monitoring framework at global and basin scales; and as part of regional dam planning and management strategies.

Comparing Habitat Suitability and Connectivity Modeling Methods for Conserving Pronghorn Migrations

PubMed Central

Poor, Erin E.; Loucks, Colby; Jakes, Andrew; Urban, Dean L.

2012-01-01

Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements. PMID:23166656

Comparing habitat suitability and connectivity modeling methods for conserving pronghorn migrations.

PubMed

Poor, Erin E; Loucks, Colby; Jakes, Andrew; Urban, Dean L

2012-01-01

Terrestrial long-distance migrations are declining globally: in North America, nearly 75% have been lost. Yet there has been limited research comparing habitat suitability and connectivity models to identify migration corridors across increasingly fragmented landscapes. Here we use pronghorn (Antilocapra americana) migrations in prairie habitat to compare two types of models that identify habitat suitability: maximum entropy (Maxent) and expert-based (Analytic Hierarchy Process). We used distance to wells, distance to water, NDVI, land cover, distance to roads, terrain shape and fence presence to parameterize the models. We then used the output of these models as cost surfaces to compare two common connectivity models, least-cost modeling (LCM) and circuit theory. Using pronghorn movement data from spring and fall migrations, we identified potential migration corridors by combining each habitat suitability model with each connectivity model. The best performing model combination was Maxent with LCM corridors across both seasons. Maxent out-performed expert-based habitat suitability models for both spring and fall migrations. However, expert-based corridors can perform relatively well and are a cost-effective alternative if species location data are unavailable. Corridors created using LCM out-performed circuit theory, as measured by the number of pronghorn GPS locations present within the corridors. We suggest the use of a tiered approach using different corridor widths for prioritizing conservation and mitigation actions, such as fence removal or conservation easements.

The connection Between Plasma Protein Binding and Acute Toxicity as Determined by the LD50 Value.

PubMed

Svennebring, Andreas

2016-02-01

Preclinical Research A dataset of three drug classes (acids, bases, and neutrals) with LD50 values in mice was analysed to investigate a possible connection between high plasma protein binding and acute toxicity. Initially, it was found that high plasma protein binding was associated with toxicity for acids and neutrals, but after compensating for differences in lipophilicity, plasma protein binding was found not to be associated with toxicity. The therapeutic index established by the quotient between mouse LD50 and the defined daily dose was unaffected by both lipophilicity and plasma protein binding. © 2015 Wiley Periodicals, Inc.

Comparing Stream Discharge, Dissolved Organic Carbon, and Selected MODIS Indices in Freshwater Basins

NASA Astrophysics Data System (ADS)

Shaver, W. T.; Wollheim, W. M.

2009-12-01

In a preliminary study of the Ipswich Basin in Massachusetts, a good correlation was found to exist between the MODIS (Moderate Resolution Imaging Spectroradiometer) Enhanced Vegetation Index and stream dissolved organic carbon (DOC). Further study was warranted to determine the utility of MODIS indices in predicting temporal stream DOC. Stream discharge rates and DOC data were obtained from the USGS National Water Quality Assessment Program (NAWQA) database. Twelve NAWQA monitoring sites were selected for evaluation based on the criteria of having drainage basin sizes less than 600 km2 with relatively continuous, long-term DOC and discharge data. MODIS indices were selected based on their connections with terrestrial DOC and were obtained for each site's catchment area. These included the Normalized Vegetation Index (NDVI), the Enhanced Vegetation Index (EVI), the Daily Photosynthesis (PSN) and the Leaf Area Index (LAI). Regression analysis was used to evaluate the relationships between DOC, discharge and MODIS products. Data analysis revealed several important trends. Sites with strong positive correlation coefficients (r values ranging from 0.462 to 0.831) between DOC and discharge displayed weak correlations with all of the MODIS indices (r values ranging from 0 to 0.322). For sites where the DOC/discharge correlation was weak or negative, MODIS indices were moderately correlated, with r values ranging from 0.35 to 0.647, all of which were significant at less than 1 percent. Some sites that had weak positive correlations with MODIS indices displayed a lag time, that is, the MODIS index rose and fell shortly before the DOC concentration rose and fell. Shifting the MODIS data forward in time by roughly one month significantly increased the DOC/MODIS r values by about 10%. NDVI and EVI displayed the strongest correlations with temporal DOC variability (r values ranging from 0.471 to 0.647), and therefore these indices are the most promising for being incorporated into a model for remotely sensing terrestrial DOC.

Default mode network abnormalities in posttraumatic stress disorder: A novel network-restricted topology approach.

PubMed

Akiki, Teddy J; Averill, Christopher L; Wrocklage, Kristen M; Scott, J Cobb; Averill, Lynnette A; Schweinsburg, Brian; Alexander-Bloch, Aaron; Martini, Brenda; Southwick, Steven M; Krystal, John H; Abdallah, Chadi G

2018-08-01

Disruption in the default mode network (DMN) has been implicated in numerous neuropsychiatric disorders, including posttraumatic stress disorder (PTSD). However, studies have largely been limited to seed-based methods and involved inconsistent definitions of the DMN. Recent advances in neuroimaging and graph theory now permit the systematic exploration of intrinsic brain networks. In this study, we used resting-state functional magnetic resonance imaging (fMRI), diffusion MRI, and graph theoretical analyses to systematically examine the DMN connectivity and its relationship with PTSD symptom severity in a cohort of 65 combat-exposed US Veterans. We employed metrics that index overall connectivity strength, network integration (global efficiency), and network segregation (clustering coefficient). Then, we conducted a modularity and network-based statistical analysis to identify DMN regions of particular importance in PTSD. Finally, structural connectivity analyses were used to probe whether white matter abnormalities are associated with the identified functional DMN changes. We found decreased DMN functional connectivity strength to be associated with increased PTSD symptom severity. Further topological characterization suggests decreased functional integration and increased segregation in subjects with severe PTSD. Modularity analyses suggest a spared connectivity in the posterior DMN community (posterior cingulate, precuneus, angular gyrus) despite overall DMN weakened connections with increasing PTSD severity. Edge-wise network-based statistical analyses revealed a prefrontal dysconnectivity. Analysis of the diffusion networks revealed no alterations in overall strength or prefrontal structural connectivity. DMN abnormalities in patients with severe PTSD symptoms are characterized by decreased overall interconnections. On a finer scale, we found a pattern of prefrontal dysconnectivity, but increased cohesiveness in the posterior DMN community and relative sparing of connectivity in this region. The DMN measures established in this study may serve as a biomarker of disease severity and could have potential utility in developing circuit-based therapeutics. Published by Elsevier Inc.

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors

PubMed Central

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-01-01

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ-connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm. PMID:28587084

A Max-Flow Based Algorithm for Connected Target Coverage with Probabilistic Sensors.

PubMed

Shan, Anxing; Xu, Xianghua; Cheng, Zongmao; Wang, Wensheng

2017-05-25

Coverage is a fundamental issue in the research field of wireless sensor networks (WSNs). Connected target coverage discusses the sensor placement to guarantee the needs of both coverage and connectivity. Existing works largely leverage on the Boolean disk model, which is only a coarse approximation to the practical sensing model. In this paper, we focus on the connected target coverage issue based on the probabilistic sensing model, which can characterize the quality of coverage more accurately. In the probabilistic sensing model, sensors are only be able to detect a target with certain probability. We study the collaborative detection probability of target under multiple sensors. Armed with the analysis of collaborative detection probability, we further formulate the minimum ϵ -connected target coverage problem, aiming to minimize the number of sensors satisfying the requirements of both coverage and connectivity. We map it into a flow graph and present an approximation algorithm called the minimum vertices maximum flow algorithm (MVMFA) with provable time complex and approximation ratios. To evaluate our design, we analyze the performance of MVMFA theoretically and also conduct extensive simulation studies to demonstrate the effectiveness of our proposed algorithm.

Connectivity ranking of heterogeneous random conductivity models

NASA Astrophysics Data System (ADS)

Rizzo, C. B.; de Barros, F.

2017-12-01

To overcome the challenges associated with hydrogeological data scarcity, the hydraulic conductivity (K) field is often represented by a spatial random process. The state-of-the-art provides several methods to generate 2D or 3D random K-fields, such as the classic multi-Gaussian fields or non-Gaussian fields, training image-based fields and object-based fields. We provide a systematic comparison of these models based on their connectivity. We use the minimum hydraulic resistance as a connectivity measure, which it has been found to be strictly correlated with early time arrival of dissolved contaminants. A computationally efficient graph-based algorithm is employed, allowing a stochastic treatment of the minimum hydraulic resistance through a Monte-Carlo approach and therefore enabling the computation of its uncertainty. The results show the impact of geostatistical parameters on the connectivity for each group of random fields, being able to rank the fields according to their minimum hydraulic resistance.

Large-scale DCMs for resting-state fMRI.

PubMed

Razi, Adeel; Seghier, Mohamed L; Zhou, Yuan; McColgan, Peter; Zeidman, Peter; Park, Hae-Jeong; Sporns, Olaf; Rees, Geraint; Friston, Karl J

2017-01-01

This paper considers the identification of large directed graphs for resting-state brain networks based on biophysical models of distributed neuronal activity, that is, effective connectivity . This identification can be contrasted with functional connectivity methods based on symmetric correlations that are ubiquitous in resting-state functional MRI (fMRI). We use spectral dynamic causal modeling (DCM) to invert large graphs comprising dozens of nodes or regions. The ensuing graphs are directed and weighted, hence providing a neurobiologically plausible characterization of connectivity in terms of excitatory and inhibitory coupling. Furthermore, we show that the use of to discover the most likely sparse graph (or model) from a parent (e.g., fully connected) graph eschews the arbitrary thresholding often applied to large symmetric (functional connectivity) graphs. Using empirical fMRI data, we show that spectral DCM furnishes connectivity estimates on large graphs that correlate strongly with the estimates provided by stochastic DCM. Furthermore, we increase the efficiency of model inversion using functional connectivity modes to place prior constraints on effective connectivity. In other words, we use a small number of modes to finesse the potentially redundant parameterization of large DCMs. We show that spectral DCM-with functional connectivity priors-is ideally suited for directed graph theoretic analyses of resting-state fMRI. We envision that directed graphs will prove useful in understanding the psychopathology and pathophysiology of neurodegenerative and neurodevelopmental disorders. We will demonstrate the utility of large directed graphs in clinical populations in subsequent reports, using the procedures described in this paper.

Pattern-Based Inverse Modeling for Characterization of Subsurface Flow Models with Complex Geologic Heterogeneity

NASA Astrophysics Data System (ADS)

Golmohammadi, A.; Jafarpour, B.; M Khaninezhad, M. R.

2017-12-01

Calibration of heterogeneous subsurface flow models leads to ill-posed nonlinear inverse problems, where too many unknown parameters are estimated from limited response measurements. When the underlying parameters form complex (non-Gaussian) structured spatial connectivity patterns, classical variogram-based geostatistical techniques cannot describe the underlying connectivity patterns. Modern pattern-based geostatistical methods that incorporate higher-order spatial statistics are more suitable for describing such complex spatial patterns. Moreover, when the underlying unknown parameters are discrete (geologic facies distribution), conventional model calibration techniques that are designed for continuous parameters cannot be applied directly. In this paper, we introduce a novel pattern-based model calibration method to reconstruct discrete and spatially complex facies distributions from dynamic flow response data. To reproduce complex connectivity patterns during model calibration, we impose a feasibility constraint to ensure that the solution follows the expected higher-order spatial statistics. For model calibration, we adopt a regularized least-squares formulation, involving data mismatch, pattern connectivity, and feasibility constraint terms. Using an alternating directions optimization algorithm, the regularized objective function is divided into a continuous model calibration problem, followed by mapping the solution onto the feasible set. The feasibility constraint to honor the expected spatial statistics is implemented using a supervised machine learning algorithm. The two steps of the model calibration formulation are repeated until the convergence criterion is met. Several numerical examples are used to evaluate the performance of the developed method.

Soil erosion and sediment connectivity modelling in Burgundy vineyards: case study of Mercurey, France

NASA Astrophysics Data System (ADS)

Fressard, Mathieu; Cossart, Étienne; Lejot, Jêrome; Michel, Kristell; Perret, Franck; Christol, Aurélien; Mathian, Hélène; Navratil, Oldrich

2017-04-01

This research aims at assessing the impact of agricultural landscape structure on soil erosion and sediment connectivity at the catchment scale. The investigations were conducted the vineyards of Mercurey (Burgundy, France), characterized by important issues related to soil loss, flash floods and associated management infrastructures maintenance. The methodology is based on two main steps that include (1) field investigations and (2) modelling. The field investigations consists in DEM acquisition by LiDAR imaging from a drone, soil mapping and human infrastructures impacting runoff classification and mapping (such as crop rows, storm water-basins, drainage network, roads, etc.). These data aims at supplying the models with field observations. The modelling strategy is based on two main steps: First, the modelling of soil sensitivity to erosion, using the spatial application of the RUSLE equation. Secondly, to assess the sediment connectivity in this area, a model based on graph theory developed by Cossart and Fressard (2017) is tested. The results allow defining the influence of different anthropogenic structures on the sediment connectivity and soil erosion at the basin scale. A set of sub-basins influenced by various anthropogenic infrastructures have been identified and show contrasted sensitivities to erosion. The modelling of sediment connectivity show that the runoff pattern is strongly influenced by the vine rows orientation and the drainage network. I has also permitted to identify non collected (by storm water-basins) areas that strongly contribute to the turbid floods sediment supply and to soil loss during high intensity precipitations events.

The oral-systemic disease connection: a retrospective study.

PubMed

Joseph, Bobby K; Kullman, Leif; Sharma, Prem N

2016-11-01

The study aimed at determining the association between oral disease and systemic health based on panoramic radiographs and general health of patients treated at Kuwait University Dental Center. The objective was to determine whether individuals exhibiting good oral health have lower propensity to systemic diseases. A total of 1000 adult patients treated at Kuwait University Dental Center were randomly selected from the patient's records. The general health of patients was assessed from the medical history of each patient recorded during their visit to the clinic. The number of reported diseases and serious symptoms were used to develop a medical index. The oral health of these patients was assessed from panoramic radiographs to create an oral index by evaluating such parameters as caries, periodontitis, periapical lesions, pericoronitis, and tooth loss. In a total of 887 patients, 43.8 % had an oral index between 3 and 8, of which significantly higher (62.1 %) patients were with medical conditions compared to those without (33.2 %; p < 0.001). The Spearmans's correlation (rho') revealed a positive correlation (rho' = 0.360, p 0.001) between oral and medical index. Partial correlation, while controlling demographics, gender, nationality, and age, also showed a significant positive correlation (p < 0.001) between medical and oral index. The findings of this study showed a significant association between oral health and general health and confirmed the findings of previous reports as regards the existing correlation between dental infections and medical disorders. These results are not indicative of a causal relationship when the diagnosis of oral disease was based primarily on radiographic findings. Future research needs to include prospective clinical and interventional studies. The significance of the oral-systemic disease connection highlights the importance of preventing and treating oral disease which have profound medical implications on general health.

The effects of habitat connectivity and regional heterogeneity on artificial pond metacommunities.

PubMed

Pedruski, Michael T; Arnott, Shelley E

2011-05-01

Habitat connectivity and regional heterogeneity represent two factors likely to affect biodiversity across different spatial scales. We performed a 3 × 2 factorial design experiment to investigate the effects of connectivity, heterogeneity, and their interaction on artificial pond communities of freshwater invertebrates at the local (α), among-community (β), and regional (γ) scales. Despite expectations that the effects of connectivity would depend on levels of regional heterogeneity, no significant interactions were found for any diversity index investigated at any spatial scale. While observed responses of biodiversity to connectivity and heterogeneity depended to some extent on the diversity index and spatial partitioning formula used, the general pattern shows that these factors largely act at the β scale, as opposed to the α or γ scales. We conclude that the major role of connectivity in aquatic invertebrate communities is to act as a homogenizing force with relatively little effect on diversity at the α or γ levels. Conversely, heterogeneity acts as a force maintaining differences between communities.

Thermal history of sedimentary basins, maturation indices, and kinetics of oil and gas generation

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

Tissot, B.P.; Pelet, R.; Ungerer, P.

1987-12-01

Temperature is the most sensitive parameter in hydrocarbon generation. Thus, reconstruction of temperature history is essential when evaluating petroleum prospects. No measurable parameter can be directly converted to paleotemperature. Maturation indices such as vitrinite reflectance, T/sub max/ from Rock-Eval pyrolysis, spore coloration, Thermal Alteration Index (TAI), or concentration of biological markers offer an indirect approach. All these indices are a function of the thermal history through rather complex kinetics, frequently influenced by the type of organic matter. Their significance and validity are reviewed. Besides the problems of identification (e.g. vitrinite) and interlaboratory calibration, it is important to simultaneously interpret kerogenmore » type and maturation and to avoid difficult conversions from one index to another. Geodynamic models, where structural and thermal histories are connected, are another approach to temperature reconstruction which could be calibrated against the present distribution of temperature and the present value of maturation indices. Kinetics of kerogen decomposition controls the amount and composition of hydrocarbons generated. An empirical time-temperature index (TTI), originally introduced by Lopatin, does not allow such a quantitative evaluation. Due to several limitations (no provision for different types of kerogen and different rates of reactions, poor calibration on vitrinite reflectance), it is of limited interest unless one has no access to a desk-top computer. Kinetic models, based on a specific calibration made on actual source rock samples, can simulate the evolution of all types of organic matter and can provide a quantitative evaluation of oil and gas generated. 29 figures.« less

Complementary Network-Based Approaches for Exploring Genetic Structure and Functional Connectivity in Two Vulnerable, Endemic Ground Squirrels

PubMed Central

Zero, Victoria H.; Barocas, Adi; Jochimsen, Denim M.; Pelletier, Agnès; Giroux-Bougard, Xavier; Trumbo, Daryl R.; Castillo, Jessica A.; Evans Mack, Diane; Linnell, Mark A.; Pigg, Rachel M.; Hoisington-Lopez, Jessica; Spear, Stephen F.; Murphy, Melanie A.; Waits, Lisette P.

2017-01-01

The persistence of small populations is influenced by genetic structure and functional connectivity. We used two network-based approaches to understand the persistence of the northern Idaho ground squirrel (Urocitellus brunneus) and the southern Idaho ground squirrel (U. endemicus), two congeners of conservation concern. These graph theoretic approaches are conventionally applied to social or transportation networks, but here are used to study population persistence and connectivity. Population graph analyses revealed that local extinction rapidly reduced connectivity for the southern species, while connectivity for the northern species could be maintained following local extinction. Results from gravity models complemented those of population graph analyses, and indicated that potential vegetation productivity and topography drove connectivity in the northern species. For the southern species, development (roads) and small-scale topography reduced connectivity, while greater potential vegetation productivity increased connectivity. Taken together, the results of the two network-based methods (population graph analyses and gravity models) suggest the need for increased conservation action for the southern species, and that management efforts have been effective at maintaining habitat quality throughout the current range of the northern species. To prevent further declines, we encourage the continuation of management efforts for the northern species, whereas conservation of the southern species requires active management and additional measures to curtail habitat fragmentation. Our combination of population graph analyses and gravity models can inform conservation strategies of other species exhibiting patchy distributions. PMID:28659969

Complementary Network-Based Approaches for Exploring Genetic Structure and Functional Connectivity in Two Vulnerable, Endemic Ground Squirrels.

PubMed

Zero, Victoria H; Barocas, Adi; Jochimsen, Denim M; Pelletier, Agnès; Giroux-Bougard, Xavier; Trumbo, Daryl R; Castillo, Jessica A; Evans Mack, Diane; Linnell, Mark A; Pigg, Rachel M; Hoisington-Lopez, Jessica; Spear, Stephen F; Murphy, Melanie A; Waits, Lisette P

2017-01-01

The persistence of small populations is influenced by genetic structure and functional connectivity. We used two network-based approaches to understand the persistence of the northern Idaho ground squirrel ( Urocitellus brunneus) and the southern Idaho ground squirrel ( U. endemicus ), two congeners of conservation concern. These graph theoretic approaches are conventionally applied to social or transportation networks, but here are used to study population persistence and connectivity. Population graph analyses revealed that local extinction rapidly reduced connectivity for the southern species, while connectivity for the northern species could be maintained following local extinction. Results from gravity models complemented those of population graph analyses, and indicated that potential vegetation productivity and topography drove connectivity in the northern species. For the southern species, development (roads) and small-scale topography reduced connectivity, while greater potential vegetation productivity increased connectivity. Taken together, the results of the two network-based methods (population graph analyses and gravity models) suggest the need for increased conservation action for the southern species, and that management efforts have been effective at maintaining habitat quality throughout the current range of the northern species. To prevent further declines, we encourage the continuation of management efforts for the northern species, whereas conservation of the southern species requires active management and additional measures to curtail habitat fragmentation. Our combination of population graph analyses and gravity models can inform conservation strategies of other species exhibiting patchy distributions.

Studying the Transfer of Magnetic Helicity in Solar Active Regions with the Connectivity-based Helicity Flux Density Method

NASA Astrophysics Data System (ADS)

Dalmasse, K.; Pariat, É.; Valori, G.; Jing, J.; Démoulin, P.

2018-01-01

In the solar corona, magnetic helicity slowly and continuously accumulates in response to plasma flows tangential to the photosphere and magnetic flux emergence through it. Analyzing this transfer of magnetic helicity is key for identifying its role in the dynamics of active regions (ARs). The connectivity-based helicity flux density method was recently developed for studying the 2D and 3D transfer of magnetic helicity in ARs. The method takes into account the 3D nature of magnetic helicity by explicitly using knowledge of the magnetic field connectivity, which allows it to faithfully track the photospheric flux of magnetic helicity. Because the magnetic field is not measured in the solar corona, modeled 3D solutions obtained from force-free magnetic field extrapolations must be used to derive the magnetic connectivity. Different extrapolation methods can lead to markedly different 3D magnetic field connectivities, thus questioning the reliability of the connectivity-based approach in observational applications. We address these concerns by applying this method to the isolated and internally complex AR 11158 with different magnetic field extrapolation models. We show that the connectivity-based calculations are robust to different extrapolation methods, in particular with regard to identifying regions of opposite magnetic helicity flux. We conclude that the connectivity-based approach can be reliably used in observational analyses and is a promising tool for studying the transfer of magnetic helicity in ARs and relating it to their flaring activity.

Alterations of white matter structural networks in patients with non-neuropsychiatric systemic lupus erythematosus identified by probabilistic tractography and connectivity-based analyses.

PubMed

Xu, Man; Tan, Xiangliang; Zhang, Xinyuan; Guo, Yihao; Mei, Yingjie; Feng, Qianjin; Xu, Yikai; Feng, Yanqiu

2017-01-01

Systemic lupus erythematosus (SLE) is a chronic inflammatory female-predominant autoimmune disease that can affect the central nervous system and exhibit neuropsychiatric symptoms. In SLE patients without neuropsychiatric symptoms (non-NPSLE), recent diffusion tensor imaging studies showed white matter abnormalities in their brains. The present study investigated the entire brain white matter structural connectivity in non-NPSLE patients by using probabilistic tractography and connectivity-based analyses. Whole-brain structural networks of 29 non-NPSLE patients and 29 healthy controls (HCs) were examined. The structural networks were constructed with interregional probabilistic connectivity. Graph theory analysis was performed to investigate the topological properties, and network-based statistic was employed to assess the alterations of the interregional connections among non-NPSLE patients and controls. Compared with HCs, non-NPSLE patients demonstrated significantly decreased global and local network efficiencies and showed increased characteristic path length. This finding suggests that the global integration and local specialization were impaired. Moreover, the regional properties (nodal efficiency and degree) in the frontal, occipital, and cingulum regions of the non-NPSLE patients were significantly changed and negatively correlated with the disease activity index. The distribution pattern of the hubs measured by nodal degree was altered in the patient group. Finally, the non-NPSLE group exhibited decreased structural connectivity in the left median cingulate-centered component and increased connectivity in the left precuneus-centered component and right middle temporal lobe-centered component. This study reveals an altered topological organization of white matter networks in non-NPSLE patients. Furthermore, this research provides new insights into the structural disruptions underlying the functional and neurocognitive deficits in non-NPSLE patients.

Examining Neuronal Connectivity and Its Role in Learning and Memory

NASA Astrophysics Data System (ADS)

Gala, Rohan

Learning and long-term memory formation are accompanied with changes in the patterns and weights of synaptic connections in the underlying neuronal network. However, the fundamental rules that drive connectivity changes, and the precise structure-function relationships within neuronal networks remain elusive. Technological improvements over the last few decades have enabled the observation of large but specific subsets of neurons and their connections in unprecedented detail. Devising robust and automated computational methods is critical to distill information from ever-increasing volumes of raw experimental data. Moreover, statistical models and theoretical frameworks are required to interpret the data and assemble evidence into understanding of brain function. In this thesis, I first describe computational methods to reconstruct connectivity based on light microscopy imaging experiments. Next, I use these methods to quantify structural changes in connectivity based on in vivo time-lapse imaging experiments. Finally, I present a theoretical model of associative learning that can explain many stereotypical features of experimentally observed connectivity.

PPSITE - A New Method of Site Evaluation for Longleaf Pine: Model Development and User's Guide

Treesearch

Constance A. Harrington

1990-01-01

A model was developed to predict site index (base age 50 years) for longleaf pine (Pinus palustris Mill.). The model, named PPSITE, was based on soil characteristics, site location on the landscape, and land history. The model was constrained so that the relationship between site index and each soil-site variable was consistent with what was known...

Connectivity-based neurofeedback: Dynamic causal modeling for real-time fMRI☆

PubMed Central

Koush, Yury; Rosa, Maria Joao; Robineau, Fabien; Heinen, Klaartje; W. Rieger, Sebastian; Weiskopf, Nikolaus; Vuilleumier, Patrik; Van De Ville, Dimitri; Scharnowski, Frank

2013-01-01

Neurofeedback based on real-time fMRI is an emerging technique that can be used to train voluntary control of brain activity. Such brain training has been shown to lead to behavioral effects that are specific to the functional role of the targeted brain area. However, real-time fMRI-based neurofeedback so far was limited to mainly training localized brain activity within a region of interest. Here, we overcome this limitation by presenting near real-time dynamic causal modeling in order to provide feedback information based on connectivity between brain areas rather than activity within a single brain area. Using a visual–spatial attention paradigm, we show that participants can voluntarily control a feedback signal that is based on the Bayesian model comparison between two predefined model alternatives, i.e. the connectivity between left visual cortex and left parietal cortex vs. the connectivity between right visual cortex and right parietal cortex. Our new approach thus allows for training voluntary control over specific functional brain networks. Because most mental functions and most neurological disorders are associated with network activity rather than with activity in a single brain region, this novel approach is an important methodological innovation in order to more directly target functionally relevant brain networks. PMID:23668967

Advances in the spatially distributed ages-w model: parallel computation, java connection framework (JCF) integration, and streamflow/nitrogen dynamics assessment

USDA-ARS?s Scientific Manuscript database

AgroEcoSystem-Watershed (AgES-W) is a modular, Java-based spatially distributed model which implements hydrologic and water quality (H/WQ) simulation components under the Java Connection Framework (JCF) and the Object Modeling System (OMS) environmental modeling framework. AgES-W is implicitly scala...

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture

PubMed Central

Meszlényi, Regina J.; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network. PMID:29089883

Resting State fMRI Functional Connectivity-Based Classification Using a Convolutional Neural Network Architecture.

PubMed

Meszlényi, Regina J; Buza, Krisztian; Vidnyánszky, Zoltán

2017-01-01

Machine learning techniques have become increasingly popular in the field of resting state fMRI (functional magnetic resonance imaging) network based classification. However, the application of convolutional networks has been proposed only very recently and has remained largely unexplored. In this paper we describe a convolutional neural network architecture for functional connectome classification called connectome-convolutional neural network (CCNN). Our results on simulated datasets and a publicly available dataset for amnestic mild cognitive impairment classification demonstrate that our CCNN model can efficiently distinguish between subject groups. We also show that the connectome-convolutional network is capable to combine information from diverse functional connectivity metrics and that models using a combination of different connectivity descriptors are able to outperform classifiers using only one metric. From this flexibility follows that our proposed CCNN model can be easily adapted to a wide range of connectome based classification or regression tasks, by varying which connectivity descriptor combinations are used to train the network.

Real time bolt preload monitoring using piezoceramic transducers and time reversal technique—a numerical study with experimental verification

NASA Astrophysics Data System (ADS)

Parvasi, Seyed Mohammad; Ho, Siu Chun Michael; Kong, Qingzhao; Mousavi, Reza; Song, Gangbing

2016-08-01

Bolted joints are ubiquitous structural elements, and form critical connections in mechanical and civil structures. As such, loosened bolted joints may lead to catastrophic failures of these structures, thus inspiring a growing interest in monitoring of bolted joints. A novel energy based wave method is proposed in this study to monitor the axial load of bolted joint connections. In this method, the time reversal technique was used to focus the energy of a piezoelectric (PZT)-generated ultrasound wave from one side of the interface to be measured as a signal peak by another PZT transducer on the other side of the interface. A tightness index (TI) was defined and used to correlate the peak amplitude to the bolt axial load. The TI bypasses the need for more complex signal processing required in other energy-based methods. A coupled, electro-mechanical analysis with elasto-plastic finite element method was used to simulate and analyze the PZT based ultrasonic wave propagation through the interface of two steel plates connected by a single nut and bolt connection. Numerical results, backed by experimental results from testing on a bolted connection between two steel plates, revealed that the peak amplitude of the focused signal increases as the bolt preload (torque level) increases due to the enlarging true contact area of the steel plates. The amplitude of the focused peak saturates and the TI reaches unity as the bolt axial load reaches a threshold value. These conditions are associated with the maximum possible true contact area between the surfaces of the bolted connection.

Groundwater similarity across a watershed derived from time-warped and flow-corrected time series

NASA Astrophysics Data System (ADS)

Rinderer, M.; McGlynn, B. L.; van Meerveld, H. J.

2017-05-01

Information about catchment-scale groundwater dynamics is necessary to understand how catchments store and release water and why water quantity and quality varies in streams. However, groundwater level monitoring is often restricted to a limited number of sites. Knowledge of the factors that determine similarity between monitoring sites can be used to predict catchment-scale groundwater storage and connectivity of different runoff source areas. We used distance-based and correlation-based similarity measures to quantify the spatial and temporal differences in shallow groundwater similarity for 51 monitoring sites in a Swiss prealpine catchment. The 41 months long time series were preprocessed using Dynamic Time-Warping and a Flow-corrected Time Transformation to account for small timing differences and bias toward low-flow periods. The mean distance-based groundwater similarity was correlated to topographic indices, such as upslope contributing area, topographic wetness index, and local slope. Correlation-based similarity was less related to landscape position but instead revealed differences between seasons. Analysis of variance and partial Mantel tests showed that landscape position, represented by the topographic wetness index, explained 52% of the variability in mean distance-based groundwater similarity, while spatial distance, represented by the Euclidean distance, explained only 5%. The variability in distance-based similarity and correlation-based similarity between groundwater and streamflow time series was significantly larger for midslope locations than for other landscape positions. This suggests that groundwater dynamics at these midslope sites, which are important to understand runoff source areas and hydrological connectivity at the catchment scale, are most difficult to predict.

The role of group index engineering in series-connected photonic crystal microcavities for high density sensor microarrays

PubMed Central

Zou, Yi; Chakravarty, Swapnajit; Zhu, Liang; Chen, Ray T.

2014-01-01

We experimentally demonstrate an efficient and robust method for series connection of photonic crystal microcavities that are coupled to photonic crystal waveguides in the slow light transmission regime. We demonstrate that group index taper engineering provides excellent optical impedance matching between the input and output strip waveguides and the photonic crystal waveguide, a nearly flat transmission over the entire guided mode spectrum and clear multi-resonance peaks corresponding to individual microcavities that are connected in series. Series connected photonic crystal microcavities are further multiplexed in parallel using cascaded multimode interference power splitters to generate a high density silicon nanophotonic microarray comprising 64 photonic crystal microcavity sensors, all of which are interrogated simultaneously at the same instant of time. PMID:25316921

High figure of merit ultra-compact 3-channel parallel-connected photonic crystal mini-hexagonal-H1 defect microcavity sensor array

NASA Astrophysics Data System (ADS)

Wang, Chunhong; Sun, Fujun; Fu, Zhongyuan; Ding, Zhaoxiang; Wang, Chao; Zhou, Jian; Wang, Jiawen; Tian, Huiping

2017-08-01

In this paper, a photonic crystal (PhC) butt-coupled mini-hexagonal-H1 defect (MHHD) microcavity sensor is proposed. The MHHD microcavity is designed by introducing six mini-holes into the initial H1 defect region. Further, based on a well-designed 1 ×3 PhC Beam Splitter and three optimal MHHD microcavity sensors with different lattice constants (a), a 3-channel parallel-connected PhC sensor array on monolithic silicon on insulator (SOI) is proposed. Finite-difference time-domain (FDTD) simulations method is performed to demonstrate the high performance of our structures. As statistics show, the quality factor (Q) of our optimal MHHD microcavity attains higher than 7×104, while the sensitivity (S) reaches up to 233 nm/RIU(RIU = refractive index unit). Thus, the figure of merit (FOM) >104 of the sensor is obtained, which is enhanced by two orders of magnitude compared to the previous butt-coupled sensors [1-4]. As for the 3-channel parallel-connected PhC MHHD microcavity sensor array, the FOMs of three independent MHHD microcavity sensors are 8071, 8250 and 8250, respectively. In addition, the total footprint of the proposed 3-channel parallel-connected PhC sensor array is ultra-compactness of 12.5 μm ×31 μm (width × length). Therefore, the proposed high FOM sensor array is an ideal platform for realizing ultra-compact highly parallel refractive index (RI) sensing.

Node-based measures of connectivity in genetic networks.

PubMed

Koen, Erin L; Bowman, Jeff; Wilson, Paul J

2016-01-01

At-site environmental conditions can have strong influences on genetic connectivity, and in particular on the immigration and settlement phases of dispersal. However, at-site processes are rarely explored in landscape genetic analyses. Networks can facilitate the study of at-site processes, where network nodes are used to model site-level effects. We used simulated genetic networks to compare and contrast the performance of 7 node-based (as opposed to edge-based) genetic connectivity metrics. We simulated increasing node connectivity by varying migration in two ways: we increased the number of migrants moving between a focal node and a set number of recipient nodes, and we increased the number of recipient nodes receiving a set number of migrants. We found that two metrics in particular, the average edge weight and the average inverse edge weight, varied linearly with simulated connectivity. Conversely, node degree was not a good measure of connectivity. We demonstrated the use of average inverse edge weight to describe the influence of at-site habitat characteristics on genetic connectivity of 653 American martens (Martes americana) in Ontario, Canada. We found that highly connected nodes had high habitat quality for marten (deep snow and high proportions of coniferous and mature forest) and were farther from the range edge. We recommend the use of node-based genetic connectivity metrics, in particular, average edge weight or average inverse edge weight, to model the influences of at-site habitat conditions on the immigration and settlement phases of dispersal. © 2015 John Wiley & Sons Ltd.

Computing the Ediz eccentric connectivity index of discrete dynamic structures

NASA Astrophysics Data System (ADS)

Wu, Hualong; Kamran Siddiqui, Muhammad; Zhao, Bo; Gan, Jianhou; Gao, Wei

2017-06-01

From the earlier studies in physical and chemical sciences, it is found that the physico-chemical characteristics of chemical compounds are internally connected with their molecular structures. As a theoretical basis, it provides a new way of thinking by analyzing the molecular structure of the compounds to understand their physical and chemical properties. In our article, we study the physico-chemical properties of certain molecular structures via computing the Ediz eccentric connectivity index from mathematical standpoint. The results we yielded mainly apply to the techniques of distance and degree computation of mathematical derivation, and the conclusions have guiding significance in physical engineering.

An analysis of mathematical connection ability based on student learning style on visualization auditory kinesthetic (VAK) learning model with self-assessment

NASA Astrophysics Data System (ADS)

Apipah, S.; Kartono; Isnarto

2018-03-01

This research aims to analyze the quality of VAK learning with self-assessment toward the ability of mathematical connection performed by students and to analyze students’ mathematical connection ability based on learning styles in VAK learning model with self-assessment. This research applies mixed method type with concurrent embedded design. The subject of this research consists of VIII grade students from State Junior High School 9 Semarang who apply visual learning style, auditory learning style, and kinesthetic learning style. The data of learning style is collected by using questionnaires, the data of mathematical connection ability is collected by performing tests, and the data of self-assessment is collected by using assessment sheets. The quality of learning is qualitatively valued from planning stage, realization stage, and valuation stage. The result of mathematical connection ability test is analyzed quantitatively by mean test, conducting completeness test, mean differentiation test, and mean proportional differentiation test. The result of the research shows that VAK learning model results in well-qualified learning regarded from qualitative and quantitative sides. Students with visual learning style perform the highest mathematical connection ability, students with kinesthetic learning style perform average mathematical connection ability, and students with auditory learning style perform the lowest mathematical connection ability.

A cloud-based framework for large-scale traditional Chinese medical record retrieval.

PubMed

Liu, Lijun; Liu, Li; Fu, Xiaodong; Huang, Qingsong; Zhang, Xianwen; Zhang, Yin

2018-01-01

Electronic medical records are increasingly common in medical practice. The secondary use of medical records has become increasingly important. It relies on the ability to retrieve the complete information about desired patient populations. How to effectively and accurately retrieve relevant medical records from large- scale medical big data is becoming a big challenge. Therefore, we propose an efficient and robust framework based on cloud for large-scale Traditional Chinese Medical Records (TCMRs) retrieval. We propose a parallel index building method and build a distributed search cluster, the former is used to improve the performance of index building, and the latter is used to provide high concurrent online TCMRs retrieval. Then, a real-time multi-indexing model is proposed to ensure the latest relevant TCMRs are indexed and retrieved in real-time, and a semantics-based query expansion method and a multi- factor ranking model are proposed to improve retrieval quality. Third, we implement a template-based visualization method for displaying medical reports. The proposed parallel indexing method and distributed search cluster can improve the performance of index building and provide high concurrent online TCMRs retrieval. The multi-indexing model can ensure the latest relevant TCMRs are indexed and retrieved in real-time. The semantics expansion method and the multi-factor ranking model can enhance retrieval quality. The template-based visualization method can enhance the availability and universality, where the medical reports are displayed via friendly web interface. In conclusion, compared with the current medical record retrieval systems, our system provides some advantages that are useful in improving the secondary use of large-scale traditional Chinese medical records in cloud environment. The proposed system is more easily integrated with existing clinical systems and be used in various scenarios. Copyright © 2017. Published by Elsevier Inc.

Link prediction based on local weighted paths for complex networks

NASA Astrophysics Data System (ADS)

Yao, Yabing; Zhang, Ruisheng; Yang, Fan; Yuan, Yongna; Hu, Rongjing; Zhao, Zhili

As a significant problem in complex networks, link prediction aims to find the missing and future links between two unconnected nodes by estimating the existence likelihood of potential links. It plays an important role in understanding the evolution mechanism of networks and has broad applications in practice. In order to improve prediction performance, a variety of structural similarity-based methods that rely on different topological features have been put forward. As one topological feature, the path information between node pairs is utilized to calculate the node similarity. However, many path-dependent methods neglect the different contributions of paths for a pair of nodes. In this paper, a local weighted path (LWP) index is proposed to differentiate the contributions between paths. The LWP index considers the effect of the link degrees of intermediate links and the connectivity influence of intermediate nodes on paths to quantify the path weight in the prediction procedure. The experimental results on 12 real-world networks show that the LWP index outperforms other seven prediction baselines.

A method to assess longitudinal riverine connectivity in tropical streams dominated by migratory biota

USGS Publications Warehouse

Crook, K.E.; Pringle, C.M.; Freeman, Mary C.

2009-01-01

1. One way in which dams affect ecosystem function is by altering the distribution and abundance of aquatic species. 2. Previous studies indicate that migratory shrimps have significant effects on ecosystem processes in Puerto Rican streams, but are vulnerable to impediments to upstream or downstream passage, such as dams and associated water intakes where stream water is withdrawn for human water supplies. Ecological effects of dams and water withdrawals from streams depend on spatial context and temporal variability of flow in relation to the amount of water withdrawn. 3. This paper presents a conceptual model for estimating the probability that an individual shrimp is able to migrate from a stream's headwaters to the estuary as a larva, and then return to the headwaters as a juvenile, given a set of dams and water withdrawals in the stream network. The model is applied to flow and withdrawal data for a set of dams and water withdrawals in the Caribbean National Forest (CNF) in Puerto Rico. 4. The index of longitudinal riverine connectivity (ILRC), is used to classify 17 water intakes in streams draining the CNF as having low, moderate, or high connectivity in terms of shrimp migration in both directions. An in-depth comparison of two streams showed that the stream characterized by higher water withdrawal had low connectivity, even during wet periods. Severity of effects is illustrated by a drought year, where the most downstream intake caused 100% larval shrimp mortality 78% of the year. 5. The ranking system provided by the index can be used as a tool for conservation ecologists and water resource managers to evaluate the relative vulnerability of migratory biota in streams, across different scales (reach-network), to seasonally low flows and extended drought. This information can be used to help evaluate the environmental tradeoffs of future water withdrawals. ?? 2008 John Wiley & Sons, Ltd.

Underlying dynamics of typical fluctuations of an emerging market price index: The Heston model from minutes to months

NASA Astrophysics Data System (ADS)

Vicente, Renato; de Toledo, Charles M.; Leite, Vitor B. P.; Caticha, Nestor

2006-02-01

We investigate the Heston model with stochastic volatility and exponential tails as a model for the typical price fluctuations of the Brazilian São Paulo Stock Exchange Index (IBOVESPA). Raw prices are first corrected for inflation and a period spanning 15 years characterized by memoryless returns is chosen for the analysis. Model parameters are estimated by observing volatility scaling and correlation properties. We show that the Heston model with at least two time scales for the volatility mean reverting dynamics satisfactorily describes price fluctuations ranging from time scales larger than 20 min to 160 days. At time scales shorter than 20 min we observe autocorrelated returns and power law tails incompatible with the Heston model. Despite major regulatory changes, hyperinflation and currency crises experienced by the Brazilian market in the period studied, the general success of the description provided may be regarded as an evidence for a general underlying dynamics of price fluctuations at intermediate mesoeconomic time scales well approximated by the Heston model. We also notice that the connection between the Heston model and Ehrenfest urn models could be exploited for bringing new insights into the microeconomic market mechanics.

Hydro-geomorphic connectivity and landslide features extraction to identifying potential threats and hazardous areas

NASA Astrophysics Data System (ADS)

Tarolli, Paolo; Fuller, Ian C.; Basso, Federica; Cavalli, Marco; Sofia, Giulia

2017-04-01

Hydro-geomorphic connectivity has significantly emerged as a new concept to understand the transfer of surface water and sediment through landscapes. A further scientific challenge is determining how the concept can be used to enable sustainable land and water management. This research proposes an interesting approach to integrating remote sensing techniques, connectivity theory, and geomorphometry based on high-resolution digital terrain model (HR-DTMs) to automatically extract landslides crowns and gully erosion, to determine the different rate of connectivity among the main extracted features and the river network, and thus determine a possible categorization of hazardous areas. The study takes place in two mountainous regions in the Wellington Region (New Zealand). The methodology is a three step approach. Firstly, we performed an automatic detection of the likely landslides crowns through the use of thresholds obtained by the statistical analysis of the variability of landform curvature. After that, the research considered the Connectivity Index to analyse how a complex and rugged topography induces large variations in erosion and sediment delivery in the two catchments. Lastly, the two methods have been integrated to create a unique procedure able to classify the different rate of connectivity among the main features and the river network and thus identifying potential threats and hazardous areas. The methodology is fast, and it can produce a detailed and updated inventory map that could be a key tool for erosional and sediment delivery hazard mitigation. This fast and simple method can be a useful tool to manage emergencies giving priorities to more failure-prone zones. Furthermore, it could be considered to do a preliminary interpretations of geomorphological phenomena and more in general, it could be the base to develop inventory maps. References Cavalli M, Trevisani S, Comiti F, Marchi L. 2013. Geomorphometric assessment of spatial sediment connectivity in small Alpine catchments. Geomorphology 188: 31-41 DOI: 10.1016/j.geomorph.2012.05.007 Sofia G, Dalla Fontana G, Tarolli P. 2014. High-resolution topography and anthropogenic feature extraction: testing geomorphometric parameters in floodplains. Hydrological Processes 28 (4): 2046-2061 DOI: 10.1002/hyp.9727 Tarolli P, Sofia G, Dalla Fontana G. 2012. Geomorphic features extraction from high-resolution topography: landslide crowns and bank erosion. Natural Hazards 61 (1): 65-83 DOI: 10.1007/s11069-010-9695-2

An objective decision model of power grid environmental protection based on environmental influence index and energy-saving and emission-reducing index

NASA Astrophysics Data System (ADS)

Feng, Jun-shu; Jin, Yan-ming; Hao, Wei-hua

2017-01-01

Based on modelling the environmental influence index of power transmission and transformation project and energy-saving and emission-reducing index of source-grid-load of power system, this paper establishes an objective decision model of power grid environmental protection, with constraints of power grid environmental protection objectives being legal and economical, and considering both positive and negative influences of grid on the environmental in all-life grid cycle. This model can be used to guide the programming work of power grid environmental protection. A numerical simulation of Jiangsu province’s power grid environmental protection objective decision model has been operated, and the results shows that the maximum goal of energy-saving and emission-reducing benefits would be reached firstly as investment increasing, and then the minimum goal of environmental influence.

Chemistry explained by topology: an alternative approach.

PubMed

Galvez, Jorge; Villar, Vincent M; Galvez-Llompart, Maria; Amigó, José M

2011-05-01

Molecular topology can be considered an application of graph theory in which the molecular structure is characterized through a set of graph-theoretical descriptors called topological indices. Molecular topology has found applications in many different fields, particularly in biology, chemistry, and pharmacology. The first topological index was introduced by H. Wiener in 1947 [1]. Although its very first application was the prediction of the boiling points of the alkanes, the Wiener index has demonstrated since then a predictive capability far beyond that. Along with the Wiener index, in this paper we focus on a few pioneering topological indices, just to illustrate the connection between physicochemical properties and molecular connectivity.

Automated map sharpening by maximization of detail and connectivity

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

Terwilliger, Thomas C.; Sobolev, Oleg V.; Afonine, Pavel V.

An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures inmore » a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a model withBfactors (atomic displacement factors; ADPs) set to zero. Finally, this model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.« less

Automated map sharpening by maximization of detail and connectivity

DOE PAGES

Terwilliger, Thomas C.; Sobolev, Oleg V.; Afonine, Pavel V.; ...

2018-05-18

An algorithm for automatic map sharpening is presented that is based on optimization of the detail and connectivity of the sharpened map. The detail in the map is reflected in the surface area of an iso-contour surface that contains a fixed fraction of the volume of the map, where a map with high level of detail has a high surface area. The connectivity of the sharpened map is reflected in the number of connected regions defined by the same iso-contour surfaces, where a map with high connectivity has a small number of connected regions. By combining these two measures inmore » a metric termed the `adjusted surface area', map quality can be evaluated in an automated fashion. This metric was used to choose optimal map-sharpening parameters without reference to a model or other interpretations of the map. Map sharpening by optimization of the adjusted surface area can be carried out for a map as a whole or it can be carried out locally, yielding a locally sharpened map. To evaluate the performance of various approaches, a simple metric based on map–model correlation that can reproduce visual choices of optimally sharpened maps was used. The map–model correlation is calculated using a model withBfactors (atomic displacement factors; ADPs) set to zero. Finally, this model-based metric was used to evaluate map sharpening and to evaluate map-sharpening approaches, and it was found that optimization of the adjusted surface area can be an effective tool for map sharpening.« less

Fringes in FTIR spectroscopy revisited: understanding and modelling fringes in infrared spectroscopy of thin films.

PubMed

Konevskikh, Tatiana; Ponossov, Arkadi; Blümel, Reinhold; Lukacs, Rozalia; Kohler, Achim

2015-06-21

The appearance of fringes in the infrared spectroscopy of thin films seriously hinders the interpretation of chemical bands because fringes change the relative peak heights of chemical spectral bands. Thus, for the correct interpretation of chemical absorption bands, physical properties need to be separated from chemical characteristics. In the paper at hand we revisit the theory of the scattering of infrared radiation at thin absorbing films. Although, in general, scattering and absorption are connected by a complex refractive index, we show that for the scattering of infrared radiation at thin biological films, fringes and chemical absorbance can in good approximation be treated as additive. We further introduce a model-based pre-processing technique for separating fringes from chemical absorbance by extended multiplicative signal correction (EMSC). The technique is validated by simulated and experimental FTIR spectra. It is further shown that EMSC, as opposed to other suggested filtering methods for the removal of fringes, does not remove information related to chemical absorption.

Bulk boundary correspondence and the existence of Majorana bound states on the edges of 2D topological superconductors

NASA Astrophysics Data System (ADS)

Sedlmayr, Nicholas; Kaladzhyan, Vardan; Dutreix, Clément; Bena, Cristina

2017-11-01

The bulk-boundary correspondence establishes a connection between the bulk topological index of an insulator or superconductor, and the number of topologically protected edge bands or states. For topological superconductors in two dimensions, the first Chern number is related to the number of protected bands within the bulk energy gap, and is therefore assumed to give the number of Majorana band states in the system. Here we show that this is not necessarily the case. As an example, we consider a hexagonal-lattice topological superconductor based on a model of graphene with Rashba spin-orbit coupling, proximity-induced s -wave superconductivity, and a Zeeman magnetic field. We explore the full Chern number phase diagram of this model, extending what is already known about its parity. We then demonstrate that, despite the high Chern numbers that can be seen in some phases, these do not strictly always contain Majorana bound states.

Runoff thresholds and land-to-marine ecosystem connectivity in a dry tropical setting: St. John, US Virgin Islands

NASA Astrophysics Data System (ADS)

Ramos-Scharron, C. E.; LaFevor, M. C.; Roy, J.

2017-12-01

Developing a conceptually sound yet practical understanding of runoff and sediment delivery from human occupied lands to tropical ocean waters still represents a pivotal need of coral reef management worldwide. In the dry tropical and ephemeral streamflow setting that typifies the small watersheds ( 1s km2) draining the US Virgin Islands, changes in hydrologic and sediment delivery dynamics provoked by unsurfaced road networks represent a major threat to coral reefs and other sensitive marine ecosystems. Through a combined empirical and modeling approach, this study evaluates how road building and associated stormflow restoration strategies affect rainfall thresholds for runoff generation at varying spatial scales and their impact on land-to-sea connectivity. Rainfall thresholds and runoff coefficients for precipitation excess on unpaved roads are 2-3 mm and 22-30% (respectively) or a full order of magnitude different from those for undisturbed hillslopes and watersheds. Here we discuss the use of a `volume-to-breakthrough' inspired index to predict the potential of road runoff to reach downslope portions of the watershed and the coastline as runon. The index integrates the effects of storm-by-storm runoff accumulation for every road drainage point with its flow distance to specific locations along the stream network. While large runoff volumes and short flow distances imply a relatively high connectivity potential, small volumes and long distances are associated to low delivery potential. The index has proven able to discern observed runoff responses under a variety of road-stream network scenarios and rainfall conditions. These results enhance our understanding of ephemeral stream hydrology and are serving to improve coral reef management strategies throughout the Northeastern Caribbean.

Evaluation of Multispectral Based Radiative Transfer Model Inversion to Estimate Leaf Area Index in Wheat

USDA-ARS?s Scientific Manuscript database

Leaf area index (LAI) is a critical variable for predicting the growth and productivity of crops. Remote sensing estimates of LAI have relied upon empirical relationships between spectral vegetation indices and ground measurements that are costly to obtain. Radiative transfer model inversion based o...

Creating a Student Price Index. Lesson Plan.

ERIC Educational Resources Information Center

Lewin, Roland

This lesson plan gives students a hands-on understanding of a price index, how it is composed, what it is used for, and some of its limitations. Students then can make the connection to some of the popular price indices such as the Consumer Price Index and the Producer Price Index. The lesson states a purpose; cites learning objectives; suggests…

Research into robotic automation of drilling equipment by the Institute of Mining, UB RAS

NASA Astrophysics Data System (ADS)

Regotunov, AS; Sukhov, RI

2018-03-01

The article discusses the issues connected with the development of instrumentation for the express-determination of strength characteristics of rocks during blasthole drilling in open pit mines. The trial results of the instrumentation are reported in terms of the drilling rate–energy content interrelation determined in the analyses of experimental drilling block data and by the digital model of rock distribution in depth versus drilling complexity index.

Urban growth and landscape connectivity threats assessment at Saguaro National Park, Arizona, USA

USGS Publications Warehouse

Perkl, Ryan; Norman, Laura M.; Mitchell, David; Feller, Mark R.; Smith, Garrett; Wilson, Natalie R.

2018-01-01

Urban and exurban expansion results in habitat and biodiversity loss globally. We hypothesize that a coupled-model approach could connect urban planning for future cities with landscape ecology to consider wildland habitat connectivity. Our work combines urban growth simulations with models of wildlife corridors to examine how species will be impacted by development to test this hypothesis. We leverage a land use change model (SLEUTH) with structural and functional landscape-connectivity modeling techniques to ascertain the spatial extent and locations of connectivity related threats to a national park in southern Arizona, USA, and describe how protected areas might be impacted by urban expansion. Results of projected growth significantly altered structural connectivity (80%) when compared to current (baseline) corridor conditions. Moreover, projected growth impacted functional connectivity differently amongst species, indicating resilience of some species and near-complete displacement of others. We propose that implementing a geospatial-design-based model will allow for a better understanding of the impacts management decisions have on wildlife populations. The application provides the potential to understand both human and environmental impacts of land-system dynamics, critical for long-term sustainability.

Measurement of Scenic Spots Sustainable Capacity Based on PCA-Entropy TOPSIS: A Case Study from 30 Provinces, China

PubMed Central

Liang, Xuedong; Liu, Canmian; Li, Zhi

2017-01-01

In connection with the sustainable development of scenic spots, this paper, with consideration of resource conditions, economic benefits, auxiliary industry scale and ecological environment, establishes a comprehensive measurement model of the sustainable capacity of scenic spots; optimizes the index system by principal components analysis to extract principal components; assigns the weight of principal components by entropy method; analyzes the sustainable capacity of scenic spots in each province of China comprehensively in combination with TOPSIS method and finally puts forward suggestions aid decision-making. According to the study, this method provides an effective reference for the study of the sustainable development of scenic spots and is very significant for considering the sustainable development of scenic spots and auxiliary industries to establish specific and scientific countermeasures for improvement. PMID:29271947

Measurement of Scenic Spots Sustainable Capacity Based on PCA-Entropy TOPSIS: A Case Study from 30 Provinces, China.

PubMed

Liang, Xuedong; Liu, Canmian; Li, Zhi

2017-12-22

In connection with the sustainable development of scenic spots, this paper, with consideration of resource conditions, economic benefits, auxiliary industry scale and ecological environment, establishes a comprehensive measurement model of the sustainable capacity of scenic spots; optimizes the index system by principal components analysis to extract principal components; assigns the weight of principal components by entropy method; analyzes the sustainable capacity of scenic spots in each province of China comprehensively in combination with TOPSIS method and finally puts forward suggestions aid decision-making. According to the study, this method provides an effective reference for the study of the sustainable development of scenic spots and is very significant for considering the sustainable development of scenic spots and auxiliary industries to establish specific and scientific countermeasures for improvement.

2008 GEM Modeling Challenge: Metrics Study of the Dst Index in Physics-Based Magnetosphere and Ring Current Models and in Statistical and Analytic Specifications

NASA Technical Reports Server (NTRS)

Rastaetter, L.; Kuznetsova, M.; Hesse, M.; Pulkkinen, A.; Glocer, A.; Yu, Y.; Meng, X.; Raeder, J.; Wiltberger, M.; Welling, D.;

Time-Dependent Behavior of Diabase and a Nonlinear Creep Model

NASA Astrophysics Data System (ADS)

Yang, Wendong; Zhang, Qiangyong; Li, Shucai; Wang, Shugang

2014-07-01

Triaxial creep tests were performed on diabase specimens from the dam foundation of the Dagangshan hydropower station, and the typical characteristics of creep curves were analyzed. Based on the test results under different stress levels, a new nonlinear visco-elasto-plastic creep model with creep threshold and long-term strength was proposed by connecting an instantaneous elastic Hooke body, a visco-elasto-plastic Schiffman body, and a nonlinear visco-plastic body in series mode. By introducing the nonlinear visco-plastic component, this creep model can describe the typical creep behavior, which includes the primary creep stage, the secondary creep stage, and the tertiary creep stage. Three-dimensional creep equations under constant stress conditions were deduced. The yield approach index (YAI) was used as the criterion for the piecewise creep function to resolve the difficulty in determining the creep threshold value and the long-term strength. The expression of the visco-plastic component was derived in detail and the three-dimensional central difference form was given. An example was used to verify the credibility of the model. The creep parameters were identified, and the calculated curves were in good agreement with the experimental curves, indicating that the model is capable of replicating the physical processes.

Wildfire Risk Mapping over the State of Mississippi: Land Surface Modeling Approach

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

Cooke, William H.; Mostovoy, Georgy; Anantharaj, Valentine G

2012-01-01

Three fire risk indexes based on soil moisture estimates were applied to simulate wildfire probability over the southern part of Mississippi using the logistic regression approach. The fire indexes were retrieved from: (1) accumulated difference between daily precipitation and potential evapotranspiration (P-E); (2) top 10 cm soil moisture content simulated by the Mosaic land surface model; and (3) the Keetch-Byram drought index (KBDI). The P-E, KBDI, and soil moisture based indexes were estimated from gridded atmospheric and Mosaic-simulated soil moisture data available from the North American Land Data Assimilation System (NLDAS-2). Normalized deviations of these indexes from the 31-year meanmore » (1980-2010) were fitted into the logistic regression model describing probability of wildfires occurrence as a function of the fire index. It was assumed that such normalization provides more robust and adequate description of temporal dynamics of soil moisture anomalies than the original (not normalized) set of indexes. The logistic model parameters were evaluated for 0.25 x0.25 latitude/longitude cells and for probability representing at least one fire event occurred during 5 consecutive days. A 23-year (1986-2008) forest fires record was used. Two periods were selected and examined (January mid June and mid September December). The application of the logistic model provides an overall good agreement between empirical/observed and model-fitted fire probabilities over the study area during both seasons. The fire risk indexes based on the top 10 cm soil moisture and KBDI have the largest impact on the wildfire odds (increasing it by almost 2 times in response to each unit change of the corresponding fire risk index during January mid June period and by nearly 1.5 times during mid September-December) observed over 0.25 x0.25 cells located along the state of Mississippi Coast line. This result suggests a rather strong control of fire risk indexes on fire occurrence probability over this region.« less

[Aquatic Ecological Index based on freshwater (ICE(RN-MAE)) for the Rio Negro watershed, Colombia].

PubMed

Forero, Laura Cristina; Longo, Magnolia; John Jairo, Ramirez; Guillermo, Chalar

2014-04-01

Aquatic Ecological Index based on freshwater (ICE(RN-MAE)) for the Rio Negro watershed, Colombia. Available indices to assess the ecological status of rivers in Colombia are mostly based on subjective hypotheses about macroinvertebrate tolerance to pollution, which have important limitations. Here we present the application of a method to establish an index of ecological quality for lotic systems in Colombia. The index, based on macroinvertebrate abundance and physicochemical variables, was developed as an alternative to the BMWP-Col index. The method consists on determining an environmental gradient from correlations between physicochemical variables and abundance. The scores obtained in each sampling point are used in a standardized correlation for a model of weighted averages (WA). In the WA model abundances are also weighted to estimate the optimum and tolerance values of each taxon; using this information we estimated the index of ecological quality based also on macroinvertebrate (ICE(RN-MAE)) abundance in each sampling site. Subsequently, we classified all sites using the index and concentrations of total phosphorus (TP) in a cluster analysis. Using TP and ICE(RN-MAE), mean, maximum, minimum and standard deviation, we defined threshold values corresponding to three categories of ecological status: good, fair and critical.

Modeled Population Connectivity across the Hawaiian Archipelago

PubMed Central

Wren, Johanna L. K.; Kobayashi, Donald R.; Jia, Yanli; Toonen, Robert J.

2016-01-01

We present the first comprehensive estimate of connectivity of passive pelagic particles released from coral reef habitat throughout the Hawaiian Archipelago. Potential connectivity is calculated using a Lagrangian particle transport model coupled offline with currents generated by an oceanographic circulation model, MITgcm. The connectivity matrices show a surprising degree of self-recruitment and directional dispersal towards the northwest, from the Main Hawaiian Islands (MHI) to the northwestern Hawaiian Islands (NWHI). We identify three predicted connectivity breaks in the archipelago, that is, areas in the mid and northern part of the archipelago that have limited connections with surrounding islands and reefs. Predicted regions of limited connectivity generally match observed patterns of genetic structure reported for coral reef species in the uninhabited NWHI, but multiple genetic breaks observed in the inhabited MHI are not explained by passive dispersal. The better congruence in our modeling results based on physical transport of passive particles in the low-lying atolls of the uninhabited NWHI, but not in the anthropogenically impacted high islands of the MHI begs the question: what ultimately controls connectivity in this system? PMID:27930680

A Markovian model of evolving world input-output network

PubMed Central

Isacchini, Giulio

2017-01-01

The initial theoretical connections between Leontief input-output models and Markov chains were established back in 1950s. However, considering the wide variety of mathematical properties of Markov chains, so far there has not been a full investigation of evolving world economic networks with Markov chain formalism. In this work, using the recently available world input-output database, we investigated the evolution of the world economic network from 1995 to 2011 through analysis of a time series of finite Markov chains. We assessed different aspects of this evolving system via different known properties of the Markov chains such as mixing time, Kemeny constant, steady state probabilities and perturbation analysis of the transition matrices. First, we showed how the time series of mixing times and Kemeny constants could be used as an aggregate index of globalization. Next, we focused on the steady state probabilities as a measure of structural power of the economies that are comparable to GDP shares of economies as the traditional index of economies welfare. Further, we introduced two measures of systemic risk, called systemic influence and systemic fragility, where the former is the ratio of number of influenced nodes to the total number of nodes, caused by a shock in the activity of a node, and the latter is based on the number of times a specific economic node is affected by a shock in the activity of any of the other nodes. Finally, focusing on Kemeny constant as a global indicator of monetary flow across the network, we showed that there is a paradoxical effect of a change in activity levels of economic nodes on the overall flow of the world economic network. While the economic slowdown of the majority of nodes with high structural power results to a slower average monetary flow over the network, there are some nodes, where their slowdowns improve the overall quality of the network in terms of connectivity and the average flow of the money. PMID:29065145

[Comparison of precision in retrieving soybean leaf area index based on multi-source remote sensing data].

PubMed

Gao, Lin; Li, Chang-chun; Wang, Bao-shan; Yang Gui-jun; Wang, Lei; Fu, Kui

2016-01-01

With the innovation of remote sensing technology, remote sensing data sources are more and more abundant. The main aim of this study was to analyze retrieval accuracy of soybean leaf area index (LAI) based on multi-source remote sensing data including ground hyperspectral, unmanned aerial vehicle (UAV) multispectral and the Gaofen-1 (GF-1) WFV data. Ratio vegetation index (RVI), normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), difference vegetation index (DVI), and triangle vegetation index (TVI) were used to establish LAI retrieval models, respectively. The models with the highest calibration accuracy were used in the validation. The capability of these three kinds of remote sensing data for LAI retrieval was assessed according to the estimation accuracy of models. The experimental results showed that the models based on the ground hyperspectral and UAV multispectral data got better estimation accuracy (R² was more than 0.69 and RMSE was less than 0.4 at 0.01 significance level), compared with the model based on WFV data. The RVI logarithmic model based on ground hyperspectral data was little superior to the NDVI linear model based on UAV multispectral data (The difference in E(A), R² and RMSE were 0.3%, 0.04 and 0.006, respectively). The models based on WFV data got the lowest estimation accuracy with R2 less than 0.30 and RMSE more than 0.70. The effects of sensor spectral response characteristics, sensor geometric location and spatial resolution on the soybean LAI retrieval were discussed. The results demonstrated that ground hyperspectral data were advantageous but not prominent over traditional multispectral data in soybean LAI retrieval. WFV imagery with 16 m spatial resolution could not meet the requirements of crop growth monitoring at field scale. Under the condition of ensuring the high precision in retrieving soybean LAI and working efficiently, the approach to acquiring agricultural information by UAV remote sensing could yet be regarded as an optimal plan. Therefore, in the case of more and more available remote sensing information sources, agricultural UAV remote sensing could become an important information resource for guiding field-scale crop management and provide more scientific and accurate information for precision agriculture research.

Performance assessment of geospatial simulation models of land-use change--a landscape metric-based approach.

PubMed

Sakieh, Yousef; Salmanmahiny, Abdolrassoul

2016-03-01

Performance evaluation is a critical step when developing land-use and cover change (LUCC) models. The present study proposes a spatially explicit model performance evaluation method, adopting a landscape metric-based approach. To quantify GEOMOD model performance, a set of composition- and configuration-based landscape metrics including number of patches, edge density, mean Euclidean nearest neighbor distance, largest patch index, class area, landscape shape index, and splitting index were employed. The model takes advantage of three decision rules including neighborhood effect, persistence of change direction, and urbanization suitability values. According to the results, while class area, largest patch index, and splitting indices demonstrated insignificant differences between spatial pattern of ground truth and simulated layers, there was a considerable inconsistency between simulation results and real dataset in terms of the remaining metrics. Specifically, simulation outputs were simplistic and the model tended to underestimate number of developed patches by producing a more compact landscape. Landscape-metric-based performance evaluation produces more detailed information (compared to conventional indices such as the Kappa index and overall accuracy) on the model's behavior in replicating spatial heterogeneity features of a landscape such as frequency, fragmentation, isolation, and density. Finally, as the main characteristic of the proposed method, landscape metrics employ the maximum potential of observed and simulated layers for a performance evaluation procedure, provide a basis for more robust interpretation of a calibration process, and also deepen modeler insight into the main strengths and pitfalls of a specific land-use change model when simulating a spatiotemporal phenomenon.

Three Ways in Which Midline Regions Contribute to Self-Evaluation

PubMed Central

Flagan, Taru; Beer, Jennifer S.

2013-01-01

An integration of existing research and newly conducted psychophysiological interaction (PPI) connectivity analyses suggest a new framework for understanding the contribution of midline regions to social cognition. Recent meta-analyses suggest that there are no midline regions that are exclusively associated with self-processing. Whereas medial prefrontal cortex (MPFC) is broadly modulated by self-processing, subdivisions within MPFC are differentially modulated by the evaluation of close others (ventral MPFC: BA 10/32) and the evaluation of other social targets (dorsal MPFC: BA 9/32). The role of DMPFC in social cognition may also be less uniquely social than previously thought; it may be better characterized as a region that indexes certainty about evaluation rather than previously considered social mechanisms (i.e., correction of self-projection). VMPFC, a region often described as an important mediator of socioemotional significance, may instead perform a more cognitive role by reflecting the type of information brought to bear on evaluations of people we know well. Furthermore, the new framework moves beyond MPFC and hypothesizes that two other midline regions, ventral anterior cingulate cortex (VACC: BA 25) and medial orbitofrontal cortex (MOFC: BA 11), aid motivational influences on social cognition. Despite the central role of motivation in psychological models of self-perception, neural models have largely ignored the topic. Positive connectivity between VACC and MOFC may mediate bottom-up sensitivity to information based on its potential for helping us evaluate ourselves or others the way we want. As connectivity becomes more positive with striatum and less positive with middle frontal gyrus (BA 9/44), MOFC mediates top-down motivational influences by adjusting the standards we bring to bear on evaluations of ourselves and other people. PMID:23935580

Connections between intraparietal sulcus and a sensorimotor network underpin sustained tactile attention.

PubMed

Goltz, Dominique; Gundlach, Christopher; Nierhaus, Till; Villringer, Arno; Müller, Matthias; Pleger, Burkhard

2015-05-20

Previous studies on sustained tactile attention draw conclusions about underlying cortical networks by averaging over experimental conditions without considering attentional variance in single trials. This may have formed an imprecise picture of brain processes underpinning sustained tactile attention. In the present study, we simultaneously recorded EEG-fMRI and used modulations of steady-state somatosensory evoked potentials (SSSEPs) as a measure of attentional trial-by-trial variability. Therefore, frequency-tagged streams of vibrotactile stimulations were simultaneously presented to both index fingers. Human participants were cued to sustain attention to either the left or right finger stimulation and to press a button whenever they perceived a target pulse embedded in the to-be-attended stream. In-line with previous studies, a classical general linear model (GLM) analysis based on cued attention conditions revealed increased activity mainly in somatosensory and cerebellar regions. Yet, parametric modeling of the BOLD response using simultaneously recorded SSSEPs as a marker of attentional trial-by-trial variability quarried the intraparietal sulcus (IPS). The IPS in turn showed enhanced functional connectivity to a modality-unspecific attention network. However, this was only revealed on the basis of cued attention conditions in the classical GLM. By considering attentional variability as captured by SSSEPs, the IPS showed increased connectivity to a sensorimotor network, underpinning attentional selection processes between competing tactile stimuli and action choices (press a button or not). Thus, the current findings highlight the potential value by considering attentional variations in single trials and extend previous knowledge on the role of the IPS in tactile attention. Copyright © 2015 the authors 0270-6474/15/357938-12$15.00/0.

Modeling of Micro Deval abrasion loss based on some rock properties

NASA Astrophysics Data System (ADS)

Capik, Mehmet; Yilmaz, Ali Osman

2017-10-01

Aggregate is one of the most widely used construction material. The quality of the aggregate is determined using some testing methods. Among these methods, the Micro Deval Abrasion Loss (MDAL) test is commonly used for the determination of the quality and the abrasion resistance of aggregate. The main objective of this study is to develop models for the prediction of MDAL from rock properties, including uniaxial compressive strength, Brazilian tensile strength, point load index, Schmidt rebound hardness, apparent porosity, void ratio Cerchar abrasivity index and Bohme abrasion test are examined. Additionally, the MDAL is modeled using simple regression analysis and multiple linear regression analysis based on the rock properties. The study shows that the MDAL decreases with the increase of uniaxial compressive strength, Brazilian tensile strength, point load index, Schmidt rebound hardness and Cerchar abrasivity index. It is also concluded that the MDAL increases with the increase of apparent porosity, void ratio and Bohme abrasion test. The modeling results show that the models based on Bohme abrasion test and L type Schmidt rebound hardness give the better forecasting performances for the MDAL. More models, including the uniaxial compressive strength, the apparent porosity and Cerchar abrasivity index, are developed for the rapid estimation of the MDAL of the rocks. The developed models were verified by statistical tests. Additionally, it can be stated that the proposed models can be used as a forecasting for aggregate quality.

Computer-Aided Engineering Of Cabling

NASA Technical Reports Server (NTRS)

Billitti, Joseph W.

1989-01-01

Program generates data sheets, drawings, and other information on electrical connections. DFACS program, centered around single data base, has built-in menus providing easy input of, and access to, data for all personnel involved in system, subsystem, and cabling. Enables parallel design of circuit-data sheets and drawings of harnesses. Also recombines raw information to generate automatically various project documents and drawings, including index of circuit-data sheets, list of electrical-interface circuits, lists of assemblies and equipment, cabling trees, and drawings of cabling electrical interfaces and harnesses. Purpose of program to provide engineering community with centralized data base for putting in, and gaining access to, functional definition of system as specified in terms of details of pin connections of end circuits of subsystems and instruments and data on harnessing. Primary objective to provide instantaneous single point of interchange of information, thus avoiding

How does the connectivity index change through year in an agricultural catchment?

NASA Astrophysics Data System (ADS)

Cantreul, Vincent; Degré, Aurore

2017-04-01

The emerging concept of hydrological connectivity is difficult to quantify. Some indices have been proposed. The most cited is Borselli's one. It gives the advantage to visualize connectivity at watershed scale with very few inputs. But it is not a dynamic index and the resulting map is not time dependent. However, vegetation cover changes through year and possibly affects the connectivity dynamics. The objective of this poster is to show the evolution of the CI during the year looking at a few "strategic" times. Moreover, the study permits to identify a few "key locations" in the watershed, for example permanent disconnections or at the opposite constantly connected fields. The CI was calculated in a 124ha catchment (Hevillers), in the loess belt, in Belgium. Land use is agricultural with mostly cereals, sugar beets and potatoes, little area with wood, road, path or grass strip. Used weighting factor is soil loss ratio. It is between 0 and 1 and translates the protection offered to the soil by the crop. In winter (January), cereals have the most connected fields because of almost bare soils. Cover crops on sugar beets and potatoes fields decrease connectivity, except for one big field not far from the outlet. But rainfalls are generally not so erosive during this period. In spring (March and May), the cereals have a decreasing CI with plants growth covering the soil. On the opposite, sugar beets and potatoes are planted and bare soils in spring involve much higher connectivity index. The effect of grass strip is strong for sugar beet field situated uphill and underlines the importance of such mitigation measures. In summer (July), the whole watershed is much more disconnected and it does not represent the most risky part of the year in terms of erosion. The end of the year is related to harvesting and consequent bare soil in September for potatoes and November for the rest. In conclusion, the IC is an easy tool to estimate connectivity in a watershed. With the evolution during the year using soil loss ratio in the calculation, it permits to visualize dynamically the connectivity pattern and to localize erosive parts of the catchment for the crop rotation. With a global view on several years, it could be helpful to erosion managers to think about best long-term location of mitigation measures in the watershed. Key-words: hydrological connectivity index, soil loss ratio, erosion, dynamic

Homogenization analysis of invasion dynamics in heterogeneous landscapes with differential bias and motility.

PubMed

Yurk, Brian P

2018-07-01

Animal movement behaviors vary spatially in response to environmental heterogeneity. An important problem in spatial ecology is to determine how large-scale population growth and dispersal patterns emerge within highly variable landscapes. We apply the method of homogenization to study the large-scale behavior of a reaction-diffusion-advection model of population growth and dispersal. Our model includes small-scale variation in the directed and random components of movement and growth rates, as well as large-scale drift. Using the homogenized model we derive simple approximate formulas for persistence conditions and asymptotic invasion speeds, which are interpreted in terms of residence index. The homogenization results show good agreement with numerical solutions for environments with a high degree of fragmentation, both with and without periodicity at the fast scale. The simplicity of the formulas, and their connection to residence index make them appealing for studying the large-scale effects of a variety of small-scale movement behaviors.

Projection pursuit water quality evaluation model based on chicken swam algorithm

NASA Astrophysics Data System (ADS)

Hu, Zhe

2018-03-01

In view of the uncertainty and ambiguity of each index in water quality evaluation, in order to solve the incompatibility of evaluation results of individual water quality indexes, a projection pursuit model based on chicken swam algorithm is proposed. The projection index function which can reflect the water quality condition is constructed, the chicken group algorithm (CSA) is introduced, the projection index function is optimized, the best projection direction of the projection index function is sought, and the best projection value is obtained to realize the water quality evaluation. The comparison between this method and other methods shows that it is reasonable and feasible to provide decision-making basis for water pollution control in the basin.

Left ventricular diastolic dysfunction and increased left ventricular mass index related to pulmonary hypertension in patients with systemic autoimmune disease without pericardial effusion.

PubMed

Sugiura, Atsushi; Funabashi, Nobusada; Ozawa, Koya; Kobayashi, Yoshio

2016-10-01

We investigated the relationship of left ventricular (LV) diastolic dysfunction and LV mass index (LVMI) against pulmonary hypertension (PH) in systemic autoimmune disease (SAD). A total of 84 SAD patients (68 females; 53±17years; systemic lupus erythematosus, 27%; scleroderma, 17%; vasculitis, 16%; mixed connective tissue disease, 13% and polymyositis/dermatomyositis complex, 10%) without significant pericardial effusion (PE) on TTE (Vivid E9, GE) were analyzed. On TTE, PH was defined as peak tricuspid regurgitation velocity (TRV) of ≥2.9m/s based upon 2015 ESC guideline. Left atrial volume index (LAVI) and E/E' were measured as indicators of LV diastolic dysfunction. LVMI was also measured. Seven patients (8%) had PH. PH patients had greater LAVI (p<0.001), E/E' (p=0.004), LVMI (p=0.009) than non-PH patients. LAVI (R=0.458), E/E' (R=0.337), and LVMI (R=0.313) significantly and positively correlated with TRV (all p<0.05). Multiple regression analysis was performed to explore determinants of TRV. Age, female sex, and brain natriuretic peptide (BNP) were included in all the models. Three multiple regression models were generated using 1) LAVI, 2) E/E', and 3) LVMI and included LAVI, E/E', LVMI, and BNP as significant variables influencing TRV. Multi logistic regression analysis for predicting TRV of ≥2.9m/s showed that LAVI, and E/E' were significant predictors (Odds ratio, 1.296, and 1.370, respectively). In SAD patients without PE, LV diastolic dysfunction and increment of LVMI was closely associated with PH based upon TRV. LAVI and E/E' were independent predictors for PH. Measuring LAVI and E/E' may be a key to determine the mechanism of PH in these patients. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Examining the Association Between Comorbidity Indexes and Functional Status in Hospitalized Medicare Fee-for-Service Beneficiaries

PubMed Central

Graham, James E.; Resnik, Linda; Karmarkar, Amol M.; Deutsch, Anne; Tan, Alai; Al Snih, Soham; Ottenbacher, Kenneth J.

2016-01-01

Background Medicare data from acute hospitals do not contain information on functional status. This lack of information limits the ability to conduct rehabilitation-related health services research. Objective The purpose of this study was to examine the associations between 5 comorbidity indexes derived from acute care claims data and functional status assessed at admission to an inpatient rehabilitation facility (IRF). Comorbidity indexes included tier comorbidity, Functional Comorbidity Index (FCI), Charlson Comorbidity Index, Elixhauser Comorbidity Index, and Hierarchical Condition Category (HCC). Design This was a retrospective cohort study. Methods Medicare beneficiaries with stroke, lower extremity joint replacement, and lower extremity fracture discharged to an IRF in 2011 were studied (N=105,441). Data from the beneficiary summary file, Medicare Provider Analysis and Review (MedPAR) file, and Inpatient Rehabilitation Facility–Patient Assessment Instrument (IRF-PAI) file were linked. Inpatient rehabilitation facility admission functional status was used as a proxy for acute hospital discharge functional status. Separate linear regression models for each impairment group were developed to assess the relationships between the comorbidity indexes and functional status. Base models included age, sex, race/ethnicity, disability, dual eligibility, and length of stay. Subsequent models included individual comorbidity indexes. Values of variance explained (R2) with each comorbidity index were compared. Results Base models explained 7.7% of the variance in motor function ratings for stroke, 3.8% for joint replacement, and 7.3% for fracture. The R2 increased marginally when comorbidity indexes were added to base models for stroke, joint replacement, and fracture: Charlson Comorbidity Index (0.4%, 0.5%, 0.3%), tier comorbidity (0.2%, 0.6%, 0.5%), FCI (0.4%, 1.2%, 1.6%), Elixhauser Comorbidity Index (1.2%, 1.9%, 3.5%), and HCC (2.2%, 2.1%, 2.8%). Limitation Patients from 3 impairment categories were included in the sample. Conclusions The 5 comorbidity indexes contributed little to predicting functional status. The indexes examined were not useful as proxies for functional status in the acute settings studied. PMID:26564253

A transmission line model for propagation in elliptical core optical fibers

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

Georgantzos, E.; Boucouvalas, A. C.; Papageorgiou, C.

The calculation of mode propagation constants of elliptical core fibers has been the purpose of extended research leading to many notable methods, with the classic step index solution based on Mathieu functions. This paper seeks to derive a new innovative method for the determination of mode propagation constants in single mode fibers with elliptic core by modeling the elliptical fiber as a series of connected coupled transmission line elements. We develop a matrix formulation of the transmission line and the resonance of the circuits is used to calculate the mode propagation constants. The technique, used with success in the casemore » of cylindrical fibers, is now being extended for the case of fibers with elliptical cross section. The advantage of this approach is that it is very well suited to be able to calculate the mode dispersion of arbitrary refractive index profile elliptical waveguides. The analysis begins with the deployment Maxwell’s equations adjusted for elliptical coordinates. Further algebraic analysis leads to a set of equations where we are faced with the appearance of harmonics. Taking into consideration predefined fixed number of harmonics simplifies the problem and enables the use of the resonant circuits approach. According to each case, programs have been created in Matlab, providing with a series of results (mode propagation constants) that are further compared with corresponding results from the ready known Mathieu functions method.« less

New optimization model for routing and spectrum assignment with nodes insecurity

NASA Astrophysics Data System (ADS)

Xuan, Hejun; Wang, Yuping; Xu, Zhanqi; Hao, Shanshan; Wang, Xiaoli

2017-04-01

By adopting the orthogonal frequency division multiplexing technology, elastic optical networks can provide the flexible and variable bandwidth allocation to each connection request and get higher spectrum utilization. The routing and spectrum assignment problem in elastic optical network is a well-known NP-hard problem. In addition, information security has received worldwide attention. We combine these two problems to investigate the routing and spectrum assignment problem with the guaranteed security in elastic optical network, and establish a new optimization model to minimize the maximum index of the used frequency slots, which is used to determine an optimal routing and spectrum assignment schemes. To solve the model effectively, a hybrid genetic algorithm framework integrating a heuristic algorithm into a genetic algorithm is proposed. The heuristic algorithm is first used to sort the connection requests and then the genetic algorithm is designed to look for an optimal routing and spectrum assignment scheme. In the genetic algorithm, tailor-made crossover, mutation and local search operators are designed. Moreover, simulation experiments are conducted with three heuristic strategies, and the experimental results indicate that the effectiveness of the proposed model and algorithm framework.

Rainfall simulation and Structure-from-Motion photogrammetry for the analysis of soil water erosion in Mediterranean vineyards.

PubMed

Prosdocimi, Massimo; Burguet, Maria; Di Prima, Simone; Sofia, Giulia; Terol, Enric; Rodrigo Comino, Jesús; Cerdà, Artemi; Tarolli, Paolo

2017-01-01

Soil water erosion is a serious problem, especially in agricultural lands. Among these, vineyards deserve attention, because they constitute for the Mediterranean areas a type of land use affected by high soil losses. A significant problem related to the study of soil water erosion in these areas consists in the lack of a standardized procedure of collecting data and reporting results, mainly due to a variability among the measurement methods applied. Given this issue and the seriousness of soil water erosion in Mediterranean vineyards, this works aims to quantify the soil losses caused by simulated rainstorms, and compare them with each other depending on two different methodologies: (i) rainfall simulation and (ii) surface elevation change-based, relying on high-resolution Digital Elevation Models (DEMs) derived from a photogrammetric technique (Structure-from-Motion or SfM). The experiments were carried out in a typical Mediterranean vineyard, located in eastern Spain, at very fine scales. SfM data were obtained from one reflex camera and a smartphone built-in camera. An index of sediment connectivity was also applied to evaluate the potential effect of connectivity within the plots. DEMs derived from the smartphone and the reflex camera were comparable with each other in terms of accuracy and capability of estimating soil loss. Furthermore, soil loss estimated with the surface elevation change-based method resulted to be of the same order of magnitude of that one obtained with rainfall simulation, as long as the sediment connectivity within the plot was considered. High-resolution topography derived from SfM revealed to be essential in the sediment connectivity analysis and, therefore, in the estimation of eroded materials, when comparing them to those derived from the rainfall simulation methodology. The fact that smartphones built-in cameras could produce as much satisfying results as those derived from reflex cameras is a high value added for using SfM. Copyright © 2016 Elsevier B.V. All rights reserved.

Specialty Payment Model Opportunities and Assessment

PubMed Central

Mulcahy, Andrew W.; Chan, Chris; Hirshman, Samuel; Huckfeldt, Peter J.; Kofner, Aaron; Liu, Jodi L.; Lovejoy, Susan L.; Popescu, Ioana; Timbie, Justin W.; Hussey, Peter S.

2015-01-01

Abstract Gastroenterology and cardiology services are common and costly among Medicare beneficiaries. Episode-based payment, which aims to create incentives for high-quality, low-cost care, has been identified as a promising alternative payment model. This article describes research related to the design of episode-based payment models for ambulatory gastroenterology and cardiology services for possible testing by the Center for Medicare and Medicaid Innovation at the Centers for Medicare and Medicaid Services (CMS). The authors analyzed Medicare claims data to describe the frequency and characteristics of gastroenterology and cardiology index procedures, the practices that delivered index procedures, and the patients that received index procedures. The results of these analyses can help inform CMS decisions about the definition of episodes in an episode-based payment model; payment adjustments for service setting, multiple procedures, or other factors; and eligibility for the payment model. PMID:28083363

Numerical Study on the Behaviour of Reduced Beam Section Presence in Rectangular Concrete Filled Tubes Connection

NASA Astrophysics Data System (ADS)

Amalia, A. R.; Suswanto, B.; Kristijanto, H.; Irawan, D.

2018-01-01

This paper discusses about the behaviour of two types of RCFT column connections with steel beams due to cyclic loads using software based on finite element method ABAQUS 6.14. This comparison involves modelling RCFT connections with rigid connection that do not allow any deformation and rotation in the joint. There are two types of model to be compared: BB and BRBS which include RCFT connections to ordinary beam without RBS (BB) and to Reduce Beam Section Beam (BRBS). The models behaviour can be discussed in this study are stress value, von misses stress pattern and rotational degree of each model. From the von misses stress pattern value, it found that the highest regions of stress occurs in vicinity of beam flange near column face for connection without RBS (BB). For earthquake resistant building, that behaviour needs to be avoided because sudden collapse often happen in that joint connection. Moreover, the connection with the presence of RBS (BRBS), the highest regions of stress occurs in reduced beam section of the beam, it means that the failure might be happen as proposed plan. The ultimate force that can be restrained by BB model (402 kN) is higher than BRBS model (257,18 kN) because of reducing of flange area. BRBS model has higher rotation angle (0,057 rad) than BB model (0,045 rad). The analysis results also observed that cyclic performances of the moment connection with RBS (BRBS) were more ductile than the connection with ordinary beam (BB).

Viscoelastic properties of bovine orbital connective tissue and fat: constitutive models

PubMed Central

Yoo, Lawrence; Gupta, Vijay; Lee, Choongyeop; Kavehpore, Pirouz

2012-01-01

Reported mechanical properties of orbital connective tissue and fat have been too sparse to model strain–stress relationships underlying biomechanical interactions in strabismus. We performed rheological tests to develop a multi-mode upper convected Maxwell (UCM) model of these tissues under shear loading. From 20 fresh bovine orbits, 30 samples of connective tissue were taken from rectus pulley regions and 30 samples of fatty tissues from the posterior orbit. Additional samples were defatted to determine connective tissue weight proportion, which was verified histologically. Mechanical testing in shear employed a triborheometer to perform: strain sweeps at 0.5–2.0 Hz; shear stress relaxation with 1% strain; viscometry at 0.01–0.5 s−1 strain rate; and shear oscillation at 1% strain. Average connective tissue weight proportion was 98% for predominantly connective tissue and 76% for fatty tissue. Connective tissue specimens reached a long-term relaxation modulus of 668 Pa after 1,500 s, while corresponding values for fatty tissue specimens were 290 Pa and 1,100 s. Shear stress magnitude for connective tissue exceeded that of fatty tissue by five-fold. Based on these data, we developed a multimode UCM model with variable viscosities and time constants, and a damped hyperelastic response that accurately described measured properties of both connective and fatty tissues. Model parameters differed significantly between the two tissues. Viscoelastic properties of predominantly connective orbital tissues under shear loading differ markedly from properties of orbital fat, but both are accurately reflected using UCM models. These viscoelastic models will facilitate realistic global modeling of EOM behavior in binocular alignment and strabismus. PMID:21207094

Specialty Payment Model Opportunities and Assessment: Gastroenterology and Cardiology Model Design Report.

PubMed

Mulcahy, Andrew W; Chan, Chris; Hirshman, Samuel; Huckfeldt, Peter J; Kofner, Aaron; Liu, Jodi L; Lovejoy, Susan L; Popescu, Ioana; Timbie, Justin W; Hussey, Peter S

2015-07-15

Gastroenterology and cardiology services are common and costly among Medicare beneficiaries. Episode-based payment, which aims to create incentives for high-quality, low-cost care, has been identified as a promising alternative payment model. This article describes research related to the design of episode-based payment models for ambulatory gastroenterology and cardiology services for possible testing by the Center for Medicare and Medicaid Innovation at the Centers for Medicare and Medicaid Services (CMS). The authors analyzed Medicare claims data to describe the frequency and characteristics of gastroenterology and cardiology index procedures, the practices that delivered index procedures, and the patients that received index procedures. The results of these analyses can help inform CMS decisions about the definition of episodes in an episode-based payment model; payment adjustments for service setting, multiple procedures, or other factors; and eligibility for the payment model.

Intrahemispheric theta rhythm desynchronization impairs working memory.

PubMed

Alekseichuk, Ivan; Pabel, Stefanie Corinna; Antal, Andrea; Paulus, Walter

2017-01-01

There is a growing interest in large-scale connectivity as one of the crucial factors in working memory. Correlative evidence has revealed the anatomical and electrophysiological players in the working memory network, but understanding of the effective role of their connectivity remains elusive. In this double-blind, placebo-controlled study we aimed to identify the causal role of theta phase connectivity in visual-spatial working memory. The frontoparietal network was over- or de-synchronized in the anterior-posterior direction by multi-electrode, 6 Hz transcranial alternating current stimulation (tACS). A decrease in memory performance and increase in reaction time was caused by frontoparietal intrahemispheric desynchronization. According to the diffusion drift model, this originated in a lower signal-to-noise ratio, known as the drift rate index, in the memory system. The EEG analysis revealed a corresponding decrease in phase connectivity between prefrontal and parietal areas after tACS-driven desynchronization. The over-synchronization did not result in any changes in either the behavioral or electrophysiological levels in healthy participants. Taken together, we demonstrate the feasibility of manipulating multi-site large-scale networks in humans, and the disruptive effect of frontoparietal desynchronization on theta phase connectivity and visual-spatial working memory.

Constructing fMRI connectivity networks: a whole brain functional parcellation method for node definition.

PubMed

Maggioni, Eleonora; Tana, Maria Gabriella; Arrigoni, Filippo; Zucca, Claudio; Bianchi, Anna Maria

2014-05-15

Functional Magnetic Resonance Imaging (fMRI) is used for exploring brain functionality, and recently it was applied for mapping the brain connection patterns. To give a meaningful neurobiological interpretation to the connectivity network, it is fundamental to properly define the network framework. In particular, the choice of the network nodes may affect the final connectivity results and the consequent interpretation. We introduce a novel method for the intra subject topological characterization of the nodes of fMRI brain networks, based on a whole brain parcellation scheme. The proposed whole brain parcellation algorithm divides the brain into clusters that are homogeneous from the anatomical and functional point of view, each of which constitutes a node. The functional parcellation described is based on the Tononi's cluster index, which measures instantaneous correlation in terms of intrinsic and extrinsic statistical dependencies. The method performance and reliability were first tested on simulated data, then on a real fMRI dataset acquired on healthy subjects during visual stimulation. Finally, the proposed algorithm was applied to epileptic patients' fMRI data recorded during seizures, to verify its usefulness as preparatory step for effective connectivity analysis. For each patient, the nodes of the network involved in ictal activity were defined according to the proposed parcellation scheme and Granger Causality Analysis (GCA) was applied to infer effective connectivity. We showed that the algorithm 1) performed well on simulated data, 2) was able to produce reliable inter subjects results and 3) led to a detailed definition of the effective connectivity pattern. Copyright © 2014 Elsevier B.V. All rights reserved.

The Relative Contribution of Dietary Habits, Leisure-Time Exercise, Exercise Attitude, and Body Mass Index to Self-Rated Health among College Students in Taiwan.

PubMed

Hsieh, Huey-Hong; Chang, Chia-Ming; Liu, Li-Wei; Huang, Hsiu-Chin

2018-05-11

Background : Self-rated health (SRH) is consistent with objective health status and can serve as a global measure of health status in the general population. The purpose of this study is to find the connections of dietary habits, leisure-time exercise, exercise attitude, and body mass index (BMI) to SRH among college students. Methods : The "dietary⁻exercise attitude and SRH" questionnaire was developed to investigate college students in Taiwan through the Internet. Partial least squares structural equation modeling (PLS-SEM) was used to test the relationship among them. Results : The reliability and validity were confirmed using PLS-SEM. The results found exercise habits, dietary habits, and BMI explained 26.5% of SRH. Poor dietary habits and being overweight led to bad health status (negative path coefficients to SRH). Additionally, the study found that positive exercise attitude had a positive relationship with exercise habits. Conclusions : Based on the results, college students should be well-informed of the potential threat of poor dietary habits and being overweight to health and should improve their attitude with respect to exercise so as to prevent overweight-related diseases.

The Relative Contribution of Dietary Habits, Leisure-Time Exercise, Exercise Attitude, and Body Mass Index to Self-Rated Health among College Students in Taiwan

PubMed Central

Hsieh, Huey-Hong; Chang, Chia-Ming; Liu, Li-Wei; Huang, Hsiu-Chin

2018-01-01

Background: Self-rated health (SRH) is consistent with objective health status and can serve as a global measure of health status in the general population. The purpose of this study is to find the connections of dietary habits, leisure-time exercise, exercise attitude, and body mass index (BMI) to SRH among college students. Methods: The “dietary–exercise attitude and SRH” questionnaire was developed to investigate college students in Taiwan through the Internet. Partial least squares structural equation modeling (PLS-SEM) was used to test the relationship among them. Results: The reliability and validity were confirmed using PLS-SEM. The results found exercise habits, dietary habits, and BMI explained 26.5% of SRH. Poor dietary habits and being overweight led to bad health status (negative path coefficients to SRH). Additionally, the study found that positive exercise attitude had a positive relationship with exercise habits. Conclusions: Based on the results, college students should be well-informed of the potential threat of poor dietary habits and being overweight to health and should improve their attitude with respect to exercise so as to prevent overweight-related diseases. PMID:29751682

Using graph approach for managing connectivity in integrative landscape modelling

NASA Astrophysics Data System (ADS)

Rabotin, Michael; Fabre, Jean-Christophe; Libres, Aline; Lagacherie, Philippe; Crevoisier, David; Moussa, Roger

2013-04-01

In cultivated landscapes, a lot of landscape elements such as field boundaries, ditches or banks strongly impact water flows, mass and energy fluxes. At the watershed scale, these impacts are strongly conditionned by the connectivity of these landscape elements. An accurate representation of these elements and of their complex spatial arrangements is therefore of great importance for modelling and predicting these impacts.We developped in the framework of the OpenFLUID platform (Software Environment for Modelling Fluxes in Landscapes) a digital landscape representation that takes into account the spatial variabilities and connectivities of diverse landscape elements through the application of the graph theory concepts. The proposed landscape representation consider spatial units connected together to represent the flux exchanges or any other information exchanges. Each spatial unit of the landscape is represented as a node of a graph and relations between units as graph connections. The connections are of two types - parent-child connection and up/downstream connection - which allows OpenFLUID to handle hierarchical graphs. Connections can also carry informations and graph evolution during simulation is possible (connections or elements modifications). This graph approach allows a better genericity on landscape representation, a management of complex connections and facilitate development of new landscape representation algorithms. Graph management is fully operational in OpenFLUID for developers or modelers ; and several graph tools are available such as graph traversal algorithms or graph displays. Graph representation can be managed i) manually by the user (for example in simple catchments) through XML-based files in easily editable and readable format or ii) by using methods of the OpenFLUID-landr library which is an OpenFLUID library relying on common open-source spatial libraries (ogr vector, geos topologic vector and gdal raster libraries). OpenFLUID-landr library has been developed in order i) to be used with no GIS expert skills needed (common gis formats can be read and simplified spatial management is provided), ii) to easily develop adapted rules of landscape discretization and graph creation to follow spatialized model requirements and iii) to allow model developers to manage dynamic and complex spatial topology. Graph management in OpenFLUID are shown with i) examples of hydrological modelizations on complex farmed landscapes and ii) the new implementation of Geo-MHYDAS tool based on the OpenFLUID-landr library, which allows to discretize a landscape and create graph structure for the MHYDAS model requirements.

What We Know About the Brain Structure-Function Relationship.

PubMed

Batista-García-Ramó, Karla; Fernández-Verdecia, Caridad Ivette

2018-04-18

How the human brain works is still a question, as is its implication with brain architecture: the non-trivial structure–function relationship. The main hypothesis is that the anatomic architecture conditions, but does not determine, the neural network dynamic. The functional connectivity cannot be explained only considering the anatomical substrate. This involves complex and controversial aspects of the neuroscience field and that the methods and methodologies to obtain structural and functional connectivity are not always rigorously applied. The goal of the present article is to discuss about the progress made to elucidate the structure–function relationship of the Central Nervous System, particularly at the brain level, based on results from human and animal studies. The current novel systems and neuroimaging techniques with high resolutive physio-structural capacity have brought about the development of an integral framework of different structural and morphometric tools such as image processing, computational modeling and graph theory. Different laboratories have contributed with in vivo, in vitro and computational/mathematical models to study the intrinsic neural activity patterns based on anatomical connections. We conclude that multi-modal techniques of neuroimaging are required such as an improvement on methodologies for obtaining structural and functional connectivity. Even though simulations of the intrinsic neural activity based on anatomical connectivity can reproduce much of the observed patterns of empirical functional connectivity, future models should be multifactorial to elucidate multi-scale relationships and to infer disorder mechanisms.

[Landscape connectivity of waterbody network in the new reclamation region of Lianyungang based on effective distance model].

PubMed

Qiao, Fu-Zhen; Zheng, Zhong-Ming; Li, Jia-Lin; Zheng, Wen-Bing

2014-08-01

Landscape connectivity is an important indicator to measure effectiveness of landscape ecological services. Waterbody connectivity in Lianyun New City, the new reclamation region of Lianyungang, was investigated based on GIS technology and effective distance model. The results showed that the total connectivity of waterbodies was poor in Lanyun New City. Connectivity of patches was related to characteristics of ecological process, ecological services value and spatial arrangement. The higher the ecosystem services value of patches was, the greater its contribution to the overall water landscape connectivity was. Some patches with long strip structure played a key role to improve the landscape connectivity. By classifying the importance of connectivity and functional groups of waterbody patches, planning of waterbodies in Lianyun New City conformed to the theory of non-substitutable pattern developed by Forman. Waterbody patches with corresponding functions should be considered with priority when planning and building a new city. The present study demonstrated that connectivity of patches should be an important factor to be considered in ecological landscape planning. Construction of ecological corridors should not only take the number of ecological landscapes into consideration, but also pay attention to spatial arrangement of landscapes in order to improve the overall landscape connectivity.

Computation of Southern Pine Site Index Using a TI-59 Calculator

Treesearch

Robert M. Farrar

1983-01-01

A program is described that permits computation of site index in the field using a Texas Instruments model TI-59 programmable, hand-held, battery-powered calculator. Based on a series of equations developed by R.M. Farrar, Jr., for the site index curves in USDA Miscellaneous Publication 50, the program can accommodate any index base age, tree age, and height within...

Research on connection structure of aluminumbody bus using multi-objective topology optimization

NASA Astrophysics Data System (ADS)

Peng, Q.; Ni, X.; Han, F.; Rhaman, K.; Ulianov, C.; Fang, X.

2018-01-01

For connecting Aluminum Alloy bus body aluminum components often occur the problem of failure, a new aluminum alloy connection structure is designed based on multi-objective topology optimization method. Determining the shape of the outer contour of the connection structure with topography optimization, establishing a topology optimization model of connections based on SIMP density interpolation method, going on multi-objective topology optimization, and improving the design of the connecting piece according to the optimization results. The results show that the quality of the aluminum alloy connector after topology optimization is reduced by 18%, and the first six natural frequencies are improved and the strength performance and stiffness performance are obviously improved.

Registering Cortical Surfaces Based on Whole-Brain Structural Connectivity and Continuous Connectivity Analysis

PubMed Central

Gutman, Boris; Leonardo, Cassandra; Jahanshad, Neda; Hibar, Derrek; Eschen-burg, Kristian; Nir, Talia; Villalon, Julio; Thompson, Paul

2014-01-01

We present a framework for registering cortical surfaces based on tractography-informed structural connectivity. We define connectivity as a continuous kernel on the product space of the cortex, and develop a method for estimating this kernel from tractography fiber models. Next, we formulate the kernel registration problem, and present a means to non-linearly register two brains’ continuous connectivity profiles. We apply theoretical results from operator theory to develop an algorithm for decomposing the connectome into its shared and individual components. Lastly, we extend two discrete connectivity measures to the continuous case, and apply our framework to 98 Alzheimer’s patients and controls. Our measures show significant differences between the two groups. PMID:25320795

An Index of Longitudinal Hydrologic Connectivity to Evaluate Effects of Water Abstraction on Streams Dominated by Migratory Shrimps

NASA Astrophysics Data System (ADS)

Crook, K. E.; Pringle, C. M.; Freeman, M. C.; Scatena, F. N.

2005-05-01

Massive water withdrawals from streams draining the Caribbean National Forest (CNF), Puerto Rico, are threatening their biotic integrity. Migratory tropical shrimps are ideal indicator species to measure water withdrawal effects on riverine connectivity and biointegrity because: (1) their migratory range encompasses the stream network from estuaries to headwater streams; (2) they represent greater than 90% of biomass in streams draining the CNF; and (3) they facilitate important in-stream ecological processes. We developed an index to evaluate individual and cumulative effects of water intakes on each stage of the shrimp's life-cycle. Effect of water withdrawal on longitudinal connectivity was evaluated by combining effects of water withdrawal on larval and juvenile shrimps. Larvae require downstream transport to the estuary for advancement to the next life-stage, and juveniles similarly require access to headwater streams. Therefore, these two life-stages represent the bi-directional connectivity of streams from headwaters to estuaries. Seventeen water intakes were evaluated in and around the CNF. Larger intakes cause a greater decrease in connectivity than smaller intakes; however, several small, high elevation intakes had very low connectivity. Also, intakes with alternative designs, such as a French drain, have reduced effects on connectivity.

An Improved Computing Method for 3D Mechanical Connectivity Rates Based on a Polyhedral Simulation Model of Discrete Fracture Network in Rock Masses

NASA Astrophysics Data System (ADS)

Li, Mingchao; Han, Shuai; Zhou, Sibao; Zhang, Ye

2018-06-01

Based on a 3D model of a discrete fracture network (DFN) in a rock mass, an improved projective method for computing the 3D mechanical connectivity rate was proposed. The Monte Carlo simulation method, 2D Poisson process and 3D geological modeling technique were integrated into a polyhedral DFN modeling approach, and the simulation results were verified by numerical tests and graphical inspection. Next, the traditional projective approach for calculating the rock mass connectivity rate was improved using the 3D DFN models by (1) using the polyhedral model to replace the Baecher disk model; (2) taking the real cross section of the rock mass, rather than a part of the cross section, as the test plane; and (3) dynamically searching the joint connectivity rates using different dip directions and dip angles at different elevations to calculate the maximum, minimum and average values of the joint connectivity at each elevation. In a case study, the improved method and traditional method were used to compute the mechanical connectivity rate of the slope of a dam abutment. The results of the two methods were further used to compute the cohesive force of the rock masses. Finally, a comparison showed that the cohesive force derived from the traditional method had a higher error, whereas the cohesive force derived from the improved method was consistent with the suggested values. According to the comparison, the effectivity and validity of the improved method were verified indirectly.

Effective Connectivity Modeling for fMRI: Six Issues and Possible Solutions Using Linear Dynamic Systems

PubMed Central

Smith, Jason F.; Pillai, Ajay; Chen, Kewei; Horwitz, Barry

2012-01-01

Analysis of directionally specific or causal interactions between regions in functional magnetic resonance imaging (fMRI) data has proliferated. Here we identify six issues with existing effective connectivity methods that need to be addressed. The issues are discussed within the framework of linear dynamic systems for fMRI (LDSf). The first concerns the use of deterministic models to identify inter-regional effective connectivity. We show that deterministic dynamics are incapable of identifying the trial-to-trial variability typically investigated as the marker of connectivity while stochastic models can capture this variability. The second concerns the simplistic (constant) connectivity modeled by most methods. Connectivity parameters of the LDSf model can vary at the same timescale as the input data. Further, extending LDSf to mixtures of multiple models provides more robust connectivity variation. The third concerns the correct identification of the network itself including the number and anatomical origin of the network nodes. Augmentation of the LDSf state space can identify additional nodes of a network. The fourth concerns the locus of the signal used as a “node” in a network. A novel extension LDSf incorporating sparse canonical correlations can select most relevant voxels from an anatomically defined region based on connectivity. The fifth concerns connection interpretation. Individual parameter differences have received most attention. We present alternative network descriptors of connectivity changes which consider the whole network. The sixth concerns the temporal resolution of fMRI data relative to the timescale of the inter-regional interactions in the brain. LDSf includes an “instantaneous” connection term to capture connectivity occurring at timescales faster than the data resolution. The LDS framework can also be extended to statistically combine fMRI and EEG data. The LDSf framework is a promising foundation for effective connectivity analysis. PMID:22279430

Propagation of Solar Energetic Particles in Three-dimensional Interplanetary Magnetic Fields: Radial Dependence of Peak Intensities

NASA Astrophysics Data System (ADS)

He, H.-Q.; Zhou, G.; Wan, W.

2017-06-01

A functional form {I}\\max (R)={{kR}}-α , where R is the radial distance of a spacecraft, was usually used to model the radial dependence of peak intensities {I}\\max (R) of solar energetic particles (SEPs). In this work, the five-dimensional Fokker-Planck transport equation incorporating perpendicular diffusion is numerically solved to investigate the radial dependence of SEP peak intensities. We consider two different scenarios for the distribution of a spacecraft fleet: (1) along the radial direction line and (2) along the Parker magnetic field line. We find that the index α in the above expression varies in a wide range, primarily depending on the properties (e.g., location and coverage) of SEP sources and on the longitudinal and latitudinal separations between the sources and the magnetic foot points of the observers. Particularly, whether the magnetic foot point of the observer is located inside or outside the SEP source is a crucial factor determining the values of index α. A two-phase phenomenon is found in the radial dependence of peak intensities. The “position” of the break point (transition point/critical point) is determined by the magnetic connection status of the observers. This finding suggests that a very careful examination of the magnetic connection between the SEP source and each spacecraft should be taken in the observational studies. We obtain a lower limit of {R}-1.7+/- 0.1 for empirically modeling the radial dependence of SEP peak intensities. Our findings in this work can be used to explain the majority of the previous multispacecraft survey results, and especially to reconcile the different or conflicting empirical values of the index α in the literature.

Modeling the Pineapple Express phenomenon via Multivariate Extreme Value Theory

NASA Astrophysics Data System (ADS)

Weller, G.; Cooley, D. S.

2011-12-01

The pineapple express (PE) phenomenon is responsible for producing extreme winter precipitation events in the coastal and mountainous regions of the western United States. Because the PE phenomenon is also associated with warm temperatures, the heavy precipitation and associated snowmelt can cause destructive flooding. In order to study impacts, it is important that regional climate models from NARCCAP are able to reproduce extreme precipitation events produced by PE. We define a daily precipitation quantity which captures the spatial extent and intensity of precipitation events produced by the PE phenomenon. We then use statistical extreme value theory to model the tail dependence of this quantity as seen in an observational data set and each of the six NARCCAP regional models driven by NCEP reanalysis. We find that most NCEP-driven NARCCAP models do exhibit tail dependence between daily model output and observations. Furthermore, we find that not all extreme precipitation events are pineapple express events, as identified by Dettinger et al. (2011). The synoptic-scale atmospheric processes that drive extreme precipitation events produced by PE have only recently begun to be examined. Much of the current work has focused on pattern recognition, rather than quantitative analysis. We use daily mean sea-level pressure (MSLP) fields from NCEP to develop a "pineapple express index" for extreme precipitation, which exhibits tail dependence with our observed precipitation quantity for pineapple express events. We build a statistical model that connects daily precipitation output from the WRFG model, daily MSLP fields from NCEP, and daily observed precipitation in the western US. Finally, we use this model to simulate future observed precipitation based on WRFG output driven by the CCSM model, and our pineapple express index derived from future CCSM output. Our aim is to use this model to develop a better understanding of the frequency and intensity of extreme precipitation events produced by PE under climate change.

Inferring Aquifer Transmissivity from River Flow Data

NASA Astrophysics Data System (ADS)

Trichakis, Ioannis; Pistocchi, Alberto

2016-04-01

Daily streamflow data is the measurable result of many different hydrological processes within a basin; therefore, it includes information about all these processes. In this work, recession analysis applied to a pan-European dataset of measured streamflow was used to estimate hydrogeological parameters of the aquifers that contribute to the stream flow. Under the assumption that base-flow in times of no precipitation is mainly due to groundwater, we estimated parameters of European shallow aquifers connected with the stream network, and identified on the basis of the 1:1,500,000 scale Hydrogeological map of Europe. To this end, Master recession curves (MRCs) were constructed based on the RECESS model of the USGS for 1601 stream gauge stations across Europe. The process consists of three stages. Firstly, the model analyses the stream flow time-series. Then, it uses regression to calculate the recession index. Finally, it infers characteristics of the aquifer from the recession index. During time-series analysis, the model identifies those segments, where the number of successive recession days is above a certain threshold. The reason for this pre-processing lies in the necessity for an adequate number of points when performing regression at a later stage. The recession index derives from the semi-logarithmic plot of stream flow over time, and the post processing involves the calculation of geometrical parameters of the watershed through a GIS platform. The program scans the full stream flow dataset of all the stations. For each station, it identifies the segments with continuous recession that exceed a predefined number of days. When the algorithm finds all the segments of a certain station, it analyses them and calculates the best linear fit between time and the logarithm of flow. The algorithm repeats this procedure for the full number of segments, thus it calculates many different values of recession index for each station. After the program has found all the recession segments, it performs calculations to determine the expression for the MRC. Further processing of the MRCs can yield estimates of transmissivity or response time representative of the aquifers upstream of the station. These estimates can be useful for large scale (e.g. continental) groundwater modelling. The above procedure allowed calculating values of transmissivity for a large share of European aquifers, ranging from Tmin = 4.13E-04 m²/d to Tmax = 8.12E+03 m²/d, with an average value Taverage = 9.65E+01 m²/d. These results are in line with the literature, indicating that the procedure may provide realistic results for large-scale groundwater modelling. In this contribution we present the results in the perspective of their application for the parameterization of a pan-European bi-dimensional shallow groundwater flow model.

Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings

PubMed Central

Lin, Tiger W.; Das, Anup; Krishnan, Giri P.; Bazhenov, Maxim; Sejnowski, Terrence J.

2017-01-01

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005; Pillow et al., 2008), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals. PMID:28777719

Differential Covariance: A New Class of Methods to Estimate Sparse Connectivity from Neural Recordings.

PubMed

Lin, Tiger W; Das, Anup; Krishnan, Giri P; Bazhenov, Maxim; Sejnowski, Terrence J

2017-10-01

With our ability to record more neurons simultaneously, making sense of these data is a challenge. Functional connectivity is one popular way to study the relationship of multiple neural signals. Correlation-based methods are a set of currently well-used techniques for functional connectivity estimation. However, due to explaining away and unobserved common inputs (Stevenson, Rebesco, Miller, & Körding, 2008 ), they produce spurious connections. The general linear model (GLM), which models spike trains as Poisson processes (Okatan, Wilson, & Brown, 2005 ; Truccolo, Eden, Fellows, Donoghue, & Brown, 2005 ; Pillow et al., 2008 ), avoids these confounds. We develop here a new class of methods by using differential signals based on simulated intracellular voltage recordings. It is equivalent to a regularized AR(2) model. We also expand the method to simulated local field potential recordings and calcium imaging. In all of our simulated data, the differential covariance-based methods achieved performance better than or similar to the GLM method and required fewer data samples. This new class of methods provides alternative ways to analyze neural signals.

Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study

PubMed Central

Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

2017-01-01

Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed. PMID:28009983

Abnormal brain functional connectivity leads to impaired mood and cognition in hyperthyroidism: a resting-state functional MRI study.

PubMed

Li, Ling; Zhi, Mengmeng; Hou, Zhenghua; Zhang, Yuqun; Yue, Yingying; Yuan, Yonggui

2017-01-24

Patients with hyperthyroidism frequently have neuropsychiatric complaints such as lack of concentration, poor memory, depression, anxiety, nervousness, and irritability, suggesting brain dysfunction. However, the underlying process of these symptoms remains unclear. Using resting-state functional magnetic resonance imaging (rs-fMRI), we depicted the altered graph theoretical metric degree centrality (DC) and seed-based resting-state functional connectivity (FC) in 33 hyperthyroid patients relative to 33 healthy controls. The peak points of significantly altered DC between the two groups were defined as the seed regions to calculate FC to the whole brain. Then, partial correlation analyses were performed between abnormal DC, FC and neuropsychological performances, as well as some clinical indexes. The decreased intrinsic functional connectivity in the posterior lobe of cerebellum (PLC) and medial frontal gyrus (MeFG), as well as the abnormal seed-based FC anchored in default mode network (DMN), attention network, visual network and cognitive network in this study, possibly constitutes the latent mechanism for emotional and cognitive changes in hyperthyroidism, including anxiety and impaired processing speed.

Evaluation of computer-based computer tomography stratification against outcome models in connective tissue disease-related interstitial lung disease: a patient outcome study.

PubMed

Jacob, Joseph; Bartholmai, Brian J; Rajagopalan, Srinivasan; Brun, Anne Laure; Egashira, Ryoko; Karwoski, Ronald; Kokosi, Maria; Wells, Athol U; Hansell, David M

2016-11-23

To evaluate computer-based computer tomography (CT) analysis (CALIPER) against visual CT scoring and pulmonary function tests (PFTs) when predicting mortality in patients with connective tissue disease-related interstitial lung disease (CTD-ILD). To identify outcome differences between distinct CTD-ILD groups derived following automated stratification of CALIPER variables. A total of 203 consecutive patients with assorted CTD-ILDs had CT parenchymal patterns evaluated by CALIPER and visual CT scoring: honeycombing, reticular pattern, ground glass opacities, pulmonary vessel volume, emphysema, and traction bronchiectasis. CT scores were evaluated against pulmonary function tests: forced vital capacity, diffusing capacity for carbon monoxide, carbon monoxide transfer coefficient, and composite physiologic index for mortality analysis. Automated stratification of CALIPER-CT variables was evaluated in place of and alongside forced vital capacity and diffusing capacity for carbon monoxide in the ILD gender, age physiology (ILD-GAP) model using receiver operating characteristic curve analysis. Cox regression analyses identified four independent predictors of mortality: patient age (P < 0.0001), smoking history (P = 0.0003), carbon monoxide transfer coefficient (P = 0.003), and pulmonary vessel volume (P < 0.0001). Automated stratification of CALIPER variables identified three morphologically distinct groups which were stronger predictors of mortality than all CT and functional indices. The Stratified-CT model substituted automated stratified groups for functional indices in the ILD-GAP model and maintained model strength (area under curve (AUC) = 0.74, P < 0.0001), ILD-GAP (AUC = 0.72, P < 0.0001). Combining automated stratified groups with the ILD-GAP model (stratified CT-GAP model) strengthened predictions of 1- and 2-year mortality: ILD-GAP (AUC = 0.87 and 0.86, respectively); stratified CT-GAP (AUC = 0.89 and 0.88, respectively). CALIPER-derived pulmonary vessel volume is an independent predictor of mortality across all CTD-ILD patients. Furthermore, automated stratification of CALIPER CT variables represents a novel method of prognostication at least as robust as PFTs in CTD-ILD patients.

Development of agent-based on-line adaptive signal control (ASC) framework using connected vehicle (CV) technology.

DOT National Transportation Integrated Search

2016-04-01

In this study, we developed an adaptive signal control (ASC) framework for connected vehicles (CVs) using agent-based modeling technique. : The proposed framework consists of two types of agents: 1) vehicle agents (VAs); and 2) signal controller agen...

Effective connectivity between superior temporal gyrus and Heschl's gyrus during white noise listening: linear versus non-linear models.

PubMed

Hamid, Ka; Yusoff, An; Rahman, Mza; Mohamad, M; Hamid, Aia

2012-04-01

This fMRI study is about modelling the effective connectivity between Heschl's gyrus (HG) and the superior temporal gyrus (STG) in human primary auditory cortices. MATERIALS #ENTITYSTARTX00026; Ten healthy male participants were required to listen to white noise stimuli during functional magnetic resonance imaging (fMRI) scans. Statistical parametric mapping (SPM) was used to generate individual and group brain activation maps. For input region determination, two intrinsic connectivity models comprising bilateral HG and STG were constructed using dynamic causal modelling (DCM). The models were estimated and inferred using DCM while Bayesian Model Selection (BMS) for group studies was used for model comparison and selection. Based on the winning model, six linear and six non-linear causal models were derived and were again estimated, inferred, and compared to obtain a model that best represents the effective connectivity between HG and the STG, balancing accuracy and complexity. Group results indicated significant asymmetrical activation (p(uncorr) < 0.001) in bilateral HG and STG. Model comparison results showed strong evidence of STG as the input centre. The winning model is preferred by 6 out of 10 participants. The results were supported by BMS results for group studies with the expected posterior probability, r = 0.7830 and exceedance probability, ϕ = 0.9823. One-sample t-tests performed on connection values obtained from the winning model indicated that the valid connections for the winning model are the unidirectional parallel connections from STG to bilateral HG (p < 0.05). Subsequent model comparison between linear and non-linear models using BMS prefers non-linear connection (r = 0.9160, ϕ = 1.000) from which the connectivity between STG and the ipsi- and contralateral HG is gated by the activity in STG itself. We are able to demonstrate that the effective connectivity between HG and STG while listening to white noise for the respective participants can be explained by a non-linear dynamic causal model with the activity in STG influencing the STG-HG connectivity non-linearly.

Packet Radio Temporary Note Index.

DTIC Science & Technology

1984-05-07

Dynamic Control in Carrier Sense Multiple Access 180 Cross-Radio Debugger Beeler 06/76 BBN 179 New Capabilities of the PR Gitman 05/76 NAC Simulation...Program 178 An Approximate Analytical Model for Gitman 05/76 NAC Initialization of Single Hop PRNETs 177 SPP Definition Beeler 04/76 BBN 176 PR Protocol...Sussman 03/79 BBN Labeling Process (Revision 7) 173 Interfacing Terminals to the PRN Fralick 04/76 BBN 172 Connectivity Issues in Mobile PR Gitman 03/76

A participatory sensing approach to characterize ride quality

NASA Astrophysics Data System (ADS)

Bridgelall, Raj

2014-03-01

Rough roads increase vehicle operation and road maintenance costs. Consequently, transportation agencies spend a significant portion of their budgets on ride-quality characterization to forecast maintenance needs. The ubiquity of smartphones and social media, and the emergence of a connected vehicle environment present lucrative opportunities for cost-reduction and continuous, network-wide, ride-quality characterization. However, there is a lack of models to transform inertial and position information from voluminous data flows into indices that transportation agencies currently use. This work expands on theories of the Road Impact Factor introduced in previous research. The index characterizes road roughness by aggregating connected vehicle data and reporting roughness in direct proportion to the International Roughness Index. Their theoretical relationships are developed, and a case study is presented to compare the relative data quality from an inertial profiler and a regular passenger vehicle. Results demonstrate that the approach is a viable alternative to existing models that require substantially more resources and provide less network coverage. One significant benefit of the participatory sensing approach is that transportation agencies can monitor all network facilities continuously to locate distress symptoms, such as frost heaves, that appear and disappear between ride assessment cycles. Another benefit of the approach is continuous monitoring of all high-risk intersections such as rail grade crossings to better understand the relationship between ride-quality and traffic safety.

Robust check loss-based variable selection of high-dimensional single-index varying-coefficient model

NASA Astrophysics Data System (ADS)

Song, Yunquan; Lin, Lu; Jian, Ling

2016-07-01

Single-index varying-coefficient model is an important mathematical modeling method to model nonlinear phenomena in science and engineering. In this paper, we develop a variable selection method for high-dimensional single-index varying-coefficient models using a shrinkage idea. The proposed procedure can simultaneously select significant nonparametric components and parametric components. Under defined regularity conditions, with appropriate selection of tuning parameters, the consistency of the variable selection procedure and the oracle property of the estimators are established. Moreover, due to the robustness of the check loss function to outliers in the finite samples, our proposed variable selection method is more robust than the ones based on the least squares criterion. Finally, the method is illustrated with numerical simulations.

Peres experiment using photons: No test for hypercomplex (quaternionic) quantum theories

NASA Astrophysics Data System (ADS)

Adler, Stephen L.

2017-06-01

Assuming the standard axioms for quaternionic quantum theory and a spatially localized scattering interaction, the S matrix in quaternionic quantum theory is complex valued, not quaternionic. Using the standard connections between the S matrix, the forward scattering amplitude for electromagnetic wave scattering, and the index of refraction, we show that the index of refraction is necessarily complex, not quaternionic. This implies that the recent optical experiment of Procopio et al. [Nat. Commun. 8, 15044 (2017), 10.1038/ncomms15044] based on the Peres proposal does not test for hypercomplex or quaternionic quantum effects arising within the standard Hilbert space framework. Such a test requires looking at near zone fields, not radiation zone fields.

Diversity of Poissonian populations.

PubMed

Eliazar, Iddo I; Sokolov, Igor M

2010-01-01

Populations represented by collections of points scattered randomly on the real line are ubiquitous in science and engineering. The statistical modeling of such populations leads naturally to Poissonian populations-Poisson processes on the real line with a distinguished maximal point. Poissonian populations are infinite objects underlying key issues in statistical physics, probability theory, and random fractals. Due to their infiniteness, measuring the diversity of Poissonian populations depends on the lower-bound cut-off applied. This research characterizes the classes of Poissonian populations whose diversities are invariant with respect to the cut-off level applied and establishes an elemental connection between these classes and extreme-value theory. The measures of diversity considered are variance and dispersion, Simpson's index and inverse participation ratio, Shannon's entropy and Rényi's entropy, and Gini's index.

Multi-subject hierarchical inverse covariance modelling improves estimation of functional brain networks.

PubMed

Colclough, Giles L; Woolrich, Mark W; Harrison, Samuel J; Rojas López, Pedro A; Valdes-Sosa, Pedro A; Smith, Stephen M

2018-05-07

A Bayesian model for sparse, hierarchical, inver-covariance estimation is presented, and applied to multi-subject functional connectivity estimation in the human brain. It enables simultaneous inference of the strength of connectivity between brain regions at both subject and population level, and is applicable to fMRI, MEG and EEG data. Two versions of the model can encourage sparse connectivity, either using continuous priors to suppress irrelevant connections, or using an explicit description of the network structure to estimate the connection probability between each pair of regions. A large evaluation of this model, and thirteen methods that represent the state of the art of inverse covariance modelling, is conducted using both simulated and resting-state functional imaging datasets. Our novel Bayesian approach has similar performance to the best extant alternative, Ng et al.'s Sparse Group Gaussian Graphical Model algorithm, which also is based on a hierarchical structure. Using data from the Human Connectome Project, we show that these hierarchical models are able to reduce the measurement error in MEG beta-band functional networks by 10%, producing concomitant increases in estimates of the genetic influence on functional connectivity. Copyright © 2018. Published by Elsevier Inc.

An information sources map for Occupational and Environmental Medicine: guidance to network-based information through domain-specific indexing.

PubMed Central

Silverstein, S. M.; Miller, P. L.; Cullen, M. R.

1993-01-01

This paper describes a prototype information sources map (ISM), an on-line information source finder, for Occupational and Environmental Medicine (OEM). The OEM ISM was built as part of the Unified Medical Language System (UMLS) project of the National Library of Medicine. It allows a user to identify sources of on-line information appropriate to a specific OEM question, and connect to the sources. In the OEM ISM we explore a domain-specific method of indexing information source contents, and also a domain-specific user interface. The indexing represents a domain expert's opinion of the specificity of an information source in helping to answer specific types of domain questions. For each information source, an index field represents whether a source might provide useful information in an occupational, industrial, or environmental category. Additional fields represent the degree of specificity of a source in individual question types in each category. The paper discusses the development, design, and implementation of the prototype OEM ISM. PMID:8130548

Radiology Reporting System Data Exchange With the Electronic Health Record System: A Case Study in Iran.

PubMed

Ahmadi, Maryam; Ghazisaeidi, Marjan; Bashiri, Azadeh

2015-03-18

In order to better designing of electronic health record system in Iran, integration of health information systems based on a common language must be done to interpret and exchange this information with this system is required. This study provides a conceptual model of radiology reporting system using unified modeling language. The proposed model can solve the problem of integration this information system with the electronic health record system. By using this model and design its service based, easily connect to electronic health record in Iran and facilitate transfer radiology report data. This is a cross-sectional study that was conducted in 2013. The study population was 22 experts that working at the Imaging Center in Imam Khomeini Hospital in Tehran and the sample was accorded with the community. Research tool was a questionnaire that prepared by the researcher to determine the information requirements. Content validity and test-retest method was used to measure validity and reliability of questioner respectively. Data analyzed with average index, using SPSS. Also Visual Paradigm software was used to design a conceptual model. Based on the requirements assessment of experts and related texts, administrative, demographic and clinical data and radiological examination results and if the anesthesia procedure performed, anesthesia data suggested as minimum data set for radiology report and based it class diagram designed. Also by identifying radiology reporting system process, use case was drawn. According to the application of radiology reports in electronic health record system for diagnosing and managing of clinical problem of the patient, with providing the conceptual Model for radiology reporting system; in order to systematically design it, the problem of data sharing between these systems and electronic health records system would eliminate.

Discovering discovery patterns with Predication-based Semantic Indexing.

PubMed

Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W; Davies, Peter; Rindflesch, Thomas C

2012-12-01

In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as "discovery patterns", such as "drug x INHIBITS substance y, substance y CAUSES disease z" that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues. Copyright © 2012 Elsevier Inc. All rights reserved.

Discovering discovery patterns with predication-based Semantic Indexing

PubMed Central

Cohen, Trevor; Widdows, Dominic; Schvaneveldt, Roger W.; Davies, Peter; Rindflesch, Thomas C.

2012-01-01

In this paper we utilize methods of hyperdimensional computing to mediate the identification of therapeutically useful connections for the purpose of literature-based discovery. Our approach, named Predication-based Semantic Indexing, is utilized to identify empirically sequences of relationships known as “discovery patterns”, such as “drug x INHIBITS substance y, substance y CAUSES disease z” that link pharmaceutical substances to diseases they are known to treat. These sequences are derived from semantic predications extracted from the biomedical literature by the SemRep system, and subsequently utilized to direct the search for known treatments for a held out set of diseases. Rapid and efficient inference is accomplished through the application of geometric operators in PSI space, allowing for both the derivation of discovery patterns from a large set of known TREATS relationships, and the application of these discovered patterns to constrain search for therapeutic relationships at scale. Our results include the rediscovery of discovery patterns that have been constructed manually by other authors in previous research, as well as the discovery of a set of previously unrecognized patterns. The application of these patterns to direct search through PSI space results in better recovery of therapeutic relationships than is accomplished with models based on distributional statistics alone. These results demonstrate the utility of efficient approximate inference in geometric space as a means to identify therapeutic relationships, suggesting a role of these methods in drug repurposing efforts. In addition, the results provide strong support for the utility of the discovery pattern approach pioneered by Hristovski and his colleagues. PMID:22841748

Characterizing attention with predictive network models

PubMed Central

Rosenberg, M. D.; Finn, E. S.; Scheinost, D.; Constable, R. T.; Chun, M. M.

2017-01-01

Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals’ attentional abilities. Some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that (1) attention is a network property of brain computation, (2) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task, and (3) this architecture supports a general attentional ability common to several lab-based tasks and impaired in attention deficit hyperactivity disorder. Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. PMID:28238605

Development and optimization of water treatment reactors using TiO2-modified polymer beads with a refractive index identical to that of water

NASA Astrophysics Data System (ADS)

Myoga, Arata; Iwashita, Ryutaro; Unno, Noriyuki; Satake, Shin-ichi; Taniguchi, Jun; Yuki, Kazuhisa; Seki, Yohji

2018-03-01

Various water purification reactors were constructed using beads of TiO2-coated MEXFLON, which is a fluoropolymer exhibiting a refractive index identical to that of water. The performance of these reactors was evaluated in a recirculation experiment utilizing an aqueous solution of methylene blue. Reactor pipes (length = 150 mm, internal diameter = 10 mm) were made of a fluorinated ethylene polymer with a refractive index of 1.338 and contained 206-bead clusters. A UV lamp was used to irradiate eight reactor pipes surrounding it. The above-mentioned eight bead-packed pipes were connected both in series and in parallel, and the performances of these two reactor types were compared. A pseudo-first-order rate constant of 0.70 h- 1 was obtained for the series connection, whereas the corresponding value for the parallel connection was 1.5 times smaller, confirming the effectiveness of increasing the reaction surface by employing a larger number of beads.

Development and optimization of water treatment reactors using TiO2-modified polymer beads with a refractive index identical to that of water

NASA Astrophysics Data System (ADS)

Myoga, Arata; Iwashita, Ryutaro; Unno, Noriyuki; Satake, Shin-ichi; Taniguchi, Jun; Yuki, Kazuhisa; Seki, Yohji

2018-06-01

Various water purification reactors were constructed using beads of TiO2-coated MEXFLON, which is a fluoropolymer exhibiting a refractive index identical to that of water. The performance of these reactors was evaluated in a recirculation experiment utilizing an aqueous solution of methylene blue. Reactor pipes (length = 150 mm, internal diameter = 10 mm) were made of a fluorinated ethylene polymer with a refractive index of 1.338 and contained 206-bead clusters. A UV lamp was used to irradiate eight reactor pipes surrounding it. The above-mentioned eight bead-packed pipes were connected both in series and in parallel, and the performances of these two reactor types were compared. A pseudo-first-order rate constant of 0.70 h- 1 was obtained for the series connection, whereas the corresponding value for the parallel connection was 1.5 times smaller, confirming the effectiveness of increasing the reaction surface by employing a larger number of beads.

A rough set-based measurement model study on high-speed railway safety operation.

PubMed

Hu, Qizhou; Tan, Minjia; Lu, Huapu; Zhu, Yun

2018-01-01

Aiming to solve the safety problems of high-speed railway operation and management, one new method is urgently needed to construct on the basis of the rough set theory and the uncertainty measurement theory. The method should carefully consider every factor of high-speed railway operation that realizes the measurement indexes of its safety operation. After analyzing the factors that influence high-speed railway safety operation in detail, a rough measurement model is finally constructed to describe the operation process. Based on the above considerations, this paper redistricts the safety influence factors of high-speed railway operation as 16 measurement indexes which include staff index, vehicle index, equipment index and environment. And the paper also provides another reasonable and effective theoretical method to solve the safety problems of multiple attribute measurement in high-speed railway operation. As while as analyzing the operation data of 10 pivotal railway lines in China, this paper respectively uses the rough set-based measurement model and value function model (one model for calculating the safety value) for calculating the operation safety value. The calculation result shows that the curve of safety value with the proposed method has smaller error and greater stability than the value function method's, which verifies the feasibility and effectiveness.

Impacts of changes in groundwater recharge on the isotopic composition and geochemistry of seasonally ice-covered lakes: insights for sustainable management

NASA Astrophysics Data System (ADS)

Arnoux, Marie; Barbecot, Florent; Gibert-Brunet, Elisabeth; Gibson, John; Noret, Aurélie

2017-11-01

Lakes are under increasing pressure due to widespread anthropogenic impacts related to rapid development and population growth. Accordingly, many lakes are currently undergoing a systematic decline in water quality. Recent studies have highlighted that global warming and the subsequent changes in water use may further exacerbate eutrophication in lakes. Lake evolution depends strongly on hydrologic balance, and therefore on groundwater connectivity. Groundwater also influences the sensitivity of lacustrine ecosystems to climate and environmental changes, and governs their resilience. Improved characterization of groundwater exchange with lakes is needed today for lake preservation, lake restoration, and sustainable management of lake water quality into the future. In this context, the aim of the present paper is to determine if the future evolution of the climate, the population, and the recharge could modify the geochemistry of lakes (mainly isotopic signature and quality via phosphorous load) and if the isotopic monitoring of lakes could be an efficient tool to highlight the variability of the water budget and quality. Small groundwater-connected lakes were chosen to simulate changes in water balance and water quality expected under future climate change scenarios, namely representative concentration pathways (RCPs) 4.5 and 8.5. Contemporary baseline conditions, including isotope mass balance and geochemical characteristics, were determined through an intensive field-based research program prior to the simulations. Results highlight that future lake geochemistry and isotopic composition trends will depend on four main parameters: location (and therefore climate conditions), lake catchment size (which impacts the intensity of the flux change), lake volume (which impacts the range of variation), and lake G index (i.e., the percentage of groundwater that makes up total lake inflows), the latter being the dominant control on water balance conditions, as revealed by the sensitivity of lake isotopic composition. Based on these model simulations, stable isotopes appear to be especially useful for detecting changes in recharge to lakes with a G index of between 50 and 80 %, but response is non-linear. Simulated monthly trends reveal that evolution of annual lake isotopic composition can be dampened by opposing monthly recharge fluctuations. It is also shown that changes in water quality in groundwater-connected lakes depend significantly on lake location and on the intensity of recharge change.

A general framework for updating belief distributions.

PubMed

Bissiri, P G; Holmes, C C; Walker, S G

2016-11-01

We propose a framework for general Bayesian inference. We argue that a valid update of a prior belief distribution to a posterior can be made for parameters which are connected to observations through a loss function rather than the traditional likelihood function, which is recovered as a special case. Modern application areas make it increasingly challenging for Bayesians to attempt to model the true data-generating mechanism. For instance, when the object of interest is low dimensional, such as a mean or median, it is cumbersome to have to achieve this via a complete model for the whole data distribution. More importantly, there are settings where the parameter of interest does not directly index a family of density functions and thus the Bayesian approach to learning about such parameters is currently regarded as problematic. Our framework uses loss functions to connect information in the data to functionals of interest. The updating of beliefs then follows from a decision theoretic approach involving cumulative loss functions. Importantly, the procedure coincides with Bayesian updating when a true likelihood is known yet provides coherent subjective inference in much more general settings. Connections to other inference frameworks are highlighted.

Viscoelastic properties of bovine orbital connective tissue and fat: constitutive models.

PubMed

Yoo, Lawrence; Gupta, Vijay; Lee, Choongyeop; Kavehpore, Pirouz; Demer, Joseph L

2011-12-01

Reported mechanical properties of orbital connective tissue and fat have been too sparse to model strain-stress relationships underlying biomechanical interactions in strabismus. We performed rheological tests to develop a multi-mode upper convected Maxwell (UCM) model of these tissues under shear loading. From 20 fresh bovine orbits, 30 samples of connective tissue were taken from rectus pulley regions and 30 samples of fatty tissues from the posterior orbit. Additional samples were defatted to determine connective tissue weight proportion, which was verified histologically. Mechanical testing in shear employed a triborheometer to perform: strain sweeps at 0.5-2.0 Hz; shear stress relaxation with 1% strain; viscometry at 0.01-0.5 s(-1) strain rate; and shear oscillation at 1% strain. Average connective tissue weight proportion was 98% for predominantly connective tissue and 76% for fatty tissue. Connective tissue specimens reached a long-term relaxation modulus of 668 Pa after 1,500 s, while corresponding values for fatty tissue specimens were 290 Pa and 1,100 s. Shear stress magnitude for connective tissue exceeded that of fatty tissue by five-fold. Based on these data, we developed a multi-mode UCM model with variable viscosities and time constants, and a damped hyperelastic response that accurately described measured properties of both connective and fatty tissues. Model parameters differed significantly between the two tissues. Viscoelastic properties of predominantly connective orbital tissues under shear loading differ markedly from properties of orbital fat, but both are accurately reflected using UCM models. These viscoelastic models will facilitate realistic global modeling of EOM behavior in binocular alignment and strabismus.

Site index model for naturally regenerated even-aged longleaf pine

Treesearch

Dwight K. Lauer; John S. Kush

2013-01-01

Data from the Regional Longleaf Growth Study (339 permanent sample plots) were used to develop a site index model for naturally regenerated, even-aged longleaf pine (Pinus palustris Mill.). The site index equation was derived using the generalized algebraic difference approach and is base-age invariant. Using height as a measure of site productivity...

LeagueTLC: Transformational Learning Connections. Connecting Community Colleges with Innovative Solutions.

ERIC Educational Resources Information Center

Perez, Stella

This document describes LeagueTLC: Transformational Learning Connections (http://www.league.org/leaguetlc/index.htm), a Web site created by the League for Innovation in the Community College with funding from the Fund for the Improvement of Post Secondary Education (FIPSE). This Web site serves as a resource for community colleges by disseminating…

Exploring Volumetrically Indexed Cups

ERIC Educational Resources Information Center

Jones, Dustin L.

2011-01-01

This article was inspired by a set of 12 cylindrical cups, which are volumetrically indexed; that is to say, the volume of cup "n" is equal to "n" times the volume of cup 1. Various sets of volumetrically indexed cylindrical cups are explored. I demonstrate how this children's toy is ripe for mathematical investigation, with connections to…

Better models are more effectively connected models

NASA Astrophysics Data System (ADS)

Nunes, João Pedro; Bielders, Charles; Darboux, Frederic; Fiener, Peter; Finger, David; Turnbull-Lloyd, Laura; Wainwright, John

2016-04-01

The concept of hydrologic and geomorphologic connectivity describes the processes and pathways which link sources (e.g. rainfall, snow and ice melt, springs, eroded areas and barren lands) to accumulation areas (e.g. foot slopes, streams, aquifers, reservoirs), and the spatial variations thereof. There are many examples of hydrological and sediment connectivity on a watershed scale; in consequence, a process-based understanding of connectivity is crucial to help managers understand their systems and adopt adequate measures for flood prevention, pollution mitigation and soil protection, among others. Modelling is often used as a tool to understand and predict fluxes within a catchment by complementing observations with model results. Catchment models should therefore be able to reproduce the linkages, and thus the connectivity of water and sediment fluxes within the systems under simulation. In modelling, a high level of spatial and temporal detail is desirable to ensure taking into account a maximum number of components, which then enables connectivity to emerge from the simulated structures and functions. However, computational constraints and, in many cases, lack of data prevent the representation of all relevant processes and spatial/temporal variability in most models. In most cases, therefore, the level of detail selected for modelling is too coarse to represent the system in a way in which connectivity can emerge; a problem which can be circumvented by representing fine-scale structures and processes within coarser scale models using a variety of approaches. This poster focuses on the results of ongoing discussions on modelling connectivity held during several workshops within COST Action Connecteur. It assesses the current state of the art of incorporating the concept of connectivity in hydrological and sediment models, as well as the attitudes of modellers towards this issue. The discussion will focus on the different approaches through which connectivity can be represented in models: either by allowing it to emerge from model behaviour or by parameterizing it inside model structures; and on the appropriate scale at which processes should be represented explicitly or implicitly. It will also explore how modellers themselves approach connectivity through the results of a community survey. Finally, it will present the outline of an international modelling exercise aimed at assessing how different modelling concepts can capture connectivity in real catchments.

Characterization of craniofacial sutures using the finite element method.

PubMed

Maloul, Asmaa; Fialkov, Jeffrey; Wagner, Diane; Whyne, Cari M

2014-01-03

Characterizing the biomechanical behavior of sutures in the human craniofacial skeleton (CFS) is essential to understand the global impact of these articulations on load transmission, but is challenging due to the complexity of their interdigitated morphology, the multidirectional loading they are exposed to and the lack of well-defined suture material properties. This study aimed to quantify the impact of morphological features, direction of loading and suture material properties on the mechanical behavior of sutures and surrounding bone in the CFS. Thirty-six idealized finite element (FE) models were developed. One additional specimen-specific FE model was developed based on the morphology obtained from a µCT scan to represent the morphological complexity inherent in CFS sutures. Outcome variables of strain energy (SE) and von Mises stress (σvm) were evaluated to characterize the sutures' biomechanical behavior. Loading direction was found to impact the relationship between SE and interdigitation index and yielded varied patterns of σvm in both the suture and surrounding bone. Adding bone connectivity reduced suture strain energy and altered the σvm distribution. Incorporating transversely isotropic material properties was found to reduce SE, but had little impact on stress patterns. High-resolution µCT scanning of the suture revealed a complex morphology with areas of high and low interdigitations. The specimen specific suture model results were reflective of SE absorption and σvm distribution patterns consistent with the simplified FE results. Suture mechanical behavior is impacted by morphologic factors (interdigitation and connectivity), which may be optimized for regional loading within the CFS. © 2013 Elsevier Ltd. All rights reserved.

Self-Reconfiguration Planning of Robot Embodiment for Inherent Safe Performance

NASA Astrophysics Data System (ADS)

Uchida, Masafumi; Nozawa, Akio; Asano, Hirotoshi; Onogaki, Hitoshi; Mizuno, Tota; Park, Young-Il; Ide, Hideto; Yokoyama, Shuichi

In the situation in which a robot and a human work together by collaborating with each other, a robot and a human share one working environment, and each interferes in each other. In other ward, it is impossible to avoid the physical contact and the interaction of force between a robot and a human. The boundary of each complex dynamic occupation area changes in the connection movement which is the component of collaborative works at this time. The main restraint condition which relates to the robustness of that connection movement is each physical charactristics, that is, the embodiment. A robot body is variability though the embodiment of a human is almost fixed. Therefore, the safe and the robust connection movement is brought when a robot has the robot body which is well suitable for the embodiment of a human. A purpose for this research is that the colaboration works between the self-reconfiguration robot and a human is realized. To achieve this purpose, a self-reconfiguration algorithm based on some indexes to evaluate a robot body in the macroscopic point of view was examined on a modular robot system of the 2-D lattice structure. In this paper, it investigated effect specially that the object of learning of each individual was limited to the cooperative behavior between the adjoining modules toward the macroscopic evaluation index.

Hybrid discrete-time neural networks.

PubMed

Cao, Hongjun; Ibarz, Borja

2010-11-13

Hybrid dynamical systems combine evolution equations with state transitions. When the evolution equations are discrete-time (also called map-based), the result is a hybrid discrete-time system. A class of biological neural network models that has recently received some attention falls within this category: map-based neuron models connected by means of fast threshold modulation (FTM). FTM is a connection scheme that aims to mimic the switching dynamics of a neuron subject to synaptic inputs. The dynamic equations of the neuron adopt different forms according to the state (either firing or not firing) and type (excitatory or inhibitory) of their presynaptic neighbours. Therefore, the mathematical model of one such network is a combination of discrete-time evolution equations with transitions between states, constituting a hybrid discrete-time (map-based) neural network. In this paper, we review previous work within the context of these models, exemplifying useful techniques to analyse them. Typical map-based neuron models are low-dimensional and amenable to phase-plane analysis. In bursting models, fast-slow decomposition can be used to reduce dimensionality further, so that the dynamics of a pair of connected neurons can be easily understood. We also discuss a model that includes electrical synapses in addition to chemical synapses with FTM. Furthermore, we describe how master stability functions can predict the stability of synchronized states in these networks. The main results are extended to larger map-based neural networks.

Quantitative structure-retention relationships of polycyclic aromatic hydrocarbons gas-chromatographic retention indices.

PubMed

Drosos, Juan Carlos; Viola-Rhenals, Maricela; Vivas-Reyes, Ricardo

2010-06-25

Polycyclic aromatic compounds (PAHs) are of concern in environmental chemistry and toxicology. In the present work, a QSRR study was performed for 209 previously reported PAHs using quantum mechanics and other sources descriptors estimated by different approaches. The B3LYP/6-31G* level of theory was used for geometrical optimization and quantum mechanics related variables. A good linear relationship between gas-chromatographic retention index and electronic or topologic descriptors was found by stepwise linear regression analysis. The molecular polarizability (alpha) and the second order molecular connectivity Kier and Hall index ((2)chi) showed evidence of significant correlation with retention index by means of important squared coefficient of determination, (R(2)), values (R(2)=0.950 and 0.962, respectively). A one variable QSRR model is presented for each descriptor and both models demonstrates a significant predictive capacity established using the leave-many-out LMO (excluding 25% of rows) cross validation method's q(2) cross-validation coefficients q(2)(CV-LMO25%), (obtained q(2)(CV-LMO25%) 0.947 and 0.960, respectively). Furthermore, the physicochemical interpretation of selected descriptors allowed detailed explanation of the source of the observed statistical correlation. The model analysis suggests that only one descriptor is sufficient to establish a consistent retention index-structure relationship. Moderate or non-significant improve was observed for quantitative results or statistical validation parameters when introducing more terms in predictive equation. The one parameter QSRR proposed model offers a consistent scheme to predict chromatographic properties of PAHs compounds. Copyright 2010 Elsevier B.V. All rights reserved.

An adaptive state of charge estimation approach for lithium-ion series-connected battery system

NASA Astrophysics Data System (ADS)

Peng, Simin; Zhu, Xuelai; Xing, Yinjiao; Shi, Hongbing; Cai, Xu; Pecht, Michael

2018-07-01

Due to the incorrect or unknown noise statistics of a battery system and its cell-to-cell variations, state of charge (SOC) estimation of a lithium-ion series-connected battery system is usually inaccurate or even divergent using model-based methods, such as extended Kalman filter (EKF) and unscented Kalman filter (UKF). To resolve this problem, an adaptive unscented Kalman filter (AUKF) based on a noise statistics estimator and a model parameter regulator is developed to accurately estimate the SOC of a series-connected battery system. An equivalent circuit model is first built based on the model parameter regulator that illustrates the influence of cell-to-cell variation on the battery system. A noise statistics estimator is then used to attain adaptively the estimated noise statistics for the AUKF when its prior noise statistics are not accurate or exactly Gaussian. The accuracy and effectiveness of the SOC estimation method is validated by comparing the developed AUKF and UKF when model and measurement statistics noises are inaccurate, respectively. Compared with the UKF and EKF, the developed method shows the highest SOC estimation accuracy.

Investigations of Novel Surface Modification Techniques for Wear Resistant Al and Mg Based Materials

DTIC Science & Technology

1994-01-01

microhardness to resist the abrasive wear. Moreover it is required to form dense or fine-porous uniform layers to provide the antifriction characteristics...technological regimes for production of OCC having maximum of thickness, microhardness and uniformity is expediently to carry on using the silicate-alkali...includes at the same time both the index of the process effectiveness and the strength and geometrical characteristics of the product . In connection

Synchronization from Second Order Network Connectivity Statistics

PubMed Central

Zhao, Liqiong; Beverlin, Bryce; Netoff, Theoden; Nykamp, Duane Q.

2011-01-01

We investigate how network structure can influence the tendency for a neuronal network to synchronize, or its synchronizability, independent of the dynamical model for each neuron. The synchrony analysis takes advantage of the framework of second order networks, which defines four second order connectivity statistics based on the relative frequency of two-connection network motifs. The analysis identifies two of these statistics, convergent connections, and chain connections, as highly influencing the synchrony. Simulations verify that synchrony decreases with the frequency of convergent connections and increases with the frequency of chain connections. These trends persist with simulations of multiple models for the neuron dynamics and for different types of networks. Surprisingly, divergent connections, which determine the fraction of shared inputs, do not strongly influence the synchrony. The critical role of chains, rather than divergent connections, in influencing synchrony can be explained by their increasing the effective coupling strength. The decrease of synchrony with convergent connections is primarily due to the resulting heterogeneity in firing rates. PMID:21779239

Quantifying hydrologic connectivity with measures from the brain neurosciences - a feasibility study

NASA Astrophysics Data System (ADS)

Rinderer, Michael; Ali, Genevieve; Larsen, Laurel

2017-04-01

While the concept of connectivity is increasingly applied in hydrology and ecology, little agreement exists on its definition and quantification approaches. In contrast, the neurosciences have developed a systematic conceptualization of connectivity and methods to quantify it. In particular, neuroscientists make a clear distinction between: 1) structural connectivity, which is determined by the anatomy of the brain neural network, 2) functional connectivity, that is based on statistical dependencies between neural signals, and 3) effective connectivity, that allows to infer causal relations based on the assumption that "true" interactions occur with a certain time delay. In a similar vein, in hydrology, structural connectivity can be defined as the physical adjacency of landscape elements that are seen as a prerequisite of material transfer, while functional or process connectivity would rather describe interactions or causal relations between spatial adjacency characteristics and temporally varying factors. While hydrologists have suggested methods to derive structural connectivity (SC), the quantification of functional (FC) or effective connectivity (EC) has remained elusive. The goal of the current study was therefore to apply timeseries analysis methods from brain neuroscience to quantify EC and FC among groundwater (n = 34) and stream discharge (n = 1) monitoring sites in a 20-ha Swiss catchment where topography is assumed to be a major driver of connectivity. SC was assessed through influence maps that quantify the percentage of flow from an upslope site to a downslope site by applying a multiple flow direction algorithm. FC was assessed by cross-correlation, total and partial mutual information while EC was quantified via total and partial entropy, Granger causality and a phase slope index. Our results showed that many structural connections were also expressed as functional or effective connections, which is reasonable in a catchment with shallow perched groundwater tables. The differentiation between FC and EC measures allowed us to distinguish between hydrological connectivity (i.e., Darcian fluxes of water) and hydraulic connectivity (i.e. pressure wave-driven processes). However, some FC and EC measures also detected the presence of connectivity despite the absence of SC, which highlights the limits of applying brain connectivity measures to hydrology. We therefore conclude that brain neuroscience methods for assessing FC and EC can be powerful tools in assessing hydrological connectivity as long as they are constrained by SC measures.

Ionosonde-based indices for improved representation of solar cycle variation in the International Reference Ionosphere model

NASA Astrophysics Data System (ADS)

Brown, Steven; Bilitza, Dieter; Yiǧit, Erdal

2018-06-01

A new monthly ionospheric index, IGNS, is presented to improve the representation of the solar cycle variation of the ionospheric F2 peak plasma frequency, foF2. IGNS is calculated using a methodology similar to the construction of the "global effective sunspot number", IG, given by Liu et al. (1983) but selects ionosonde observations based on hemispheres. We incorporated the updated index into the International Reference Ionosphere (IRI) model and compared the foF2 model predictions with global ionospheric observations. We also investigated the influence of the underlying foF2 model on the IG index. IRI has two options for foF2 specification, the CCIR-66 and URSI-88 foF2 models. For the first time, we have calculated IG using URSI-88 and assessed the impact on model predictions. Through a retrospective model-data comparison, results show that the inclusion of the new monthly IGNS index in place of the current 12-month smoothed IG index reduce the foF2 model prediction errors by nearly a factor of two. These results apply to both day-time and nightime predictions. This is due to an overall improved prediction of foF2 seasonal and solar cycle variations in the different hemispheres.

Development and validation of the Korea Dementia Comorbidity Index (KDCI): A nationwide population-based cohort study from 2002 to 2013.

PubMed

Kim, Jae-Hyun; Yoo, Ki-Bong; Lee, Yunhwan

2017-09-01

This study develop and validate a simple and accessible measure of comorbidity, named the Korean Dementia Comorbidity index (KDCI), to assist in predicting the onset of dementia. This study used the National Health Insurance Service-Cohort Sample Database from 2002 to 2013 (n=23,856). Cox proportional hazard model was used to estimate incident dementia (International Classification of Disease, 10th edition (ICD-10) codes: F00-F03, G30, G311), with a hazard ratio higher than 1.05 for each comorbid condition being assigned a score. Scores ranging from 1 to 4 were assigned based on the magnitude of the hazard ratio (HR): 1 (1.050≤HR≤1.099), 2 (1.100≤HR≤1.149), 3 (1.150≤HR≤1.199), and 4 (HR≥1.200) Summated scores of comorbidities for each individual constituted the Korean Dementia Comorbidity Index (KDCI). Five patterns were extracted: (1) disease of the eye and adnexa; (2) endocrine and metabolic disease, and disease of circulatory system; (3) disease of the musculoskeletal system and connective tissue; (4) disease of the respiratory system; and (5) disease of the nervous system, and mental and behavioral disorders through factor analysis. Fitting performance by Akaike information criterion (AIC) of CCI by Charlson, CCI by Quan and KDCI adjusting for age and sex was 29,486, 29,488 and 29,444, respectively. Our analysis results on discriminatory abilities provided evidence that KDCI is superior to other comorbidity indices on incident dementia in terms of comorbidity adjustment. Therefore, KDCI can be a useful tool to identify incident dementia. This has implications for clinical management of patients with multimorbidity as well as risk adjustment for database studies. Copyright © 2017 Elsevier B.V. All rights reserved.

Modelling highly variable environmental factors to assess potential microbial respiration in complex floodplain landscapes

PubMed Central

Tritthart, Michael; Welti, Nina; Bondar-Kunze, Elisabeth; Pinay, Gilles; Hein, Thomas; Habersack, Helmut

2011-01-01

The hydrological exchange conditions strongly determine the biogeochemical dynamics in river systems. More specifically, the connectivity of surface waters between main channels and floodplains is directly controlling the delivery of organic matter and nutrients into the floodplains, where biogeochemical processes recycle them with high rates of activity. Hence, an in-depth understanding of the connectivity patterns between main channel and floodplains is important for the modelling of potential gas emissions in floodplain landscapes. A modelling framework that combines steady-state hydrodynamic simulations with long-term discharge hydrographs was developed to calculate water depths as well as statistical probabilities and event durations for every node of a computation mesh being connected to the main river. The modelling framework was applied to two study sites in the floodplains of the Austrian Danube River, East of Vienna. Validation of modelled flood events showed good agreement with gauge readings. Together with measured sediment properties, results of the validated connectivity model were used as basis for a predictive model yielding patterns of potential microbial respiration based on the best fit between characteristics of a number of sampling sites and the corresponding modelled parameters. Hot spots of potential microbial respiration were found in areas of lower connectivity if connected during higher discharges and areas of high water depths. PMID:27667961

Better state-of-good-repair indicators for the transportation performance index.

DOT National Transportation Integrated Search

2014-07-01

The Transportation Performance Index was developed for the US Chamber of Commerce to track the : performance of transportation infrastructure over time and explore the connection between economic : health and infrastructure performance. This project ...

Psychophysiological whole-brain network clustering based on connectivity dynamics analysis in naturalistic conditions.

PubMed

Raz, Gal; Shpigelman, Lavi; Jacob, Yael; Gonen, Tal; Benjamini, Yoav; Hendler, Talma

2016-12-01

We introduce a novel method for delineating context-dependent functional brain networks whose connectivity dynamics are synchronized with the occurrence of a specific psychophysiological process of interest. In this method of context-related network dynamics analysis (CRNDA), a continuous psychophysiological index serves as a reference for clustering the whole-brain into functional networks. We applied CRNDA to fMRI data recorded during the viewing of a sadness-inducing film clip. The method reliably demarcated networks in which temporal patterns of connectivity related to the time series of reported emotional intensity. Our work successfully replicated the link between network connectivity and emotion rating in an independent sample group for seven of the networks. The demarcated networks have clear common functional denominators. Three of these networks overlap with distinct empathy-related networks, previously identified in distinct sets of studies. The other networks are related to sensorimotor processing, language, attention, and working memory. The results indicate that CRNDA, a data-driven method for network clustering that is sensitive to transient connectivity patterns, can productively and reliably demarcate networks that follow psychologically meaningful processes. Hum Brain Mapp 37:4654-4672, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

On the connection between financial processes with stochastic volatility and nonextensive statistical mechanics

NASA Astrophysics Data System (ADS)

Queirós, S. M. D.; Tsallis, C.

2005-11-01

The GARCH algorithm is the most renowned generalisation of Engle's original proposal for modelising returns, the ARCH process. Both cases are characterised by presenting a time dependent and correlated variance or volatility. Besides a memory parameter, b, (present in ARCH) and an independent and identically distributed noise, ω, GARCH involves another parameter, c, such that, for c=0, the standard ARCH process is reproduced. In this manuscript we use a generalised noise following a distribution characterised by an index qn, such that qn=1 recovers the Gaussian distribution. Matching low statistical moments of GARCH distribution for returns with a q-Gaussian distribution obtained through maximising the entropy Sq=1-sumipiq/q-1, basis of nonextensive statistical mechanics, we obtain a sole analytical connection between q and left( b,c,qnright) which turns out to be remarkably good when compared with computational simulations. With this result we also derive an analytical approximation for the stationary distribution for the (squared) volatility. Using a generalised Kullback-Leibler relative entropy form based on Sq, we also analyse the degree of dependence between successive returns, zt and zt+1, of GARCH(1,1) processes. This degree of dependence is quantified by an entropic index, qop. Our analysis points the existence of a unique relation between the three entropic indexes qop, q and qn of the problem, independent of the value of (b,c).

A generative model of whole-brain effective connectivity.

PubMed

Frässle, Stefan; Lomakina, Ekaterina I; Kasper, Lars; Manjaly, Zina M; Leff, Alex; Pruessmann, Klaas P; Buhmann, Joachim M; Stephan, Klaas E

2018-05-25

The development of whole-brain models that can infer effective (directed) connection strengths from fMRI data represents a central challenge for computational neuroimaging. A recently introduced generative model of fMRI data, regression dynamic causal modeling (rDCM), moves towards this goal as it scales gracefully to very large networks. However, large-scale networks with thousands of connections are difficult to interpret; additionally, one typically lacks information (data points per free parameter) for precise estimation of all model parameters. This paper introduces sparsity constraints to the variational Bayesian framework of rDCM as a solution to these problems in the domain of task-based fMRI. This sparse rDCM approach enables highly efficient effective connectivity analyses in whole-brain networks and does not require a priori assumptions about the network's connectivity structure but prunes fully (all-to-all) connected networks as part of model inversion. Following the derivation of the variational Bayesian update equations for sparse rDCM, we use both simulated and empirical data to assess the face validity of the model. In particular, we show that it is feasible to infer effective connection strengths from fMRI data using a network with more than 100 regions and 10,000 connections. This demonstrates the feasibility of whole-brain inference on effective connectivity from fMRI data - in single subjects and with a run-time below 1 min when using parallelized code. We anticipate that sparse rDCM may find useful application in connectomics and clinical neuromodeling - for example, for phenotyping individual patients in terms of whole-brain network structure. Copyright © 2018. Published by Elsevier Inc.

Network diffusion accurately models the relationship between structural and functional brain connectivity networks

PubMed Central

Abdelnour, Farras; Voss, Henning U.; Raj, Ashish

2014-01-01

The relationship between anatomic connectivity of large-scale brain networks and their functional connectivity is of immense importance and an area of active research. Previous attempts have required complex simulations which model the dynamics of each cortical region, and explore the coupling between regions as derived by anatomic connections. While much insight is gained from these non-linear simulations, they can be computationally taxing tools for predicting functional from anatomic connectivities. Little attention has been paid to linear models. Here we show that a properly designed linear model appears to be superior to previous non-linear approaches in capturing the brain’s long-range second order correlation structure that governs the relationship between anatomic and functional connectivities. We derive a linear network of brain dynamics based on graph diffusion, whereby the diffusing quantity undergoes a random walk on a graph. We test our model using subjects who underwent diffusion MRI and resting state fMRI. The network diffusion model applied to the structural networks largely predicts the correlation structures derived from their fMRI data, to a greater extent than other approaches. The utility of the proposed approach is that it can routinely be used to infer functional correlation from anatomic connectivity. And since it is linear, anatomic connectivity can also be inferred from functional data. The success of our model confirms the linearity of ensemble average signals in the brain, and implies that their long-range correlation structure may percolate within the brain via purely mechanistic processes enacted on its structural connectivity pathways. PMID:24384152

The degree-related clustering coefficient and its application to link prediction

NASA Astrophysics Data System (ADS)

Liu, Yangyang; Zhao, Chengli; Wang, Xiaojie; Huang, Qiangjuan; Zhang, Xue; Yi, Dongyun

2016-07-01

Link prediction plays a significant role in explaining the evolution of networks. However it is still a challenging problem that has been addressed only with topological information in recent years. Based on the belief that network nodes with a great number of common neighbors are more likely to be connected, many similarity indices have achieved considerable accuracy and efficiency. Motivated by the natural assumption that the effect of missing links on the estimation of a node's clustering ability could be related to node degree, in this paper, we propose a degree-related clustering coefficient index to quantify the clustering ability of nodes. Unlike the classical clustering coefficient, our new coefficient is highly robust when the observed bias of links is considered. Furthermore, we propose a degree-related clustering ability path (DCP) index, which applies the proposed coefficient to the link prediction problem. Experiments on 12 real-world networks show that our proposed method is highly accurate and robust compared with four common-neighbor-based similarity indices (Common Neighbors(CN), Adamic-Adar(AA), Resource Allocation(RA), and Preferential Attachment(PA)), and the recently introduced clustering ability (CA) index.

Objectively measured walkability and active transport and weight-related outcomes in adults: a systematic review.

PubMed

Grasser, Gerlinde; Van Dyck, Delfien; Titze, Sylvia; Stronegger, Willibald

2013-08-01

The aim of this study was to investigate which GIS-based measures of walkability (density, land-use mix, connectivity and walkability indexes) in urban and suburban neighbourhoods are used in research and which of them are consistently associated with walking and cycling for transport, overall active transportation and weight-related measures in adults. A systematic review of English publications using PubMed, Science Direct, Active Living Research Literature Database, the Transportation Research Information Service and reference lists was conducted. The search terms utilised were synonyms for GIS in combination with synonyms for the outcomes. Thirty-four publications based on 19 different studies were eligible. Walkability measures such as gross population density, intersection density and walkability indexes most consistently correlated with measures of physical activity for transport. Results on weight-related measures were inconsistent. More research is needed to determine whether walkability is an appropriate measure for predicting weight-related measures and overall active transportation. As most of the consistent correlates, gross population density, intersection density and the walkability indexes have the potential to be used in planning and monitoring.

Organizational performance comparative study of Jakarta and Medan city happy planet index

NASA Astrophysics Data System (ADS)

Perdamenta Tarigan, Nuah

2018-03-01

Comparative Study of Organizational Performance relating to the Happy Planet Index between Jakarta and Medan is quite challenging, the performance of the organization here is related to organizational arrangements relating to the potential associated with Corporate Social Responsibility (CSR), which is based on ISO 26000, how local leaders put the idea to build a city not only by the government budget each area, but also invite the participation of companies that have programs related to community empowerment is not a fund for cash, but the real form that is present in removing the great problems in society cities beyond than just its obligations but has become a conscious citizen that cares about its environment both natural and artificial. In the end of this research, we will see which one is the best based on the standard Happy Planet Index (HPI) which is phenomenal in the world now, connected again with 17 pieces of Sustainable Development Goals, particularly the goal of the 17th. The study was conducted by the research literature and implemented in a short time. However, a large study being conducted by the researcher.

Thalamic functional connectivity predicts seizure laterality in individual TLE patients: application of a biomarker development strategy.

PubMed

Barron, Daniel S; Fox, Peter T; Pardoe, Heath; Lancaster, Jack; Price, Larry R; Blackmon, Karen; Berry, Kristen; Cavazos, Jose E; Kuzniecky, Ruben; Devinsky, Orrin; Thesen, Thomas

2015-01-01

Noninvasive markers of brain function could yield biomarkers in many neurological disorders. Disease models constrained by coordinate-based meta-analysis are likely to increase this yield. Here, we evaluate a thalamic model of temporal lobe epilepsy that we proposed in a coordinate-based meta-analysis and extended in a diffusion tractography study of an independent patient population. Specifically, we evaluated whether thalamic functional connectivity (resting-state fMRI-BOLD) with temporal lobe areas can predict seizure onset laterality, as established with intracranial EEG. Twenty-four lesional and non-lesional temporal lobe epilepsy patients were studied. No significant differences in functional connection strength in patient and control groups were observed with Mann-Whitney Tests (corrected for multiple comparisons). Notwithstanding the lack of group differences, individual patient difference scores (from control mean connection strength) successfully predicted seizure onset zone as shown in ROC curves: discriminant analysis (two-dimensional) predicted seizure onset zone with 85% sensitivity and 91% specificity; logistic regression (four-dimensional) achieved 86% sensitivity and 100% specificity. The strongest markers in both analyses were left thalamo-hippocampal and right thalamo-entorhinal cortex functional connection strength. Thus, this study shows that thalamic functional connections are sensitive and specific markers of seizure onset laterality in individual temporal lobe epilepsy patients. This study also advances an overall strategy for the programmatic development of neuroimaging biomarkers in clinical and genetic populations: a disease model informed by coordinate-based meta-analysis was used to anatomically constrain individual patient analyses.

Age-dependence of the average and equivalent refractive indices of the crystalline lens

PubMed Central

Charman, W. Neil; Atchison, David A.

2013-01-01

Lens average and equivalent refractive indices are required for purposes such as lens thickness estimation and optical modeling. We modeled the refractive index gradient as a power function of the normalized distance from lens center. Average index along the lens axis was estimated by integration. Equivalent index was estimated by raytracing through a model eye to establish ocular refraction, and then backward raytracing to determine the constant refractive index yielding the same refraction. Assuming center and edge indices remained constant with age, at 1.415 and 1.37 respectively, average axial refractive index increased (1.408 to 1.411) and equivalent index decreased (1.425 to 1.420) with age increase from 20 to 70 years. These values agree well with experimental estimates based on different techniques, although the latter show considerable scatter. The simple model of index gradient gives reasonable estimates of average and equivalent lens indices, although refinements in modeling and measurements are required. PMID:24466474

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

Intra-hemispheric intrinsic connectivity asymmetry and its relationships with handedness and language Lateralization.

PubMed

Joliot, M; Tzourio-Mazoyer, N; Mazoyer, B

2016-12-01

Asymmetry in intra-hemispheric intrinsic connectivity, and its association with handedness and hemispheric dominance for language, were investigated in a sample of 290 healthy volunteers enriched in left-handers (52.7%). From the resting-state FMRI data of each participant, we derived an intra-hemispheric intrinsic connectivity asymmetry (HICA) matrix as the difference between the left and right intra-hemispheric matrices of intrinsic correlation computed for each pair of the AICHA atlas ROIs. We defined a similarity measure between the HICA matrices of two individuals as the correlation coefficient of their corresponding elements, and computed for each individual an index of intra-hemispheric intrinsic connectivity asymmetry as the average similarity measure of his HICA matrix to those of the other subjects of the sample (HICAs). Gaussian-mixture modeling of the age-corrected HICAs sample distribution revealed that two types of HICA patterns were present, one (Typical_HICA) including 92.4% of the participants while the other (Atypical_HICA) included only 7.6% of them, mostly left-handers. In addition, we investigated the relationship between asymmetry in intra-hemispheric intrinsic connectivity and language hemispheric dominance, including a potential effect of handedness on this relationship, thanks to an FMRI acquisition during language production from which an hemispheric functional lateralization index for language (HFLI) and a type of hemispheric dominance for language, namely leftward, ambilateral, or rightward, were derived for each individual. There was a significant association between the types of language hemispheric dominance and of intra-hemispheric intrinsic connectivity asymmetry, occurrence of Atypical_HICAs individuals being very high in the group of individuals rightward-lateralized for language (80%), reduced in the ambilateral group (19%) and rare in individuals leftward-lateralized for language (less than 3%). Quantitatively, we found a significant positive linear relationship between the HICAs and HFLI indices, with an effect of handedness on the intercept but not on the slope of this relationship. These findings demonstrate that handedness and hemispheric dominance for language are significantly but independently associated with the asymmetry of intra-hemispheric intrinsic connectivity. These findings suggest that asymmetry in intra-hemispheric connectivity is a variable phenotype shaped in part by hemispheric lateralization for language, but possibly also depending on other lateralized functions. Copyright © 2016 Elsevier Ltd. All rights reserved.

PTSITE--a new method of site evaluation for loblolly pine: model development and user's guide

Treesearch

Constance A. Harrington

1991-01-01

A model, named PTSITE, was developed to predict site index for loblolly pine based on soil characteristics, site location on the landscape, and land history. The model was tested with data from several sources and judged to predict site index within + 4 feet (P

Path connectivity based spectral defragmentation in flexible bandwidth networks.

PubMed

Wang, Ying; Zhang, Jie; Zhao, Yongli; Zhang, Jiawei; Zhao, Jie; Wang, Xinbo; Gu, Wanyi

2013-01-28

Optical networks with flexible bandwidth provisioning have become a very promising networking architecture. It enables efficient resource utilization and supports heterogeneous bandwidth demands. In this paper, two novel spectrum defragmentation approaches, i.e. Maximum Path Connectivity (MPC) algorithm and Path Connectivity Triggering (PCT) algorithm, are proposed based on the notion of Path Connectivity, which is defined to represent the maximum variation of node switching ability along the path in flexible bandwidth networks. A cost-performance-ratio based profitability model is given to denote the prons and cons of spectrum defragmentation. We compare these two proposed algorithms with non-defragmentation algorithm in terms of blocking probability. Then we analyze the differences of defragmentation profitability between MPC and PCT algorithms.

[Modeling and Simulation of Spectral Polarimetric BRDF].

PubMed

Ling, Jin-jiang; Li, Gang; Zhang, Ren-bin; Tang, Qian; Ye, Qiu

2016-01-01

Under the conditions of the polarized light, The reflective surface of the object is affected by many factors, refractive index, surface roughness, and so the angle of incidence. For the rough surface in the different wavelengths of light exhibit different reflection characteristics of polarization, a spectral polarimetric BRDF based on Kirchhof theory is proposee. The spectral model of complex refraction index is combined with refraction index and extinction coefficient spectral model which were got by using the known complex refraction index at different value. Then get the spectral model of surface roughness derived from the classical surface roughness measuring method combined with the Fresnel reflection function. Take the spectral model of refraction index and roughness into the BRDF model, then the spectral polarimetirc BRDF model is proposed. Compare the simulation results of the refractive index varies with wavelength, roughness is constant, the refraction index and roughness both vary with wavelength and origin model with other papers, it shows that, the spectral polarimetric BRDF model can show the polarization characteristics of the surface accurately, and can provide a reliable basis for the application of polarization remote sensing, and other aspects of the classification of substances.

Connection between quantum systems involving the fourth Painlevé transcendent and k-step rational extensions of the harmonic oscillator related to Hermite exceptional orthogonal polynomial

NASA Astrophysics Data System (ADS)

Marquette, Ian; Quesne, Christiane

2016-05-01

The purpose of this communication is to point out the connection between a 1D quantum Hamiltonian involving the fourth Painlevé transcendent PIV, obtained in the context of second-order supersymmetric quantum mechanics and third-order ladder operators, with a hierarchy of families of quantum systems called k-step rational extensions of the harmonic oscillator and related with multi-indexed Xm1,m2,…,mk Hermite exceptional orthogonal polynomials of type III. The connection between these exactly solvable models is established at the level of the equivalence of the Hamiltonians using rational solutions of the fourth Painlevé equation in terms of generalized Hermite and Okamoto polynomials. We also relate the different ladder operators obtained by various combinations of supersymmetric constructions involving Darboux-Crum and Krein-Adler supercharges, their zero modes and the corresponding energies. These results will demonstrate and clarify the relation observed for a particular case in previous papers.

Range indices of geomagnetic activity

USGS Publications Warehouse

Stuart, W.F.; Green, A.W.

1988-01-01

The simplest index of geomagnetic activity is the range in nT from maximum to minimum value of the field in a given time interval. The hourly range R was recommended by IAGA for use at observatories at latitudes greater than 65??, but was superceded by AE. The most used geomagnetic index K is based on the range of activity in a 3 h interval corrected for the regular daily variation. In order to take advantage of real time data processing, now available at many observatories, it is proposed to introduce a 1 h range index and also a 3 h range index. Both will be computed hourly, i.e. each will have a series of 24 per day, the 3 h values overlapping. The new data will be available as the range (R) of activity in nT and also as a logarithmic index (I) of the range. The exponent relating index to range in nT is based closely on the scale used for computing K values. The new ranges and range indices are available, from June 1987, to users in real time and can be accessed by telephone connection or computer network. Their first year of production is regarded as a trial period during which their value to the scientific and commercial communities will be assessed, together with their potential as indicators of regional and global disturbances' and in which trials will be conducted into ways of eliminating excessive bias at quiet times due to the rate of change of the daily variation field. ?? 1988.

Force Model for Control of Tendon Driven Hands

NASA Technical Reports Server (NTRS)

Pena, Edward; Thompson, David E.

1997-01-01

Knowing the tendon forces generated for a given task such as grasping via a model, an artificial hand can be controlled. A two-dimensional force model for the index finger was developed. This system is assumed to be in static equilibrium, therefore, the equations of equilibrium were applied at each joint. Constraint equations describing the tendon branch connectivity were used. Gaussian elimination was used to solve for the unknowns of the Linear system. Results from initial work on estimating tendon forces in post-operative hands during active motion therapy were discussed. The results are important for understanding the effects of hand position on tendon tension, elastic effects on tendon tension, and overall functional anatomy of the hand.

Comparing a medical records-based and a claims-based index for measuring comorbidity in patients with lung or colon cancer.

PubMed

Kehl, Kenneth L; Lamont, Elizabeth B; McNeil, Barbara J; Bozeman, Samuel R; Kelley, Michael J; Keating, Nancy L

2015-05-01

Ascertaining comorbid conditions in cancer patients is important for research and clinical quality measurement, and is particularly important for understanding care and outcomes for older patients and those with multi-morbidity. We compared the medical records-based ACE-27 index and the claims-based Charlson index in predicting receipt of therapy and survival for lung and colon cancer patients. We calculated the Charlson index using administrative data and the ACE-27 score using medical records for Veterans Affairs patients diagnosed with stage I/II non-small cell lung or stage III colon cancer from January 2003 to December 2004. We compared the proportion of patients identified by each index as having any comorbidity. We used multivariable logistic regression to ascertain the predictive power of each index regarding delivery of guideline-recommended therapies and two-year survival, comparing the c-statistic and the Akaike information criterion (AIC). Overall, 97.2% of lung and 90.9% of colon cancer patients had any comorbidity according to the ACE-27 index, versus 59.5% and 49.7%, respectively, according to the Charlson. Multivariable models including the ACE-27 index outperformed Charlson-based models when assessing receipt of guideline-recommended therapies, with higher c-statistics and lower AICs. Neither index was clearly superior in prediction of two-year survival. The ACE-27 index measured using medical records captured more comorbidity and outperformed the Charlson index measured using administrative data for predicting receipt of guideline-recommended therapies, demonstrating the potential value of more detailed comorbidity data. However, the two indices had relatively similar performance when predicting survival. Copyright © 2015 Elsevier Inc. All rights reserved.

Heuristic Model Of The Composite Quality Index Of Environmental Assessment

NASA Astrophysics Data System (ADS)

Khabarov, A. N.; Knyaginin, A. A.; Bondarenko, D. V.; Shepet, I. P.; Korolkova, L. N.

2017-01-01

The goal of the paper is to present the heuristic model of the composite environmental quality index based on the integrated application of the elements of utility theory, multidimensional scaling, expert evaluation and decision-making. The composite index is synthesized in linear-quadratic form, it provides higher adequacy of the results of the assessment preferences of experts and decision-makers.

A Flux-Corrected Transport Based Hydrodynamic Model for the Plasmasphere Refilling Problem following Geomagnetic Storms

NASA Astrophysics Data System (ADS)

Chatterjee, K.; Schunk, R. W.

2017-12-01

The refilling of the plasmasphere following a geomagnetic storm remains one of the longstanding problems in the area of ionosphere-magnetosphere coupling. Both diffusion and hydrodynamic approximations have been adopted for the modeling and solution of this problem. The diffusion approximation neglects the nonlinear inertial term in the momentum equation and so this approximation is not rigorously valid immediately after the storm. Over the last few years, we have developed a hydrodynamic refilling model using the flux-corrected transport method, a numerical method that is extremely well suited to handling nonlinear problems with shocks and discontinuities. The plasma transport equations are solved along 1D closed magnetic field lines that connect conjugate ionospheres and the model currently includes three ion (H+, O+, He+) and two neutral (O, H) species. In this work, each ion species under consideration has been modeled as two separate streams emanating from the conjugate hemispheres and the model correctly predicts supersonic ion speeds and the presence of high levels of Helium during the early hours of refilling. The ultimate objective of this research is the development of a 3D model for the plasmasphere refilling problem and with additional development, the same methodology can potentially be applied to the study of other complex space plasma coupling problems in closed flux tube geometries. Index Terms: 2447 Modeling and forecasting [IONOSPHERE] 2753 Numerical modeling [MAGNETOSPHERIC PHYSICS] 7959 Models [SPACE WEATHER

Agent-Based Modeling of China's Rural-Urban Migration and Social Network Structure.

PubMed

Fu, Zhaohao; Hao, Lingxin

2018-01-15

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k -core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

Agent-based modeling of China's rural-urban migration and social network structure

NASA Astrophysics Data System (ADS)

Fu, Zhaohao; Hao, Lingxin

2018-01-01

We analyze China's rural-urban migration and endogenous social network structures using agent-based modeling. The agents from census micro data are located in their rural origin with an empirical-estimated prior propensity to move. The population-scale social network is a hybrid one, combining observed family ties and locations of the origin with a parameter space calibrated from census, survey and aggregate data and sampled using a stepwise Latin Hypercube Sampling method. At monthly intervals, some agents migrate and these migratory acts change the social network by turning within-nonmigrant connections to between-migrant-nonmigrant connections, turning local connections to nonlocal connections, and adding among-migrant connections. In turn, the changing social network structure updates migratory propensities of those well-connected nonmigrants who become more likely to move. These two processes iterate over time. Using a core-periphery method developed from the k-core decomposition method, we identify and quantify the network structural changes and map these changes with the migration acceleration patterns. We conclude that network structural changes are essential for explaining migration acceleration observed in China during the 1995-2000 period.

[The Promotion of Resources Integration in Long-Term Care Service: The Experience of Taipei City Hospital].

PubMed

Wu, Meng-Ping; Huang, Chao-Ming; Sun, Wen-Jung; Shih, Chih-Yuan; Hsu, Su-Hsuan; Huang, Sheng-Jean

2018-02-01

The home-based medical care integrated plan under Taiwan National Health Insurance has changed from paying for home-based medical care, home-based nursing, home-based respiratory treatment, and palliative care to paying for a single, continuous home-based care service package. Formerly, physician-visit regulations limited home visits for home-based nursing to providing medical related assessments only. This limitation not only did not provide practical assistance to the public but also caused additional problems for those with mobility problems or who faced difficulties in making visits hospital. This 2016 change in regulations opens the door for doctors to step out their 'ivory tower', while offering the public more options to seek medical assistance in the hope that patients may change their health-seeking behavior. The home-based concept that underlies the medical service system is rooted deeply in the community in order to set up a sound, integrated model of community medical care. It is a critical issue to proceed with timely job handover confirmation with the connecting team and to provide patients with continuous-care services prior to discharge through the discharge-planning service and the connection with the connecting team. This is currently believed to be the only continuous home-based medical care integrated service model in the world. This model not only connects services such as health literacy, rehabilitation, home-based medical care, home-based nursing, community palliative care, and death but also integrates community resources, builds community resources networks, and provides high quality community care services.

Connecting Vulnerable Children and Families to Community-Based Programs Strengthens Parents' Perceptions of Protective Factors

ERIC Educational Resources Information Center

Hughes, Marcia; Joslyn, Allison; Wojton, Morella; O'Reilly, Mairead; Dworkin, Paul H.

2016-01-01

We employed principles from a nationally recognized prevention model on family support to investigate whether connecting vulnerable children to community-based programs and services through a statewide intervention system, the "Help Me Grow" program, strengthens parents' perceptions of protective factors. We used a parent survey modeled…

Structural connectivity allows for multi-threading during rest: the structure of the cortex leads to efficient alternation between resting state exploratory behavior and default mode processing.

PubMed

Senden, Mario; Goebel, Rainer; Deco, Gustavo

2012-05-01

Despite the absence of stimulation or task conditions the cortex exhibits highly structured spatio-temporal activity patterns. These patterns are known as resting state networks (RSNs) and emerge as low-frequency fluctuations (<0.1 Hz) observed in the fMRI signal of human subjects during rest. We are interested in the relationship between structural connectivity of the cortex and the fluctuations exhibited during resting conditions. We are especially interested in the effect of degree of connectivity on resting state dynamics as the default mode network (DMN) is highly connected. We find in experimental resting fMRI data that the DMN is the functional network that is most frequently active and for the longest time. In large-scale computational simulations of the cortex based on the corresponding underlying DTI/DSI based neuroanatomical connectivity matrix, we additionally find a strong correlation between the mean degree of functional networks and the proportion of time they are active. By artificially modifying different types of neuroanatomical connectivity matrices in the model, we were able to demonstrate that only models based on structural connectivity containing hubs give rise to this relationship. We conclude that, during rest, the cortex alternates efficiently between explorations of its externally oriented functional repertoire and internally oriented processing as a consequence of the DMN's high degree of connectivity. Copyright © 2012 Elsevier Inc. All rights reserved.

Using synchronization in multi-model ensembles to improve prediction

NASA Astrophysics Data System (ADS)

Hiemstra, P.; Selten, F.

2012-04-01

In recent decades, many climate models have been developed to understand and predict the behavior of the Earth's climate system. Although these models are all based on the same basic physical principles, they still show different behavior. This is for example caused by the choice of how to parametrize sub-grid scale processes. One method to combine these imperfect models, is to run a multi-model ensemble. The models are given identical initial conditions and are integrated forward in time. A multi-model estimate can for example be a weighted mean of the ensemble members. We propose to go a step further, and try to obtain synchronization between the imperfect models by connecting the multi-model ensemble, and exchanging information. The combined multi-model ensemble is also known as a supermodel. The supermodel has learned from observations how to optimally exchange information between the ensemble members. In this study we focused on the density and formulation of the onnections within the supermodel. The main question was whether we could obtain syn-chronization between two climate models when connecting only a subset of their state spaces. Limiting the connected subspace has two advantages: 1) it limits the transfer of data (bytes) between the ensemble, which can be a limiting factor in large scale climate models, and 2) learning the optimal connection strategy from observations is easier. To answer the research question, we connected two identical quasi-geostrohic (QG) atmospheric models to each other, where the model have different initial conditions. The QG model is a qualitatively realistic simulation of the winter flow on the Northern hemisphere, has three layers and uses a spectral imple-mentation. We connected the models in the original spherical harmonical state space, and in linear combinations of these spherical harmonics, i.e. Empirical Orthogonal Functions (EOFs). We show that when connecting through spherical harmonics, we only need to connect 28% of the state variables to obtain synchronization. In addition, when connecting through EOFs, we can reduce this percentage even more to 12%. This reduction is caused by the more efficient description of the model state variables when using EOFs. The connected state variables center around the medium scale structures in the model. Small and large scale structures need not be connected in order to obtain synchronization. This could be related to the baroclinic instabilities in the QG model which are located in the medium scale structures of the model. The baroclinic instabilities are the main source of divergence between the two connected models.

Autonomic and brain responses associated with empathy deficits in autism spectrum disorder

PubMed Central

Eilam‐Stock, Tehila; Zhou, Thomas; Anagnostou, Evdokia; Kolevzon, Alexander; Soorya, Latha; Hof, Patrick R.; Friston, Karl J.

2015-01-01

Abstract Accumulating evidence suggests that autonomic signals and their cortical representations are closely linked to emotional processes, and that related abnormalities could lead to social deficits. Although socio‐emotional impairments are a defining feature of autism spectrum disorder (ASD), empirical evidence directly supporting the link between autonomic, cortical, and socio‐emotional abnormalities in ASD is still lacking. In this study, we examined autonomic arousal indexed by skin conductance responses (SCR), concurrent cortical responses measured by functional magnetic resonance imaging, and effective brain connectivity estimated by dynamic causal modeling in seventeen unmedicated high‐functioning adults with ASD and seventeen matched controls while they performed an empathy‐for‐pain task. Compared to controls, adults with ASD showed enhanced SCR related to empathetic pain, along with increased neural activity in the anterior insular cortex, although their behavioral empathetic pain discriminability was reduced and overall SCR was decreased. ASD individuals also showed enhanced correlation between SCR and neural activities in the anterior insular cortex. Importantly, significant group differences in effective brain connectivity were limited to greater reduction in the negative intrinsic connectivity of the anterior insular cortex in the ASD group, indicating a failure in attenuating anterior insular responses to empathetic pain. These results suggest that aberrant interoceptive precision, as indexed by abnormalities in autonomic activity and its central representations, may underlie empathy deficits in ASD. Hum Brain Mapp 36:3323–3338, 2015. © 2015 The Authors Human Brain Mapping Published byWiley Periodicals, Inc. PMID:25995134

Environmental perceptions as mediators of the relationship between the objective built environment and walking among socio-economically disadvantaged women.

PubMed

Van Dyck, Delfien; Veitch, Jenny; De Bourdeaudhuij, Ilse; Thornton, Lukar; Ball, Kylie

2013-09-19

Women living in socio-economically disadvantaged neighbourhoods are at increased risk for physical inactivity and associated health outcomes and are difficult to reach through personally tailored interventions. Targeting the built environment may be an effective strategy in this population subgroup. The aim of this study was to examine the mediating role of environmental perceptions in the relationship between the objective environment and walking for transportation/recreation among women from socio-economically disadvantaged neighbourhoods. Baseline data of the Resilience for Eating and Activity Despite Inequality (READI) study were used. In total, 4139 women (18-46 years) completed a postal survey assessing physical environmental perceptions (aesthetics, neighbourhood physical activity environment, personal safety, neighbourhood social cohesion), physical activity, and socio-demographics. Objectively-assessed data on street connectivity and density of destinations were collected using a Geographic Information System database and based on the objective z-scores, an objective destinations/connectivity score was calculated. This index was positively scored, with higher scores representing a more favourable environment. Two-level mixed models regression analyses were conducted and the MacKinnon product-of-coefficients test was used to examine the mediating effects. The destinations/connectivity score was positively associated with transport-related walking. The perceived physical activity environment mediated 6.1% of this positive association. The destinations/connectivity score was negatively associated with leisure-time walking. Negative perceptions of aesthetics, personal safety and social cohesion of the neighbourhood jointly mediated 24.1% of this negative association. For women living in socio-economically disadvantaged neighbourhoods, environmental perceptions were important mediators of the relationship between the objective built environment and walking. To increase both transport-related and leisure-time walking, it is necessary to improve both objective walkability-related characteristics (street connectivity and proximity of destinations), and perceptions of personal safety, favourable aesthetics and neighbourhood social cohesion.

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

Soffientini, Chiara Dolores, E-mail: chiaradolores.soffientini@polimi.it; Baselli, Giuseppe; De Bernardi, Elisabetta

Purpose: Quantitative {sup 18}F-fluorodeoxyglucose positron emission tomography is limited by the uncertainty in lesion delineation due to poor SNR, low resolution, and partial volume effects, subsequently impacting oncological assessment, treatment planning, and follow-up. The present work develops and validates a segmentation algorithm based on statistical clustering. The introduction of constraints based on background features and contiguity priors is expected to improve robustness vs clinical image characteristics such as lesion dimension, noise, and contrast level. Methods: An eight-class Gaussian mixture model (GMM) clustering algorithm was modified by constraining the mean and variance parameters of four background classes according to the previousmore » analysis of a lesion-free background volume of interest (background modeling). Hence, expectation maximization operated only on the four classes dedicated to lesion detection. To favor the segmentation of connected objects, a further variant was introduced by inserting priors relevant to the classification of neighbors. The algorithm was applied to simulated datasets and acquired phantom data. Feasibility and robustness toward initialization were assessed on a clinical dataset manually contoured by two expert clinicians. Comparisons were performed with respect to a standard eight-class GMM algorithm and to four different state-of-the-art methods in terms of volume error (VE), Dice index, classification error (CE), and Hausdorff distance (HD). Results: The proposed GMM segmentation with background modeling outperformed standard GMM and all the other tested methods. Medians of accuracy indexes were VE <3%, Dice >0.88, CE <0.25, and HD <1.2 in simulations; VE <23%, Dice >0.74, CE <0.43, and HD <1.77 in phantom data. Robustness toward image statistic changes (±15%) was shown by the low index changes: <26% for VE, <17% for Dice, and <15% for CE. Finally, robustness toward the user-dependent volume initialization was demonstrated. The inclusion of the spatial prior improved segmentation accuracy only for lesions surrounded by heterogeneous background: in the relevant simulation subset, the median VE significantly decreased from 13% to 7%. Results on clinical data were found in accordance with simulations, with absolute VE <7%, Dice >0.85, CE <0.30, and HD <0.81. Conclusions: The sole introduction of constraints based on background modeling outperformed standard GMM and the other tested algorithms. Insertion of a spatial prior improved the accuracy for realistic cases of objects in heterogeneous backgrounds. Moreover, robustness against initialization supports the applicability in a clinical setting. In conclusion, application-driven constraints can generally improve the capabilities of GMM and statistical clustering algorithms.« less

Connectotyping: Model Based Fingerprinting of the Functional Connectome

PubMed Central

Miranda-Dominguez, Oscar; Mills, Brian D.; Carpenter, Samuel D.; Grant, Kathleen A.; Kroenke, Christopher D.; Nigg, Joel T.; Fair, Damien A.

2014-01-01

A better characterization of how an individual’s brain is functionally organized will likely bring dramatic advances to many fields of study. Here we show a model-based approach toward characterizing resting state functional connectivity MRI (rs-fcMRI) that is capable of identifying a so-called “connectotype”, or functional fingerprint in individual participants. The approach rests on a simple linear model that proposes the activity of a given brain region can be described by the weighted sum of its functional neighboring regions. The resulting coefficients correspond to a personalized model-based connectivity matrix that is capable of predicting the timeseries of each subject. Importantly, the model itself is subject specific and has the ability to predict an individual at a later date using a limited number of non-sequential frames. While we show that there is a significant amount of shared variance between models across subjects, the model’s ability to discriminate an individual is driven by unique connections in higher order control regions in frontal and parietal cortices. Furthermore, we show that the connectotype is present in non-human primates as well, highlighting the translational potential of the approach. PMID:25386919

Using connectome-based predictive modeling to predict individual behavior from brain connectivity

PubMed Central

Shen, Xilin; Finn, Emily S.; Scheinost, Dustin; Rosenberg, Monica D.; Chun, Marvin M.; Papademetris, Xenophon; Constable, R Todd

2017-01-01

Neuroimaging is a fast developing research area where anatomical and functional images of human brains are collected using techniques such as functional magnetic resonance imaging (fMRI), diffusion tensor imaging (DTI), and electroencephalography (EEG). Technical advances and large-scale datasets have allowed for the development of models capable of predicting individual differences in traits and behavior using brain connectivity measures derived from neuroimaging data. Here, we present connectome-based predictive modeling (CPM), a data-driven protocol for developing predictive models of brain-behavior relationships from connectivity data using cross-validation. This protocol includes the following steps: 1) feature selection, 2) feature summarization, 3) model building, and 4) assessment of prediction significance. We also include suggestions for visualizing the most predictive features (i.e., brain connections). The final result should be a generalizable model that takes brain connectivity data as input and generates predictions of behavioral measures in novel subjects, accounting for a significant amount of the variance in these measures. It has been demonstrated that the CPM protocol performs equivalently or better than most of the existing approaches in brain-behavior prediction. However, because CPM focuses on linear modeling and a purely data-driven driven approach, neuroscientists with limited or no experience in machine learning or optimization would find it easy to implement the protocols. Depending on the volume of data to be processed, the protocol can take 10–100 minutes for model building, 1–48 hours for permutation testing, and 10–20 minutes for visualization of results. PMID:28182017

Isolation and connectivity: Relationships between periodic connection to the ocean and environmental variables in intermittently closed estuaries

NASA Astrophysics Data System (ADS)

Lill, Adrian Wilfred Thomas; Schallenberg, Marc; Lal, Aparna; Savage, Candida; Closs, Gerard Patrick

2013-08-01

Morphometric and physicochemical variables are key determinants of biotic community structure in estuaries and are influenced by changes to estuary mouth state (open/closed). This study examined and compared the consequences of intermittent connection to the ocean on environmental gradients among estuaries; specifically, how estuary morphology and hydrology relate to physical connection to the sea, and the influence of this relationship on the physicochemical environment. By sampling 20 estuaries across New Zealand and using historical aerial photographs, a continuous index of estuarine connection to the ocean was developed and independently validated using berm elevation derived from Airborne Laser Scanning (ALS) data. Using published literature, this index was compared to equivalent indices in South Africa and Australia. A clear relationship between connections to the ocean, freshwater flow and productivity indices underlie the environmental differences between permanently open and intermittently closed estuaries. Consistent patterns across the Southern Hemisphere, albeit with regional variations in estuarine characteristics, suggest that remote sensing is useful for predicting the physicochemical environment of small estuaries across regions. Principal components analysis for Otago estuaries showed that 40% of measured variation in the environment could be attributed to the gradient of relative connectivity (EOI), or isolation (berm elevation) to the ocean. Evaluating these relationships is central to understanding how global and local environmental changes may affect estuarine connectivity regimes and, ultimately, the functioning of estuarine ecosystems.

Using a Simple Parcel Model to Investigate the Haines Index

Treesearch

Mary Ann Jenkins; Steven K. Krueger; Ruiyu Sun

2003-01-01

The Haines Index (Haines 1988) ia fire-weather index based on stability and moisture conditions of the lower atmosphere that rates the potential for large fire growth or extreme fire behavior. The Hained Index is calculated by adding a temperature term a to a moisture term b.

Wealth, justice and freedom: Objective and subjective measures predicting poor mental health in a study across eight countries.

PubMed

Scholten, Saskia; Velten, Julia; Neher, Torsten; Margraf, Jürgen

2017-12-01

Macro-level factors (MF) such as wealth, justice and freedom measured with objective country-level indicators (objective MF), for instance the Gross Domestic Product (GDP), have been investigated in relation to health and well-being, but rarely in connection with depression, anxiety and stress subsumed as poor mental health. Also, a combination of different objective MF and of how individuals perceive those MF (subjective MF) has not been taken into consideration. In the present study, we combined subjective and objective measures of wealth, justice and freedom and examined their relationship with poor mental health. Population-based interviews were conducted in France, Germany, Poland, Russia, Spain, Sweden, U.K. and U.S.A. (n ≈ 1000 per country). GDP, GINI coefficient, Justice Index and Freedom Index were used as objective MF, whereas subjective MF were perceived wealth, justice and freedom measured at the individual level. Poor mental health was assessed as a combination of symptoms of depression, anxiety and stress. In a random-intercept-model, GINI coefficient and Freedom Index were significant positive country-level, and perceived wealth, justice, and freedom significant negative individual-level predictors of symptoms of poor mental health. Multiple subjective and objective MF should be combined to assess the macrosystem's relationship with poor mental health more precisely. The relationship between MF and poor mental health indicates that the macrosystem should be taken into account as relevant context for mental health problems, too.

Indexing sensory plasticity: Evidence for distinct Predictive Coding and Hebbian learning mechanisms in the cerebral cortex.

PubMed

Spriggs, M J; Sumner, R L; McMillan, R L; Moran, R J; Kirk, I J; Muthukumaraswamy, S D

2018-04-30

The Roving Mismatch Negativity (MMN), and Visual LTP paradigms are widely used as independent measures of sensory plasticity. However, the paradigms are built upon fundamentally different (and seemingly opposing) models of perceptual learning; namely, Predictive Coding (MMN) and Hebbian plasticity (LTP). The aim of the current study was to compare the generative mechanisms of the MMN and visual LTP, therefore assessing whether Predictive Coding and Hebbian mechanisms co-occur in the brain. Forty participants were presented with both paradigms during EEG recording. Consistent with Predictive Coding and Hebbian predictions, Dynamic Causal Modelling revealed that the generation of the MMN modulates forward and backward connections in the underlying network, while visual LTP only modulates forward connections. These results suggest that both Predictive Coding and Hebbian mechanisms are utilized by the brain under different task demands. This therefore indicates that both tasks provide unique insight into plasticity mechanisms, which has important implications for future studies of aberrant plasticity in clinical populations. Copyright © 2018 Elsevier Inc. All rights reserved.

How positive emotions build physical health: perceived positive social connections account for the upward spiral between positive emotions and vagal tone.

PubMed

Kok, Bethany E; Coffey, Kimberly A; Cohn, Michael A; Catalino, Lahnna I; Vacharkulksemsuk, Tanya; Algoe, Sara B; Brantley, Mary; Fredrickson, Barbara L

2013-07-01

The mechanisms underlying the association between positive emotions and physical health remain a mystery. We hypothesize that an upward-spiral dynamic continually reinforces the tie between positive emotions and physical health and that this spiral is mediated by people's perceptions of their positive social connections. We tested this overarching hypothesis in a longitudinal field experiment in which participants were randomly assigned to an intervention group that self-generated positive emotions via loving-kindness meditation or to a waiting-list control group. Participants in the intervention group increased in positive emotions relative to those in the control group, an effect moderated by baseline vagal tone, a proxy index of physical health. Increased positive emotions, in turn, produced increases in vagal tone, an effect mediated by increased perceptions of social connections. This experimental evidence identifies one mechanism-perceptions of social connections-through which positive emotions build physical health, indexed as vagal tone. Results suggest that positive emotions, positive social connections, and physical health influence one another in a self-sustaining upward-spiral dynamic.

Analytical stability and simulation response study for a coupled two-body system

NASA Technical Reports Server (NTRS)

Tao, K. M.; Roberts, J. R.

1975-01-01

An analytical stability study and a digital simulation response study of two connected rigid bodies are documented. Relative rotation of the bodies at the connection is allowed, thereby providing a model suitable for studying system stability and response during a soft-dock regime. Provisions are made of a docking port axes alignment torque and a despin torque capability for encountering spinning payloads. Although the stability analysis is based on linearized equations, the digital simulation is based on nonlinear models.

Optimal Control of Micro Grid Operation Mode Seamless Switching Based on Radau Allocation Method

NASA Astrophysics Data System (ADS)

Chen, Xiaomin; Wang, Gang

2017-05-01

The seamless switching process of micro grid operation mode directly affects the safety and stability of its operation. According to the switching process from island mode to grid-connected mode of micro grid, we establish a dynamic optimization model based on two grid-connected inverters. We use Radau allocation method to discretize the model, and use Newton iteration method to obtain the optimal solution. Finally, we implement the optimization mode in MATLAB and get the optimal control trajectory of the inverters.

Coupled Modes over Indian Ocean at Sub-seasonal time Scales and its Prediction

NASA Astrophysics Data System (ADS)

Jung, E.; Kirtman, B. P.

2014-12-01

Sub-seasonal variability over the Indian Ocean, such as Madden-Julian Oscillation impacts weather and climate globally. However, the prediction of tropical sub-seasonal variability (TSV) remains a challenge, and understanding air-sea interactions on TSV time-scales is likely to be an important part of the prediction problem. The purpose of this paper is to examine the predictability of sub-seasonal variability in the tropical Indo-Pacific region. The analysis emphasizes on variability associated with coupled air-sea interactions in observational estimates, and how well these coupled modes are simulated and predicted within the context of a 30-year retrospective forecast experiment with a state-of-the-art atmosphere-ocean coupled model. The analysis shows that Sea Surface Temperature anomalies (SSTA) over the Indian Ocean tend to precede precipitation anomalies by 7-11 days with maximum amplitude over the Arabian Sea and the Bay of Bengal for summer and along the Seychelles-Chagos Thermocline Ridge (SCTR) region for winter. Though these coupled modes are captured by the models, the forecasts fail to predict its evolution. Based on the diagnosis of these coupled modes, we introduce a SCTR-SST index and an index that measures the modulation of the low-frequency amplitude (LFAM) of sub-seasonal SSTA variability over SCTR as a way to predict the coupled modes. Based on correlation with the observed variability, SCTR-SST has forecast skill of about 45 days over the Indian Ocean. However the sub-seasonal SSTAs in the predictions and the observational estimates do not have any direct ENSO tele-connection. In contrast, the LFAM of the sub-seasonal SSTA variance over SCTR is strongly correlated with ENSO, suggesting enhanced sub-seasonal variance on seasonal time-scales is potentially predictable.

Modeling intragranular diffusion in low-connectivity granular media

NASA Astrophysics Data System (ADS)

Ewing, Robert P.; Liu, Chongxuan; Hu, Qinhong

2012-03-01

Characterizing the diffusive exchange of solutes between bulk water in an aquifer and water in the intragranular pores of the solid phase is still challenging despite decades of study. Many disparities between observation and theory could be attributed to low connectivity of the intragranular pores. The presence of low connectivity indicates that a useful conceptual framework is percolation theory. The present study was initiated to develop a percolation-based finite difference (FD) model, and to test it rigorously against both random walk (RW) simulations of diffusion starting from nonequilibrium, and data on Borden sand published by Ball and Roberts (1991a,b) and subsequently reanalyzed by Haggerty and Gorelick (1995) using a multirate mass transfer (MRMT) approach. The percolation-theoretical model is simple and readily incorporated into existing FD models. The FD model closely matches the RW results using only a single fitting parameter, across a wide range of pore connectivities. Simulation of the Borden sand experiment without pore connectivity effects reproduced the MRMT analysis, but including low pore connectivity effects improved the fit. Overall, the theory and simulation results show that low intragranular pore connectivity can produce diffusive behavior that appears as if the solute had undergone slow sorption, despite the absence of any sorption process, thereby explaining some hitherto confusing aspects of intragranular diffusion.

Mutual connectivity analysis (MCA) using generalized radial basis function neural networks for nonlinear functional connectivity network recovery in resting-state functional MRI

NASA Astrophysics Data System (ADS)

D'Souza, Adora M.; Abidin, Anas Zainul; Nagarajan, Mahesh B.; Wismüller, Axel

2016-03-01

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 +/- 0.037) as well as the underlying network structure (Rand index = 0.87 +/- 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Mutual Connectivity Analysis (MCA) Using Generalized Radial Basis Function Neural Networks for Nonlinear Functional Connectivity Network Recovery in Resting-State Functional MRI.

PubMed

DSouza, Adora M; Abidin, Anas Zainul; Nagarajan, Mahesh B; Wismüller, Axel

2016-03-29

We investigate the applicability of a computational framework, called mutual connectivity analysis (MCA), for directed functional connectivity analysis in both synthetic and resting-state functional MRI data. This framework comprises of first evaluating non-linear cross-predictability between every pair of time series prior to recovering the underlying network structure using community detection algorithms. We obtain the non-linear cross-prediction score between time series using Generalized Radial Basis Functions (GRBF) neural networks. These cross-prediction scores characterize the underlying functionally connected networks within the resting brain, which can be extracted using non-metric clustering approaches, such as the Louvain method. We first test our approach on synthetic models with known directional influence and network structure. Our method is able to capture the directional relationships between time series (with an area under the ROC curve = 0.92 ± 0.037) as well as the underlying network structure (Rand index = 0.87 ± 0.063) with high accuracy. Furthermore, we test this method for network recovery on resting-state fMRI data, where results are compared to the motor cortex network recovered from a motor stimulation sequence, resulting in a strong agreement between the two (Dice coefficient = 0.45). We conclude that our MCA approach is effective in analyzing non-linear directed functional connectivity and in revealing underlying functional network structure in complex systems.

Modeling motor connectivity using TMS/PET and structural equation modeling

PubMed Central

Laird, Angela R.; Robbins, Jacob M.; Li, Karl; Price, Larry R.; Cykowski, Matthew D.; Narayana, Shalini; Laird, Robert W.; Franklin, Crystal; Fox, Peter T.

2010-01-01

Structural equation modeling (SEM) was applied to positron emission tomographic (PET) images acquired during transcranial magnetic stimulation (TMS) of the primary motor cortex (M1hand). TMS was applied across a range of intensities, and responses both at the stimulation site and remotely connected brain regions covaried with stimulus intensity. Regions of interest (ROIs) were identified through an activation likelihood estimation (ALE) meta-analysis of TMS studies. That these ROIs represented the network engaged by motor planning and execution was confirmed by an ALE meta-analysis of finger movement studies. Rather than postulate connections in the form of an a priori model (confirmatory approach), effective connectivity models were developed using a model-generating strategy based on improving tentatively specified models. This strategy exploited the experimentally-imposed causal relations: (1) that response variations were caused by stimulation variations, (2) that stimulation was unidirectionally applied to the M1hand region, and (3) that remote effects must be caused, either directly or indirectly, by the M1hand excitation. The path model thus derived exhibited an exceptional level of goodness (χ2=22.150, df = 38, P = 0.981, TLI=1.0). The regions and connections derived were in good agreement with the known anatomy of the human and primate motor system. The model-generating SEM strategy thus proved highly effective and successfully identified a complex set of causal relationships of motor connectivity. PMID:18387823

Wildlife corridors based on the spatial modeling of the human pressure: A Portuguese case study

Treesearch

Lara Nunes; Ana Luisa Gomes; Alexandra Fonseca

2015-01-01

In times of economical crisis, rewilding can be a less costly conservation management approach, able to generate economic value from wild lands and to rural communities. Simultaneously, improvement of connectivity between protected areas was identified as a global priority for conservation. Allying the rewilding concept and connectivity concern, a model for...

[Quantitative relationships between hyper-spectral vegetation indices and leaf area index of rice].

PubMed

Tian, Yong-Chao; Yang, Jie; Yao, Xia; Zhu, Yan; Cao, Wei-Xing

2009-07-01

Based on field experiments with different rice varieties under different nitrogen application levels, the quantitative relationships of rice leaf area index (LAI) with canopy hyper-spectral parameters at different growth stages were analyzed. Rice LAI had good relationships with several hyper-spectral vegetation indices, the correlation coefficient being the highest with DI (difference index), followed by with RI (ratio index), and NI (normalized index), based on the spectral reflectance or the first derivative spectra. The two best spectral indices for estimating LAI were the difference index DI (854, 760) (based on two spectral bands of 850 nm and 760 nm) and the difference index DI (D676, D778) (based on two first derivative bands of 676 nm and 778 nm). In general, the hyper-spectral vegetation indices based on spectral reflectance performed better than the spectral indices based on the first derivative spectra. The tests with independent dataset suggested that the rice LAI monitoring models with difference index DI (854,760) as the variable could give an accurate LAI estimation, being available for estimation of rice LAI.

Application of satellite products and hydrological modelling for flood early warning

NASA Astrophysics Data System (ADS)

Koriche, Sifan A.; Rientjes, Tom H. M.

2016-06-01

Floods have caused devastating impacts to the environment and society in Awash River Basin, Ethiopia. Since flooding events are frequent, this marks the need to develop tools for flood early warning. In this study, we propose a satellite based flood index to identify the runoff source areas that largely contribute to extreme runoff production and floods in the basin. Satellite based products used for development of the flood index are CMORPH (Climate Prediction Center MORPHing technique: 0.25° by 0.25°, daily) product for calculation of the Standard Precipitation Index (SPI) and a Shuttle Radar Topography Mission (SRTM) digital elevation model (DEM) for calculation of the Topographic Wetness Index (TWI). Other satellite products used in this study are for rainfall-runoff modelling to represent rainfall, potential evapotranspiration, vegetation cover and topography. Results of the study show that assessment of spatial and temporal rainfall variability by satellite products may well serve in flood early warning. Preliminary findings on effectiveness of the flood index developed in this study indicate that the index is well suited for flood early warning. The index combines SPI and TWI, and preliminary results illustrate the spatial distribution of likely runoff source areas that cause floods in flood prone areas.

Indexing and the object concept: developing `what' and `where' systems.

PubMed

Leslie, A M; Xu, F; Tremoulet, P D; Scholl, B J

1998-01-01

The study of object cognition over the past 25 years has proceeded in two largely non-interacting camps. One camp has studied object-based visual attention in adults, while the other has studied the object concept in infants. We briefly review both sets of literature and distill from the adult research a theoretical model that we apply to findings from the infant studies. The key notion in our model of object representation is the `sticky' index, a mechanism of selective attention that points at a physical object in a location. An object index does not represent any of the properties of the entity at which it points. However, once an index is pointing to an object, the properties of that object can be examined and featural information can be associated with, or `bound' to, its index. The distinction between indexing and feature binding underwrites the distinction between object individuation and object identification, a distinction that turns out to be crucial in both the adult attention and the infant object-concept literature. By developing the indexing model, we draw together two disparate sets of literature and suggest new ways to study object-based attention in infancy.

A Multi-layer Dynamic Model for Coordination Based Group Decision Making in Water Resource Allocation and Scheduling

NASA Astrophysics Data System (ADS)

Huang, Wei; Zhang, Xingnan; Li, Chenming; Wang, Jianying

Management of group decision-making is an important issue in water source management development. In order to overcome the defects in lacking of effective communication and cooperation in the existing decision-making models, this paper proposes a multi-layer dynamic model for coordination in water resource allocation and scheduling based group decision making. By introducing the scheme-recognized cooperative satisfaction index and scheme-adjusted rationality index, the proposed model can solve the problem of poor convergence of multi-round decision-making process in water resource allocation and scheduling. Furthermore, the problem about coordination of limited resources-based group decision-making process can be solved based on the effectiveness of distance-based group of conflict resolution. The simulation results show that the proposed model has better convergence than the existing models.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

PubMed

Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

PubMed Central

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization. PMID:28912803

Estimating population density and connectivity of American mink using spatial capture-recapture

USGS Publications Warehouse

Fuller, Angela K.; Sutherland, Christopher S.; Royle, Andy; Hare, Matthew P.

2016-01-01

Estimating the abundance or density of populations is fundamental to the conservation and management of species, and as landscapes become more fragmented, maintaining landscape connectivity has become one of the most important challenges for biodiversity conservation. Yet these two issues have never been formally integrated together in a model that simultaneously models abundance while accounting for connectivity of a landscape. We demonstrate an application of using capture–recapture to develop a model of animal density using a least-cost path model for individual encounter probability that accounts for non-Euclidean connectivity in a highly structured network. We utilized scat detection dogs (Canis lupus familiaris) as a means of collecting non-invasive genetic samples of American mink (Neovison vison) individuals and used spatial capture–recapture models (SCR) to gain inferences about mink population density and connectivity. Density of mink was not constant across the landscape, but rather increased with increasing distance from city, town, or village centers, and mink activity was associated with water. The SCR model allowed us to estimate the density and spatial distribution of individuals across a 388 km2 area. The model was used to investigate patterns of space usage and to evaluate covariate effects on encounter probabilities, including differences between sexes. This study provides an application of capture–recapture models based on ecological distance, allowing us to directly estimate landscape connectivity. This approach should be widely applicable to provide simultaneous direct estimates of density, space usage, and landscape connectivity for many species.

Estimating population density and connectivity of American mink using spatial capture-recapture.

PubMed

Fuller, Angela K; Sutherland, Chris S; Royle, J Andrew; Hare, Matthew P

2016-06-01

Estimating the abundance or density of populations is fundamental to the conservation and management of species, and as landscapes become more fragmented, maintaining landscape connectivity has become one of the most important challenges for biodiversity conservation. Yet these two issues have never been formally integrated together in a model that simultaneously models abundance while accounting for connectivity of a landscape. We demonstrate an application of using capture-recapture to develop a model of animal density using a least-cost path model for individual encounter probability that accounts for non-Euclidean connectivity in a highly structured network. We utilized scat detection dogs (Canis lupus familiaris) as a means of collecting non-invasive genetic samples of American mink (Neovison vison) individuals and used spatial capture-recapture models (SCR) to gain inferences about mink population density and connectivity. Density of mink was not constant across the landscape, but rather increased with increasing distance from city, town, or village centers, and mink activity was associated with water. The SCR model allowed us to estimate the density and spatial distribution of individuals across a 388 km² area. The model was used to investigate patterns of space usage and to evaluate covariate effects on encounter probabilities, including differences between sexes. This study provides an application of capture-recapture models based on ecological distance, allowing us to directly estimate landscape connectivity. This approach should be widely applicable to provide simultaneous direct estimates of density, space usage, and landscape connectivity for many species.

A Weighted and Directed Interareal Connectivity Matrix for Macaque Cerebral Cortex

PubMed Central

Markov, N. T.; Ercsey-Ravasz, M. M.; Ribeiro Gomes, A. R.; Lamy, C.; Magrou, L.; Vezoli, J.; Misery, P.; Falchier, A.; Quilodran, R.; Gariel, M. A.; Sallet, J.; Gamanut, R.; Huissoud, C.; Clavagnier, S.; Giroud, P.; Sappey-Marinier, D.; Barone, P.; Dehay, C.; Toroczkai, Z.; Knoblauch, K.; Van Essen, D. C.; Kennedy, H.

2014-01-01

Retrograde tracer injections in 29 of the 91 areas of the macaque cerebral cortex revealed 1,615 interareal pathways, a third of which have not previously been reported. A weight index (extrinsic fraction of labeled neurons [FLNe]) was determined for each area-to-area pathway. Newly found projections were weaker on average compared with the known projections; nevertheless, the 2 sets of pathways had extensively overlapping weight distributions. Repeat injections across individuals revealed modest FLNe variability given the range of FLNe values (standard deviation <1 log unit, range 5 log units). The connectivity profile for each area conformed to a lognormal distribution, where a majority of projections are moderate or weak in strength. In the G29 × 29 interareal subgraph, two-thirds of the connections that can exist do exist. Analysis of the smallest set of areas that collects links from all 91 nodes of the G29 × 91 subgraph (dominating set analysis) confirms the dense (66%) structure of the cortical matrix. The G29 × 29 subgraph suggests an unexpectedly high incidence of unidirectional links. The directed and weighted G29 × 91 connectivity matrix for the macaque will be valuable for comparison with connectivity analyses in other species, including humans. It will also inform future modeling studies that explore the regularities of cortical networks. PMID:23010748

Anatomy of hierarchy: Feedforward and feedback pathways in macaque visual cortex

PubMed Central

Markov, Nikola T; Vezoli, Julien; Chameau, Pascal; Falchier, Arnaud; Quilodran, René; Huissoud, Cyril; Lamy, Camille; Misery, Pierre; Giroud, Pascale; Ullman, Shimon; Barone, Pascal; Dehay, Colette; Knoblauch, Kenneth; Kennedy, Henry

2013-01-01

The laminar location of the cell bodies and terminals of interareal connections determines the hierarchical structural organization of the cortex and has been intensively studied. However, we still have only a rudimentary understanding of the connectional principles of feedforward (FF) and feedback (FB) pathways. Quantitative analysis of retrograde tracers was used to extend the notion that the laminar distribution of neurons interconnecting visual areas provides an index of hierarchical distance (percentage of supragranular labeled neurons [SLN]). We show that: 1) SLN values constrain models of cortical hierarchy, revealing previously unsuspected areal relations; 2) SLN reflects the operation of a combinatorial distance rule acting differentially on sets of connections between areas; 3) Supragranular layers contain highly segregated bottom-up and top-down streams, both of which exhibit point-to-point connectivity. This contrasts with the infragranular layers, which contain diffuse bottom-up and top-down streams; 4) Cell filling of the parent neurons of FF and FB pathways provides further evidence of compartmentalization; 5) FF pathways have higher weights, cross fewer hierarchical levels, and are less numerous than FB pathways. Taken together, the present results suggest that cortical hierarchies are built from supra- and infragranular counterstreams. This compartmentalized dual counterstream organization allows point-to-point connectivity in both bottom-up and top-down directions. PMID:23983048

Numerical modeling of macrodispersion in heterogeneous media: a comparison of multi-Gaussian and non-multi-Gaussian models

NASA Astrophysics Data System (ADS)

Wen, Xian-Huan; Gómez-Hernández, J. Jaime

1998-03-01

The macrodispersion of an inert solute in a 2-D heterogeneous porous media is estimated numerically in a series of fields of varying heterogeneity. Four different random function (RF) models are used to model log-transmissivity (ln T) spatial variability, and for each of these models, ln T variance is varied from 0.1 to 2.0. The four RF models share the same univariate Gaussian histogram and the same isotropic covariance, but differ from one another in terms of the spatial connectivity patterns at extreme transmissivity values. More specifically, model A is a multivariate Gaussian model for which, by definition, extreme values (both high and low) are spatially uncorrelated. The other three models are non-multi-Gaussian: model B with high connectivity of high extreme values, model C with high connectivity of low extreme values, and model D with high connectivities of both high and low extreme values. Residence time distributions (RTDs) and macrodispersivities (longitudinal and transverse) are computed on ln T fields corresponding to the different RF models, for two different flow directions and at several scales. They are compared with each other, as well as with predicted values based on first-order analytical results. Numerically derived RTDs and macrodispersivities for the multi-Gaussian model are in good agreement with analytically derived values using first-order theories for log-transmissivity variance up to 2.0. The results from the non-multi-Gaussian models differ from each other and deviate largely from the multi-Gaussian results even when ln T variance is small. RTDs in non-multi-Gaussian realizations with high connectivity at high extreme values display earlier breakthrough than in multi-Gaussian realizations, whereas later breakthrough and longer tails are observed for RTDs from non-multi-Gaussian realizations with high connectivity at low extreme values. Longitudinal macrodispersivities in the non-multi-Gaussian realizations are, in general, larger than in the multi-Gaussian ones, while transverse macrodispersivities in the non-multi-Gaussian realizations can be larger or smaller than in the multi-Gaussian ones depending on the type of connectivity at extreme values. Comparing the numerical results for different flow directions, it is confirmed that macrodispersivities in multi-Gaussian realizations with isotropic spatial correlation are not flow direction-dependent. Macrodispersivities in the non-multi-Gaussian realizations, however, are flow direction-dependent although the covariance of ln T is isotropic (the same for all four models). It is important to account for high connectivities at extreme transmissivity values, a likely situation in some geological formations. Some of the discrepancies between first-order-based analytical results and field-scale tracer test data may be due to the existence of highly connected paths of extreme conductivity values.

Height system connection between island and mainland using a hydrodynamic model: a case study connecting the Dutch Wadden islands to the Amsterdam ordnance datum (NAP)

NASA Astrophysics Data System (ADS)

Slobbe, D. C.; Klees, R.; Verlaan, M.; Zijl, F.; Alberts, B.; Farahani, H. H.

2018-03-01

We present an efficient and flexible alternative method to connect islands and offshore tide gauges with the height system on land. The method uses a regional, high-resolution hydrodynamic model that provides total water levels. From the model, we obtain the differences in mean water level (MWL) between tide gauges at the mainland and at the islands or offshore platforms. Adding them to the MWL relative to the national height system at the mainland's tide gauges realizes a connection of the island and offshore platforms with the height system on the mainland. Numerical results are presented for the connection of the Dutch Wadden islands with the national height system (Normaal Amsterdams Peil, NAP). Several choices of the period over which the MWLs are computed are tested and validated. The best results were obtained when we computed the MWL only over the summer months of our 19-year simulation period. Based on this strategy, the percentage of connections for which the absolute differences between the observation- and model-derived MWL differences are ≤ 1 cm is about 34% (46 out of 135 possible leveling connections). In this case, for each Wadden island we can find several connections that allow the transfer of NAP with (sub-)centimeter accuracy.

Analysis on the Correlation of Traffic Flow in Hainan Province Based on Baidu Search

NASA Astrophysics Data System (ADS)

Chen, Caixia; Shi, Chun

2018-03-01

Internet search data records user’s search attention and consumer demand, providing necessary database for the Hainan traffic flow model. Based on Baidu Index, with Hainan traffic flow as example, this paper conduct both qualitative and quantitative analysis on the relationship between search keyword from Baidu Index and actual Hainan tourist traffic flow, and build multiple regression model by SPSS.

Assessing age- and silt index-independent diameter growth models of individual-tree Southern Appalachian hardwoods

Treesearch

Henry W. Mcnab; Thomas F. Lloyd

1999-01-01

Models of forest vegetation dynamics based on characteristics of individual trees are more suitable to predicting growth of multiple species and age classes than those based on stands. The objective of this study was to assess age- and site index-independent relationships between periodic diameter increment and tree and site effects for 11 major hardwood tree species....

Quantifying the Spatial Ecology of Wide-Ranging Marine Species in the Gulf of California: Implications for Marine Conservation Planning

PubMed Central

Anadón, José Daniel; D'Agrosa, Caterina; Gondor, Anne; Gerber, Leah R.

2011-01-01

There is growing interest in systematic establishment of marine protected area (MPA) networks and representative conservation sites. This movement toward networks of no-take zones requires that reserves are deliberately and adequately spaced for connectivity. Here, we test the network functionality of an ecoregional assessment configuration of marine conservation areas by evaluating the habitat protection and connectivity offered to wide-ranging fauna in the Gulf of California (GOC, Mexico). We first use expert opinion to identify representative species of wide-ranging fauna of the GOC. These include leopard grouper, hammerhead sharks, California brown pelicans and green sea turtles. Analyzing habitat models with both structural and functional connectivity indexes, our results indicate that the configuration includes large proportions of biologically important habitat for the four species considered (25–40%), particularly, the best quality habitats (46–57%). Our results also show that connectivity levels offered by the conservation area design for these four species may be similar to connectivity levels offered by the entire Gulf of California, thus indicating that connectivity offered by the areas may resemble natural connectivity. The selected focal species comprise different life histories among marine or marine-related vertebrates and are associated with those habitats holding the most biodiversity values (i.e. coastal habitats); our results thus suggest that the proposed configuration may function as a network for connectivity and may adequately represent the marine megafauna in the GOC, including the potential connectivity among habitat patches. This work highlights the range of approaches that can be used to quantify habitat protection and connectivity for wide-ranging marine species in marine reserve networks. PMID:22163013

Quantifying the spatial ecology of wide-ranging marine species in the Gulf of California: implications for marine conservation planning.

PubMed

Anadón, José Daniel; D'Agrosa, Caterina; Gondor, Anne; Gerber, Leah R

2011-01-01

There is growing interest in systematic establishment of marine protected area (MPA) networks and representative conservation sites. This movement toward networks of no-take zones requires that reserves are deliberately and adequately spaced for connectivity. Here, we test the network functionality of an ecoregional assessment configuration of marine conservation areas by evaluating the habitat protection and connectivity offered to wide-ranging fauna in the Gulf of California (GOC, Mexico). We first use expert opinion to identify representative species of wide-ranging fauna of the GOC. These include leopard grouper, hammerhead sharks, California brown pelicans and green sea turtles. Analyzing habitat models with both structural and functional connectivity indexes, our results indicate that the configuration includes large proportions of biologically important habitat for the four species considered (25-40%), particularly, the best quality habitats (46-57%). Our results also show that connectivity levels offered by the conservation area design for these four species may be similar to connectivity levels offered by the entire Gulf of California, thus indicating that connectivity offered by the areas may resemble natural connectivity. The selected focal species comprise different life histories among marine or marine-related vertebrates and are associated with those habitats holding the most biodiversity values (i.e. coastal habitats); our results thus suggest that the proposed configuration may function as a network for connectivity and may adequately represent the marine megafauna in the GOC, including the potential connectivity among habitat patches. This work highlights the range of approaches that can be used to quantify habitat protection and connectivity for wide-ranging marine species in marine reserve networks.

Adaptation to nursing home: The role of leisure activities in light of motivation and relatedness.

PubMed

Altintas, Emin; De Benedetto, Giorgio; Gallouj, Karim

Based on the motivational sequence described in Self-Determination Theory, this study explored the relationship between relatedness, motivation, adaptation and leisure in nursing homes. We formulated the hypothesis that the variables of the study would be found in an integrative mediational sequence: Participation in leisure activities→Relatedness→Self-determined motivation→Adaptation to nursing homes. Participants (N=112, mean age=84.17) were invited to complete questionnaires assessing these variables. Results of the path analysis found an unsatisfactory fit for this model but revealed another model (Model 2) with a good fit index: Relatedness→Participation in leisure activities→Self-determined motivation→Adaptation to nursing homes→Relatedness. Model 2 fitted better than model 1: the Chi-square values were not significant, Chi 2 (df=2)=5.1, p=0.078 and other indices were satisfactory (CFI=0.930, RMSEA=0.049 and NFI=0.918). These results suggest that feeling connected and secure in the relationships with others, and integrated as an individual to the group contribute to enhance leisure practice, self-determined motivation, and finally adaptation to life environment. Consequently, the relatedness promotes leisure activities practice which represents a central adaptive behavior in nursing homes. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The diffuse neutrino flux from FR-II radio galaxies and blazars: A source property based estimate

NASA Astrophysics Data System (ADS)

Becker, Julia K.; Biermann, Peter L.; Rhode, Wolfgang

2005-05-01

Water and ice Cherenkov telescopes of the present and future aim for the detection of a neutrino signal from extraterrestrial sources at energies Eν > PeV [Woschnagg and AMANDA Collaboration, Astro-ph/0409423, talk at Neutrino 2004; Montaruli, in: Peter W. Gorham, Particle Astrophysics Instrumentation, Proceedings of the SPIE, vol. 4858, 2003, p. 92; IceCube Collaboration, Astropart. Phys. 20 (2004) 507]. Some of the most promising extragalactic sources are active galactic nuclei (AGN). In this paper, the neutrino flux from two kinds of AGN sources will be estimated assuming pγ interactions in the jets of the AGN. The first analyzed sample contains FR-II radio galaxies while the second AGN type examined are blazars. The result is highly dependent on the proton's index of the energy spectrum. To normalize the spectrum, the connection between neutrino and disk luminosity will be used by applying the jet-disk symbiosis model from Falcke and Biermann [Astron. Astrophys. 293 (1995) 665]. The maximum proton energy and thus, also the maximum neutrino energy of the source is connected to its disk luminosity, which was shown by Lovelace [Nature 262 (1976) 649] and was confirmed by Falcke et al. [Astron. Astrophys. 298 (1995) 375].

Identifying Dynamic Functional Connectivity Changes in Dementia with Lewy Bodies Based on Product Hidden Markov Models.

PubMed

Sourty, Marion; Thoraval, Laurent; Roquet, Daniel; Armspach, Jean-Paul; Foucher, Jack; Blanc, Frédéric

2016-01-01

Exploring time-varying connectivity networks in neurodegenerative disorders is a recent field of research in functional MRI. Dementia with Lewy bodies (DLB) represents 20% of the neurodegenerative forms of dementia. Fluctuations of cognition and vigilance are the key symptoms of DLB. To date, no dynamic functional connectivity (DFC) investigations of this disorder have been performed. In this paper, we refer to the concept of connectivity state as a piecewise stationary configuration of functional connectivity between brain networks. From this concept, we propose a new method for group-level as well as for subject-level studies to compare and characterize connectivity state changes between a set of resting-state networks (RSNs). Dynamic Bayesian networks, statistical and graph theory-based models, enable one to learn dependencies between interacting state-based processes. Product hidden Markov models (PHMM), an instance of dynamic Bayesian networks, are introduced here to capture both statistical and temporal aspects of DFC of a set of RSNs. This analysis was based on sliding-window cross-correlations between seven RSNs extracted from a group independent component analysis performed on 20 healthy elderly subjects and 16 patients with DLB. Statistical models of DFC differed in patients compared to healthy subjects for the occipito-parieto-frontal network, the medial occipital network and the right fronto-parietal network. In addition, pairwise comparisons of DFC of RSNs revealed a decrease of dependency between these two visual networks (occipito-parieto-frontal and medial occipital networks) and the right fronto-parietal control network. The analysis of DFC state changes thus pointed out networks related to the cognitive functions that are known to be impaired in DLB: visual processing as well as attentional and executive functions. Besides this context, product HMM applied to RSNs cross-correlations offers a promising new approach to investigate structural and temporal aspects of brain DFC.

Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.

PubMed

Knick, Steven T; Hanser, Steven E; Preston, Kristine L

2013-06-01

Greater sage-grouse Centrocercus urophasianus (Bonaparte) currently occupy approximately half of their historical distribution across western North America. Sage-grouse are a candidate for endangered species listing due to habitat and population fragmentation coupled with inadequate regulation to control development in critical areas. Conservation planning would benefit from accurate maps delineating required habitats and movement corridors. However, developing a species distribution model that incorporates the diversity of habitats used by sage-grouse across their widespread distribution has statistical and logistical challenges. We first identified the ecological minimums limiting sage-grouse, mapped similarity to the multivariate set of minimums, and delineated connectivity across a 920,000 km(2) region. We partitioned a Mahalanobis D (2) model of habitat use into k separate additive components each representing independent combinations of species-habitat relationships to identify the ecological minimums required by sage-grouse. We constructed the model from abiotic, land cover, and anthropogenic variables measured at leks (breeding) and surrounding areas within 5 km. We evaluated model partitions using a random subset of leks and historic locations and selected D (2) (k = 10) for mapping a habitat similarity index (HSI). Finally, we delineated connectivity by converting the mapped HSI to a resistance surface. Sage-grouse required sagebrush-dominated landscapes containing minimal levels of human land use. Sage-grouse used relatively arid regions characterized by shallow slopes, even terrain, and low amounts of forest, grassland, and agriculture in the surrounding landscape. Most populations were interconnected although several outlying populations were isolated because of distance or lack of habitat corridors for exchange. Land management agencies currently are revising land-use plans and designating critical habitat to conserve sage-grouse and avoid endangered species listing. Our results identifying attributes important for delineating habitats or modeling connectivity will facilitate conservation and management of landscapes important for supporting current and future sage-grouse populations.

Modeling ecological minimum requirements for distribution of greater sage-grouse leks: implications for population connectivity across their western range, U.S.A.

USGS Publications Warehouse

Knick, Steven T.; Hanser, Steven E.; Preston, Kristine L.

2013-01-01

Greater sage-grouse Centrocercus urophasianus (Bonaparte) currently occupy approximately half of their historical distribution across western North America. Sage-grouse are a candidate for endangered species listing due to habitat and population fragmentation coupled with inadequate regulation to control development in critical areas. Conservation planning would benefit from accurate maps delineating required habitats and movement corridors. However, developing a species distribution model that incorporates the diversity of habitats used by sage-grouse across their widespread distribution has statistical and logistical challenges. We first identified the ecological minimums limiting sage-grouse, mapped similarity to the multivariate set of minimums, and delineated connectivity across a 920,000 km2 region. We partitioned a Mahalanobis D2 model of habitat use into k separate additive components each representing independent combinations of species–habitat relationships to identify the ecological minimums required by sage-grouse. We constructed the model from abiotic, land cover, and anthropogenic variables measured at leks (breeding) and surrounding areas within 5 km. We evaluated model partitions using a random subset of leks and historic locations and selected D2 (k = 10) for mapping a habitat similarity index (HSI). Finally, we delineated connectivity by converting the mapped HSI to a resistance surface. Sage-grouse required sagebrush-dominated landscapes containing minimal levels of human land use. Sage-grouse used relatively arid regions characterized by shallow slopes, even terrain, and low amounts of forest, grassland, and agriculture in the surrounding landscape. Most populations were interconnected although several outlying populations were isolated because of distance or lack of habitat corridors for exchange. Land management agencies currently are revising land-use plans and designating critical habitat to conserve sage-grouse and avoid endangered species listing. Our results identifying attributes important for delineating habitats or modeling connectivity will facilitate conservation and management of landscapes important for supporting current and future sage-grouse populations.

Landscape metrics as predictors of hydrologic connectivity between Coastal Plain forested wetlands and streams

PubMed Central

Epting, Steven M.; Hosen, Jacob D.; Alexander, Laurie C.; Lang, Megan W.; Armstrong, Alec W.

2018-01-01

Abstract Geographically isolated wetlands, those entirely surrounded by uplands, provide numerous landscape‐scale ecological functions, many of which are dependent on the degree to which they are hydrologically connected to nearby waters. There is a growing need for field‐validated, landscape‐scale approaches for classifying wetlands on the basis of their expected degree of hydrologic connectivity with stream networks. This study quantified seasonal variability in surface hydrologic connectivity (SHC) patterns between forested Delmarva bay wetland complexes and perennial/intermittent streams at 23 sites over a full‐water year (2014–2015). Field data were used to develop metrics to predict SHC using hypothesized landscape drivers of connectivity duration and timing. Connection duration was most strongly related to the number and area of wetlands within wetland complexes as well as the channel width of the temporary stream connecting the wetland complex to a perennial/intermittent stream. Timing of SHC onset was related to the topographic wetness index and drainage density within the catchment. Stepwise regression modelling found that landscape metrics could be used to predict SHC duration as a function of wetland complex catchment area, wetland area, wetland number, and soil available water storage (adj‐R 2 = 0.74, p < .0001). Results may be applicable to assessments of forested depressional wetlands elsewhere in the U.S. Mid‐Atlantic and Southeastern Coastal Plain, where climate, landscapes, and hydrological inputs and losses are expected to be similar to the study area. PMID:29576682

Coupling the WRF model with a temperature index model based on remote sensing for snowmelt simulations in a river basin in the Altay Mountains, northwest China

NASA Astrophysics Data System (ADS)

Wu, X.; Shen, Y.; Wang, N.; Pan, X.; Zhang, W.; He, J.; Wang, G.

2017-12-01

Snowmelt water is an important freshwater resource in the Altay Mountains in northwest China, and it is also crucial for local ecological system, economic and social sustainable development; however, warming climate and rapid spring snowmelt can cause floods that endanger both eco-environment and public and personal property and safety. This study simulates snowmelt in the Kayiertesi River catchment using a temperature-index model based on remote sensing coupled with high-resolution meteorological data obtained from NCEP reanalysis fields that were downscaled using Weather Research Forecasting model, then bias-corrected using a statistical downscaled model. Validation of the forcing data revealed that the high-resolution meteorological fields derived from downscaled NCEP reanalysis were reliable for driving the snowmelt model. Parameters of temperature-index model based on remote sensing were calibrated for spring 2014, and model performance was validated using MODIS snow cover and snow observations from spring 2012. The results show that the temperature-index model based on remote sensing performed well, with a simulation mean relative error of 6.7% and a Nash-Sutchliffe efficiency of 0.98 in spring 2012 in the river of Altay Mountains. Based on the reliable distributed snow water equivalent simulation, daily snowmelt runoff was calculated for spring 2012 in the basin. In the study catchment, spring snowmelt runoff accounts for 72% of spring runoff and 21% of annual runoff. Snowmelt is the main source of runoff for the catchment and should be managed and utilized effectively. The results provide a basis for snowmelt runoff predictions, so as to prevent snowmelt-induced floods, and also provide a generalizable approach that can be applied to other remote locations where high-density, long-term observational data is lacking.

Performance model for grid-connected photovoltaic inverters.

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

Boyson, William Earl; Galbraith, Gary M.; King, David L.

2007-09-01

This document provides an empirically based performance model for grid-connected photovoltaic inverters used for system performance (energy) modeling and for continuous monitoring of inverter performance during system operation. The versatility and accuracy of the model were validated for a variety of both residential and commercial size inverters. Default parameters for the model can be obtained from manufacturers specification sheets, and the accuracy of the model can be further refined using measurements from either well-instrumented field measurements in operational systems or using detailed measurements from a recognized testing laboratory. An initial database of inverter performance parameters was developed based on measurementsmore » conducted at Sandia National Laboratories and at laboratories supporting the solar programs of the California Energy Commission.« less

User-Centered Indexing for Adaptive Information Access

NASA Technical Reports Server (NTRS)

Chen, James R.; Mathe, Nathalie

1996-01-01

We are focusing on information access tasks characterized by large volume of hypermedia connected technical documents, a need for rapid and effective access to familiar information, and long-term interaction with evolving information. The problem for technical users is to build and maintain a personalized task-oriented model of the information to quickly access relevant information. We propose a solution which provides user-centered adaptive information retrieval and navigation. This solution supports users in customizing information access over time. It is complementary to information discovery methods which provide access to new information, since it lets users customize future access to previously found information. It relies on a technique, called Adaptive Relevance Network, which creates and maintains a complex indexing structure to represent personal user's information access maps organized by concepts. This technique is integrated within the Adaptive HyperMan system, which helps NASA Space Shuttle flight controllers organize and access large amount of information. It allows users to select and mark any part of a document as interesting, and to index that part with user-defined concepts. Users can then do subsequent retrieval of marked portions of documents. This functionality allows users to define and access personal collections of information, which are dynamically computed. The system also supports collaborative review by letting users share group access maps. The adaptive relevance network provides long-term adaptation based both on usage and on explicit user input. The indexing structure is dynamic and evolves over time. Leading and generalization support flexible retrieval of information under similar concepts. The network is geared towards more recent information access, and automatically manages its size in order to maintain rapid access when scaling up to large hypermedia space. We present results of simulated learning experiments.

The connection characteristics of flux pinned docking interface

NASA Astrophysics Data System (ADS)

Zhang, Mingliang; Han, Yanjun; Guo, Xing; Zhao, Cunbao; Deng, Feiyue

2017-03-01

This paper presents the mechanism and potential advantages of flux pinned docking interface mainly composed of a high temperature superconductor and an electromagnet. In order to readily assess the connection characteristics of flux pinned docking interface, the force between a high temperature superconductor and an electromagnet needs to be investigated. Based on the magnetic dipole method and the Ampere law method, the force between two current coils can be compared, which shows that the Ampere law method has the higher calculated accuracy. Based on the improved frozen image model and the Ampere law method, the force between high temperature superconductor bulk and permanent magnet can be calculated, which is validated experimentally. Moreover, the force between high temperature superconductor and electromagnet applied to flux pinned docking interface is able to be predicted and analyzed. The connection stiffness between high temperature superconductor and permanent magnet can be calculated based on the improved frozen image model and Hooke's law. The relationship between the connection stiffness and field cooling height is analyzed. Furthermore, the connection stiffness of the flux pinned docking interface is predicted and optimized, and its effective working range is defined and analyzed in case of some different parameters.

Evaluation of cortical plasticity in children with cerebral palsy undergoing constraint-induced movement therapy based on functional near-infrared spectroscopy

NASA Astrophysics Data System (ADS)

Cao, Jianwei; Khan, Bilal; Hervey, Nathan; Tian, Fenghua; Delgado, Mauricio R.; Clegg, Nancy J.; Smith, Linsley; Roberts, Heather; Tulchin-Francis, Kirsten; Shierk, Angela; Shagman, Laura; MacFarlane, Duncan; Liu, Hanli; Alexandrakis, George

2015-04-01

Sensorimotor cortex plasticity induced by constraint-induced movement therapy (CIMT) in six children (10.2±2.1 years old) with hemiplegic cerebral palsy was assessed by functional near-infrared spectroscopy (fNIRS). The activation laterality index and time-to-peak/duration during a finger-tapping task and the resting-state functional connectivity were quantified before, immediately after, and 6 months after CIMT. These fNIRS-based metrics were used to help explain changes in clinical scores of manual performance obtained concurrently with imaging time points. Five age-matched healthy children (9.8±1.3 years old) were also imaged to provide comparative activation metrics for normal controls. Interestingly, the activation time-to-peak/duration for all sensorimotor centers displayed significant normalization immediately after CIMT that persisted 6 months later. In contrast to this improved localized activation response, the laterality index and resting-state connectivity metrics that depended on communication between sensorimotor centers improved immediately after CIMT, but relapsed 6 months later. In addition, for the subjects measured in this work, there was either a trade-off between improving unimanual versus bimanual performance when sensorimotor activation patterns normalized after CIMT, or an improvement occurred in both unimanual and bimanual performance but at the cost of very abnormal plastic changes in sensorimotor activity.

Identifying effective connectivity parameters in simulated fMRI: a direct comparison of switching linear dynamic system, stochastic dynamic causal, and multivariate autoregressive models

PubMed Central

Smith, Jason F.; Chen, Kewei; Pillai, Ajay S.; Horwitz, Barry

2013-01-01

The number and variety of connectivity estimation methods is likely to continue to grow over the coming decade. Comparisons between methods are necessary to prune this growth to only the most accurate and robust methods. However, the nature of connectivity is elusive with different methods potentially attempting to identify different aspects of connectivity. Commonalities of connectivity definitions across methods upon which base direct comparisons can be difficult to derive. Here, we explicitly define “effective connectivity” using a common set of observation and state equations that are appropriate for three connectivity methods: dynamic causal modeling (DCM), multivariate autoregressive modeling (MAR), and switching linear dynamic systems for fMRI (sLDSf). In addition while deriving this set, we show how many other popular functional and effective connectivity methods are actually simplifications of these equations. We discuss implications of these connections for the practice of using one method to simulate data for another method. After mathematically connecting the three effective connectivity methods, simulated fMRI data with varying numbers of regions and task conditions is generated from the common equation. This simulated data explicitly contains the type of the connectivity that the three models were intended to identify. Each method is applied to the simulated data sets and the accuracy of parameter identification is analyzed. All methods perform above chance levels at identifying correct connectivity parameters. The sLDSf method was superior in parameter estimation accuracy to both DCM and MAR for all types of comparisons. PMID:23717258

Rain/No-Rain Identification from Bispectral Satellite Information using Deep Neural Networks

NASA Astrophysics Data System (ADS)

Tao, Y.

2016-12-01

Satellite-based precipitation estimation products have the advantage of high resolution and global coverage. However, they still suffer from insufficient accuracy. To accurately estimate precipitation from satellite data, there are two most important aspects: sufficient precipitation information in the satellite information and proper methodologies to extract such information effectively. This study applies the state-of-the-art machine learning methodologies to bispectral satellite information for Rain/No-Rain detection. Specifically, we use deep neural networks to extract features from infrared and water vapor channels and connect it to precipitation identification. To evaluate the effectiveness of the methodology, we first applies it to the infrared data only (Model DL-IR only), the most commonly used inputs for satellite-based precipitation estimation. Then we incorporates water vapor data (Model DL-IR + WV) to further improve the prediction performance. Radar stage IV dataset is used as ground measurement for parameter calibration. The operational product, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks Cloud Classification System (PERSIANN-CCS), is used as a reference to compare the performance of both models in both winter and summer seasons.The experiments show significant improvement for both models in precipitation identification. The overall performance gains in the Critical Success Index (CSI) are 21.60% and 43.66% over the verification periods for Model DL-IR only and Model DL-IR+WV model compared to PERSIANN-CCS, respectively. Moreover, specific case studies show that the water vapor channel information and the deep neural networks effectively help recover a large number of missing precipitation pixels under warm clouds while reducing false alarms under cold clouds.

Climate change and habitat fragmentation drive the occurrence of Borrelia burgdorferi, the agent of Lyme disease, at the northeastern limit of its distribution

PubMed Central

Simon, Julie A; Marrotte, Robby R; Desrosiers, Nathalie; Fiset, Jessica; Gaitan, Jorge; Gonzalez, Andrew; Koffi, Jules K; Lapointe, Francois-Joseph; Leighton, Patrick A; Lindsay, Lindsay R; Logan, Travis; Milord, Francois; Ogden, Nicholas H; Rogic, Anita; Roy-Dufresne, Emilie; Suter, Daniel; Tessier, Nathalie; Millien, Virginie

2014-01-01

Lyme borreliosis is rapidly emerging in Canada, and climate change is likely a key driver of the northern spread of the disease in North America. We used field and modeling approaches to predict the risk of occurrence of Borrelia burgdorferi, the bacteria causing Lyme disease in North America. We combined climatic and landscape variables to model the current and future (2050) potential distribution of the black-legged tick and the white-footed mouse at the northeastern range limit of Lyme disease and estimated a risk index for B. burgdorferi from these distributions. The risk index was mostly constrained by the distribution of the white-footed mouse, driven by winter climatic conditions. The next factor contributing to the risk index was the distribution of the black-legged tick, estimated from the temperature. Landscape variables such as forest habitat and connectivity contributed little to the risk index. We predict a further northern expansion of B. burgdorferi of approximately 250–500 km by 2050 – a rate of 3.5–11 km per year – and identify areas of rapid rise in the risk of occurrence of B. burgdorferi. Our results will improve understanding of the spread of Lyme disease and inform management strategies at the most northern limit of its distribution. PMID:25469157

Tulsa's IndEx Program. A Business-Led Initiative for Welfare Reform and Economic Development. Connections To Work.

ERIC Educational Resources Information Center

Buck, Maria L.

In 1992, the Metropolitan Tulsa Chamber of Commerce in Oklahoma established a welfare-to-work program called Industrial Exchange, Inc. (IndEx). IndEx provides welfare recipients with a combination of education activities and work experience. By contracting with local companies to perform light manufacturing and packaging work at a central site,…

Prognosis after surgical excision of canine fibrous connective tissue sarcomas.

PubMed

Bostock, D E; Dye, M T

1980-09-01

One hundred eighty seven dogs from which fibrous connective tissue sarcomas had been excised were studied until death or for at least 3 years after surgery. Dogs with a skin fibrosarcoma had a median survival time of 80 weeks, compared with 140 weeks for animals with haemangiopericytoma in similar sites, this difference being statistically significant. However, the difference in survival time between the two histologic types disappeared when tumours with a similar mitotic index were compared. Dogs with a tumour of mitotic index 9 or more had a median survival time of 49 weeks, compared with 118 weeks for those with a tumour of mitotic index less than 9, regardless of tumour morphology. Tumour recurrence rates of 62% and 25% respectively for the two groups were also significantly different.

Retrieving and Indexing Spatial Data in the Cloud Computing Environment

NASA Astrophysics Data System (ADS)

Wang, Yonggang; Wang, Sheng; Zhou, Daliang

In order to solve the drawbacks of spatial data storage in common Cloud Computing platform, we design and present a framework for retrieving, indexing, accessing and managing spatial data in the Cloud environment. An interoperable spatial data object model is provided based on the Simple Feature Coding Rules from the OGC such as Well Known Binary (WKB) and Well Known Text (WKT). And the classic spatial indexing algorithms like Quad-Tree and R-Tree are re-designed in the Cloud Computing environment. In the last we develop a prototype software based on Google App Engine to implement the proposed model.

Evaluating energy saving system of data centers based on AHP and fuzzy comprehensive evaluation model

NASA Astrophysics Data System (ADS)

Jiang, Yingni

2018-03-01

Due to the high energy consumption of communication, energy saving of data centers must be enforced. But the lack of evaluation mechanisms has restrained the process on energy saving construction of data centers. In this paper, energy saving evaluation index system of data centers was constructed on the basis of clarifying the influence factors. Based on the evaluation index system, analytical hierarchy process was used to determine the weights of the evaluation indexes. Subsequently, a three-grade fuzzy comprehensive evaluation model was constructed to evaluate the energy saving system of data centers.

IMPROVED SEARCH OF PRINCIPAL COMPONENT ANALYSIS DATABASES FOR SPECTRO-POLARIMETRIC INVERSION

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

Casini, R.; Lites, B. W.; Ramos, A. Asensio

2013-08-20

We describe a simple technique for the acceleration of spectro-polarimetric inversions based on principal component analysis (PCA) of Stokes profiles. This technique involves the indexing of the database models based on the sign of the projections (PCA coefficients) of the first few relevant orders of principal components of the four Stokes parameters. In this way, each model in the database can be attributed a distinctive binary number of 2{sup 4n} bits, where n is the number of PCA orders used for the indexing. Each of these binary numbers (indices) identifies a group of ''compatible'' models for the inversion of amore » given set of observed Stokes profiles sharing the same index. The complete set of the binary numbers so constructed evidently determines a partition of the database. The search of the database for the PCA inversion of spectro-polarimetric data can profit greatly from this indexing. In practical cases it becomes possible to approach the ideal acceleration factor of 2{sup 4n} as compared to the systematic search of a non-indexed database for a traditional PCA inversion. This indexing method relies on the existence of a physical meaning in the sign of the PCA coefficients of a model. For this reason, the presence of model ambiguities and of spectro-polarimetric noise in the observations limits in practice the number n of relevant PCA orders that can be used for the indexing.« less

Method for selection of optimal road safety composite index with examples from DEA and TOPSIS method.

PubMed

Rosić, Miroslav; Pešić, Dalibor; Kukić, Dragoslav; Antić, Boris; Božović, Milan

2017-01-01

Concept of composite road safety index is a popular and relatively new concept among road safety experts around the world. As there is a constant need for comparison among different units (countries, municipalities, roads, etc.) there is need to choose an adequate method which will make comparison fair to all compared units. Usually comparisons using one specific indicator (parameter which describes safety or unsafety) can end up with totally different ranking of compared units which is quite complicated for decision maker to determine "real best performers". Need for composite road safety index is becoming dominant since road safety presents a complex system where more and more indicators are constantly being developed to describe it. Among wide variety of models and developed composite indexes, a decision maker can come to even bigger dilemma than choosing one adequate risk measure. As DEA and TOPSIS are well-known mathematical models and have recently been increasingly used for risk evaluation in road safety, we used efficiencies (composite indexes) obtained by different models, based on DEA and TOPSIS, to present PROMETHEE-RS model for selection of optimal method for composite index. Method for selection of optimal composite index is based on three parameters (average correlation, average rank variation and average cluster variation) inserted into a PROMETHEE MCDM method in order to choose the optimal one. The model is tested by comparing 27 police departments in Serbia. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gamma-Ray Observations of the Supernova Remnant RX J0852.0-4622 with the Fermi Large Area Telescope

NASA Technical Reports Server (NTRS)

Tanaka, T.; Allafort, A.; Ballet, J.; Funk, S.; Giordano, F.; Hewitt, J.; Lemoine-Goumard, M.; Tajima, H.; Tibolla, O.; Uchiyama, Y.

2011-01-01

We report on gamma-ray observations of the supernova remnant (SNR) RX J0852.04622 with the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope. In the Fermi-LAT data, we find a spatially extended source at the location of the SNR. The extension is consistent with the SNR size seen in other wavelengths such as X-rays and TeV gamma rays, leading to the identification of the gamma-ray source with the SNR. The spectrum is well described as a power law with a photon index of = 1.85 0.06 (stat)+0.18 0.19 (sys), which smoothly connects to the H.E.S.S. spectrum in the TeV energy band. We discuss the gamma-ray emission mechanism based on multiwavelength data. The broadband data can be fit well by a model in which the gamma rays are of hadronic origin. We also consider a scenario with inverse Compton scattering of electrons as the emission mechanism of the gamma rays. Although the leptonic model predicts a harder spectrum in the Fermi-LAT energy range, the model can fit the data considering the statistical and systematic errors.

Prediction of compressibility parameters of the soils using artificial neural network.

PubMed

Kurnaz, T Fikret; Dagdeviren, Ugur; Yildiz, Murat; Ozkan, Ozhan

2016-01-01

The compression index and recompression index are one of the important compressibility parameters to determine the settlement calculation for fine-grained soil layers. These parameters can be determined by carrying out laboratory oedometer test on undisturbed samples; however, the test is quite time-consuming and expensive. Therefore, many empirical formulas based on regression analysis have been presented to estimate the compressibility parameters using soil index properties. In this paper, an artificial neural network (ANN) model is suggested for prediction of compressibility parameters from basic soil properties. For this purpose, the input parameters are selected as the natural water content, initial void ratio, liquid limit and plasticity index. In this model, two output parameters, including compression index and recompression index, are predicted in a combined network structure. As the result of the study, proposed ANN model is successful for the prediction of the compression index, however the predicted recompression index values are not satisfying compared to the compression index.

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation

PubMed Central

Wang, Yikai; Kang, Jian; Kemmer, Phebe B.; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package “DensParcorr” can be downloaded from CRAN for implementing the proposed statistical methods. PMID:27242395

An Efficient and Reliable Statistical Method for Estimating Functional Connectivity in Large Scale Brain Networks Using Partial Correlation.

PubMed

Wang, Yikai; Kang, Jian; Kemmer, Phebe B; Guo, Ying

2016-01-01

Currently, network-oriented analysis of fMRI data has become an important tool for understanding brain organization and brain networks. Among the range of network modeling methods, partial correlation has shown great promises in accurately detecting true brain network connections. However, the application of partial correlation in investigating brain connectivity, especially in large-scale brain networks, has been limited so far due to the technical challenges in its estimation. In this paper, we propose an efficient and reliable statistical method for estimating partial correlation in large-scale brain network modeling. Our method derives partial correlation based on the precision matrix estimated via Constrained L1-minimization Approach (CLIME), which is a recently developed statistical method that is more efficient and demonstrates better performance than the existing methods. To help select an appropriate tuning parameter for sparsity control in the network estimation, we propose a new Dens-based selection method that provides a more informative and flexible tool to allow the users to select the tuning parameter based on the desired sparsity level. Another appealing feature of the Dens-based method is that it is much faster than the existing methods, which provides an important advantage in neuroimaging applications. Simulation studies show that the Dens-based method demonstrates comparable or better performance with respect to the existing methods in network estimation. We applied the proposed partial correlation method to investigate resting state functional connectivity using rs-fMRI data from the Philadelphia Neurodevelopmental Cohort (PNC) study. Our results show that partial correlation analysis removed considerable between-module marginal connections identified by full correlation analysis, suggesting these connections were likely caused by global effects or common connection to other nodes. Based on partial correlation, we find that the most significant direct connections are between homologous brain locations in the left and right hemisphere. When comparing partial correlation derived under different sparse tuning parameters, an important finding is that the sparse regularization has more shrinkage effects on negative functional connections than on positive connections, which supports previous findings that many of the negative brain connections are due to non-neurophysiological effects. An R package "DensParcorr" can be downloaded from CRAN for implementing the proposed statistical methods.

Estimation of Mangrove Net Primary Production and Carbon Sequestration service using Light Use Efficiency model in the Sunderban Biosphere region, India

NASA Astrophysics Data System (ADS)

Sannigrahi, Srikanta; Sen, Somnath; Paul, Saikat

2016-04-01

Net Primary Production (NPP) of mangrove ecosystem and its capacity to sequester carbon from the atmosphere may be used to quantify the regulatory ecosystem services. Three major group of parameters has been set up as BioClimatic Parameters (BCP): (Photosynthetically Active Radiation (PAR), Absorbed PAR (APAR), Fraction of PAR (FPAR), Photochemical Reflectance Index (PRI), Light Use Efficiency (LUE)), BioPhysical Parameters (BPP) :(Normalize Difference Vegetation Index (NDVI), scaled NDVI, Enhanced Vegetation Index (EVI), scaled EVI, Optimised and Modified Soil Adjusted Vegetation Index (OSAVI, MSAVI), Leaf Area Index (LAI)), and Environmental Limiting Parameters (ELP) (Temperature Stress (TS), Land Surface Water Index (LSWI), Normalize Soil Water Index (NSWI), Water Stress Scalar (WS), Inversed WS (iWS) Land Surface Temperature (LST), scaled LST, Vapor Pressure Deficit (VPD), scaled VPD, and Soil Water Deficit Index (SWDI)). Several LUE models namely Carnegie Ames Stanford Approach (CASA), Eddy Covariance - LUE (EC-LUE), Global Production Efficiency Model (GloPEM), Vegetation Photosynthesis Model (VPM), MOD NPP model, Temperature and Greenness Model (TG), Greenness and Radiation model (GR) and MOD17 was adopted in this study to assess the spatiotemporal nature of carbon fluxes. Above and Below Ground Biomass (AGB & BGB) was calculated using field based estimation of OSAVI and NDVI. Microclimatic zonation has been set up to assess the impact of coastal climate on environmental limiting factors. MODerate Resolution Imaging Spectroradiometer (MODIS) based yearly Gross Primary Production (GPP) and NPP product MOD17 was also tested with LUE based results with standard model validation statistics: Root Mean Square of Error (RMSE), Mean Absolute Error (MEA), Bias, Coefficient of Variation (CV) and Coefficient of Determination (R2). The performance of CASA NPP was tested with the ground based NPP with R2 = 0.89 RMSE = 3.28 P = 0.01. Among the all adopted models, EC-LUE and VPM models has explained the maximum variances (>80%) in comparison to the other model. Study result has also showed that the BPP has explained the maximum model variances (>93%) followed by BCP (>65%) and ELP (>50%). Scaled WS, iWS, LST, VPD, NDVI was performed better in a minimum ELP condition whereas surface moisture and wetness was highly correlated with the AGB and NPP (R2 = 0.86 RMSE = 1.83). During this study period (2000-2013), it was found that there was a significantly declining trend (R2 = 0.32 P = 0.05) of annual NPP and the maximum decrease was found in the eastern part where built-up area was mainly accounted for reduction of NPP. BCP are explained higher variances (>80%) in the optimum climatic condition exist along the coastal stretches in comparison to the landward extent (>45%).

Estimating Pressure Reactivity Using Noninvasive Doppler-Based Systolic Flow Index.

PubMed

Zeiler, Frederick A; Smielewski, Peter; Donnelly, Joseph; Czosnyka, Marek; Menon, David K; Ercole, Ari

2018-04-05

The study objective was to derive models that estimate the pressure reactivity index (PRx) using the noninvasive transcranial Doppler (TCD) based systolic flow index (Sx_a) and mean flow index (Mx_a), both based on mean arterial pressure, in traumatic brain injury (TBI). Using a retrospective database of 347 patients with TBI with intracranial pressure and TCD time series recordings, we derived PRx, Sx_a, and Mx_a. We first derived the autocorrelative structure of PRx based on: (A) autoregressive integrative moving average (ARIMA) modeling in representative patients, and (B) within sequential linear mixed effects (LME) models with various embedded ARIMA error structures for PRx for the entire population. Finally, we performed sequential LME models with embedded PRx ARIMA modeling to find the best model for estimating PRx using Sx_a and Mx_a. Model adequacy was assessed via normally distributed residual density. Model superiority was assessed via Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), log likelihood (LL), and analysis of variance testing between models. The most appropriate ARIMA structure for PRx in this population was (2,0,2). This was applied in sequential LME modeling. Two models were superior (employing random effects in the independent variables and intercept): (A) PRx ∼ Sx_a, and (B) PRx ∼ Sx_a + Mx_a. Correlation between observed and estimated PRx with these two models was: (A) 0.794 (p < 0.0001, 95% confidence interval (CI) = 0.788-0.799), and (B) 0.814 (p < 0.0001, 95% CI = 0.809-0.819), with acceptable agreement on Bland-Altman analysis. Through using linear mixed effects modeling and accounting for the ARIMA structure of PRx, one can estimate PRx using noninvasive TCD-based indices. We have described our first attempts at such modeling and PRx estimation, establishing the strong link between two aspects of cerebral autoregulation: measures of cerebral blood flow and those of pulsatile cerebral blood volume. Further work is required to validate.

A cricket Gene Index: a genomic resource for studying neurobiology, speciation, and molecular evolution

PubMed Central

Danley, Patrick D; Mullen, Sean P; Liu, Fenglong; Nene, Vishvanath; Quackenbush, John; Shaw, Kerry L

2007-01-01

Background As the developmental costs of genomic tools decline, genomic approaches to non-model systems are becoming more feasible. Many of these systems may lack advanced genetic tools but are extremely valuable models in other biological fields. Here we report the development of expressed sequence tags (EST's) in an orthopteroid insect, a model for the study of neurobiology, speciation, and evolution. Results We report the sequencing of 14,502 EST's from clones derived from a nerve cord cDNA library, and the subsequent construction of a Gene Index from these sequences, from the Hawaiian trigonidiine cricket Laupala kohalensis. The Gene Index contains 8607 unique sequences comprised of 2575 tentative consensus (TC) sequences and 6032 singletons. For each of the unique sequences, an attempt was made to assign a provisional annotation and to categorize its function using a Gene Ontology-based classification through a sequence-based comparison to known proteins. In addition, a set of unique 70 base pair oligomers that can be used for DNA microarrays was developed. All Gene Index information is posted at the DFCI Gene Indices web page Conclusion Orthopterans are models used to understand the neurophysiological basis of complex motor patterns such as flight and stridulation. The sequences presented in the cricket Gene Index will provide neurophysiologists with many genetic tools that have been largely absent in this field. The cricket Gene Index is one of only two gene indices to be developed in an evolutionary model system. Species within the genus Laupala have speciated recently, rapidly, and extensively. Therefore, the genes identified in the cricket Gene Index can be used to study the genomics of speciation. Furthermore, this gene index represents a significant EST resources for basal insects. As such, this resource is a valuable comparative tool for the understanding of invertebrate molecular evolution. The sequences presented here will provide much needed genomic resources for three distinct but overlapping fields of inquiry: neurobiology, speciation, and molecular evolution. PMID:17459168

Drought index driven by L-band microwave soil moisture data

NASA Astrophysics Data System (ADS)

Bitar, Ahmad Al; Kerr, Yann; Merlin, Olivier; Cabot, François; Choné, Audrey; Wigneron, Jean-Pierre

2014-05-01

Drought is considered in many areas across the globe as one of the major extreme events. Studies do not all agree on the increase of the frequency of drought events over the past 60 years [1], but they all agree that the impact of droughts has increased and the need for efficient global monitoring tools has become most than ever urgent. Droughts are monitored through drought indexes, many of which are based on precipitation (Palmer index(s), PDI…), on vegetation status (VDI) or on surface temperatures. They can also be derived from climate prediction models outputs. The GMO has selected the (SPI) Standardized Precipitation Index as the reference index for the monitoring of drought at global scale. The drawback of this index is that it is directly dependent on global precipitation products that are not accurate over global scale. On the other hand, Vegetation based indexes show the a posteriori effect of drought, since they are based on NDVI. In this study, we choose to combine the surface soil moisture from microwave sensor with climate data to access a drought index. The microwave data are considered from the SMOS (Soil Moisture and Ocean Salinity) mission at L-Band (1.4 Ghz) interferometric radiometer from ESA (European Space Agency) [2]. Global surface soil moisture maps with 3 days coverage for ascending 6AM and descending 6PM orbits SMOS have been delivered since January 2010 at a 40 km nominal resolution. We use in this study the daily L3 global soil moisture maps from CATDS (Centre Aval de Traitement des Données SMOS) [3,4]. We present a drought index computed by a double bucket hydrological model driven by operational remote sensing data and ancillary datasets. The SPI is also compared to other drought indicators like vegetation indexes and Palmer drought index. Comparison of drought index to vegetation indexes from AVHRR and MODIS over continental United States show that the drought index can be used as an early warning system for drought monitoring as the water shortage can be sensed several weeks before the vegetation dryness occures. Keywords: SMOS, microwave, level 4, soil moisture, drought, precipitation, hydrological model, vegetation index

Connecting today's climates to future climate analogs to facilitate movement of species under climate change.

PubMed

Littlefield, Caitlin E; McRae, Brad H; Michalak, Julia L; Lawler, Joshua J; Carroll, Carlos

2017-12-01

Increasing connectivity is an important strategy for facilitating species range shifts and maintaining biodiversity in the face of climate change. To date, however, few researchers have included future climate projections in efforts to prioritize areas for increasing connectivity. We identified key areas likely to facilitate climate-induced species' movement across western North America. Using historical climate data sets and future climate projections, we mapped potential species' movement routes that link current climate conditions to analogous climate conditions in the future (i.e., future climate analogs) with a novel moving-window analysis based on electrical circuit theory. In addition to tracing shifting climates, the approach accounted for landscape permeability and empirically derived species' dispersal capabilities. We compared connectivity maps generated with our climate-change-informed approach with maps of connectivity based solely on the degree of human modification of the landscape. Including future climate projections in connectivity models substantially shifted and constrained priority areas for movement to a smaller proportion of the landscape than when climate projections were not considered. Potential movement, measured as current flow, decreased in all ecoregions when climate projections were included, particularly when dispersal was limited, which made climate analogs inaccessible. Many areas emerged as important for connectivity only when climate change was modeled in 2 time steps rather than in a single time step. Our results illustrate that movement routes needed to track changing climatic conditions may differ from those that connect present-day landscapes. Incorporating future climate projections into connectivity modeling is an important step toward facilitating successful species movement and population persistence in a changing climate. © 2017 Society for Conservation Biology.

Pore Space Connectivity and the Transport Properties of Rocks

DOE PAGES

Bernabé, Yves; Li, Min; Tang, Yan-Bing; ...

2016-06-23

Pore connectivity is likely one of the most important factors affecting the permeability of reservoir rocks. Furthermore, connectivity effects are not restricted to materials approaching a percolation transition but can continuously and gradually occur in rocks undergoing geological processes such as mechanical and chemical diagenesis. Here, we compiled sets of published measurements of porosity, permeability and formation factor, performed in samples of unconsolidated granular aggregates, in which connectivity does not change, and in two other materials, sintered glass beads and Fontainebleau sandstone, in which connectivity does change. We compared these data to the predictions of a Kozeny-Carman model of permeability,more » which does not account for variations in connectivity, and to those of Bernabé et al. (2010, 2011) model, which does [Bernabé Y., Li M., Maineult A. (2010) Permeability and pore connectivity: a new model based on network simulations, J. Geophys. Res. 115, B10203; Bernabé Y., Zamora M., Li M., Maineult A., Tang Y.B. (2011) Pore connectivity, permeability and electrical formation factor: a new model and comparison to experimental data, J. Geophys. Res. 116, B11204]. Both models agreed equally well with experimental data obtained in unconsolidated granular media. But, in the other materials, especially in the low porosity samples that had undergone the greatest amount of sintering or diagenesis, only Bernabé et al. model matched the experimental data satisfactorily. In comparison, predictions of the Kozeny-Carman model differed by orders of magnitude. The advantage of the Bernabé et al. model was its ability to account for a continuous, gradual reduction in pore connectivity during sintering or diagenesis. Though we can only speculate at this juncture about the mechanisms responsible for the connectivity reduction, we propose two possible mechanisms, likely to be active at different stages of sintering and diagenesis, and thus allowing the gradual evolution observed experimentally.« less

Pore Space Connectivity and the Transport Properties of Rocks

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

Bernabé, Yves; Li, Min; Tang, Yan-Bing

Pore connectivity is likely one of the most important factors affecting the permeability of reservoir rocks. Furthermore, connectivity effects are not restricted to materials approaching a percolation transition but can continuously and gradually occur in rocks undergoing geological processes such as mechanical and chemical diagenesis. Here, we compiled sets of published measurements of porosity, permeability and formation factor, performed in samples of unconsolidated granular aggregates, in which connectivity does not change, and in two other materials, sintered glass beads and Fontainebleau sandstone, in which connectivity does change. We compared these data to the predictions of a Kozeny-Carman model of permeability,more » which does not account for variations in connectivity, and to those of Bernabé et al. (2010, 2011) model, which does [Bernabé Y., Li M., Maineult A. (2010) Permeability and pore connectivity: a new model based on network simulations, J. Geophys. Res. 115, B10203; Bernabé Y., Zamora M., Li M., Maineult A., Tang Y.B. (2011) Pore connectivity, permeability and electrical formation factor: a new model and comparison to experimental data, J. Geophys. Res. 116, B11204]. Both models agreed equally well with experimental data obtained in unconsolidated granular media. But, in the other materials, especially in the low porosity samples that had undergone the greatest amount of sintering or diagenesis, only Bernabé et al. model matched the experimental data satisfactorily. In comparison, predictions of the Kozeny-Carman model differed by orders of magnitude. The advantage of the Bernabé et al. model was its ability to account for a continuous, gradual reduction in pore connectivity during sintering or diagenesis. Though we can only speculate at this juncture about the mechanisms responsible for the connectivity reduction, we propose two possible mechanisms, likely to be active at different stages of sintering and diagenesis, and thus allowing the gradual evolution observed experimentally.« less

From brain topography to brain topology: relevance of graph theory to functional neuroscience.

PubMed

Minati, Ludovico; Varotto, Giulia; D'Incerti, Ludovico; Panzica, Ferruccio; Chan, Dennis

2013-07-10

Although several brain regions show significant specialization, higher functions such as cross-modal information integration, abstract reasoning and conscious awareness are viewed as emerging from interactions across distributed functional networks. Analytical approaches capable of capturing the properties of such networks can therefore enhance our ability to make inferences from functional MRI, electroencephalography and magnetoencephalography data. Graph theory is a branch of mathematics that focuses on the formal modelling of networks and offers a wide range of theoretical tools to quantify specific features of network architecture (topology) that can provide information complementing the anatomical localization of areas responding to given stimuli or tasks (topography). Explicit modelling of the architecture of axonal connections and interactions among areas can furthermore reveal peculiar topological properties that are conserved across diverse biological networks, and highly sensitive to disease states. The field is evolving rapidly, partly fuelled by computational developments that enable the study of connectivity at fine anatomical detail and the simultaneous interactions among multiple regions. Recent publications in this area have shown that graph-based modelling can enhance our ability to draw causal inferences from functional MRI experiments, and support the early detection of disconnection and the modelling of pathology spread in neurodegenerative disease, particularly Alzheimer's disease. Furthermore, neurophysiological studies have shown that network topology has a profound link to epileptogenesis and that connectivity indices derived from graph models aid in modelling the onset and spread of seizures. Graph-based analyses may therefore significantly help understand the bases of a range of neurological conditions. This review is designed to provide an overview of graph-based analyses of brain connectivity and their relevance to disease aimed principally at general neuroscientists and clinicians.

Characterizing Attention with Predictive Network Models.

PubMed

Rosenberg, M D; Finn, E S; Scheinost, D; Constable, R T; Chun, M M

2017-04-01

Recent work shows that models based on functional connectivity in large-scale brain networks can predict individuals' attentional abilities. While being some of the first generalizable neuromarkers of cognitive function, these models also inform our basic understanding of attention, providing empirical evidence that: (i) attention is a network property of brain computation; (ii) the functional architecture that underlies attention can be measured while people are not engaged in any explicit task; and (iii) this architecture supports a general attentional ability that is common to several laboratory-based tasks and is impaired in attention deficit hyperactivity disorder (ADHD). Looking ahead, connectivity-based predictive models of attention and other cognitive abilities and behaviors may potentially improve the assessment, diagnosis, and treatment of clinical dysfunction. Copyright © 2017 Elsevier Ltd. All rights reserved.

Electronic implementation of associative memory based on neural network models

NASA Technical Reports Server (NTRS)

Moopenn, A.; Lambe, John; Thakoor, A. P.

1987-01-01

An electronic embodiment of a neural network based associative memory in the form of a binary connection matrix is described. The nature of false memory errors, their effect on the information storage capacity of binary connection matrix memories, and a novel technique to eliminate such errors with the help of asymmetrical extra connections are discussed. The stability of the matrix memory system incorporating a unique local inhibition scheme is analyzed in terms of local minimization of an energy function. The memory's stability, dynamic behavior, and recall capability are investigated using a 32-'neuron' electronic neural network memory with a 1024-programmable binary connection matrix.

A new class of methods for functional connectivity estimation

NASA Astrophysics Data System (ADS)

Lin, Wutu

Measuring functional connectivity from neural recordings is important in understanding processing in cortical networks. The covariance-based methods are the current golden standard for functional connectivity estimation. However, the link between the pair-wise correlations and the physiological connections inside the neural network is unclear. Therefore, the power of inferring physiological basis from functional connectivity estimation is limited. To build a stronger tie and better understand the relationship between functional connectivity and physiological neural network, we need (1) a realistic model to simulate different types of neural recordings with known ground truth for benchmarking; (2) a new functional connectivity method that produce estimations closely reflecting the physiological basis. In this thesis, (1) I tune a spiking neural network model to match with human sleep EEG data, (2) introduce a new class of methods for estimating connectivity from different kinds of neural signals and provide theory proof for its superiority, (3) apply it to simulated fMRI data as an application.

[Seedling index of Salvia miltiorrhiza and its simulation model].

PubMed

Huang, Shu-Hua; Xu, Fu-Li; Wang, Wei-Ling; Du, Jun-Bo; Ru, Mei; Wang, Jing; Cao, Xian-Yan

2012-10-01

Through the correlation analysis on the quantitative traits and their ratios of Salvia miltiorrhiza seedlings and seedling quality, a series of representative indices reflecting the seedling quality of the plant species were determined, and the seedling index suitable to the S. miltiorrhiza seedlings was ascertained by correlation degree analysis. Meanwhile, based on the relationships between the seedling index and the air temperature, solar radiation and air humidity, a simulation model for the seedling index of S. miltiorrhiza was established. The experimental data of different test plots and planting dates were used to validate the model. The results showed that the root diameter, stem diameter, crown dry mass, root dry mass, and plant dry mass had significant positive relationships with the other traits, and could be used as the indicators of the seedling's health. The seedling index of S. miltiorrhiza could be calculated by (stem diameter/root diameter + root dry mass/crown dry mass) x plant dry mass. The stem diameter, root dry mass, crown dry mass and plant dry mass had higher correlations with the seedling index, and thus, the seedling index determined by these indicators could better reflect the seedling's quality. The coefficient of determination (R2) between the predicted and measured values based on 1:1 line was 0.95, and the root mean squared error (RMSE) was 0.15, indicating that the model established in this study could precisely reflect the quantitative relationships between the seedling index of S. miltiorrhiza and the environmental factors.

Examining speed versus selection in connectivity models using elk migration as an example

USGS Publications Warehouse

Brennan, Angela; Hanks, Ephraim M.; Merkle, Jerod A.; Cole, Eric K.; Dewey, Sarah R.; Courtemanch, Alyson B.; Cross, Paul C.

2018-01-01

ContextLandscape resistance is vital to connectivity modeling and frequently derived from resource selection functions (RSFs). RSFs estimate relative probability of use and tend to focus on understanding habitat preferences during slow, routine animal movements (e.g., foraging). Dispersal and migration, however, can produce rarer, faster movements, in which case models of movement speed rather than resource selection may be more realistic for identifying habitats that facilitate connectivity.ObjectiveTo compare two connectivity modeling approaches applied to resistance estimated from models of movement rate and resource selection.MethodsUsing movement data from migrating elk, we evaluated continuous time Markov chain (CTMC) and movement-based RSF models (i.e., step selection functions [SSFs]). We applied circuit theory and shortest random path (SRP) algorithms to CTMC, SSF and null (i.e., flat) resistance surfaces to predict corridors between elk seasonal ranges. We evaluated prediction accuracy by comparing model predictions to empirical elk movements.ResultsAll connectivity models predicted elk movements well, but models applied to CTMC resistance were more accurate than models applied to SSF and null resistance. Circuit theory models were more accurate on average than SRP models.ConclusionsCTMC can be more realistic than SSFs for estimating resistance for fast movements, though SSFs may demonstrate some predictive ability when animals also move slowly through corridors (e.g., stopover use during migration). High null model accuracy suggests seasonal range data may also be critical for predicting direct migration routes. For animals that migrate or disperse across large landscapes, we recommend incorporating CTMC into the connectivity modeling toolkit.

Database and new models based on a group contribution method to predict the refractive index of ionic liquids.

PubMed

Wang, Xinxin; Lu, Xingmei; Zhou, Qing; Zhao, Yongsheng; Li, Xiaoqian; Zhang, Suojiang

2017-08-02

Refractive index is one of the important physical properties, which is widely used in separation and purification. In this study, the refractive index data of ILs were collected to establish a comprehensive database, which included about 2138 pieces of data from 1996 to 2014. The Group Contribution-Artificial Neural Network (GC-ANN) model and Group Contribution (GC) method were employed to predict the refractive index of ILs at different temperatures from 283.15 K to 368.15 K. Average absolute relative deviations (AARD) of the GC-ANN model and the GC method were 0.179% and 0.628%, respectively. The results showed that a GC-ANN model provided an effective way to estimate the refractive index of ILs, whereas the GC method was simple and extensive. In summary, both of the models were accurate and efficient approaches for estimating refractive indices of ILs.

Complex Network Simulation of Forest Network Spatial Pattern in Pearl River Delta

NASA Astrophysics Data System (ADS)

Zeng, Y.

2017-09-01

Forest network-construction uses for the method and model with the scale-free features of complex network theory based on random graph theory and dynamic network nodes which show a power-law distribution phenomenon. The model is suitable for ecological disturbance by larger ecological landscape Pearl River Delta consistent recovery. Remote sensing and GIS spatial data are available through the latest forest patches. A standard scale-free network node distribution model calculates the area of forest network's power-law distribution parameter value size; The recent existing forest polygons which are defined as nodes can compute the network nodes decaying index value of the network's degree distribution. The parameters of forest network are picked up then make a spatial transition to GIS real world models. Hence the connection is automatically generated by minimizing the ecological corridor by the least cost rule between the near nodes. Based on scale-free network node distribution requirements, select the number compared with less, a huge point of aggregation as a future forest planning network's main node, and put them with the existing node sequence comparison. By this theory, the forest ecological projects in the past avoid being fragmented, scattered disorderly phenomena. The previous regular forest networks can be reduced the required forest planting costs by this method. For ecological restoration of tropical and subtropical in south China areas, it will provide an effective method for the forest entering city project guidance and demonstration with other ecological networks (water, climate network, etc.) for networking a standard and base datum.

Your perspective and my benefit: multiple lesion models of self-other integration strategies during social bargaining.

PubMed

Melloni, Margherita; Billeke, Pablo; Baez, Sandra; Hesse, Eugenia; de la Fuente, Laura; Forno, Gonzalo; Birba, Agustina; García-Cordero, Indira; Serrano, Cecilia; Plastino, Angelo; Slachevsky, Andrea; Huepe, David; Sigman, Mariano; Manes, Facundo; García, Adolfo M; Sedeño, Lucas; Ibáñez, Agustín

2016-11-01

Recursive social decision-making requires the use of flexible, context-sensitive long-term strategies for negotiation. To succeed in social bargaining, participants' own perspectives must be dynamically integrated with those of interactors to maximize self-benefits and adapt to the other's preferences, respectively. This is a prerequisite to develop a successful long-term self-other integration strategy. While such form of strategic interaction is critical to social decision-making, little is known about its neurocognitive correlates. To bridge this gap, we analysed social bargaining behaviour in relation to its structural neural correlates, ongoing brain dynamics (oscillations and related source space), and functional connectivity signatures in healthy subjects and patients offering contrastive lesion models of neurodegeneration and focal stroke: behavioural variant frontotemporal dementia, Alzheimer's disease, and frontal lesions. All groups showed preserved basic bargaining indexes. However, impaired self-other integration strategy was found in patients with behavioural variant frontotemporal dementia and frontal lesions, suggesting that social bargaining critically depends on the integrity of prefrontal regions. Also, associations between behavioural performance and data from voxel-based morphometry and voxel-based lesion-symptom mapping revealed a critical role of prefrontal regions in value integration and strategic decisions for self-other integration strategy. Furthermore, as shown by measures of brain dynamics and related sources during the task, the self-other integration strategy was predicted by brain anticipatory activity (alpha/beta oscillations with sources in frontotemporal regions) associated with expectations about others' decisions. This pattern was reduced in all clinical groups, with greater impairments in behavioural variant frontotemporal dementia and frontal lesions than Alzheimer's disease. Finally, connectivity analysis from functional magnetic resonance imaging evidenced a fronto-temporo-parietal network involved in successful self-other integration strategy, with selective compromise of long-distance connections in frontal disorders. In sum, this work provides unprecedented evidence of convergent behavioural and neurocognitive signatures of strategic social bargaining in different lesion models. Our findings offer new insights into the critical roles of prefrontal hubs and associated temporo-parietal networks for strategic social negotiation. © The Author (2016). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

A fractal growth model: Exploring the connection pattern of hubs in complex networks

NASA Astrophysics Data System (ADS)

Li, Dongyan; Wang, Xingyuan; Huang, Penghe

2017-04-01

Fractal is ubiquitous in many real-world networks. Previous researches showed that the strong disassortativity between the hub-nodes on all length scales was the key principle that gave rise to the fractal architecture of networks. Although fractal property emerged in some models, there were few researches about the fractal growth model and quantitative analyses about the strength of the disassortativity for fractal model. In this paper, we proposed a novel inverse renormalization method, named Box-based Preferential Attachment (BPA), to build the fractal growth models in which the Preferential Attachment was performed at box level. The proposed models provided a new framework that demonstrated small-world-fractal transition. Also, we firstly demonstrated the statistical characteristic of connection patterns of the hubs in fractal networks. The experimental results showed that, given proper growing scale and added edges, the proposed models could clearly show pure small-world or pure fractal or both of them. It also showed that the hub connection ratio showed normal distribution in many real-world networks. At last, the comparisons of connection pattern between the proposed models and the biological and technical networks were performed. The results gave useful reference for exploring the growth principle and for modeling the connection patterns for real-world networks.

Distributed parameter modeling to prevent charge cancellation for discrete thickness piezoelectric energy harvester

NASA Astrophysics Data System (ADS)

Krishnasamy, M.; Qian, Feng; Zuo, Lei; Lenka, T. R.

2018-03-01

The charge cancellation due to the change of strain along single continuous piezoelectric layer can remarkably affect the performance of a cantilever based harvester. In this paper, analytical models using distributed parameters are developed with some extent of averting the charge cancellation in cantilever piezoelectric transducer where the piezoelectric layers are segmented at strain nodes of concerned vibration mode. The electrode of piezoelectric segments are parallelly connected with a single external resistive load in the 1st model (Model 1). While each bimorph piezoelectric layers are connected in parallel to a resistor to form an independent circuit in the 2nd model (Model 2). The analytical expressions of the closed-form electromechanical coupling responses in frequency domain under harmonic base excitation are derived based on the Euler-Bernoulli beam assumption for both models. The developed analytical models are validated by COMSOL and experimental results. The results demonstrate that the energy harvesting performance of the developed segmented piezoelectric layer models is better than the traditional model of continuous piezoelectric layer.

Hydrologic connectivity of geographically isolated wetlands to surface water systems

NASA Astrophysics Data System (ADS)

Creed, I. F.; Ameli, A.

2016-12-01

Hydrologic connectivity of wetlands is poorly characterized and understood. Our inability to quantify this connectivity compromises our understanding of the potential impacts of land use (e.g., wetland drainage) and climate changes on watershed structure, function and water supplies. We develop a computationally efficient physically-based subsurface-surface hydrological model to map both the subsurface and surface hydrologic connectivity of geographically isolated wetlands (i.e., wetlands without surface outlets) and explore the time and length variations in these connections to a river within the Prairie Pothole Region of North America. Despite a high density of geographically isolated wetlands, modeled connections show that these wetlands are not hydrologically isolated. Hydrologic subsurface connectivity differs significantly from surface connectivity in terms of timing and length of connections. Slow subsurface connections between wetlands and the downstream river originate from wetlands throughout the watershed, whereas fast surface connections were limited to large events and originate from wetlands located near the river. Results also suggest that prioritization of protection of wetlands that relies on shortest distance of wetland to the river or surface connections alone can lead to unintended consequences in terms of loss of attending wetland ecosystem functions, services and their benefits to society. This modeling approach provides first ever insight on the nature of geographically isolated wetland subsurface and surface hydrological connections to rivers, and can provide guidance on the development of watershed management and conservation plans (e.g., wetlands drainage/restoration) under different climate and land management scenarios.

The risk of misclassifying subjects within principal component based asset index

PubMed Central

2014-01-01

The asset index is often used as a measure of socioeconomic status in empirical research as an explanatory variable or to control confounding. Principal component analysis (PCA) is frequently used to create the asset index. We conducted a simulation study to explore how accurately the principal component based asset index reflects the study subjects’ actual poverty level, when the actual poverty level is generated by a simple factor analytic model. In the simulation study using the PC-based asset index, only 1% to 4% of subjects preserved their real position in a quintile scale of assets; between 44% to 82% of subjects were misclassified into the wrong asset quintile. If the PC-based asset index explained less than 30% of the total variance in the component variables, then we consistently observed more than 50% misclassification across quintiles of the index. The frequency of misclassification suggests that the PC-based asset index may not provide a valid measure of poverty level and should be used cautiously as a measure of socioeconomic status. PMID:24987446

Meta-modeling of the pesticide fate model MACRO for groundwater exposure assessments using artificial neural networks

NASA Astrophysics Data System (ADS)

Stenemo, Fredrik; Lindahl, Anna M. L.; Gärdenäs, Annemieke; Jarvis, Nicholas

2007-08-01

Several simple index methods that use easily accessible data have been developed and included in decision-support systems to estimate pesticide leaching across larger areas. However, these methods often lack important process descriptions (e.g. macropore flow), which brings into question their reliability. Descriptions of macropore flow have been included in simulation models, but these are too complex and demanding for spatial applications. To resolve this dilemma, a neural network simulation meta-model of the dual-permeability macropore flow model MACRO was created for pesticide groundwater exposure assessment. The model was parameterized using pedotransfer functions that require as input the clay and sand content of the topsoil and subsoil, and the topsoil organic carbon content. The meta-model also requires the topsoil pesticide half-life and the soil organic carbon sorption coefficient as input. A fully connected feed-forward multilayer perceptron classification network with two hidden layers, linked to fully connected feed-forward multilayer perceptron neural networks with one hidden layer, trained on sub-sets of the target variable, was shown to be a suitable meta-model for the intended purpose. A Fourier amplitude sensitivity test showed that the model output (the 80th percentile average yearly pesticide concentration at 1 m depth for a 20 year simulation period) was sensitive to all input parameters. The two input parameters related to pesticide characteristics (i.e. soil organic carbon sorption coefficient and topsoil pesticide half-life) were the most influential, but texture in the topsoil was also quite important since it was assumed to control the mass exchange coefficient that regulates the strength of macropore flow. This is in contrast to models based on the advection-dispersion equation where soil texture is relatively unimportant. The use of the meta-model is exemplified with a case-study where the spatial variability of pesticide leaching is mapped for a small field. It was shown that the area of the field that contributes most to leaching depends on the properties of the compound in question. It is concluded that the simulation meta-model of MACRO should prove useful for mapping relative pesticide leaching risks at large scales.

Kirchhoff Index of Cyclopolyacenes

NASA Astrophysics Data System (ADS)

Wang, Yan; Zhang, Wenwen

2010-10-01

The resistance distance between two vertices of a connected graph G is computed as the effective resistance between them in the corresponding network constructed from G by replacing each edge with a unit resistor. The Kirchhoff index of G is the sum of resistance distances between all pairs of vertices. In this paper, following the method of Y. J. Yang and H. P. Zhang in the proof of the Kirchhoff index of the linear hexagonal chain, we obtain the Kirchhoff index of cyclopolyacenes, denoted by HRn, in terms of its Laplacian spectrum. We show that the Kirchhoff index of HRnis approximately one third of its Wiener index.

A Multi Criteria Group Decision-Making Model for Teacher Evaluation in Higher Education Based on Cloud Model and Decision Tree

ERIC Educational Resources Information Center

Chang, Ting-Cheng; Wang, Hui

2016-01-01

This paper proposes a cloud multi-criteria group decision-making model for teacher evaluation in higher education which is involving subjectivity, imprecision and fuzziness. First, selecting the appropriate evaluation index depending on the evaluation objectives, indicating a clear structural relationship between the evaluation index and…