An incremental DPMM-based method for trajectory clustering, modeling, and retrieval.
Hu, Weiming; Li, Xi; Tian, Guodong; Maybank, Stephen; Zhang, Zhongfei
2013-05-01
Trajectory analysis is the basis for many applications, such as indexing of motion events in videos, activity recognition, and surveillance. In this paper, the Dirichlet process mixture model (DPMM) is applied to trajectory clustering, modeling, and retrieval. We propose an incremental version of a DPMM-based clustering algorithm and apply it to cluster trajectories. An appropriate number of trajectory clusters is determined automatically. When trajectories belonging to new clusters arrive, the new clusters can be identified online and added to the model without any retraining using the previous data. A time-sensitive Dirichlet process mixture model (tDPMM) is applied to each trajectory cluster for learning the trajectory pattern which represents the time-series characteristics of the trajectories in the cluster. Then, a parameterized index is constructed for each cluster. A novel likelihood estimation algorithm for the tDPMM is proposed, and a trajectory-based video retrieval model is developed. The tDPMM-based probabilistic matching method and the DPMM-based model growing method are combined to make the retrieval model scalable and adaptable. Experimental comparisons with state-of-the-art algorithms demonstrate the effectiveness of our algorithm.
Going beyond Clustering in MD Trajectory Analysis: An Application to Villin Headpiece Folding
Rajan, Aruna; Freddolino, Peter L.; Schulten, Klaus
2010-01-01
Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous. PMID:20419160
Going beyond clustering in MD trajectory analysis: an application to villin headpiece folding.
Rajan, Aruna; Freddolino, Peter L; Schulten, Klaus
2010-04-15
Recent advances in computing technology have enabled microsecond long all-atom molecular dynamics (MD) simulations of biological systems. Methods that can distill the salient features of such large trajectories are now urgently needed. Conventional clustering methods used to analyze MD trajectories suffer from various setbacks, namely (i) they are not data driven, (ii) they are unstable to noise and changes in cut-off parameters such as cluster radius and cluster number, and (iii) they do not reduce the dimensionality of the trajectories, and hence are unsuitable for finding collective coordinates. We advocate the application of principal component analysis (PCA) and a non-metric multidimensional scaling (nMDS) method to reduce MD trajectories and overcome the drawbacks of clustering. To illustrate the superiority of nMDS over other methods in reducing data and reproducing salient features, we analyze three complete villin headpiece folding trajectories. Our analysis suggests that the folding process of the villin headpiece is structurally heterogeneous.
A Dimensionality Reduction-Based Multi-Step Clustering Method for Robust Vessel Trajectory Analysis
Liu, Jingxian; Wu, Kefeng
2017-01-01
The Shipboard Automatic Identification System (AIS) is crucial for navigation safety and maritime surveillance, data mining and pattern analysis of AIS information have attracted considerable attention in terms of both basic research and practical applications. Clustering of spatio-temporal AIS trajectories can be used to identify abnormal patterns and mine customary route data for transportation safety. Thus, the capacities of navigation safety and maritime traffic monitoring could be enhanced correspondingly. However, trajectory clustering is often sensitive to undesirable outliers and is essentially more complex compared with traditional point clustering. To overcome this limitation, a multi-step trajectory clustering method is proposed in this paper for robust AIS trajectory clustering. In particular, the Dynamic Time Warping (DTW), a similarity measurement method, is introduced in the first step to measure the distances between different trajectories. The calculated distances, inversely proportional to the similarities, constitute a distance matrix in the second step. Furthermore, as a widely-used dimensional reduction method, Principal Component Analysis (PCA) is exploited to decompose the obtained distance matrix. In particular, the top k principal components with above 95% accumulative contribution rate are extracted by PCA, and the number of the centers k is chosen. The k centers are found by the improved center automatically selection algorithm. In the last step, the improved center clustering algorithm with k clusters is implemented on the distance matrix to achieve the final AIS trajectory clustering results. In order to improve the accuracy of the proposed multi-step clustering algorithm, an automatic algorithm for choosing the k clusters is developed according to the similarity distance. Numerous experiments on realistic AIS trajectory datasets in the bridge area waterway and Mississippi River have been implemented to compare our proposed method with traditional spectral clustering and fast affinity propagation clustering. Experimental results have illustrated its superior performance in terms of quantitative and qualitative evaluations. PMID:28777353
Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F; Perez, Danny
2017-10-21
Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.
NASA Astrophysics Data System (ADS)
Huang, Rao; Lo, Li-Ta; Wen, Yuhua; Voter, Arthur F.; Perez, Danny
2017-10-01
Modern molecular-dynamics-based techniques are extremely powerful to investigate the dynamical evolution of materials. With the increase in sophistication of the simulation techniques and the ubiquity of massively parallel computing platforms, atomistic simulations now generate very large amounts of data, which have to be carefully analyzed in order to reveal key features of the underlying trajectories, including the nature and characteristics of the relevant reaction pathways. We show that clustering algorithms, such as the Perron Cluster Cluster Analysis, can provide reduced representations that greatly facilitate the interpretation of complex trajectories. To illustrate this point, clustering tools are used to identify the key kinetic steps in complex accelerated molecular dynamics trajectories exhibiting shape fluctuations in Pt nanoclusters. This analysis provides an easily interpretable coarse representation of the reaction pathways in terms of a handful of clusters, in contrast to the raw trajectory that contains thousands of unique states and tens of thousands of transitions.
Identification of PM10 air pollution origins at a rural background site
NASA Astrophysics Data System (ADS)
Reizer, Magdalena; Orza, José A. G.
2018-01-01
Trajectory cluster analysis and concentration weighted trajectory (CWT) approach have been applied to investigate the origins of PM10 air pollution recorded at a rural background site in North-eastern Poland (Diabla Góra). Air mass back-trajectories used in this study have been computed with the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model for a 10-year period of 2006-2015. A cluster analysis grouped back-trajectories into 7 clusters. Most of the trajectories correspond to fast and moderately moving westerly and northerly flows (45% and 25% of the cases, respectively). However, significantly higher PM10 concentrations were observed for slow moving easterly (11%) and southerly (20%) air masses. The CWT analysis shows that high PM10 levels are observed at Diabla Góra site when air masses are originated and passed over the heavily industrialized areas in Central-Eastern Europe located to the south and south-east of the site.
NASA Astrophysics Data System (ADS)
Solorzano, N. N.; Hafner, W.; Jaffe, D.
2005-12-01
We calculated daily kinematic back-trajectories using the NOAA-HYSPLIT model to analyze 7 years of PM2.5 data from National Park sites in the Western U.S. (Glacier N.P., Mount Rainier N.P., Sequoia N.P., Rocky Mountain N.P. and Denali N.P.) The back-trajectories were clustered using a k-means clustering algorithm to segregate the trajectories into 6 main transport patterns. We calculated trajectory clusters for 1, 5 and 10 days to represent short, medium and long-range flow patterns. Some trajectory types and clusters show marked seasonality. Generally faster flow patterns are more prevalent in winter and slower/stagnant patterns are more prevalent in summer. In addition, we found significant inter-annual variability that may be important for explaining variations in rainfall and/or pollutant concentrations. The 5 and 10-day analyses revealed that, for the 4 non-Alaskan sites, trajectories from Asia tend to be less frequent in the summer, compared to the rest of the year. The clusters of different duration show very different predictive power for rainfall and PM2.5. We found that the 1-day clusters are a better predictor for precipitation and PM2.5 concentrations, as compared to the 5 and 10-day clusters. At each of the sites, there is at least one cluster with an average PM2.5 concentration that is different than the average for the site, indicating distinctive transport patterns. The same is true for 5 and 10-day clusters. Interestingly, only one site, Mount Rainier N.P., shows seasonal differences in PM2.5 concentrations between the clusters that differ from the average.
Mixed Pattern Matching-Based Traffic Abnormal Behavior Recognition
Cui, Zhiming; Zhao, Pengpeng
2014-01-01
A motion trajectory is an intuitive representation form in time-space domain for a micromotion behavior of moving target. Trajectory analysis is an important approach to recognize abnormal behaviors of moving targets. Against the complexity of vehicle trajectories, this paper first proposed a trajectory pattern learning method based on dynamic time warping (DTW) and spectral clustering. It introduced the DTW distance to measure the distances between vehicle trajectories and determined the number of clusters automatically by a spectral clustering algorithm based on the distance matrix. Then, it clusters sample data points into different clusters. After the spatial patterns and direction patterns learned from the clusters, a recognition method for detecting vehicle abnormal behaviors based on mixed pattern matching was proposed. The experimental results show that the proposed technical scheme can recognize main types of traffic abnormal behaviors effectively and has good robustness. The real-world application verified its feasibility and the validity. PMID:24605045
Analysis of Tropical Cyclone Tracks in the North Indian Ocean
NASA Astrophysics Data System (ADS)
Patwardhan, A.; Paliwal, M.; Mohapatra, M.
2011-12-01
Cyclones are regarded as one of the most dangerous meteorological phenomena of the tropical region. The probability of landfall of a tropical cyclone depends on its movement (trajectory). Analysis of trajectories of tropical cyclones could be useful for identifying potentially predictable characteristics. There is long history of analysis of tropical cyclones tracks. A common approach is using different clustering techniques to group the cyclone tracks on the basis of certain characteristics. Various clustering method have been used to study the tropical cyclones in different ocean basins like western North Pacific ocean (Elsner and Liu, 2003; Camargo et al., 2007), North Atlantic Ocean (Elsner, 2003; Gaffney et al. 2007; Nakamura et al., 2009). In this study, tropical cyclone tracks in the North Indian Ocean basin, for the period 1961-2010 have been analyzed and grouped into clusters based on their spatial characteristics. A tropical cyclone trajectory is approximated as an open curve and described by its first two moments. The resulting clusters have different centroid locations and also differently shaped variance ellipses. These track characteristics are then used in the standard clustering algorithms which allow the whole track shape, length, and location to be incorporated into the clustering methodology. The resulting clusters have different genesis locations and trajectory shapes. We have also examined characteristics such as life span, maximum sustained wind speed, landfall, seasonality, many of which are significantly different across the identified clusters. The clustering approach groups cyclones with higher maximum wind speed and longest life span in to one cluster. Another cluster includes short duration cyclonic events that are mostly deep depressions and significant for rainfall over Eastern and Central India. The clustering approach is likely to prove useful for analysis of events of significance with regard to impacts.
Symptom Cluster Trajectories During Chemotherapy in Breast Cancer Outpatients.
Hsu, Hsin-Tien; Lin, Kuan-Chia; Wu, Li-Min; Juan, Chiung-Hui; Hou, Ming-Feng; Hwang, Shiow-Li; Liu, Yi; Dodd, Marylin J
2017-06-01
Breast cancer patients often experience multiple symptoms and substantial discomfort. Some symptoms may occur simultaneously and throughout the duration of chemotherapy treatment. The aim of this study was to investigate symptom severity and symptom cluster trajectories during chemotherapy in outpatients with breast cancer in Taiwan. This prospective, longitudinal, repeated measures study administered a standardized questionnaire (M. D. Anderson Symptom Inventory Taiwan version) to 103 breast cancer patients during each day of the third 21-day cycle of chemotherapy. Latent class growth analysis was performed to examine symptom cluster trajectories. Three symptom clusters were identified within the first 14 days of the 21-day chemotherapy cycle: the neurocognition cluster (pain, shortness of breath, vomiting, memory problems, and numbness/tingling) with a trajectory of Y = 2.09 - 0.11 (days), the emotion-nausea cluster (nausea, disturbed sleep, distress/upset, drowsiness, and sadness) with a trajectory ofY = 3.57 - 0.20 (days), and the fatigue-anorexia cluster (fatigue, lack of appetite, and dry mouth) with a trajectory of Y = 4.22 - 0.21 (days). The "fatigue-anorexia cluster" and "emotion-nausea cluster" peaked at moderate levels on chemotherapy days 3-5, and then gradually decreased to mild levels within the first 14 days of the 21-day chemotherapy cycle. Distinct symptom clusters were observed during the third cycle of chemotherapy. Systematic and ongoing evaluation of symptom cluster trajectories during cancer treatment is essential. Healthcare providers can use these findings to enhance communication with their breast cancer patients and to prioritize symptoms that require attention and intervention. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
Dynamic Trajectory Extraction from Stereo Vision Using Fuzzy Clustering
NASA Astrophysics Data System (ADS)
Onishi, Masaki; Yoda, Ikushi
In recent years, many human tracking researches have been proposed in order to analyze human dynamic trajectory. These researches are general technology applicable to various fields, such as customer purchase analysis in a shopping environment and safety control in a (railroad) crossing. In this paper, we present a new approach for tracking human positions by stereo image. We use the framework of two-stepped clustering with k-means method and fuzzy clustering to detect human regions. In the initial clustering, k-means method makes middle clusters from objective features extracted by stereo vision at high speed. In the last clustering, c-means fuzzy method cluster middle clusters based on attributes into human regions. Our proposed method can be correctly clustered by expressing ambiguity using fuzzy clustering, even when many people are close to each other. The validity of our technique was evaluated with the experiment of trajectories extraction of doctors and nurses in an emergency room of a hospital.
Zhang, Jingjing; Dennis, Todd E.
2015-01-01
We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known ‘artificial behaviours’ comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified. PMID:25922935
Zhang, Jingjing; O'Reilly, Kathleen M; Perry, George L W; Taylor, Graeme A; Dennis, Todd E
2015-01-01
We present a simple framework for classifying mutually exclusive behavioural states within the geospatial lifelines of animals. This method involves use of three sequentially applied statistical procedures: (1) behavioural change point analysis to partition movement trajectories into discrete bouts of same-state behaviours, based on abrupt changes in the spatio-temporal autocorrelation structure of movement parameters; (2) hierarchical multivariate cluster analysis to determine the number of different behavioural states; and (3) k-means clustering to classify inferred bouts of same-state location observations into behavioural modes. We demonstrate application of the method by analysing synthetic trajectories of known 'artificial behaviours' comprised of different correlated random walks, as well as real foraging trajectories of little penguins (Eudyptula minor) obtained by global-positioning-system telemetry. Our results show that the modelling procedure correctly classified 92.5% of all individual location observations in the synthetic trajectories, demonstrating reasonable ability to successfully discriminate behavioural modes. Most individual little penguins were found to exhibit three unique behavioural states (resting, commuting/active searching, area-restricted foraging), with variation in the timing and locations of observations apparently related to ambient light, bathymetry, and proximity to coastlines and river mouths. Addition of k-means clustering extends the utility of behavioural change point analysis, by providing a simple means through which the behaviours inferred for the location observations comprising individual movement trajectories can be objectively classified.
Cluster Analysis of Atmospheric Dynamics and Pollution Transport in a Coastal Area
NASA Astrophysics Data System (ADS)
Sokolov, Anton; Dmitriev, Egor; Maksimovich, Elena; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmentin, Marc; Locoge, Nadine
2016-11-01
Summertime atmospheric dynamics in the coastal zone of the industrialized Dunkerque agglomeration in northern France was characterized by a cluster analysis of back trajectories in the context of pollution transport. The MESO-NH atmospheric model was used to simulate the local dynamics at multiple scales with horizontal resolution down to 500 m, and for the online calculation of the Lagrangian backward trajectories with 30-min temporal resolution. Airmass transport was performed along six principal pathways obtained by the weighted k-means clustering technique. Four of these centroids corresponded to a range of wind speeds over the English Channel: two for wind directions from the north-east and two from the south-west. Another pathway corresponded to a south-westerly continental transport. The backward trajectories of the largest and most dispersed sixth cluster contained low wind speeds, including sea-breeze circulations. Based on analyses of meteorological data and pollution measurements, the principal atmospheric pathways were related to local air-contamination events. Continuous air quality and meteorological data were collected during the Benzene-Toluene-Ethylbenzene-Xylene 2006 campaign. The sites of the pollution measurements served as the endpoints for the backward trajectories. Pollutant transport pathways corresponding to the highest air contamination were defined.
Adaptive density trajectory cluster based on time and space distance
NASA Astrophysics Data System (ADS)
Liu, Fagui; Zhang, Zhijie
2017-10-01
There are some hotspot problems remaining in trajectory cluster for discovering mobile behavior regularity, such as the computation of distance between sub trajectories, the setting of parameter values in cluster algorithm and the uncertainty/boundary problem of data set. As a result, based on the time and space, this paper tries to define the calculation method of distance between sub trajectories. The significance of distance calculation for sub trajectories is to clearly reveal the differences in moving trajectories and to promote the accuracy of cluster algorithm. Besides, a novel adaptive density trajectory cluster algorithm is proposed, in which cluster radius is computed through using the density of data distribution. In addition, cluster centers and number are selected by a certain strategy automatically, and uncertainty/boundary problem of data set is solved by designed weighted rough c-means. Experimental results demonstrate that the proposed algorithm can perform the fuzzy trajectory cluster effectively on the basis of the time and space distance, and obtain the optimal cluster centers and rich cluster results information adaptably for excavating the features of mobile behavior in mobile and sociology network.
Chattopadhyay, Aditya; Zheng, Min; Waller, Mark Paul; Priyakumar, U Deva
2018-05-23
Knowledge of the structure and dynamics of biomolecules is essential for elucidating the underlying mechanisms of biological processes. Given the stochastic nature of many biological processes, like protein unfolding, it's almost impossible that two independent simulations will generate the exact same sequence of events, which makes direct analysis of simulations difficult. Statistical models like Markov Chains, transition networks etc. help in shedding some light on the mechanistic nature of such processes by predicting long-time dynamics of these systems from short simulations. However, such methods fall short in analyzing trajectories with partial or no temporal information, for example, replica exchange molecular dynamics or Monte Carlo simulations. In this work we propose a probabilistic algorithm, borrowing concepts from graph theory and machine learning, to extract reactive pathways from molecular trajectories in the absence of temporal data. A suitable vector representation was chosen to represent each frame in the macromolecular trajectory (as a series of interaction and conformational energies) and dimensionality reduction was performed using principal component analysis (PCA). The trajectory was then clustered using a density-based clustering algorithm, where each cluster represents a metastable state on the potential energy surface (PES) of the biomolecule under study. A graph was created with these clusters as nodes with the edges learnt using an iterative expectation maximization algorithm. The most reactive path is conceived as the widest path along this graph. We have tested our method on RNA hairpin unfolding trajectory in aqueous urea solution. Our method makes the understanding of the mechanism of unfolding in RNA hairpin molecule more tractable. As this method doesn't rely on temporal data it can be used to analyze trajectories from Monte Carlo sampling techniques and replica exchange molecular dynamics (REMD).
Chandramouli, Balasubramanian; Mancini, Giordano
2016-01-01
Classical Molecular Dynamics (MD) simulations can provide insights at the nanoscopic scale into protein dynamics. Currently, simulations of large proteins and complexes can be routinely carried out in the ns-μs time regime. Clustering of MD trajectories is often performed to identify selective conformations and to compare simulation and experimental data coming from different sources on closely related systems. However, clustering techniques are usually applied without a careful validation of results and benchmark studies involving the application of different algorithms to MD data often deal with relatively small peptides instead of average or large proteins; finally clustering is often applied as a means to analyze refined data and also as a way to simplify further analysis of trajectories. Herein, we propose a strategy to classify MD data while carefully benchmarking the performance of clustering algorithms and internal validation criteria for such methods. We demonstrate the method on two showcase systems with different features, and compare the classification of trajectories in real and PCA space. We posit that the prototype procedure adopted here could be highly fruitful in clustering large trajectories of multiple systems or that resulting especially from enhanced sampling techniques like replica exchange simulations. Copyright: © 2016 by Fabrizio Serra editore, Pisa · Roma.
Trajectories of acute low back pain: a latent class growth analysis.
Downie, Aron S; Hancock, Mark J; Rzewuska, Magdalena; Williams, Christopher M; Lin, Chung-Wei Christine; Maher, Christopher G
2016-01-01
Characterising the clinical course of back pain by mean pain scores over time may not adequately reflect the complexity of the clinical course of acute low back pain. We analysed pain scores over 12 weeks for 1585 patients with acute low back pain presenting to primary care to identify distinct pain trajectory groups and baseline patient characteristics associated with membership of each cluster. This was a secondary analysis of the PACE trial that evaluated paracetamol for acute low back pain. Latent class growth analysis determined a 5 cluster model, which comprised 567 (35.8%) patients who recovered by week 2 (cluster 1, rapid pain recovery); 543 (34.3%) patients who recovered by week 12 (cluster 2, pain recovery by week 12); 222 (14.0%) patients whose pain reduced but did not recover (cluster 3, incomplete pain recovery); 167 (10.5%) patients whose pain initially decreased but then increased by week 12 (cluster 4, fluctuating pain); and 86 (5.4%) patients who experienced high-level pain for the whole 12 weeks (cluster 5, persistent high pain). Patients with longer pain duration were more likely to experience delayed recovery or nonrecovery. Belief in greater risk of persistence was associated with nonrecovery, but not delayed recovery. Higher pain intensity, longer duration, and workers' compensation were associated with persistent high pain, whereas older age and increased number of episodes were associated with fluctuating pain. Identification of discrete pain trajectory groups offers the potential to better manage acute low back pain.
Six-month trajectories of self-reported depressive symptoms in long-term care.
McCusker, Jane; Cole, Martin G; Voyer, Philippe; Monette, Johanne; Champoux, Nathalie; Ciampi, Antonio; Vu, Minh; Belzile, Eric; Bai, Chun
2016-01-01
Depression is a common problem in long-term care (LTC) settings. We sought to characterize depression symptom trajectories over six months among older residents, and to identify resident characteristics at baseline that predict symptom trajectory. This study was a secondary analysis of data from a six-month prospective, observational, and multi-site study. Severity of depressive symptoms was assessed with the 15-item Geriatric Depression Scale (GDS) at baseline and with up to six monthly follow-up assessments. Participants were 130 residents with a Mini-Mental State Examination score of 15 or more at baseline and of at least two of the six monthly follow-up assessments. Individual resident GDS trajectories were grouped using hierarchical clustering. The baseline predictors of a more severe trajectory were identified using the Proportional Odds Model. Three clusters of depression symptom trajectory were found that described "lower," "intermediate," and "higher" levels of depressive symptoms over time (mean GDS scores for three clusters at baseline were 2.2, 4.9, and 9.0 respectively). The GDS scores in all groups were generally stable over time. Baseline predictors of a more severe trajectory were as follows: Initial GDS score of 7 or more, female sex, LTC residence for less than 12 months, and corrected visual impairment. The six-month course of depressive symptoms in LTC is generally stable. Most residents who experience a more severe symptom trajectory can be identified at baseline.
KmL3D: a non-parametric algorithm for clustering joint trajectories.
Genolini, C; Pingault, J B; Driss, T; Côté, S; Tremblay, R E; Vitaro, F; Arnaud, C; Falissard, B
2013-01-01
In cohort studies, variables are measured repeatedly and can be considered as trajectories. A classic way to work with trajectories is to cluster them in order to detect the existence of homogeneous patterns of evolution. Since cohort studies usually measure a large number of variables, it might be interesting to study the joint evolution of several variables (also called joint-variable trajectories). To date, the only way to cluster joint-trajectories is to cluster each trajectory independently, then to cross the partitions obtained. This approach is unsatisfactory because it does not take into account a possible co-evolution of variable-trajectories. KmL3D is an R package that implements a version of k-means dedicated to clustering joint-trajectories. It provides facilities for the management of missing values, offers several quality criteria and its graphic interface helps the user to select the best partition. KmL3D can work with any number of joint-variable trajectories. In the restricted case of two joint trajectories, it proposes 3D tools to visualize the partitioning and then export 3D dynamic rotating-graphs to PDF format. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
Network visualization of conformational sampling during molecular dynamics simulation.
Ahlstrom, Logan S; Baker, Joseph Lee; Ehrlich, Kent; Campbell, Zachary T; Patel, Sunita; Vorontsov, Ivan I; Tama, Florence; Miyashita, Osamu
2013-11-01
Effective data reduction methods are necessary for uncovering the inherent conformational relationships present in large molecular dynamics (MD) trajectories. Clustering algorithms provide a means to interpret the conformational sampling of molecules during simulation by grouping trajectory snapshots into a few subgroups, or clusters, but the relationships between the individual clusters may not be readily understood. Here we show that network analysis can be used to visualize the dominant conformational states explored during simulation as well as the connectivity between them, providing a more coherent description of conformational space than traditional clustering techniques alone. We compare the results of network visualization against 11 clustering algorithms and principal component conformer plots. Several MD simulations of proteins undergoing different conformational changes demonstrate the effectiveness of networks in reaching functional conclusions. Copyright © 2013 Elsevier Inc. All rights reserved.
Transition paths of Met-enkephalin from Markov state modeling of a molecular dynamics trajectory.
Banerjee, Rahul; Cukier, Robert I
2014-03-20
Conformational states and their interconversion pathways of the zwitterionic form of the pentapeptide Met-enkephalin (MetEnk) are identified. An explicit solvent molecular dynamics (MD) trajectory is used to construct a Markov state model (MSM) based on dihedral space clustering of the trajectory, and transition path theory (TPT) is applied to identify pathways between open and closed conformers. In the MD trajectory, only four of the eight backbone dihedrals exhibit bistable behavior. Defining a conformer as the string XXXX with X = "+" or "-" denoting, respectively, positive or negative values of a given dihedral angle and obtaining the populations of these conformers shows that only four conformers are highly populated, implying a strong correlation among these dihedrals. Clustering in dihedral space to construct the MSM finds the same four bistable dihedral angles. These state populations are very similar to those found directly from the MD trajectory. TPT is used to obtain pathways, parametrized by committor values, in dihedral state space that are followed in transitioning from closed to open states. Pathway costs are estimated by introducing a kinetics-based procedure that orders pathways from least (shortest) to greater cost paths. The least costly pathways in dihedral space are found to only involve the same XXXX set of dihedral angles, and the conformers accessed in the closed to open transition pathways are identified. For these major pathways, a correlation between reaction path progress (committors) and the end-to-end distance is identified. A dihedral space principal component analysis of the MD trajectory shows that the first three modes capture most of the overall fluctuation, and pick out the same four dihedrals having essentially all the weight in those modes. A MSM based on root-mean-square backbone clustering was also carried out, with good agreement found with dihedral clustering for the static information, but with results that differ significantly for the pathway analysis.
Dalhuisen, Lydia; Koenraadt, Frans; Liem, Marieke
2017-02-01
Prior research has classified firesetters by motive. The multi-trajectory theory of adult firesetting (M-TTAF) takes a more aetiological perspective, differentiating between five hypothesised trajectories towards firesetting: antisocial cognition, grievance, fire interest, emotionally expressive/need for recognition and multifaceted trajectories. The objective of this study was to validate the five routes to firesetting as proposed in the M-TTAF. All 389 adult firesetters referred for forensic mental health assessment to one central clinic in the Netherlands between 1950 and 2012 were rated on variables linked to the M-TTAF. Cluster analysis was then applied. A reliable cluster solution emerged revealing five subtypes of firesetters - labelled instrumental, reward, multi-problem, disturbed relationship and disordered. Significant differences were observed regarding both offender and offence characteristics. Our five-cluster solution with five subtypes of firesetters partially validates the proposed M-TTAF trajectories and suggests that for offenders with and without mental disorder, this classification may be useful. If further validated with larger and more diverse samples, the M-TTAF could provide guidance on staging evidence-based treatment. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moreno, Edmundo; Pichardo, Bárbara; Velázquez, Héctor
2014-10-01
We calculate orbits, tidal radii, and bulge-bar and disk shocking destruction rates for 63 globular clusters in our Galaxy. Orbits are integrated in both an axisymmetric and a nonaxisymmetric Galactic potential that includes a bar and a three-dimensional model for the spiral arms. With the use of a Monte Carlo scheme, we consider in our simulations observational uncertainties in the kinematical data of the clusters. In the analysis of destruction rates due to the bulge-bar, we consider the rigorous treatment of using the real Galactic cluster orbit instead of the usual linear trajectory employed in previous studies. We compare resultsmore » in both treatments. We find that the theoretical tidal radius computed in the nonaxisymmetric Galactic potential compares better with the observed tidal radius than that obtained in the axisymmetric potential. In both Galactic potentials, bulge-shocking destruction rates computed with a linear trajectory of a cluster at its perigalacticons give a good approximation of the result obtained with the real trajectory of the cluster. Bulge-shocking destruction rates for clusters with perigalacticons in the inner Galactic region are smaller in the nonaxisymmetric potential than those in the axisymmetric potential. For the majority of clusters with high orbital eccentricities (e > 0.5), their total bulge+disk destruction rates are smaller in the nonaxisymmetric potential.« less
Wolf, Antje; Kirschner, Karl N
2013-02-01
With improvements in computer speed and algorithm efficiency, MD simulations are sampling larger amounts of molecular and biomolecular conformations. Being able to qualitatively and quantitatively sift these conformations into meaningful groups is a difficult and important task, especially when considering the structure-activity paradigm. Here we present a study that combines two popular techniques, principal component (PC) analysis and clustering, for revealing major conformational changes that occur in molecular dynamics (MD) simulations. Specifically, we explored how clustering different PC subspaces effects the resulting clusters versus clustering the complete trajectory data. As a case example, we used the trajectory data from an explicitly solvated simulation of a bacteria's L11·23S ribosomal subdomain, which is a target of thiopeptide antibiotics. Clustering was performed, using K-means and average-linkage algorithms, on data involving the first two to the first five PC subspace dimensions. For the average-linkage algorithm we found that data-point membership, cluster shape, and cluster size depended on the selected PC subspace data. In contrast, K-means provided very consistent results regardless of the selected subspace. Since we present results on a single model system, generalization concerning the clustering of different PC subspaces of other molecular systems is currently premature. However, our hope is that this study illustrates a) the complexities in selecting the appropriate clustering algorithm, b) the complexities in interpreting and validating their results, and c) by combining PC analysis with subsequent clustering valuable dynamic and conformational information can be obtained.
NASA Astrophysics Data System (ADS)
Fawole, O. G.; Cai, X.; MacKenzie, A. R.
2015-12-01
Aerosol remote sensing techniques and back-trajectory modeling can be combined to identify aerosol types. We have clustered 7 years of AERONET aerosol signals using trajectory analysis to identify dominant aerosol sources at two AERONET sites in West Africa: Ilorin (4.34 oE, 8.32 oN) and Djougou (1.60 oE, 9.76 oN). Of particular interest are air masses that have passed through the gas flaring region in the Niger Delta area, of Nigeria, en-route the AERONET sites. 7-day back trajectories were calculated using the UK UGAMP trajectory model driven by ECMWF wind analyses data. Dominant sources identified, using literature classifications, are desert dust (DD), Biomass burning (BB) and Urban-Industrial (UI). Below, we use a combination of synoptic trajectories and aerosol optical properties to distinguish a fourth source: that due to gas flaring. Gas flaring, (GF) the disposal of gas through stack in an open-air flame, is believed to be a prominent source of black carbon (BC) and greenhouse gases. For these different aerosol source signatures, single scattering albedo (SSA), refractive index , extinction Angstrom exponent (EEA) and absorption Angstrom exponent (AAE) were used to classify the light absorption characteristics of the aerosols for λ = 440, 675, 870 and1020 nm. A total of 1625 daily averages of aerosol data were collected for the two sites. Of which 245 make up the GF cluster for both sites. For GF cluster, the range of fine-mode fraction is 0.4 - 0.7. Average values SSA(λ), for the total and GF clusters are 0.90(440), 0.93(675), 0.95(870) and 0.96(1020), and 0.93(440), 0.92(675), 0.9(870) and 0.9(1020), respectively. Values of for the GF clusters for both sites are 0.62 - 1.11, compared to 1.28 - 1.66 for the remainder of the clusters, which strongly indicates the dominance of carbonaceous particles (BC), typical of a highly industrial area. An average value of 1.58 for the real part of the refractive index at low SSA for aerosol in the GF cluster is also an indicator of high BC content. Extinction Angstrom exponent, is an indicator of the particle size. EAE values of 0.95-1.32 for aerosol in the GF cluster shows that the aerosols are mainly fine or accumulation mode while values of EAE (0.36-0.6) for the other cluster indicate coarse mode domination of the aerosol. See table 1 for a summary of result.
NASA Astrophysics Data System (ADS)
Kong, Xiangzhen; He, Wei; Qin, Ning; He, Qishuang; Yang, Bin; Ouyang, Huiling; Wang, Qingmei; Xu, Fuliu
2013-03-01
Trajectory cluster analysis, including the two-stage cluster method based on Euclidean metrics and the one-stage clustering method based on Mahalanobis metrics and self-organizing maps (SOM), was applied and compared to identify the transport pathways of PM10 for the cities of Chaohu and Hefei, both located near Lake Chaohu in China. The two-stage cluster method was modified to further investigate the long trajectories in the second stage in order to eliminate the observed disaggregation among them. Twelve trajectory clusters were identified for both cities. The one-stage clustering method based on Mahalanobis metrics gives the best performance regarding the variances within clusters. The results showed that local PM10 emission was one of the most important sources in both cities and that the local emission in Hefei was higher than in Chaohu. In addition, Chaohu suffered greater effects from the eastern region (Yangtze River Delta, YRD) than Hefei. On the other hand, the long-range transportation from the northwestern pathway had a higher influence on the PM10 level in Hefei. Receptor models, including potential source contribution function (PSCF) and residence time weighted concentrations (RTWC), were utilized to identify the potential source locations of PM10 for both cities. However, the combined PSCF and RTWC results for the two cities provided PM10 source locations that were more consistent with the results of transport pathways and the total anthropogenic PM10 emission inventory. This indicates that the combined method's ability to identify the source regions is superior to that of the individual PSCF or RTWC methods. Henan and Shanxi Provinces and the YRD were important PM10 source regions for the two cities, but the Henan and Shanxi area was more important for Hefei than for Chaohu, while the YRD region was less important. In addition, the PSCF, RTWC and the combined results all had higher correlation coefficients with PM10 emission from traffic than from industry, electricity generation or residential sources, suggesting the relatively higher contribution of traffic emissions to the PM10 pollution in Lake Chaohu.
NASA Astrophysics Data System (ADS)
Cannella, Marco; Sciuto, Salvatore Andrea
2001-04-01
An evaluation of errors for a method for determination of trajectories and velocities of supersonic objects is conducted. The analytical study of a cluster, composed of three pressure transducers and generally used as an apparatus for cinematic determination of parameters of supersonic objects, is developed. Furthermore, detailed investigation into the accuracy of this cluster on determination of the slope of an incoming shock wave is carried out for optimization of the device. In particular, a specific non-dimensional parameter is proposed in order to evaluate accuracies for various values of parameters and reference graphs are provided in order to properly design the sensor cluster. Finally, on the basis of the error analysis conducted, a discussion on the best estimation of the relative distance for the sensor as a function of temporal resolution of the measuring system is presented.
In vitro motility evaluation of aggregated cancer cells by means of automatic image processing.
De Hauwer, C; Darro, F; Camby, I; Kiss, R; Van Ham, P; Decaesteker, C
1999-05-01
Set up of an automatic image processing based method that enables the motility of in vitro aggregated cells to be evaluated for a number of hours. Our biological model included the PC-3 human prostate cancer cell line growing as a monolayer on the bottom of Falcon plastic dishes containing conventional culture media. Our equipment consisted of an incubator, an inverted phase contrast microscope, a Charge Coupled Device (CCD) video camera, and a computer equipped with an image processing software developed in our laboratory. This computer-assisted microscope analysis of aggregated cells enables global cluster motility to be evaluated. This analysis also enables the trajectory of each cell to be isolated and parametrized within a given cluster or, indeed, the trajectories of individual cells outside a cluster. The results show that motility inside a PC-3 cluster is not restricted to slight motion due to cluster expansion, but rather consists of a marked cell movement within the cluster. The proposed equipment enables in vitro aggregated cell motility to be studied. This method can, therefore, be used in pharmacological studies in order to select anti-motility related compounds. The compounds selected by the equipment described could then be tested in vivo as potential anti-metastatic.
ANALYSIS AND CHARACTERIZATION OF OZONE-RICH EPISODES IN NORTHEAST PORTUGAL
NASA Astrophysics Data System (ADS)
Carvalho, A.; Monteiro, A.; Ribeiro, I.; Tchepel, O.; Miranda, A.; Borrego, C.; Saavedra, S.; Souto, J. A.; Casares, J. J.
2009-12-01
Each summer period extremely high ozone levels are registered at the rural background station of Lamas d’Olo, located in the Northeast of Portugal. In average, 30% of the total alert threshold registered in Portugal is detected at this site. The main purpose of this study is to characterize the atmospheric conditions that lead to the ozone-rich episodes. Synoptic patterns anomalies and back trajectories cluster analysis were performed for a period of 76 days where ozone maximum concentrations were above 200 µg.m-3. This analysis was performed for the period between 2004 and 2007. The obtained anomaly fields suggested that a positive temperature anomaly is visible above the Iberian Peninsula. In addition, a strong wind flow pattern from NE is visible in the North of Portugal and Galicia, in Spain. These two features may lead to an enhancement of the photochemical production and to the transport of pollutants from Spain to Portugal. In addition, the 3D mean back trajectories associated to the ozone episode days were analysed. A clustering method has been applied to the obtained back trajectories. Four main clusters of ozone-rich episodes were identified, with different frequencies of occurrence: north-westerly flows (11%); north-easterly flows (45%), southern flow (4%) and westerly flows (40%). Both analyses highlight the NE flow as a dominant pattern over the North of Portugal. The analysis of the ozone concentrations for each selected cluster indicates that this northeast circulation pattern, together with the southern flow, is responsible for the highest ozone peak episodes. This also suggests that long-range transport of atmospheric pollutants may be the main contributor to the ozone levels registered at Lamas d’Olo. This is also highlighted by the correlation of the ozone time series with the meteorological parameters analysed in the frequency domain.
ERIC Educational Resources Information Center
Luo, Wen; Hughes, Jan N.; Liew, Jeffrey; Kwok, Oiman
2009-01-01
Based on a sample of 480 academically at-risk first graders, we used a cluster analysis involving multimethod assessment (i.e., teacher-report, peer-evaluation, and self-report) of behavioral and psychological engagement to identify subtypes of academic engagement. Four theoretically and practically meaningful clusters were identified and labeled…
Abramyan, Tigran M; Snyder, James A; Thyparambil, Aby A; Stuart, Steven J; Latour, Robert A
2016-08-05
Clustering methods have been widely used to group together similar conformational states from molecular simulations of biomolecules in solution. For applications such as the interaction of a protein with a surface, the orientation of the protein relative to the surface is also an important clustering parameter because of its potential effect on adsorbed-state bioactivity. This study presents cluster analysis methods that are specifically designed for systems where both molecular orientation and conformation are important, and the methods are demonstrated using test cases of adsorbed proteins for validation. Additionally, because cluster analysis can be a very subjective process, an objective procedure for identifying both the optimal number of clusters and the best clustering algorithm to be applied to analyze a given dataset is presented. The method is demonstrated for several agglomerative hierarchical clustering algorithms used in conjunction with three cluster validation techniques. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Firl, Daniel J; Hashimoto, Koji; O'Rourke, Colin; Diago-Uso, Teresa; Fujiki, Masato; Aucejo, Federico N; Quintini, Cristiano; Kelly, Dympna M; Miller, Charles M; Fung, John J; Eghtesad, Bijan
2016-11-01
Donation after circulatory death (DCD) donors show heterogeneous hemodynamic trajectories following withdrawal of life support. Impact of hemodynamics in DCD liver transplant is unclear, and objective measures of graft viability would ease transplant surgeon decision making and inform safe expansion of the donor organ pool. This retrospective study tested whether hemodynamic trajectories were associated with transplant outcomes in DCD liver transplantation (n = 87). Using longitudinal clustering statistical techniques, we phenotyped DCD donors based on hemodynamic trajectory for both mean arterial pressure (MAP) and peripheral oxygen saturation (SpO 2 ) following withdrawal of life support. Donors were categorized into 3 clusters: those who gradually decline after withdrawal of life support (cluster 1), those who maintain stable hemodynamics followed by rapid decline (cluster 2), and those who decline rapidly (cluster 3). Clustering outputs were used to compare characteristics and transplant outcomes. Cox proportional hazards modeling revealed hepatocellular carcinoma (hazard ratio [HR] = 2.53; P = 0.047), cold ischemia time (HR = 1.50 per hour; P = 0.027), and MAP cluster 1 were associated with increased risk of graft loss (HR = 3.13; P = 0.021), but not SpO 2 cluster (P = 0.172) or donor warm ischemia time (DWIT; P = 0.154). Despite longer DWIT, MAP and SpO 2 clusters 2 showed similar graft survival to MAP and SpO 2 clusters 3, respectively. In conclusion, despite heterogeneity in hemodynamic trajectories, DCD donors can be categorized into 3 clinically meaningful subgroups that help predict graft prognosis. Further studies should confirm the utility of liver grafts from cluster 2. Liver Transplantation 22 1469-1481 2016 AASLD. © 2016 by the American Association for the Study of Liver Diseases.
High ozone levels in the northeast of Portugal: Analysis and characterization
NASA Astrophysics Data System (ADS)
Carvalho, A.; Monteiro, A.; Ribeiro, I.; Tchepel, O.; Miranda, A. I.; Borrego, C.; Saavedra, S.; Souto, J. A.; Casares, J. J.
2010-03-01
Each summer period extremely high ozone levels are registered at the rural background station of Lamas d'Olo, located in the Northeast of Portugal. In average, 30% of the total alert threshold registered in Portugal is detected at this site. The main purpose of this study is to characterize the atmospheric conditions that lead to the ozone-rich episodes at this site. Synoptic patterns anomalies and back trajectories cluster analysis were performed, for the period between 2004 and 2007, considering 76 days when ozone maximum hourly concentrations were above 200 μg m -3. The obtained atmospheric anomaly fields suggested that a positive temperature anomaly is visible above the Iberian Peninsula. A strong wind flow pattern from NE is observable in the North of Portugal and Galicia, in Spain. These two features may lead to an enhancement of the photochemical production and to the transport of pollutants from Spain to Portugal. In addition, the 3D mean back trajectories associated to the ozone episode days were analysed. A clustering method has been applied to the obtained back trajectories. Four main clusters of ozone-rich episodes were identified, with different frequencies of occurrence: north-westerly flows (11%); north-easterly flows (45%), southern flow (4%) and westerly flows (40%). Both analyses highlight the NE flow as a dominant pattern over the North of Portugal during summer. The analysis of the ozone concentrations for each selected cluster indicates that this northeast circulation pattern, together with the southern flow, are responsible for the highest ozone peak episodes. This also suggests that long-range transport of atmospheric pollutants is the main contributor to the ozone levels registered at Lamas d'Olo. This is also highlighted by the correlation of the ozone time-series with the meteorological parameters analysed in the frequency domain.
Zufiria, Pedro J; Pastor-Escuredo, David; Úbeda-Medina, Luis; Hernandez-Medina, Miguel A; Barriales-Valbuena, Iker; Morales, Alfredo J; Jacques, Damien C; Nkwambi, Wilfred; Diop, M Bamba; Quinn, John; Hidalgo-Sanchís, Paula; Luengo-Oroz, Miguel
2018-01-01
We propose a framework for the systematic analysis of mobile phone data to identify relevant mobility profiles in a population. The proposed framework allows finding distinct human mobility profiles based on the digital trace of mobile phone users characterized by a Matrix of Individual Trajectories (IT-Matrix). This matrix gathers a consistent and regularized description of individual trajectories that enables multi-scale representations along time and space, which can be used to extract aggregated indicators such as a dynamic multi-scale population count. Unsupervised clustering of individual trajectories generates mobility profiles (clusters of similar individual trajectories) which characterize relevant group behaviors preserving optimal aggregation levels for detailed and privacy-secured mobility characterization. The application of the proposed framework is illustrated by analyzing fully anonymized data on human mobility from mobile phones in Senegal at the arrondissement level over a calendar year. The analysis of monthly mobility patterns at the livelihood zone resolution resulted in the discovery and characterization of seasonal mobility profiles related with economic activities, agricultural calendars and rainfalls. The use of these mobility profiles could support the timely identification of mobility changes in vulnerable populations in response to external shocks (such as natural disasters, civil conflicts or sudden increases of food prices) to monitor food security.
Papaleo, Elena; Mereghetti, Paolo; Fantucci, Piercarlo; Grandori, Rita; De Gioia, Luca
2009-01-01
Several molecular dynamics (MD) simulations were used to sample conformations in the neighborhood of the native structure of holo-myoglobin (holo-Mb), collecting trajectories spanning 0.22 micros at 300 K. Principal component (PCA) and free-energy landscape (FEL) analyses, integrated by cluster analysis, which was performed considering the position and structures of the individual helices of the globin fold, were carried out. The coherence between the different structural clusters and the basins of the FEL, together with the convergence of parameters derived by PCA indicates that an accurate description of the Mb conformational space around the native state was achieved by multiple MD trajectories spanning at least 0.14 micros. The integration of FEL, PCA, and structural clustering was shown to be a very useful approach to gain an overall view of the conformational landscape accessible to a protein and to identify representative protein substates. This method could be also used to investigate the conformational and dynamical properties of Mb apo-, mutant, or delete versions, in which greater conformational variability is expected and, therefore identification of representative substates from the simulations is relevant to disclose structure-function relationship.
NASA Astrophysics Data System (ADS)
Sokolov, Anton; Dmitriev, Egor; Delbarre, Hervé; Augustin, Patrick; Gengembre, Cyril; Fourmenten, Marc
2016-04-01
The problem of atmospheric contamination by principal air pollutants was considered in the industrialized coastal region of English Channel in Dunkirk influenced by north European metropolitan areas. MESO-NH nested models were used for the simulation of the local atmospheric dynamics and the online calculation of Lagrangian backward trajectories with 15-minute temporal resolution and the horizontal resolution down to 500 m. The one-month mesoscale numerical simulation was coupled with local pollution measurements of volatile organic components, particulate matter, ozone, sulphur dioxide and nitrogen oxides. Principal atmospheric pathways were determined by clustering technique applied to backward trajectories simulated. Six clusters were obtained which describe local atmospheric dynamics, four winds blowing through the English Channel, one coming from the south, and the biggest cluster with small wind speeds. This last cluster includes mostly sea breeze events. The analysis of meteorological data and pollution measurements allows relating the principal atmospheric pathways with local air contamination events. It was shown that contamination events are mostly connected with a channelling of pollution from local sources and low-turbulent states of the local atmosphere.
Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps
2011-01-01
Background Molecular dynamics (MD) simulations are powerful tools to investigate the conformational dynamics of proteins that is often a critical element of their function. Identification of functionally relevant conformations is generally done clustering the large ensemble of structures that are generated. Recently, Self-Organising Maps (SOMs) were reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data mining problems. We present a novel strategy to analyse and compare conformational ensembles of protein domains using a two-level approach that combines SOMs and hierarchical clustering. Results The conformational dynamics of the α-spectrin SH3 protein domain and six single mutants were analysed by MD simulations. The Cα's Cartesian coordinates of conformations sampled in the essential space were used as input data vectors for SOM training, then complete linkage clustering was performed on the SOM prototype vectors. A specific protocol to optimize a SOM for structural ensembles was proposed: the optimal SOM was selected by means of a Taguchi experimental design plan applied to different data sets, and the optimal sampling rate of the MD trajectory was selected. The proposed two-level approach was applied to single trajectories of the SH3 domain independently as well as to groups of them at the same time. The results demonstrated the potential of this approach in the analysis of large ensembles of molecular structures: the possibility of producing a topological mapping of the conformational space in a simple 2D visualisation, as well as of effectively highlighting differences in the conformational dynamics directly related to biological functions. Conclusions The use of a two-level approach combining SOMs and hierarchical clustering for conformational analysis of structural ensembles of proteins was proposed. It can easily be extended to other study cases and to conformational ensembles from other sources. PMID:21569575
Clustering Multivariate Time Series Using Hidden Markov Models
Ghassempour, Shima; Girosi, Federico; Maeder, Anthony
2014-01-01
In this paper we describe an algorithm for clustering multivariate time series with variables taking both categorical and continuous values. Time series of this type are frequent in health care, where they represent the health trajectories of individuals. The problem is challenging because categorical variables make it difficult to define a meaningful distance between trajectories. We propose an approach based on Hidden Markov Models (HMMs), where we first map each trajectory into an HMM, then define a suitable distance between HMMs and finally proceed to cluster the HMMs with a method based on a distance matrix. We test our approach on a simulated, but realistic, data set of 1,255 trajectories of individuals of age 45 and over, on a synthetic validation set with known clustering structure, and on a smaller set of 268 trajectories extracted from the longitudinal Health and Retirement Survey. The proposed method can be implemented quite simply using standard packages in R and Matlab and may be a good candidate for solving the difficult problem of clustering multivariate time series with categorical variables using tools that do not require advanced statistic knowledge, and therefore are accessible to a wide range of researchers. PMID:24662996
Wu, Jiun-yu; Hughes, Jan N.; Kwok, Oi-man
2010-01-01
Teacher, peer, and student reports of the quality of the teacher-student relationship were obtained for an ethnically diverse and academically at-risk sample of 706 second and third grade students. Cluster analysis identified four types of relationships based on the consistency of child reports of support and conflict in the relationship with reports of others: Congruent positive, Congruent Negative, Incongruent Child Negative and Incongruent Child Positive. The cluster solution evidenced good internal consistency and construct validity. Cluster membership predicted growth trajectories for teacher-rated engagement and standardized achievement scores over the following three years, above prior performance. The predictive associations between child reports of teacher support and conflict and outcomes depended on whether child reports were consistent or inconsistent with reports of others. Study findings have implications for theory development, assessment of teacher-student relationships, and teacher professional development. PMID:20728688
Contribution of long-range transport to the ozone levels recorded in the Northeast of Portugal
NASA Astrophysics Data System (ADS)
Gama, C.; Nunes, T.; Marques, M. C.; Ferreira, F.
2009-04-01
In the past four years (2004-2007), measurements carried out at Lamas de Olo, the only air quality monitoring background station in the Northeast of Portugal, showed high ozone concentrations (97,7±29,7 g.m-3). This remote site, located in the middle of Alvão Natural Park, in Portugal, 1086 m asl, plays a significant role on the total amount of exceedances registered in the national air quality network. The analysis of the data recorded at this monitoring station revealed an annual cycle of ozone concentrations similar to the ones observed in other background sites of the Northern Hemisphere (Monks, 2000; Vingarzan and Taylor, 2003). This common feature comprises a distinct maximum during spring (peaking during the month of April). Nevertheless it is during the summer that the hourly concentrations are higher, due to the typical atmospheric and meteorological conditions that promote photochemical pollution episodes. Photochemical pollution episodes can be related with production of ozone in a local scale or in a global scale due to the transportation of polluted air masses. For this reason analysing these events is crucial to fully understand the behaviour of ozone in the Northeast of Portugal, in order to adopt the correct long-term policies. With the purpose of studying the influence of long-range transport on the ozone levels recorded at Lamas de Olo, a cluster analysis was performed on 96-hour back trajectories air masses. Different trajectory clusters represent air masses with different source regions of atmospheric pollutants and the influence of these regions on the atmospheric composition at the arrival point (receptor) of the trajectories can therefore be assessed (EMPA, 2008). The back trajectories were simulated 4 times per day, using HYSPLIT model. A "bottom-up" cluster methodology was used to group trajectories into clusters according to their characteristics, for several time periods with similar ozone levels and/or distributions. Ozone average levels were calculated for each cluster and the differences between the groups were validated using the Kruskal-Wallis statistical test. The results have shown a significant influence of the transport path on ozone concentrations, which is more noticeable when the probability of occurring photochemical pollution phenomena is higher. Air masses from Europe (Spain, France, United Kingdom, etc.) generally originate higher ozone levels than the ones arriving from the Atlantic Ocean. This feature shows the role of photochemical production along long-range transport phenomena, and the input of pollutants into air masses, along their path. A more detailed analysis at local/regional scale, supported mainly by an intensive field campaign performed during spring/summer of 2006 in the vicinity of Alvão Natural Park (FOTONET Project), at different altitudes, together with pollutant measurements from rural air quality stations in the north of Portugal and one from Spain (Peñausende) was carried out in order to evaluate the extension of photochemical pollution in the Northeast of Portugal. Ozone concentrations measurements in the region showed a noticeable decrease with altitude, mainly at night. In resume back trajectories based analysis has demonstrated that other countries, mainly Spain, contribute decisively to the ozone levels registered in the station used for this study. Backed on this knowledge we point out towards the need of considering common international policies when dealing with controlling ozone levels in the environment. References: Monks, P. (2000): A review of the observations and origins of the spring ozone maximum. Atmospheric Environment 34, 3545-3561. Vingarzan, R., Taylor, B. (2003): Trend analysis of ground level ozone in the greater Vancouver / Fraser Valley area of British Columbia. Atmospheric Environment 37, 2159-2171. EMPA (2008): Air mass trajectory clustering. Retrieved 01 November 2008 from: http://www.empa.ch/plugin/template/empa/*/63288/—/l=1
Luo, Ze; Baoping, Yan; Takekawa, John Y.; Prosser, Diann J.
2012-01-01
We propose a new method to help ornithologists and ecologists discover shared segments on the migratory pathway of the bar-headed geese by time-based plane-sweeping trajectory clustering. We present a density-based time parameterized line segment clustering algorithm, which extends traditional comparable clustering algorithms from temporal and spatial dimensions. We present a time-based plane-sweeping trajectory clustering algorithm to reveal the dynamic evolution of spatial-temporal object clusters and discover common motion patterns of bar-headed geese in the process of migration. Experiments are performed on GPS-based satellite telemetry data from bar-headed geese and results demonstrate our algorithms can correctly discover shared segments of the bar-headed geese migratory pathway. We also present findings on the migratory behavior of bar-headed geese determined from this new analytical approach.
Clustering molecular dynamics trajectories for optimizing docking experiments.
De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D; Norberto de Souza, Osmar; Barros, Rodrigo C
2015-01-01
Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand.
Trajectories of delinquency and parenting styles.
Hoeve, Machteld; Blokland, Arjan; Dubas, Judith Semon; Loeber, Rolf; Gerris, Jan R M; van der Laan, Peter H
2008-02-01
We investigated trajectories of adolescent delinquent development using data from the Pittsburgh Youth Study and examined the extent to which these different trajectories are differentially predicted by childhood parenting styles. Based on self-reported and official delinquency seriousness, covering ages 10-19, we identified five distinct delinquency trajectories differing in both level and change in seriousness over time: a nondelinquent, minor persisting, moderate desisting, serious persisting, and serious desisting trajectory. More serious delinquents tended to more frequently engage in delinquency, and to report a higher proportion of theft. Proportionally, serious persistent delinquents were the most violent of all trajectory groups. Using cluster analysis we identified three parenting styles: authoritative, authoritarian (moderately supportive), and neglectful (punishing). Controlling for demographic characteristics and childhood delinquency, neglectful parenting was more frequent in moderate desisters, serious persisters, and serious desisters, suggesting that parenting styles differentiate non- or minor delinquents from more serious delinquents.
Trajectories of Delinquency and Parenting Styles
Blokland, Arjan; Dubas, Judith Semon; Loeber, Rolf; Gerris, Jan R. M.; van der Laan, Peter H.
2007-01-01
We investigated trajectories of adolescent delinquent development using data from the Pittsburgh Youth Study and examined the extent to which these different trajectories are differentially predicted by childhood parenting styles. Based on self-reported and official delinquency seriousness, covering ages 10–19, we identified five distinct delinquency trajectories differing in both level and change in seriousness over time: a nondelinquent, minor persisting, moderate desisting, serious persisting, and serious desisting trajectory. More serious delinquents tended to more frequently engage in delinquency, and to report a higher proportion of theft. Proportionally, serious persistent delinquents were the most violent of all trajectory groups. Using cluster analysis we identified three parenting styles: authoritative, authoritarian (moderately supportive), and neglectful (punishing). Controlling for demographic characteristics and childhood delinquency, neglectful parenting was more frequent in moderate desisters, serious persisters, and serious desisters, suggesting that parenting styles differentiate non- or minor delinquents from more serious delinquents. PMID:17786548
Principles and Algorithms for Natural and Engineered Systems
2014-12-16
Toolbox for MATLAB into C/C++. The target for the calibration is a 2D black and white checkerboard pattern. In a typical set of calibration images...errors the dynamic clusters typically contain entangled trajectories i.e. links form between two different dynamic clusters (see Figures 8 and 9). To...all dynamic clusters is L, and the average number of trajectories a given dynamic cluster are entangled with for its entire length is known as the
Milestoning with coarse memory
NASA Astrophysics Data System (ADS)
Hawk, Alexander T.
2013-04-01
Milestoning is a method used to calculate the kinetics of molecular processes occurring on timescales inaccessible to traditional molecular dynamics (MD) simulations. In the method, the phase space of the system is partitioned by milestones (hypersurfaces), trajectories are initialized on each milestone, and short MD simulations are performed to calculate transitions between neighboring milestones. Long trajectories of the system are then reconstructed with a semi-Markov process from the observed statistics of transition. The procedure is typically justified by the assumption that trajectories lose memory between crossing successive milestones. Here we present Milestoning with Coarse Memory (MCM), a generalization of Milestoning that relaxes the memory loss assumption of conventional Milestoning. In the method, milestones are defined and sample transitions are calculated in the standard Milestoning way. Then, after it is clear where trajectories sample milestones, the milestones are broken up into distinct neighborhoods (clusters), and each sample transition is associated with two clusters: the cluster containing the coordinates the trajectory was initialized in, and the cluster (on the terminal milestone) containing trajectory's final coordinates. Long trajectories of the system are then reconstructed with a semi-Markov process in an extended state space built from milestone and cluster indices. To test the method, we apply it to a process that is particularly ill suited for Milestoning: the dynamics of a polymer confined to a narrow cylinder. We show that Milestoning calculations of both the mean first passage time and the mean transit time of reversal—which occurs when the end-to-end vector reverses direction—are significantly improved when MCM is applied. Finally, we note the overhead of performing MCM on top of conventional Milestoning is negligible.
NASA Astrophysics Data System (ADS)
Hernández-Ceballos, M. A.; García-Mozo, H.; Galán, C.
2015-08-01
The impact of regional and local weather and of local topography on intradiurnal variations in airborne pollen levels was assessed by analysing bi-hourly holm oak ( Quercus ilex subsp. ballota (Desf.) Samp.) pollen counts at two sampling stations located 40 km apart, in southwestern Spain (Cordoba city and El Cabril nature reserve) over the period 2010-2011. Pollen grains were captured using Hirst-type volumetric spore traps. Analysis of regional weather conditions was based on the computation of backward trajectories using the HYSPLIT model. Sampling days were selected on the basis of phenological data; rainy days were eliminated, as were days lying outside a given range of percentiles (P95-P5). Analysis of cycles for the study period, as a whole, revealed differences between sampling sites, with peak bi-hourly pollen counts at night in Cordoba and at midday in El Cabril. Differences were also noted in the influence of surface weather conditions (temperature, relative humidity and wind). Cluster analysis of diurnal holm oak pollen cycles revealed the existence of five clusters at each sampling site. Analysis of backward trajectories highlighted specific regional air-flow patterns associated with each site. Findings indicated the contribution of both nearby and distant pollen sources to diurnal cycles. The combined use of cluster analysis and meteorological analysis proved highly suitable for charting the impact of local weather conditions on airborne pollen-count patterns. This method, and the specific tools used here, could be used not only to study diurnal variations in counts for other pollen types and in other biogeographical settings, but also in a number of other research fields involving airborne particle transport modelling, e.g. radionuclide transport in emergency preparedness exercises.
Hernández-Ceballos, M A; García-Mozo, H; Galán, C
2015-08-01
The impact of regional and local weather and of local topography on intradiurnal variations in airborne pollen levels was assessed by analysing bi-hourly holm oak (Quercus ilex subsp. ballota (Desf.) Samp.) pollen counts at two sampling stations located 40 km apart, in southwestern Spain (Cordoba city and El Cabril nature reserve) over the period 2010-2011. Pollen grains were captured using Hirst-type volumetric spore traps. Analysis of regional weather conditions was based on the computation of backward trajectories using the HYSPLIT model. Sampling days were selected on the basis of phenological data; rainy days were eliminated, as were days lying outside a given range of percentiles (P95-P5). Analysis of cycles for the study period, as a whole, revealed differences between sampling sites, with peak bi-hourly pollen counts at night in Cordoba and at midday in El Cabril. Differences were also noted in the influence of surface weather conditions (temperature, relative humidity and wind). Cluster analysis of diurnal holm oak pollen cycles revealed the existence of five clusters at each sampling site. Analysis of backward trajectories highlighted specific regional air-flow patterns associated with each site. Findings indicated the contribution of both nearby and distant pollen sources to diurnal cycles. The combined use of cluster analysis and meteorological analysis proved highly suitable for charting the impact of local weather conditions on airborne pollen-count patterns. This method, and the specific tools used here, could be used not only to study diurnal variations in counts for other pollen types and in other biogeographical settings, but also in a number of other research fields involving airborne particle transport modelling, e.g. radionuclide transport in emergency preparedness exercises.
Clustering Molecular Dynamics Trajectories for Optimizing Docking Experiments
De Paris, Renata; Quevedo, Christian V.; Ruiz, Duncan D.; Norberto de Souza, Osmar; Barros, Rodrigo C.
2015-01-01
Molecular dynamics simulations of protein receptors have become an attractive tool for rational drug discovery. However, the high computational cost of employing molecular dynamics trajectories in virtual screening of large repositories threats the feasibility of this task. Computational intelligence techniques have been applied in this context, with the ultimate goal of reducing the overall computational cost so the task can become feasible. Particularly, clustering algorithms have been widely used as a means to reduce the dimensionality of molecular dynamics trajectories. In this paper, we develop a novel methodology for clustering entire trajectories using structural features from the substrate-binding cavity of the receptor in order to optimize docking experiments on a cloud-based environment. The resulting partition was selected based on three clustering validity criteria, and it was further validated by analyzing the interactions between 20 ligands and a fully flexible receptor (FFR) model containing a 20 ns molecular dynamics simulation trajectory. Our proposed methodology shows that taking into account features of the substrate-binding cavity as input for the k-means algorithm is a promising technique for accurately selecting ensembles of representative structures tailored to a specific ligand. PMID:25873944
Global, Multi-Objective Trajectory Optimization With Parametric Spreading
NASA Technical Reports Server (NTRS)
Vavrina, Matthew A.; Englander, Jacob A.; Phillips, Sean M.; Hughes, Kyle M.
2017-01-01
Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.
Brief Report: Clusters and Trajectories Across the Autism and/or ADHD Spectrum.
LaBianca, S; Pagsberg, A K; Jakobsen, K D; Demur, A B; Bartalan, M; LaBianca, J; Werge, T
2018-06-07
Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) frequently co-occur and show high genetic correlation. With the introduction of DSM-5, there is a new concept of an ASD and/or ADHD spectrum (ASD/ADHD). This study aimed to identify predictors of severity and need of healthcare within this spectrum. 39 families with multiple individuals affected by ASD/ADHD were recruited from a psychiatric clinic. Diagnoses, functional and demographic characteristics were retrieved from journals while hospital admissions were identified in the Danish health register. An estimated fraction of 31% ASD/ADHD patients had never been hospitalized and 35% remained undiagnosed despite hospitalization. Cluster analysis identified trajectories that discriminate age of diagnosis, educational attainment to degree of severity, need of hospitalization and genetic risk.
NASA Astrophysics Data System (ADS)
Jensen, Christian H.; Nerukh, Dmitry; Glen, Robert C.
2008-03-01
We investigate the sensitivity of a Markov model with states and transition probabilities obtained from clustering a molecular dynamics trajectory. We have examined a 500ns molecular dynamics trajectory of the peptide valine-proline-alanine-leucine in explicit water. The sensitivity is quantified by varying the boundaries of the clusters and investigating the resulting variation in transition probabilities and the average transition time between states. In this way, we represent the effect of clustering using different clustering algorithms. It is found that in terms of the investigated quantities, the peptide dynamics described by the Markov model is sensitive to the clustering; in particular, the average transition times are found to vary up to 46%. Moreover, inclusion of nonphysical sparsely populated clusters can lead to serious errors of up to 814%. In the investigation, the time step used in the transition matrix is determined by the minimum time scale on which the system behaves approximately Markovian. This time step is found to be about 100ps. It is concluded that the description of peptide dynamics with transition matrices should be performed with care, and that using standard clustering algorithms to obtain states and transition probabilities may not always produce reliable results.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rintoul, Mark Daniel; Wilson, Andrew T.; Valicka, Christopher G.
We want to organize a body of trajectories in order to identify, search for, classify and predict behavior among objects such as aircraft and ships. Existing compari- son functions such as the Fr'echet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as total distance traveled and distance be- tween start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally, these features can generallymore » be mapped easily to behaviors of interest to humans that are searching large databases. Most of these geometric features are invariant under rigid transformation. We demonstrate the use of different subsets of these features to iden- tify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories, predict destination and apply unsupervised machine learning algorithms.« less
Trajectory analysis via a geometric feature space approach
DOE Office of Scientific and Technical Information (OSTI.GOV)
Rintoul, Mark D.; Wilson, Andrew T.
This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less
Trajectory analysis via a geometric feature space approach
Rintoul, Mark D.; Wilson, Andrew T.
2015-10-05
This study aimed to organize a body of trajectories in order to identify, search for and classify both common and uncommon behaviors among objects such as aircraft and ships. Existing comparison functions such as the Fréchet distance are computationally expensive and yield counterintuitive results in some cases. We propose an approach using feature vectors whose components represent succinctly the salient information in trajectories. These features incorporate basic information such as the total distance traveled and the distance between start/stop points as well as geometric features related to the properties of the convex hull, trajectory curvature and general distance geometry. Additionally,more » these features can generally be mapped easily to behaviors of interest to humans who are searching large databases. Most of these geometric features are invariant under rigid transformation. Furthermore, we demonstrate the use of different subsets of these features to identify trajectories similar to an exemplar, cluster a database of several hundred thousand trajectories and identify outliers.« less
Mapping concentrations of posttraumatic stress and depression trajectories following Hurricane Ike
Gruebner, Oliver; Lowe, Sarah R.; Tracy, Melissa; Joshi, Spruha; Cerdá, Magdalena; Norris, Fran H.; Subramanian, S. V.; Galea, Sandro
2016-01-01
We investigated geographic concentration in elevated risk for a range of postdisaster trajectories of chronic posttraumatic stress symptom (PTSS) and depression symptoms in a longitudinal study (N = 561) of a Hurricane Ike affected population in Galveston and Chambers counties, TX. Using an unadjusted spatial scan statistic, we detected clusters of elevated risk of PTSS trajectories, but not depression trajectories, on Galveston Island. We then tested for predictors of membership in each trajectory of PTSS and depression (e.g., demographic variables, trauma exposure, social support), not taking the geographic nature of the data into account. After adjusting for significant predictors in the spatial scan statistic, we noted that spatial clusters of PTSS persisted and additional clusters of depression trajectories emerged. This is the first study to show that longitudinal trajectories of postdisaster mental health problems may vary depending on the geographic location and the individual- and community-level factors present at these locations. Such knowledge is crucial to identifying vulnerable regions and populations within them, to provide guidance for early responders, and to mitigate mental health consequences through early detection of mental health needs in the population. As human-made disasters increase, our approach may be useful also in other regions in comparable settings worldwide. PMID:27558011
Mapping concentrations of posttraumatic stress and depression trajectories following Hurricane Ike.
Gruebner, Oliver; Lowe, Sarah R; Tracy, Melissa; Joshi, Spruha; Cerdá, Magdalena; Norris, Fran H; Subramanian, S V; Galea, Sandro
2016-08-25
We investigated geographic concentration in elevated risk for a range of postdisaster trajectories of chronic posttraumatic stress symptom (PTSS) and depression symptoms in a longitudinal study (N = 561) of a Hurricane Ike affected population in Galveston and Chambers counties, TX. Using an unadjusted spatial scan statistic, we detected clusters of elevated risk of PTSS trajectories, but not depression trajectories, on Galveston Island. We then tested for predictors of membership in each trajectory of PTSS and depression (e.g., demographic variables, trauma exposure, social support), not taking the geographic nature of the data into account. After adjusting for significant predictors in the spatial scan statistic, we noted that spatial clusters of PTSS persisted and additional clusters of depression trajectories emerged. This is the first study to show that longitudinal trajectories of postdisaster mental health problems may vary depending on the geographic location and the individual- and community-level factors present at these locations. Such knowledge is crucial to identifying vulnerable regions and populations within them, to provide guidance for early responders, and to mitigate mental health consequences through early detection of mental health needs in the population. As human-made disasters increase, our approach may be useful also in other regions in comparable settings worldwide.
Spatial-temporal travel pattern mining using massive taxi trajectory data
NASA Astrophysics Data System (ADS)
Zheng, Linjiang; Xia, Dong; Zhao, Xin; Tan, Longyou; Li, Hang; Chen, Li; Liu, Weining
2018-07-01
Deep understanding of residents' travel patterns would provide helpful insights into the mechanisms of many socioeconomic phenomena. With the rapid development of location-aware computing technologies, researchers have easy access to large quantities of travel data. As an important data source, taxi trajectory data are featured by their high quality, good continuity and wide distribution, making it suitable for travel pattern mining. In this paper, we use taxi trajectory data to study spatial-temporal characterization of urban residents' travel patterns from two aspects: attractive areas and hot paths. Firstly, a framework of trajectory preprocessing, including data cleaning and extracting the taxi passenger pick-up/drop-off points, is presented to reduce the noise and redundancy in raw trajectory data. Then, a grid density based clustering algorithm is proposed to discover travel attractive areas in different periods of a day. On this basis, we put forward a spatial-temporal trajectory clustering method to discover hot paths among travel attractive areas. Compared with previous algorithms, which only consider the spatial constraint between trajectories, temporal constraint is also considered in our method. Through the experiments, we discuss how to determine the optimal parameters of the two clustering algorithms and verify the effectiveness of the algorithms using real data. Furthermore, we analyze spatial-temporal characterization of Chongqing residents' travel pattern.
Statistical and clustering analysis for disturbances: A case study of voltage dips in wind farms
Garcia-Sanchez, Tania; Gomez-Lazaro, Emilio; Muljadi, Eduard; ...
2016-01-28
This study proposes and evaluates an alternative statistical methodology to analyze a large number of voltage dips. For a given voltage dip, a set of lengths is first identified to characterize the root mean square (rms) voltage evolution along the disturbance, deduced from partial linearized time intervals and trajectories. Principal component analysis and K-means clustering processes are then applied to identify rms-voltage patterns and propose a reduced number of representative rms-voltage profiles from the linearized trajectories. This reduced group of averaged rms-voltage profiles enables the representation of a large amount of disturbances, which offers a visual and graphical representation ofmore » their evolution along the events, aspects that were not previously considered in other contributions. The complete process is evaluated on real voltage dips collected in intense field-measurement campaigns carried out in a wind farm in Spain among different years. The results are included in this paper.« less
Trajectories of depressive symptoms among high risk African-American adolescents.
Repetto, Paula B; Caldwell, Cleopatra H; Zimmerman, Marc A
2004-12-01
To examine the trajectories of depressive symptoms among African-American youth and the psychosocial factors associated with these trajectories. The sample included 579 African-American adolescents who were at risk of dropping out of school, interviewed annually starting from ninth grade for 4 years. The measures included depressive symptoms, anxiety symptoms, self-esteem, stress, and active coping; all self-reported. We used cluster analysis to develop longitudinal trajectories of depression in our sample. Four different trajectories of depressive symptoms were found that represented the changes in depressive symptoms among the participants. These trajectories are: consistently high (15.9%), consistently low (21.1%), decreasing (41.8%), and increasing (21.2%) depressive symptoms. The results from the comparisons of the trajectories indicated that adolescents who presented consistently high levels of depressive symptoms were more likely to be female, reported more anxiety symptoms, lower self-esteem, higher stress, and lower grade point average (GPA) compared with adolescent members of the other trajectories. Depressive symptoms may be manifested in different ways according to the patterns of change. Different correlates are associated with these trajectories of depressive symptoms and provide insights about the antecedents and consequences of the patterns of change in depressive symptoms.
Hu, Weiming; Tian, Guodong; Kang, Yongxin; Yuan, Chunfeng; Maybank, Stephen
2017-09-25
In this paper, a new nonparametric Bayesian model called the dual sticky hierarchical Dirichlet process hidden Markov model (HDP-HMM) is proposed for mining activities from a collection of time series data such as trajectories. All the time series data are clustered. Each cluster of time series data, corresponding to a motion pattern, is modeled by an HMM. Our model postulates a set of HMMs that share a common set of states (topics in an analogy with topic models for document processing), but have unique transition distributions. For the application to motion trajectory modeling, topics correspond to motion activities. The learnt topics are clustered into atomic activities which are assigned predicates. We propose a Bayesian inference method to decompose a given trajectory into a sequence of atomic activities. On combining the learnt sources and sinks, semantic motion regions, and the learnt sequence of atomic activities, the action represented by the trajectory can be described in natural language in as automatic a way as possible. The effectiveness of our dual sticky HDP-HMM is validated on several trajectory datasets. The effectiveness of the natural language descriptions for motions is demonstrated on the vehicle trajectories extracted from a traffic scene.
Spatio-Temporal Characteristics of Resident Trip Based on Poi and OD Data of Float CAR in Beijing
NASA Astrophysics Data System (ADS)
Mou, N.; Li, J.; Zhang, L.; Liu, W.; Xu, Y.
2017-09-01
Due to the influence of the urban inherent regional functional distribution, the daily activities of the residents presented some spatio-temporal patterns (periodic patterns, gathering patterns, etc.). In order to further understand the spatial and temporal characteristics of urban residents, this paper research takes the taxi trajectory data of Beijing as a sample data and studies the spatio-temporal characteristics of the residents' activities on the weekdays. At first, according to the characteristics of the taxi trajectory data distributed along the road network, it takes the Voronoi generated by the road nodes as the research unit. This paper proposes a hybrid clustering method - based on grid density, which is used to cluster the OD (origin and destination) data of taxi at different times. Then combining with the POI data of Beijing, this research calculated the density of the POI data in the clustering results, and analyzed the relationship between the activities of residents in different periods and the functional types of the region. The final results showed that the residents were mainly commuting on weekdays. And it found that the distribution of travel density showed a concentric circle of the characteristics, focusing on residential areas and work areas. The results of cluster analysis and POI analysis showed that the residents' travel had experienced the process of "spatial relative dispersion - spatial aggregation - spatial relative dispersion" in one day.
Vanbinst, Kiran; Ceulemans, Eva; Peters, Lien; Ghesquière, Pol; De Smedt, Bert
2018-02-01
Although symbolic numerical magnitude processing skills are key for learning arithmetic, their developmental trajectories remain unknown. Therefore, we delineated during the first 3years of primary education (5-8years of age) groups with distinguishable developmental trajectories of symbolic numerical magnitude processing skills using a model-based clustering approach. Three clusters were identified and were labeled as inaccurate, accurate but slow, and accurate and fast. The clusters did not differ in age, sex, socioeconomic status, or IQ. We also tested whether these clusters differed in domain-specific (nonsymbolic magnitude processing and digit identification) and domain-general (visuospatial short-term memory, verbal working memory, and processing speed) cognitive competencies that might contribute to children's ability to (efficiently) process the numerical meaning of Arabic numerical symbols. We observed minor differences between clusters in these cognitive competencies except for verbal working memory for which no differences were observed. Follow-up analyses further revealed that the above-mentioned cognitive competencies did not merely account for the cluster differences in children's development of symbolic numerical magnitude processing skills, suggesting that other factors account for these individual differences. On the other hand, the three trajectories of symbolic numerical magnitude processing revealed remarkable and stable differences in children's arithmetic fact retrieval, which stresses the importance of symbolic numerical magnitude processing for learning arithmetic. Copyright © 2017 Elsevier Inc. All rights reserved.
Collie, A; Prang, K-H
2013-11-01
The rate and extent of recovery after severe traumatic brain injury (TBI) is heterogeneous making prediction of likely healthcare service utilisation (HSU) difficult. Patterns of HSU derived from nomothetic samples do not represent the diverse range of outcomes possible within this patient group. Group-based trajectory model is a semi-parametric statistical technique that seeks to identify clusters of individuals whose outcome (however measured) follows a similar pattern of change over time. To identify and characterise patterns of HSU in the 5-year period following severe TBI. Detailed healthcare treatment payments data in 316 adults with severe TBI (Glasgow Coma Scale score 3-8) from the transport accident compensation system in the state of Victoria, Australia was accessed for this analysis. A semi-parametric group-based trajectory analytical technique for longitudinal data was applied to monthly observation counts of HSU data to identify distinct clusters of participants' trajectories. Comparison between trajectory groups on demographic, injury, disability and compensation relevant outcomes was undertaken. Four distinct patterns (trajectories) of HSU were identified in the sample. The first trajectory group comprised 27% of participants and displayed a rapid decrease in HSU in the first year post-injury. The second group comprised 24% of participants and showed a sharp peak in HSU during the first 12 months post-injury followed by a decline over time. The third group comprised 32% of participants and showed a slight peak in HSU in the first few months post-injury and then a slow decline over time. The fourth group comprised 17% of participants and displayed a steady rise in HSU up to 30 months post-injury, followed by a gradual decline to a level consistent with that received in the first months post-injury. Significant differences were observed between groups on factors such as age, injury severity, and use of disability services. There is substantial variation in patterns of HSU following severe TBI. Idiographic analysis can provide rich information for describing and understanding the resources required to help people with TBI. Copyright © 2013 Elsevier Ltd. All rights reserved.
Trajectory Based Behavior Analysis for User Verification
NASA Astrophysics Data System (ADS)
Pao, Hsing-Kuo; Lin, Hong-Yi; Chen, Kuan-Ta; Fadlil, Junaidillah
Many of our activities on computer need a verification step for authorized access. The goal of verification is to tell apart the true account owner from intruders. We propose a general approach for user verification based on user trajectory inputs. The approach is labor-free for users and is likely to avoid the possible copy or simulation from other non-authorized users or even automatic programs like bots. Our study focuses on finding the hidden patterns embedded in the trajectories produced by account users. We employ a Markov chain model with Gaussian distribution in its transitions to describe the behavior in the trajectory. To distinguish between two trajectories, we propose a novel dissimilarity measure combined with a manifold learnt tuning for catching the pairwise relationship. Based on the pairwise relationship, we plug-in any effective classification or clustering methods for the detection of unauthorized access. The method can also be applied for the task of recognition, predicting the trajectory type without pre-defined identity. Given a trajectory input, the results show that the proposed method can accurately verify the user identity, or suggest whom owns the trajectory if the input identity is not provided.
Transport in the Subtropical Lowermost Stratosphere during CRYSTAL-FACE
NASA Technical Reports Server (NTRS)
Pittman, Jasna V.; Weinstock, elliot M.; Oglesby, Robert J.; Sayres, David S.; Smith, Jessica B.; Anderson, James G.; Cooper, Owen R.; Wofsy, Steven C.; Xueref, Irene; Gerbig, Cristoph;
2007-01-01
We use in situ measurements of water vapor (H2O), ozone (O3), carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), and total reactive nitrogen (NO(y)) obtained during the CRYSTAL-FACE campaign in July 2002 to study summertime transport in the subtropical lowermost stratosphere. We use an objective methodology to distinguish the latitudinal origin of the sampled air masses despite the influence of convection, and we calculate backward trajectories to elucidate their recent geographical history. The methodology consists of exploring the statistical behavior of the data by performing multivariate clustering and agglomerative hierarchical clustering calculations, and projecting cluster groups onto principal component space to identify air masses of like composition and hence presumed origin. The statistically derived cluster groups are then examined in physical space using tracer-tracer correlation plots. Interpretation of the principal component analysis suggests that the variability in the data is accounted for primarily by the mean age of air in the stratosphere, followed by the age of the convective influence, and lastly by the extent of convective influence, potentially related to the latitude of convective injection [Dessler and Sherwuud, 2004]. We find that high-latitude stratospheric air is the dominant source region during the beginning of the campaign while tropical air is the dominant source region during the rest of the campaign. Influence of convection from both local and non-local events is frequently observed. The identification of air mass origin is confirmed with backward trajectories, and the behavior of the trajectories is associated with the North American monsoon circulation.
NASA Technical Reports Server (NTRS)
Pittman, Jasna V.; Weinstock, Elliot M.; Oglesby, Robert J.; Sayres, David S.; Smith, Jessica B.; Anderson, James G.; Cooper, Owen R.; Wofsy, Steven C.; Xueref, Irene; Gerbig, Cristoph;
2007-01-01
We use in situ measurements of water vapor (H2O), ozone (O3), carbon dioxide (CO2), carbon monoxide (CO), nitric oxide (NO), and total reactive nitrogen (NOy) obtained during the CRYSTAL-FACE campaign in July 2002 to study summertime transport in the subtropical lowermost stratosphere. We use an objective methodology to distinguish the latitudinal origin of the sampled air masses despite the influence of convection, and we calculate backward trajectories to elucidate their recent geographical history. The methodology consists of exploring the statistical behavior of the data by performing multivariate clustering and agglomerative hierarchical clustering calculations and projecting cluster groups onto principal component space to identify air masses of like composition and hence presumed origin. The statistically derived cluster groups are then examined in physical space using tracer-tracer correlation plots. Interpretation of the principal component analysis suggests that the variability in the data is accounted for primarily by the mean age of air in the stratosphere, followed by the age of the convective influence, and last by the extent of convective influence, potentially related to the latitude of convective injection (Dessler and Sherwood, 2004). We find that high-latitude stratospheric air is the dominant source region during the beginning of the campaign while tropical air is the dominant source region during the rest of the campaign. Influence of convection from both local and nonlocal events is frequently observed. The identification of air mass origin is confirmed with backward trajectories, and the behavior of the trajectories is associated with the North American monsoon circulation.
Intersection Detection Based on Qualitative Spatial Reasoning on Stopping Point Clusters
NASA Astrophysics Data System (ADS)
Zourlidou, S.; Sester, M.
2016-06-01
The purpose of this research is to propose and test a method for detecting intersections by analysing collectively acquired trajectories of moving vehicles. Instead of solely relying on the geometric features of the trajectories, such as heading changes, which may indicate turning points and consequently intersections, we extract semantic features of the trajectories in form of sequences of stops and moves. Under this spatiotemporal prism, the extracted semantic information which indicates where vehicles stop can reveal important locations, such as junctions. The advantage of the proposed approach in comparison with existing turning-points oriented approaches is that it can detect intersections even when not all the crossing road segments are sampled and therefore no turning points are observed in the trajectories. The challenge with this approach is that first of all, not all vehicles stop at the same location - thus, the stop-location is blurred along the direction of the road; this, secondly, leads to the effect that nearby junctions can induce similar stop-locations. As a first step, a density-based clustering is applied on the layer of stop observations and clusters of stop events are found. Representative points of the clusters are determined (one per cluster) and in a last step the existence of an intersection is clarified based on spatial relational cluster reasoning, with which less informative geospatial clusters, in terms of whether a junction exists and where its centre lies, are transformed in more informative ones. Relational reasoning criteria, based on the relative orientation of the clusters with their adjacent ones are discussed for making sense of the relation that connects them, and finally for forming groups of stop events that belong to the same junction.
Song, Mi-Kyung; Paul, Sudeshna; Ward, Sandra E; Gilet, Constance A; Hladik, Gerald A
2018-01-25
This study evaluated 1-year linear trajectories of patient-reported dimensions of quality of life among patients receiving dialysis. Longitudinal observational study. 227 patients recruited from 12 dialysis centers. Sociodemographic and clinical characteristics. Participants completed an hour-long interview monthly for 12 months. Each interview included patient-reported outcome measures of overall symptoms (Edmonton Symptom Assessment System), physical functioning (Activities of Daily Living/Instrumental Activities of Daily Living), cognitive functioning (Patient's Assessment of Own Functioning Inventory), emotional well-being (Center for Epidemiologic Studies Depression Scale, State Anxiety Inventory, and Positive and Negative Affect Schedule), and spiritual well-being (Functional Assessment of Chronic Illness Therapy-Spiritual Well-Being Scale). For each dimension, linear and generalized linear mixed-effects models were used. Linear trajectories of the 5 dimensions were jointly modeled as a multivariate outcome over time. Although dimension scores fluctuated greatly from month to month, overall symptoms, cognitive functioning, emotional well-being, and spiritual well-being improved over time. Older compared with younger participants reported higher scores across all dimensions (all P<0.05). Higher comorbidity scores were associated with worse scores in most dimensions (all P<0.01). Nonwhite participants reported better spiritual well-being compared with their white counterparts (P<0.01). Clustering analysis of dimension scores revealed 2 distinctive clusters. Cluster 1 was characterized by better scores than those of cluster 2 in nearly all dimensions at baseline and by gradual improvement over time. Study was conducted in a single region of the United States and included mostly patients with high levels of function across the dimensions of quality of life studied. Multidimensional patient-reported quality of life varies widely from month to month regardless of whether overall trajectories improve or worsen over time. Additional research is needed to identify the best approaches to incorporate patient-reported outcome measures into dialysis care. Copyright © 2017 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Nick, Arash Safavi; Vynnycky, Michael; Fredriksson, Hasse
2016-06-01
A mathematical model is derived to predict the trajectories of pores and inclusions that are nucleated in the interdendritic region during the continuous casting of steel. Using basic fluid mechanics and heat transfer, scaling analysis, and asymptotic methods, the model accounts for the possible lateral drift of the pores as a result of the dependence of the surface tension on temperature and sulfur concentration. Moreover, the soluto-thermocapillary drift of such pores prior to final solidification, coupled to the fact that any inclusions present can only have a vertical trajectory, can help interpret recent experimental observations of pore-inclusion clusters in solidified steel castings.
The Psychology of Yoga Practitioners: A Cluster Analysis.
Genovese, Jeremy E C; Fondran, Kristine M
2017-11-01
Yoga practitioners (N = 261) completed the revised Expression of Spirituality Inventory (ESI) and the Multidimensional Body-Self Relations Questionnaire. Cluster analysis revealed three clusters: Cluster A scored high on all four spiritual constructs. They had high positive evaluations of their appearance, but a lower orientation towards their appearance. They tended to have a high evaluation of their fitness and health, and higher body satisfaction. Cluster B showed lower scores on the spiritual constructs. Like Cluster A, members of Cluster B tended to show high positive evaluations of appearance and fitness. They also had higher body satisfaction. Members of Cluster B had a higher fitness orientation and a higher appearance orientation than members of Cluster A. Members of Cluster C had low scores for all spiritual constructs. They had a low evaluation of, and unhappiness with, their appearance. They were unhappy with the size and appearance of their bodies. They tended to see themselves as overweight. There was a significant difference in years of practice between the three groups (Kruskall -Wallis, p = .0041). Members of Cluster A have the most years of yoga experience and members of Cluster B have more yoga experience than members of Cluster C. These results suggest the possible existence of a developmental trajectory for yoga practitioners. Such a developmental sequence may have important implications for yoga practice and instruction.
The Psychology of Yoga Practitioners: A Cluster Analysis.
Genovese, Jeremy E C; Fondran, Kristine M
2017-03-30
Yoga practitioners (N = 261) completed the revised Expression of Spirituality Inventory (ESI) and the Multidimensional Body-Self Relations Questionnaire. Cluster analysis revealed three clusters: Cluster A scored high on all four spiritual constructs. They had high positive evaluations of their appearance, but a lower orientation towards their appearance. They tended to have a high evaluation of their fitness and health, and higher body satisfaction. Cluster B showed lower scores on the spiritual constructs. Like Cluster A, members of Cluster B tended to show high positive evaluations of appearance and fitness. They also had higher body satisfaction. Members of Cluster B had a higher fitness orientation and a higher appearance orientation than members of Cluster A. Members of Cluster C had low scores for all spiritual constructs. They had a low evaluation of, and unhappiness with, their appearance. They were unhappy with the size and appearance of their bodies. They tended to see themselves as overweight. There was a significant difference in years of practice between the three groups (Kruskall-Wallis, p = .0041). Members of Cluster A have the most years of yoga experience and members of Cluster B have more yoga experience than members of Cluster C. These results suggest the possible existence of a developmental trajectory for yoga practitioners. Such a developmental sequence may have important implications for yoga practice and instruction.
Revealing nonergodic dynamics in living cells from a single particle trajectory
NASA Astrophysics Data System (ADS)
Lanoiselée, Yann; Grebenkov, Denis S.
2016-05-01
We propose the improved ergodicity and mixing estimators to identify nonergodic dynamics from a single particle trajectory. The estimators are based on the time-averaged characteristic function of the increments and can thus capture additional information on the process as compared to the conventional time-averaged mean-square displacement. The estimators are first investigated and validated for several models of anomalous diffusion, such as ergodic fractional Brownian motion and diffusion on percolating clusters, and nonergodic continuous-time random walks and scaled Brownian motion. The estimators are then applied to two sets of earlier published trajectories of mRNA molecules inside live Escherichia coli cells and of Kv2.1 potassium channels in the plasma membrane. These statistical tests did not reveal nonergodic features in the former set, while some trajectories of the latter set could be classified as nonergodic. Time averages along such trajectories are thus not representative and may be strongly misleading. Since the estimators do not rely on ensemble averages, the nonergodic features can be revealed separately for each trajectory, providing a more flexible and reliable analysis of single-particle tracking experiments in microbiology.
Machine Learning for Discriminating Quantum Measurement Trajectories and Improving Readout.
Magesan, Easwar; Gambetta, Jay M; Córcoles, A D; Chow, Jerry M
2015-05-22
Current methods for classifying measurement trajectories in superconducting qubit systems produce fidelities systematically lower than those predicted by experimental parameters. Here, we place current classification methods within the framework of machine learning (ML) algorithms and improve on them by investigating more sophisticated ML approaches. We find that nonlinear algorithms and clustering methods produce significantly higher assignment fidelities that help close the gap to the fidelity possible under ideal noise conditions. Clustering methods group trajectories into natural subsets within the data, which allows for the diagnosis of systematic errors. We find large clusters in the data associated with T1 processes and show these are the main source of discrepancy between our experimental and ideal fidelities. These error diagnosis techniques help provide a path forward to improve qubit measurements.
QAARM: quasi-anharmonic autoregressive model reveals molecular recognition pathways in ubiquitin
Savol, Andrej J.; Burger, Virginia M.; Agarwal, Pratul K.; Ramanathan, Arvind; Chennubhotla, Chakra S.
2011-01-01
Motivation: Molecular dynamics (MD) simulations have dramatically improved the atomistic understanding of protein motions, energetics and function. These growing datasets have necessitated a corresponding emphasis on trajectory analysis methods for characterizing simulation data, particularly since functional protein motions and transitions are often rare and/or intricate events. Observing that such events give rise to long-tailed spatial distributions, we recently developed a higher-order statistics based dimensionality reduction method, called quasi-anharmonic analysis (QAA), for identifying biophysically-relevant reaction coordinates and substates within MD simulations. Further characterization of conformation space should consider the temporal dynamics specific to each identified substate. Results: Our model uses hierarchical clustering to learn energetically coherent substates and dynamic modes of motion from a 0.5 μs ubiqutin simulation. Autoregressive (AR) modeling within and between states enables a compact and generative description of the conformational landscape as it relates to functional transitions between binding poses. Lacking a predictive component, QAA is extended here within a general AR model appreciative of the trajectory's temporal dependencies and the specific, local dynamics accessible to a protein within identified energy wells. These metastable states and their transition rates are extracted within a QAA-derived subspace using hierarchical Markov clustering to provide parameter sets for the second-order AR model. We show the learned model can be extrapolated to synthesize trajectories of arbitrary length. Contact: ramanathana@ornl.gov; chakracs@pitt.edu PMID:21685101
Spatiotemporal multistage consensus clustering in molecular dynamics studies of large proteins.
Kenn, Michael; Ribarics, Reiner; Ilieva, Nevena; Cibena, Michael; Karch, Rudolf; Schreiner, Wolfgang
2016-04-26
The aim of this work is to find semi-rigid domains within large proteins as reference structures for fitting molecular dynamics trajectories. We propose an algorithm, multistage consensus clustering, MCC, based on minimum variation of distances between pairs of Cα-atoms as target function. The whole dataset (trajectory) is split into sub-segments. For a given sub-segment, spatial clustering is repeatedly started from different random seeds, and we adopt the specific spatial clustering with minimum target function: the process described so far is stage 1 of MCC. Then, in stage 2, the results of spatial clustering are consolidated, to arrive at domains stable over the whole dataset. We found that MCC is robust regarding the choice of parameters and yields relevant information on functional domains of the major histocompatibility complex (MHC) studied in this paper: the α-helices and β-floor of the protein (MHC) proved to be most flexible and did not contribute to clusters of significant size. Three alleles of the MHC, each in complex with ABCD3 peptide and LC13 T-cell receptor (TCR), yielded different patterns of motion. Those alleles causing immunological allo-reactions showed distinct correlations of motion between parts of the peptide, the binding cleft and the complementary determining regions (CDR)-loops of the TCR. Multistage consensus clustering reflected functional differences between MHC alleles and yields a methodological basis to increase sensitivity of functional analyses of bio-molecules. Due to the generality of approach, MCC is prone to lend itself as a potent tool also for the analysis of other kinds of big data.
NASA Astrophysics Data System (ADS)
Werthmann, Britta; Marwan, Wolfgang
2017-11-01
The developmental switch to sporulation in Physarum polycephalum is a phytochrome-mediated far-red light-induced cell fate decision that synchronously encompasses the entire multinucleate plasmodial cell and is associated with extensive reprogramming of the transcriptome. By repeatedly taking samples of single cells after delivery of a light stimulus pulse, we analysed differential gene expression in two mutant strains and in a heterokaryon of the two strains all of which display a different propensity for making the cell fate decision. Multidimensional scaling of the gene expression data revealed individually different single cell trajectories eventually leading to sporulation. Characterization of the trajectories as walks through states of gene expression discretized by hierarchical clustering allowed the reconstruction of Petri nets that model and predict the observed behavior. Structural analyses of the Petri nets indicated stimulus- and genotype-dependence of both, single cell trajectories and of the quasipotential landscape through which these trajectories are taken. The Petri net-based approach to the analysis and decomposition of complex cellular responses and of complex mutant phenotypes may provide a scaffold for the data-driven reconstruction of causal molecular mechanisms that shape the topology of the quasipotential landscape.
ST-analyzer: a web-based user interface for simulation trajectory analysis.
Jeong, Jong Cheol; Jo, Sunhwan; Wu, Emilia L; Qi, Yifei; Monje-Galvan, Viviana; Yeom, Min Sun; Gorenstein, Lev; Chen, Feng; Klauda, Jeffery B; Im, Wonpil
2014-05-05
Molecular dynamics (MD) simulation has become one of the key tools to obtain deeper insights into biological systems using various levels of descriptions such as all-atom, united-atom, and coarse-grained models. Recent advances in computing resources and MD programs have significantly accelerated the simulation time and thus increased the amount of trajectory data. Although many laboratories routinely perform MD simulations, analyzing MD trajectories is still time consuming and often a difficult task. ST-analyzer, http://im.bioinformatics.ku.edu/st-analyzer, is a standalone graphical user interface (GUI) toolset to perform various trajectory analyses. ST-analyzer has several outstanding features compared to other existing analysis tools: (i) handling various formats of trajectory files from MD programs, such as CHARMM, NAMD, GROMACS, and Amber, (ii) intuitive web-based GUI environment--minimizing administrative load and reducing burdens on the user from adapting new software environments, (iii) platform independent design--working with any existing operating system, (iv) easy integration into job queuing systems--providing options of batch processing either on the cluster or in an interactive mode, and (v) providing independence between foreground GUI and background modules--making it easier to add personal modules or to recycle/integrate pre-existing scripts utilizing other analysis tools. The current ST-analyzer contains nine main analysis modules that together contain 18 options, including density profile, lipid deuterium order parameters, surface area per lipid, and membrane hydrophobic thickness. This article introduces ST-analyzer with its design, implementation, and features, and also illustrates practical analysis of lipid bilayer simulations. Copyright © 2014 Wiley Periodicals, Inc.
Dynamic evolution and biogenesis of small RNAs during sex reversal.
Liu, Jie; Luo, Majing; Sheng, Yue; Hong, Qiang; Cheng, Hanhua; Zhou, Rongjia
2015-05-06
Understanding origin, evolution and functions of small RNA (sRNA) genes has been a great challenge in the past decade. Molecular mechanisms underlying sexual reversal in vertebrates, particularly sRNAs involved in this process, are largely unknown. By deep-sequencing of small RNA transcriptomes in combination with genomic analysis, we identified a large amount of piRNAs and miRNAs including over 1,000 novel miRNAs, which were differentially expressed during gonad reversal from ovary to testis via ovotesis. Biogenesis and expressions of miRNAs were dynamically changed during the reversal. Notably, phylogenetic analysis revealed dynamic expansions of miRNAs in vertebrates and an evolutionary trajectory of conserved miR-17-92 cluster in the Eukarya. We showed that the miR-17-92 cluster in vertebrates was generated through multiple duplications from ancestor miR-92 in invertebrates Tetranychus urticae and Daphnia pulex from the Chelicerata around 580 Mya. Moreover, we identified the sexual regulator Dmrt1 as a direct target of the members miR-19a and -19b in the cluster. These data suggested dynamic biogenesis and expressions of small RNAs during sex reversal and revealed multiple expansions and evolutionary trajectory of miRNAs from invertebrates to vertebrates, which implicate small RNAs in sexual reversal and provide new insight into evolutionary and molecular mechanisms underlying sexual reversal.
NASA Astrophysics Data System (ADS)
Squizzato, Stefania; Masiol, Mauro
2015-10-01
The air quality is influenced by the potential effects of meteorology at meso- and synoptic scales. While local weather and mixing layer dynamics mainly drive the dispersion of sources at small scales, long-range transports affect the movements of air masses over regional, transboundary and even continental scales. Long-range transport may advect polluted air masses from hot-spots by increasing the levels of pollution at nearby or remote locations or may further raise air pollution levels where external air masses originate from other hot-spots. Therefore, the knowledge of ground-wind circulation and potential long-range transports is fundamental not only to evaluate how local or external sources may affect the air quality at a receptor site but also to quantify it. This review is focussed on establishing the relationships among PM2.5 sources, meteorological condition and air mass origin in the Po Valley, which is one of the most polluted areas in Europe. We have chosen the results from a recent study carried out in Venice (Eastern Po Valley) and have analysed them using different statistical approaches to understand the influence of external and local contribution of PM2.5 sources. External contributions were evaluated by applying Trajectory Statistical Methods (TSMs) based on back-trajectory analysis including (i) back-trajectories cluster analysis, (ii) potential source contribution function (PSCF) and (iii) concentration weighted trajectory (CWT). Furthermore, the relationships between the source contributions and ground-wind circulation patterns were investigated by using (iv) cluster analysis on wind data and (v) conditional probability function (CPF). Finally, local source contribution have been estimated by applying the Lenschow' approach. In summary, the integrated approach of different techniques has successfully identified both local and external sources of particulate matter pollution in a European hot-spot affected by the worst air quality.
NASA Astrophysics Data System (ADS)
Pan, Patricia Wang; Dickson, Russell J.; Gordon, Heather L.; Rothstein, Stuart M.; Tanaka, Shigenori
2005-01-01
Functionally relevant motion of proteins has been associated with a number of atoms moving in a concerted fashion along so-called "collective coordinates." We present an approach to extract collective coordinates from conformations obtained from molecular dynamics simulations. The power of this technique for differentiating local structural fuctuations between classes of conformers obtained by clustering is illustrated by analyzing nanosecond-long trajectories for the response regulator protein Spo0F of Bacillus subtilis, generated both in vacuo and using an implicit-solvent representation. Conformational clustering is performed using automated histogram filtering of the inter-Cα distances. Orthogonal (varimax) rotation of the vectors obtained by principal component analysis of these interresidue distances for the members of individual clusters is key to the interpretation of collective coordinates dominating each conformational class. The rotated loadings plots isolate significant variation in interresidue distances, and these are associated with entire mobile secondary structure elements. From this we infer concerted motions of these structural elements. For the Spo0F simulations employing an implicit-solvent representation, collective coordinates obtained in this fashion are consistent with the location of the protein's known active sites and experimentally determined mobile regions.
Inherent Structure versus Geometric Metric for State Space Discretization
Liu, Hanzhong; Li, Minghai; Fan, Jue; Huo, Shuanghong
2016-01-01
Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the micro cluster level, the IS approach and root-mean-square deviation (RMSD) based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the micro clusters are similar. The discrepancy at the micro cluster level leads to different macro clusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macro cluster level. PMID:26915811
Trajectory control of PbSe–γ-Fe2O3 nanoplatforms under viscous flow and an external magnetic field
Etgar, Lioz; Nakhmani, Arie; Tannenbaum, Allen; Lifshitz, Efrat; Tannenbaum, Rina
2010-01-01
The flow behavior of nanostructure clusters, consisting of chemically bonded PbSe quantum dots and magnetic γ -Fe2O3 nanoparticles, has been investigated. The clusters are regarded as model nanoplatforms with multiple functionalities, where the γ -Fe2O3 magnets serve as transport vehicles, manipulated by an external magnetic field gradient, and the quantum dots act as fluorescence tags within an optical window in the near-infrared regime. The clusters’ flow was characterized by visualizing their trajectories within a viscous fluid (mimicking a blood stream), using an optical imaging method, while the trajectory pictures were analyzed by a specially developed processing package. The trajectories were examined under various flow rates, viscosities and applied magnetic field strengths. The results revealed a control of the trajectories even at low magnetic fields (<1 T), validating the use of similar nanoplatforms as active targeting constituents in personalized medicine. PMID:20368678
NASA Astrophysics Data System (ADS)
Schlueter-Kuck, Kristy L.; Dabiri, John O.
2017-09-01
We present a method for identifying the coherent structures associated with individual Lagrangian flow trajectories even where only sparse particle trajectory data are available. The method, based on techniques in spectral graph theory, uses the Coherent Structure Coloring vector and associated eigenvectors to analyze the distance in higher-dimensional eigenspace between a selected reference trajectory and other tracer trajectories in the flow. By analyzing this distance metric in a hierarchical clustering, the coherent structure of which the reference particle is a member can be identified. This algorithm is proven successful in identifying coherent structures of varying complexities in canonical unsteady flows. Additionally, the method is able to assess the relative coherence of the associated structure in comparison to the surrounding flow. Although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems such as neuronal activity, gene expression, or social networks.
Cossio, Pilar; Laio, Alessandro; Pietrucci, Fabio
2011-06-14
An important step in the computer simulation of the dynamics of biomolecules is the comparison of structures in a trajectory by exploiting a measure of distance. This allows distinguishing structures which are geometrically similar from those which are different. By analyzing microseconds-long all-atom molecular dynamics simulations of a polypeptide, we find that a distance based on backbone dihedral angles performs very well in distinguishing structures that are kinetically correlated from those that are not, while the widely used C(α) root mean square distance performs more poorly. The root mean square difference between contact matrices turns out instead to be the metric providing the highest clustering coefficient, namely, according to this similarity measure, the neighbors of a structure are also, on average, neighbors among themselves. We also propose a combined distance measure which, for the system considered here, performs well both for distinguishing structures which are distant in time and for giving a consistent cluster analysis. This journal is © the Owner Societies 2011
Pouwels, J Loes; Salmivalli, Christina; Saarento, Silja; van den Berg, Yvonne H M; Lansu, Tessa A M; Cillessen, Antonius H N
2017-03-28
The aim of this study was to determine how trajectory clusters of social status (social preference and perceived popularity) and behavior (direct aggression and prosocial behavior) from age 9 to age 14 predicted adolescents' bullying participant roles at age 16 and 17 (n = 266). Clusters were identified with multivariate growth mixture modeling (GMM). The findings showed that participants' developmental trajectories of social status and social behavior across childhood and early adolescence predicted their bullying participant role involvement in adolescence. Practical implications and suggestions for further research are discussed. © 2017 The Authors. Child Development published by Wiley Periodicals, Inc. on behalf of Society for Research in Child Development.
Spectral-clustering approach to Lagrangian vortex detection.
Hadjighasem, Alireza; Karrasch, Daniel; Teramoto, Hiroshi; Haller, George
2016-06-01
One of the ubiquitous features of real-life turbulent flows is the existence and persistence of coherent vortices. Here we show that such coherent vortices can be extracted as clusters of Lagrangian trajectories. We carry out the clustering on a weighted graph, with the weights measuring pairwise distances of fluid trajectories in the extended phase space of positions and time. We then extract coherent vortices from the graph using tools from spectral graph theory. Our method locates all coherent vortices in the flow simultaneously, thereby showing high potential for automated vortex tracking. We illustrate the performance of this technique by identifying coherent Lagrangian vortices in several two- and three-dimensional flows.
Fletcher, Shelley; Elklit, Ask; Shevlin, Mark; Armour, Cherie
2017-11-01
This study aimed to (a) identify posttraumatic stress disorder (PTSD) trajectories in a sample of Danish treatment-seeking childhood sexual abuse (CSA) survivors and (b) examine the roles of social support, coping style, and individual PTSD symptom clusters (avoidance, reexperiencing, and hyperarousal) as predictors of the identified trajectories. We utilized a convenience sample of 439 CSA survivors attending personalized psychotherapy treatment in Denmark. Four assessments were conducted on a six monthly basis over a period of 18 months. We used latent class growth analysis (LCGA) to test solutions with one to six classes. Following this, a logistic regression was conducted to examine predictors of the identified trajectories. Results revealed four distinct trajectories which were labeled high PTSD gradual response, high PTSD treatment resistant, moderate PTSD rapid response, and moderate PTSD gradual response. Emotional and detached coping and more severe pretreatment avoidance and reexperiencing symptoms were associated with more severe and treatment resistant PTSD. High social support and a longer length of time since the abuse were associated with less severe PTSD which improved over time. The findings suggested that treatment response of PTSD in CSA survivors is characterized by distinct patterns with varying levels and rates of PTSD symptom improvement. Results revealed that social support is protective and that emotional and detached coping and high pretreatment levels of avoidance and reexperiencing symptoms are risk factors in relation to PTSD severity and course. These factors could potentially identify patients who are at risk of not responding to treatment. Furthermore, these factors could be specifically addressed to increase positive outcomes for treatment-seeking CSA survivors.
NASA Astrophysics Data System (ADS)
Flores, Rosa M.; Kaya, Nefel; Eşer, Övgü; Saltan, Şehnaz
2017-11-01
Mineral dust is the most significant source of natural particulate matter. In urban regions, where > 50% of the world population is currently living, local emissions of particulate matter are further aggravated by mineral dust loadings from deserts. The megacity of Istanbul is located in an area sensitive to local pollution due to transportation (i.e., private cars, public transportation, aircrafts, ships, heavy diesel trucks, etc.), industrial emissions, residential heating, and long-range transport from Europe, Asia, and deserts. In this work, the effect of desert dust transport on PM10 concentrations and physical properties was investigated for the period of 2007-2014 in the touristic area of Aksaray, Istanbul. The Dust Regional Atmospheric Model (DREAM8b) was used to predict dust loading in Istanbul during dust transport events. Variations on surface PM10 concentrations were investigated according to seasons and during dust transport events. Cluster analysis of air mass backward trajectories was useful to understand frequency analysis and air mass trajectory dependence of PM10 concentrations on dust loadings. The effect of desert dust transport on aerosol optical depths was also investigated. It was observed that PM10 concentrations exceeded the air quality standard of 50 μg m- 3 50% of the time during the study period. The largest number of exceedances in air quality standard occurred during the spring and winter seasons. Approximately 40-60% of the dust loading occurs during the spring. Desert dust and non-desert dust sources contribute to 22-72% and 48-81% of the ground-level PM10 concentrations in Aksaray, Istanbul during the study period. Averaged AOD observed during dust transport events in spring and summer ranged 0.35-0.55. Cluster analysis resolved over 82% the variability of individual air mass backward trajectories into 5 clusters. Overall, air masses arriving to Istanbul at 500 m are equally distributed into northern (52%) and southern (48%). Frequency analysis of PM10 concentrations with mean air mass backward trajectories showed that PM10 from local anthropogenic sources may be enhanced by long-range transport from the African Desert, Asian Desert, Arabian Peninsula, Russia, and Ukraine. The work presented here provides the first integrated assessment for evaluation of occurrence and quantification of the effect of dust transport to ground-level PM10 concentrations in Istanbul, which is helpful for human health prevention and implementation of air quality control measures.
ERIC Educational Resources Information Center
Collins, Brian Andrew; O'Connor, Erin Eileen; Supplee, Lauren; Shaw, Daniel S.
2017-01-01
The authors identified trajectories of teacher-child relationship conflict and closeness from Grades 1 to 6, and associations between these trajectories and externalizing and internalizing behaviors at 11 years old among low-income, urban boys (N = 262). There were three main findings. Nagin cluster analyses indicated five trajectories for…
Palmsten, Kristin; Rolland, Matthieu; Hebert, Mary F; Clowse, Megan E B; Schatz, Michael; Xu, Ronghui; Chambers, Christina D
2018-04-01
To characterize prednisone use in pregnant women with rheumatoid arthritis using individual-level heat-maps and clustering individual trajectories of prednisone dose, and to evaluate the association between prednisone dose trajectory groups and gestational length. This study included pregnant women with rheumatoid arthritis who enrolled in the MotherToBaby Autoimmune Diseases in Pregnancy Study (2003-2014) before gestational week 20 and reported prednisone use without another oral glucocorticoid during pregnancy (n = 254). Information on medication use and pregnancy outcomes was collected by telephone interview plus by medical record review. Prednisone daily dose and cumulative dose were plotted by gestational day using a heat map for each individual. K-means clustering was used to cluster individual trajectories of prednisone dose into groups. The associations between trajectory group and demographics, disease severity measured by the Health Assessment Questionnaire at enrollment, and gestational length were evaluated. Women used prednisone 3 to 292 days during pregnancy, with daily doses ranging from <1 to 60 mg. Total cumulative dose ranged from 8 to 6225 mg. Disease severity, non-biologic disease modifying anti-rheumatic drug use, and gestational length varied significantly by trajectory group. After adjusting for disease severity, non-biologic disease modifying anti-rheumatic drug use, and other covariates, the highest vs lowest daily dose trajectory group was associated with reduced gestational age at delivery (β: -2.3 weeks (95%: -3.4, -1.3)), as was the highest vs lowest cumulative dose trajectory group (β: -2.6 weeks (95%: -3.6, -1.5)). In pregnant women with rheumatoid arthritis, patterns of higher prednisone dose were associated with shorter gestational length compared with lower dose. Copyright © 2018 John Wiley & Sons, Ltd.
Eye-hand coupling during closed-loop drawing: evidence of shared motor planning?
Reina, G Anthony; Schwartz, Andrew B
2003-04-01
Previous paradigms have used reaching movements to study coupling of eye-hand kinematics. In the present study, we investigated eye-hand kinematics as curved trajectories were drawn at normal speeds. Eye and hand movements were tracked as a monkey traced ellipses and circles with the hand in free space while viewing the hand's position on a computer monitor. The results demonstrate that the movement of the hand was smooth and obeyed the 2/3 power law. Eye position, however, was restricted to 2-3 clusters along the hand's trajectory and fixed approximately 80% of the time in one of these clusters. The eye remained stationary as the hand moved away from the fixation for up to 200 ms and saccaded ahead of the hand position to the next fixation along the trajectory. The movement from one fixation cluster to another consistently occurred just after the tangential hand velocity had reached a local minimum, but before the next segment of the hand's trajectory began. The next fixation point was close to an area of high curvature along the hand's trajectory even though the hand had not reached that point along the path. A visuo-motor illusion of hand movement demonstrated that the eye movement was influenced by hand movement and not simply by visual input. During the task, neural activity of pre-motor cortex (area F4) was recorded using extracellular electrodes and used to construct a population vector of the hand's trajectory. The results suggest that the saccade onset is correlated in time with maximum curvature in the population vector trajectory for the hand movement. We hypothesize that eye and arm movements may have common, or shared, information in forming their motor plans.
Young adults' trajectories of Ecstasy use: a population based study.
Smirnov, Andrew; Najman, Jake M; Hayatbakhsh, Reza; Plotnikova, Maria; Wells, Helene; Legosz, Margot; Kemp, Robert
2013-11-01
Young adults' Ecstasy use trajectories have important implications for individual and population-level consequences of Ecstasy use, but little relevant research has been conducted. This study prospectively examines Ecstasy trajectories in a population-based sample. Data are from the Natural History Study of Drug Use, a retrospective/prospective cohort study conducted in Australia. Population screening identified a probability sample of Ecstasy users aged 19-23 years. Complete data for 30 months of follow-up, comprising 4 time intervals, were available for 297 participants (88.4% of sample). Trajectories were derived using cluster analysis based on recent Ecstasy use at each interval. Trajectory predictors were examined using a generalized ordered logit model and included Ecstasy dependence (World Mental Health Composite International Diagnostic Instrument), psychological distress (Hospital Anxiety Depression Scale), aggression (Young Adult Self Report) and contextual factors (e.g. attendance at electronic/dance music events). Three Ecstasy trajectories were identified (low, intermediate and high use). At its peak, the high-use trajectory involved 1-2 days Ecstasy use per week. Decreasing frequency of use was observed for intermediate and high-use trajectories from 12 months, independently of market factors. Intermediate and high-use trajectory membership was predicted by past Ecstasy consumption (>70 pills) and attendance at electronic/dance music events. High-use trajectory members were unlikely to have used Ecstasy for more than 3 years and tended to report consistently positive subjective effects at baseline. Given the social context and temporal course of Ecstasy use, Ecstasy trajectories might be better understood in terms of instrumental rather than addictive drug use patterns. © 2013 Elsevier Ltd. All rights reserved.
ERIC Educational Resources Information Center
Wu, Jiun-Yu; Hughes, Jan N.; Kwok, Oi-Man
2010-01-01
Teacher, peer, and student reports of the quality of the teacher-student relationship were obtained for an ethnically diverse and academically at-risk sample of 706 second- and third-grade students. Cluster analysis identified four types of relationships based on the consistency of child reports of support and conflict in the relationship with…
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hu, Lin; Maroudas, Dimitrios, E-mail: maroudas@ecs.umass.edu; Hammond, Karl D.
We report the results of a systematic atomic-scale analysis of the reactions of small mobile helium clusters (He{sub n}, 4 ≤ n ≤ 7) near low-Miller-index tungsten (W) surfaces, aiming at a fundamental understanding of the near-surface dynamics of helium-carrying species in plasma-exposed tungsten. These small mobile helium clusters are attracted to the surface and migrate to the surface by Fickian diffusion and drift due to the thermodynamic driving force for surface segregation. As the clusters migrate toward the surface, trap mutation (TM) and cluster dissociation reactions are activated at rates higher than in the bulk. TM produces W adatoms and immobile complexes ofmore » helium clusters surrounding W vacancies located within the lattice planes at a short distance from the surface. These reactions are identified and characterized in detail based on the analysis of a large number of molecular-dynamics trajectories for each such mobile cluster near W(100), W(110), and W(111) surfaces. TM is found to be the dominant cluster reaction for all cluster and surface combinations, except for the He{sub 4} and He{sub 5} clusters near W(100) where cluster partial dissociation following TM dominates. We find that there exists a critical cluster size, n = 4 near W(100) and W(111) and n = 5 near W(110), beyond which the formation of multiple W adatoms and vacancies in the TM reactions is observed. The identified cluster reactions are responsible for important structural, morphological, and compositional features in the plasma-exposed tungsten, including surface adatom populations, near-surface immobile helium-vacancy complexes, and retained helium content, which are expected to influence the amount of hydrogen re-cycling and tritium retention in fusion tokamaks.« less
Scheper, Mark C; Nicholson, Lesley L; Adams, Roger D; Tofts, Louise; Pacey, Verity
2017-12-01
The objective of the manuscript was to describe the natural history of complaints and disability in children diagnosed with joint hypermobility syndrome (JHS)/Ehlers-Danlos-hypermobility type (EDS-HT) and to identify the constructs that underlie functional decline. One hundred and one JHS/EDS-HT children were observed over 3 years and assessed at three time points on the following: functional impairments, quality of life, connective tissue laxity, muscle function, postural control and musculoskeletal and multi-systemic complaints. Cluster analysis was performed to identify subgroups in severity. Clinical profiles were determined for these subgroups, and differences were assessed by multivariate analysis of covariance. Mixed linear regression models were used to determine the subsequent trajectories. Finally, an exploratory factor analysis was used to uncover the underlying constructs of functional impairment. Three clusters of children were identified in terms of functional impairment: mild, moderately and severely affected. Functional impairment at baseline was predictive of worsening trajectories in terms of reduced walking distance and decreased quality of life (P ⩽ 0.05) over 3 years. Multiple interactions between the secondary outcomes were observed, with four underlying constructs identified. All four constructs (multi-systemic effects, pain, fatigue and loss of postural control) contributed significantly to disability (P ⩽ 0.046). Children diagnosed with JHS/EDS-HT who have a high incidence of multi-systemic complaints (particularly, orthostatic intolerance, urinary incontinence and diarrhoea) and poor postural control in addition to high levels of pain and fatigue at baseline are most likely to have a deteriorating trajectory of functional impairment and, accordingly, warrant clinical prioritization. © The Author 2017. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com
NASA Astrophysics Data System (ADS)
Pérez, Isidro A.; Sánchez, M. Luisa; García, M. Ángeles; Pardo, Nuria
2018-01-01
This study presents a simpler procedure for grouping air parcel back trajectories than others previously applied. Two-day air parcel back trajectories reaching an unpolluted site in the centre of the northern plateau of the Iberian Peninsula were calculated over a three-year period using the METEX model. A procedure based on the kernel density calculation was applied to the direction of each trajectory centroid to determine groups of trajectories. This method is much faster than the cluster procedure when it comes to retaining the directional details of groups. Seasonal analysis of six groups of trajectories revealed that the Atlantic origin prevailed against displacement from northern Europe. Moreover, Mediterranean and particularly African trajectories were infrequent, probably due to the rough peninsular orography in these directions. The location of air trajectories reaching the study site was described using a surface classification below the air parcels with improved spatial resolution compared to previous analyses. Local contribution was very marked, particularly in summer. Mean trajectories were calculated for each group together with meteorological features and CO2 and CH4 concentrations. Groups may be identified by their mean temperature, wind speed, elevation and distance values. However, only two groups should be considered when analysing the two trace gases, one for trajectories from the Atlantic Ocean and the second for trajectories from the continent. Contrasts of about 4 ppm for CO2 in summer and 0.023 ppm for CH4 in winter were observed, revealing that air trajectories from the Atlantic Ocean were cleaner than those arriving from the continent. These differences were attributed to higher air stagnation over land.
Rajani, Vishaal; Carrero, Gustavo; Golan, David E.; de Vries, Gerda; Cairo, Christopher W.
2011-01-01
The diffusion of receptors within the two-dimensional environment of the plasma membrane is a complex process. Although certain components diffuse according to a random walk model (Brownian diffusion), an overwhelming body of work has found that membrane diffusion is nonideal (anomalous diffusion). One of the most powerful methods for studying membrane diffusion is single particle tracking (SPT), which records the trajectory of a label attached to a membrane component of interest. One of the outstanding problems in SPT is the analysis of data to identify the presence of heterogeneity. We have adapted a first-passage time (FPT) algorithm, originally developed for the interpretation of animal movement, for the analysis of SPT data. We discuss the general application of the FPT analysis to molecular diffusion, and use simulations to test the method against data containing known regions of confinement. We conclude that FPT can be used to identify the presence and size of confinement within trajectories of the receptor LFA-1, and these results are consistent with previous reports on the size of LFA-1 clusters. The analysis of trajectory data for cell surface receptors by FPT provides a robust method to determine the presence and size of confined regions of diffusion. PMID:21402028
Mining spatiotemporal patterns of urban dwellers from taxi trajectory data
NASA Astrophysics Data System (ADS)
Mao, Feng; Ji, Minhe; Liu, Ting
2016-06-01
With the widespread adoption of locationaware technology, obtaining long-sequence, massive and high-accuracy spatiotemporal trajectory data of individuals has become increasingly popular in various geographic studies. Trajectory data of taxis, one of the most widely used inner-city travel modes, contain rich information about both road network traffic and travel behavior of passengers. Such data can be used to study the microscopic activity patterns of individuals as well as the macro system of urban spatial structures. This paper focuses on trajectories obtained from GPS-enabled taxis and their applications for mining urban commuting patterns. A novel approach is proposed to discover spatiotemporal patterns of household travel from the taxi trajectory dataset with a large number of point locations. The approach involves three critical steps: spatial clustering of taxi origin-destination (OD) based on urban traffic grids to discover potentially meaningful places, identifying threshold values from statistics of the OD clusters to extract urban jobs-housing structures, and visualization of analytic results to understand the spatial distribution and temporal trends of the revealed urban structures and implied household commuting behavior. A case study with a taxi trajectory dataset in Shanghai, China is presented to demonstrate and evaluate the proposed method.
All-atom calculation of protein free-energy profiles
NASA Astrophysics Data System (ADS)
Orioli, S.; Ianeselli, A.; Spagnolli, G.; Faccioli, P.
2017-10-01
The Bias Functional (BF) approach is a variational method which enables one to efficiently generate ensembles of reactive trajectories for complex biomolecular transitions, using ordinary computer clusters. For example, this scheme was applied to simulate in atomistic detail the folding of proteins consisting of several hundreds of amino acids and with experimental folding time of several minutes. A drawback of the BF approach is that it produces trajectories which do not satisfy microscopic reversibility. Consequently, this method cannot be used to directly compute equilibrium observables, such as free energy landscapes or equilibrium constants. In this work, we develop a statistical analysis which permits us to compute the potential of mean-force (PMF) along an arbitrary collective coordinate, by exploiting the information contained in the reactive trajectories calculated with the BF approach. We assess the accuracy and computational efficiency of this scheme by comparing its results with the PMF obtained for a small protein by means of plain molecular dynamics.
Statistical analysis of life history calendar data.
Eerola, Mervi; Helske, Satu
2016-04-01
The life history calendar is a data-collection tool for obtaining reliable retrospective data about life events. To illustrate the analysis of such data, we compare the model-based probabilistic event history analysis and the model-free data mining method, sequence analysis. In event history analysis, we estimate instead of transition hazards the cumulative prediction probabilities of life events in the entire trajectory. In sequence analysis, we compare several dissimilarity metrics and contrast data-driven and user-defined substitution costs. As an example, we study young adults' transition to adulthood as a sequence of events in three life domains. The events define the multistate event history model and the parallel life domains in multidimensional sequence analysis. The relationship between life trajectories and excess depressive symptoms in middle age is further studied by their joint prediction in the multistate model and by regressing the symptom scores on individual-specific cluster indices. The two approaches complement each other in life course analysis; sequence analysis can effectively find typical and atypical life patterns while event history analysis is needed for causal inquiries. © The Author(s) 2012.
An analysis of 5-day midtropospheric flow patterns for the South Pole: 1985-1989
NASA Astrophysics Data System (ADS)
Harris, Joyce M.
1992-09-01
An analysis of 5-day midtropospheric flow patterns for the South Pole during 1985-1989 is presented. Cluster analysis was used to summarize trajectories by year and by month. The results indicate that flow from the east was most often anticyclonic and light, occurring 8-18% of the time. Westerly flow patterns were the strongest and most frequent (37-51% occurrence). They were consistently cyclonic, usually reflecting storms in the Ross Sea area, the average center of the circumpolar vortex. Strong northerly flow occurred more often in 1987 than in other years. Year-to-year variability was also evident in southwesterly flow, which was enhanced in 1988, and weaker in 1987, compared with other years. The lightest winds over the South Pole occur during January, while the most vigorous long-range transport to South Pole occurs from July through October. Selected isentropic trajectories were examined to determine errors inherent in the isobaric estimates. Isentropic trajectories from the east showed little vertical motion and good agreement with isobaric ones. Over west Antarctica, however, isentropic trajectories consistently showed positive vertical motion. As a result, their isobaric counterparts were too long and overestimated the cyclonic curvature in the flow. Preferred transport from the west with warm-air advection results from the circumpolar vortex being asymmetrical, and the average isotherms, though roughly circular, being offset to the east of the South Pole.
Moens, Katrien; Siegert, Richard J; Taylor, Steve; Namisango, Eve; Harding, Richard
2015-01-01
Symptom research across conditions has historically focused on single symptoms, and the burden of multiple symptoms and their interactions has been relatively neglected especially in people living with HIV. Symptom cluster studies are required to set priorities in treatment planning, and to lessen the total symptom burden. This study aimed to identify and compare symptom clusters among people living with HIV attending five palliative care facilities in two sub-Saharan African countries. Data from cross-sectional self-report of seven-day symptom prevalence on the 32-item Memorial Symptom Assessment Scale-Short Form were used. A hierarchical cluster analysis was conducted using Ward's method applying squared Euclidean Distance as the similarity measure to determine the clusters. Contingency tables, X2 tests and ANOVA were used to compare the clusters by patient specific characteristics and distress scores. Among the sample (N=217) the mean age was 36.5 (SD 9.0), 73.2% were female, and 49.1% were on antiretroviral therapy (ART). The cluster analysis produced five symptom clusters identified as: 1) dermatological; 2) generalised anxiety and elimination; 3) social and image; 4) persistently present; and 5) a gastrointestinal-related symptom cluster. The patients in the first three symptom clusters reported the highest physical and psychological distress scores. Patient characteristics varied significantly across the five clusters by functional status (worst functional physical status in cluster one, p<0.001); being on ART (highest proportions for clusters two and three, p=0.012); global distress (F=26.8, p<0.001), physical distress (F=36.3, p<0.001) and psychological distress subscale (F=21.8, p<0.001) (all subscales worst for cluster one, best for cluster four). The greatest burden is associated with cluster one, and should be prioritised in clinical management. Further symptom cluster research in people living with HIV with longitudinally collected symptom data to test cluster stability and identify common symptom trajectories is recommended.
Bhattacharyya, Moitrayee; Vishveshwara, Saraswathi
2011-07-01
In this article, we present a novel application of a quantum clustering (QC) technique to objectively cluster the conformations, sampled by molecular dynamics simulations performed on different ligand bound structures of the protein. We further portray each conformational population in terms of dynamically stable network parameters which beautifully capture the ligand induced variations in the ensemble in atomistic detail. The conformational populations thus identified by the QC method and verified by network parameters are evaluated for different ligand bound states of the protein pyrrolysyl-tRNA synthetase (DhPylRS) from D. hafniense. The ligand/environment induced re-distribution of protein conformational ensembles forms the basis for understanding several important biological phenomena such as allostery and enzyme catalysis. The atomistic level characterization of each population in the conformational ensemble in terms of the re-orchestrated networks of amino acids is a challenging problem, especially when the changes are minimal at the backbone level. Here we demonstrate that the QC method is sensitive to such subtle changes and is able to cluster MD snapshots which are similar at the side-chain interaction level. Although we have applied these methods on simulation trajectories of a modest time scale (20 ns each), we emphasize that our methodology provides a general approach towards an objective clustering of large-scale MD simulation data and may be applied to probe multistate equilibria at higher time scales, and to problems related to protein folding for any protein or protein-protein/RNA/DNA complex of interest with a known structure.
Ravishankar, Chitra; Zak, Victor; Williams, Ismee A.; Bellinger, David C.; Gaynor, J. William; Ghanayem, Nancy S.; Krawczeski, Catherine D.; Licht, Daniel J.; Mahony, Lynn; Newburger, Jane W.; Pemberton, Victoria L.; Williams, Richard V.; Sananes, Renee; Cook, Amanda L.; Atz, Teresa; Khaikin, Svetlana; Hsu, Daphne T.
2012-01-01
Objectives To describe neurodevelopmental outcomes in infants with single ventricle (SV) physiology and determine factors associated with worse outcomes. Study design Neurodevelopmental outcomes for infants with SV enrolled in a multicenter drug trial were assessed at 14 months of age using the Bayley Scales of Infant Development-II. Multivariable regression analysis was used to identify factors associated with worse outcomes. Results Neurodevelopmental testing was performed at 14±1 months in 170/185 subjects in the trial. Hypoplastic left heart syndrome was present in 59% and 75% had undergone the Norwood operation. Mean psychomotor (PDI) and mental developmental indices (MDI) were 80±18 and 96±14 respectively (normal 100±15, P<0.001 for each). Group-based trajectory analysis provided a two-group model (high” and “low”) for height z-score trajectory and brain type natriuretic peptide (BNP) trajectory. The predicted PDI scores were 15 points higher in the “high” height z-score trajectory compared with the “low” cluster (P<.001). A higher number of serious adverse events during the trial was associated with lower PDI scores (P=.02). The predicted MDI scores were 13–17 points lower in “low height trajectory- high BNP trajectory” group compared with the other three groups (P<.001). MDI scores were also lower in subjects who required extracorporeal membrane oxygenation during the neonatal hospitalization (P=.01) or supplemental oxygen at discharge (P=.01). Conclusions Neurodevelopmental outcome at 14 months of age is impaired in infants with SV physiology. Low height trajectory and high BNP trajectory were associated with worse neurodevelopmental outcomes. Efforts to improve nutritional status alone may not improve neurodevelopmental outcomes. PMID:22939929
Statistical Exploration of Electronic Structure of Molecules from Quantum Monte-Carlo Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Prabhat, Mr; Zubarev, Dmitry; Lester, Jr., William A.
In this report, we present results from analysis of Quantum Monte Carlo (QMC) simulation data with the goal of determining internal structure of a 3N-dimensional phase space of an N-electron molecule. We are interested in mining the simulation data for patterns that might be indicative of the bond rearrangement as molecules change electronic states. We examined simulation output that tracks the positions of two coupled electrons in the singlet and triplet states of an H2 molecule. The electrons trace out a trajectory, which was analyzed with a number of statistical techniques. This project was intended to address the following scientificmore » questions: (1) Do high-dimensional phase spaces characterizing electronic structure of molecules tend to cluster in any natural way? Do we see a change in clustering patterns as we explore different electronic states of the same molecule? (2) Since it is hard to understand the high-dimensional space of trajectories, can we project these trajectories to a lower dimensional subspace to gain a better understanding of patterns? (3) Do trajectories inherently lie in a lower-dimensional manifold? Can we recover that manifold? After extensive statistical analysis, we are now in a better position to respond to these questions. (1) We definitely see clustering patterns, and differences between the H2 and H2tri datasets. These are revealed by the pamk method in a fairly reliable manner and can potentially be used to distinguish bonded and non-bonded systems and get insight into the nature of bonding. (2) Projecting to a lower dimensional subspace ({approx}4-5) using PCA or Kernel PCA reveals interesting patterns in the distribution of scalar values, which can be related to the existing descriptors of electronic structure of molecules. Also, these results can be immediately used to develop robust tools for analysis of noisy data obtained during QMC simulations (3) All dimensionality reduction and estimation techniques that we tried seem to indicate that one needs 4 or 5 components to account for most of the variance in the data, hence this 5D dataset does not necessarily lie on a well-defined, low dimensional manifold. In terms of specific clustering techniques, K-means was generally useful in exploring the dataset. The partition around medoids (pam) technique produced the most definitive results for our data showing distinctive patterns for both a sample of the complete data and time-series. The gap statistic with tibshirani criteria did not provide any distinction across the 2 dataset. The gap statistic w/DandF criteria, Model based clustering and hierarchical modeling simply failed to run on our datasets. Thankfully, the vanilla PCA technique was successful in handling our entire dataset. PCA revealed some interesting patterns for the scalar value distribution. Kernel PCA techniques (vanilladot, RBF, Polynomial) and MDS failed to run on the entire dataset, or even a significant fraction of the dataset, and we resorted to creating an explicit feature map followed by conventional PCA. Clustering using K-means and PAM in the new basis set seems to produce promising results. Understanding the new basis set in the scientific context of the problem is challenging, and we are currently working to further examine and interpret the results.« less
Machine Learning for Biological Trajectory Classification Applications
NASA Technical Reports Server (NTRS)
Sbalzarini, Ivo F.; Theriot, Julie; Koumoutsakos, Petros
2002-01-01
Machine-learning techniques, including clustering algorithms, support vector machines and hidden Markov models, are applied to the task of classifying trajectories of moving keratocyte cells. The different algorithms axe compared to each other as well as to expert and non-expert test persons, using concepts from signal-detection theory. The algorithms performed very well as compared to humans, suggesting a robust tool for trajectory classification in biological applications.
Age-Related Differences in Profiles of Mood-Change Trajectories
Stanley, Jennifer Tehan; Isaacowitz, Derek M.
2010-01-01
As a group, older adults report positive affective lives. The extent to which there are subgroups of older adults whose moods are less positive, however, is unclear. The aim of the present study was to identify and characterize different subgroups of adults who exhibit distinct trajectories of mood-change across a relatively short time period. Seventy-nine young and 103 older adults continuously reported their moods while viewing emotional and neutral faces. Cluster analysis revealed four subgroups of mood-change trajectories. Both the most positive and the most negative subgroups included more older than younger adults (ps < .05), suggesting that not all older adults exhibit higher positive affect than young adults. Analyses of variance revealed that the most negative group exhibited slower processing speed, more state anxiety and neuroticism, and looked less at happy faces, than the other groups (ps < .05). The results are discussed from an adult developmental perspective, focusing on the increased variability of mood trajectories in the older adults and whether this is a reflection of adaptive functioning, or a potential harbinger of dysfunction. PMID:21171749
Long-Term Marine Traffic Monitoring for Environmental Safety in the Aegean Sea
NASA Astrophysics Data System (ADS)
Giannakopoulos, T.; Gyftakis, S.; Charou, E.; Perantonis, S.; Nivolianitou, Z.; Koromila, I.; Makrygiorgos, A.
2015-04-01
The Aegean Sea is characterized by an extremely high marine safety risk, mainly due to the significant increase of the traffic of tankers from and to the Black Sea that pass through narrow straits formed by the 1600 Greek islands. Reducing the risk of a ship accident is therefore vital to all socio-economic and environmental sectors. This paper presents an online long-term marine traffic monitoring work-flow that focuses on extracting aggregated vessel risks using spatiotemporal analysis of multilayer information: vessel trajectories, vessel data, meteorological data, bathymetric / hydrographic data as well as information regarding environmentally important areas (e.g. protected high-risk areas, etc.). A web interface that enables user-friendly spatiotemporal queries is implemented at the frontend, while a series of data mining functionalities extracts aggregated statistics regarding: (a) marine risks and accident probabilities for particular areas (b) trajectories clustering information (c) general marine statistics (cargo types, etc.) and (d) correlation between spatial environmental importance and marine traffic risk. Towards this end, a set of data clustering and probabilistic graphical modelling techniques has been adopted.
NASA Astrophysics Data System (ADS)
Dimitriou, Konstantinos; Kassomenos, Pavlos
2014-10-01
The keystone of this paper was to calculate and interpret indicators reflecting sources and air quality impacts of PM2.5 and PMCOARSE (PM10-PM2.5) in Rome (Italy), focusing on potential exogenous influences. A backward atmospheric trajectory cluster analysis was implemented. The likelihood of daily PM10 exceedances was studied in conjunction with atmospheric patterns, whereas a Potential Source Contribution Function (PSCF) based on air mass residence time was deployed on a grid of a 0.5° × 0.5° resolution. Higher PM2.5 concentrations were associated with short/medium range airflows originated from Balkan Peninsula, whereas potential PMCOARSE sources were localized across the Mediterranean and coastal North Africa, due to dust and sea spray transportation. According to the outcome of a daily Pollution Index (PI), a slightly increased degradation of air quality is induced due to the additional quantity of exogenous PM but nevertheless, average levels of PI in all trajectory clusters belong in the low pollution category. Gaseous and particulate pollutants were also elaborated by a Principal Component Analysis (PCA), which produced 4 components: [Traffic], [photochemical], [residential] and [Secondary Coarse Aerosol], reflecting local sources of air pollution. PM2.5 levels were strongly associated with traffic, whereas PMCOARSE were produced autonomously by secondary sources.
Simultaneous multi-species tracking in live cells with quantum dot conjugates.
Clausen, Mathias P; Arnspang, Eva C; Ballou, Byron; Bear, James E; Lagerholm, B Christoffer
2014-01-01
Quantum dots are available in a range of spectrally separated emission colors and with a range of water-stabilizing surface coatings that offers great flexibility for enabling bio-specificity. In this study, we have taken advantage of this flexibility to demonstrate that it is possible to perform a simultaneous investigation of the lateral dynamics in the plasma membrane of i) the transmembrane epidermal growth factor receptor, ii) the glucosylphospatidylinositol-anchored protein CD59, and iii) ganglioside GM1-cholera toxin subunit B clusters in a single cell. We show that a large number of the trajectories are longer than 50 steps, which we by simulations show to be sufficient for robust single trajectory analysis. This analysis shows that the populations of the diffusion coefficients are heterogeneously distributed for all three species, but differ between the different species. We further show that the heterogeneity is decreased upon treating the cells with methyl-β-cyclodextrin.
Landstedt, Evelina; Brydsten, Anna; Hammarström, Anne; Virtanen, Pekka; Almquist, Ylva B
2016-11-18
While a vast amount of studies confirm the social reproduction of class and status from one generation to the next, less is known about the role of health in the child generation for these processes. Research has shown that particularly mental distress in adolescence is important for future life chances. This study aimed to examine the importance of parental socioeconomic position and depressive symptoms in youth for life-course trajectories of education and labour market attachment among men and women. Based on four waves of questionnaire data from the Northern Swedish Cohort (n = 1,001), consisting of individuals born in 1965, three steps of gender-separate analyses were undertaken. First, the individual trajectories of education and labour market attachment from age 18 to 42 were mapped through sequence analysis. Second, cluster analysis was used to identify typical trajectories. Third, two indicators of parental socioeconomic position - occupational class and employment status - and depressive symptoms at age 16 were used in multinomial regression analyses to predict adult life-course trajectories. Four typical trajectories were identified for men, of which three were characterised by stable employment and various lengths of education, and the fourth reflected a more unstable situation. Among women, five trajectories emerged, characterised by more instability compared to men. Low parental occupational class and unemployment were significantly associated with a higher risk of ending up in less advantaged trajectories for men while, for women, this was only the case for occupational class. Youth levels of depressive symptoms did not significantly differ across the trajectories. This study found support for the intergenerational reproduction of social position, particularly when measured in terms of parental occupational class. Youth depressive symptoms did not show clear differences across types of trajectories, subsequently impeding such symptoms to trigger any selection processes. While this could be a consequence of the specific framework of the current study, it may also suggest that depressive symptoms in youth are not a root cause for the more complex processes through which how social position develops across life. The possible impact of welfare and labour market policies is discussed.
We present a robust methodology for examining the relationship between synoptic-scale atmospheric transport patterns and pollutant concentration levels observed at a site. Our approach entails calculating a large number of back-trajectories from the observational site over a long...
Quantitative Assessment of Molecular Dynamics Sampling for Flexible Systems.
Nemec, Mike; Hoffmann, Daniel
2017-02-14
Molecular dynamics (MD) simulation is a natural method for the study of flexible molecules but at the same time is limited by the large size of the conformational space of these molecules. We ask by how much the MD sampling quality for flexible molecules can be improved by two means: the use of diverse sets of trajectories starting from different initial conformations to detect deviations between samples and sampling with enhanced methods such as accelerated MD (aMD) or scaled MD (sMD) that distort the energy landscape in controlled ways. To this end, we test the effects of these approaches on MD simulations of two flexible biomolecules in aqueous solution, Met-Enkephalin (5 amino acids) and HIV-1 gp120 V3 (a cycle of 35 amino acids). We assess the convergence of the sampling quantitatively with known, extensive measures of cluster number N c and cluster distribution entropy S c and with two new quantities, conformational overlap O conf and density overlap O dens , both conveniently ranging from 0 to 1. These new overlap measures quantify self-consistency of sampling in multitrajectory MD experiments, a necessary condition for converged sampling. A comprehensive assessment of sampling quality of MD experiments identifies the combination of diverse trajectory sets and aMD as the most efficient approach among those tested. However, analysis of O dens between conventional and aMD trajectories also reveals that we have not completely corrected aMD sampling for the distorted energy landscape. Moreover, for V3, the courses of N c and O dens indicate that much higher resources than those generally invested today will probably be needed to achieve convergence. The comparative analysis also shows that conventional MD simulations with insufficient sampling can be easily misinterpreted as being converged.
Coherent Structure Detection using Persistent Homology and other Topological Tools
NASA Astrophysics Data System (ADS)
Smith, Spencer; Roberts, Eric; Sindi, Suzanne; Mitchell, Kevin
2017-11-01
For non-autonomous, aperiodic fluid flows, coherent structures help organize the dynamics, much as invariant manifolds and periodic orbits do for autonomous or periodic systems. The prevalence of such flows in nature and industry has motivated many successful techniques for defining and detecting coherent structures. However, often these approaches require very fine trajectory data to reconstruct velocity fields and compute Cauchy-Green-tensor-related quantities. We use topological techniques to help detect coherent trajectory sets in relatively sparse 2D advection problems. More specifically, we have developed a homotopy-based algorithm, the ensemble-based topological entropy calculation (E-tec), which assigns to each edge in an initial triangulation of advected points a topologically forced lower bound on its future stretching rate. The triangulation and its weighted edges allow us to analyze flows using persistent homology. This topological data analysis tool detects clusters and loops in the triangulation that are robust in the presence of noise and in this case correspond to coherent trajectory sets.
Nettiksimmons, Jasmine; Beckett, Laurel; Schwarz, Christopher; Carmichael, Owen; Fletcher, Evan; DeCarli, Charles
2013-01-01
Previous work examining Alzheimer’s Disease Neuroimaging Initiative (ADNI) normal controls using cluster analysis identified a subgroup characterized by substantial brain atrophy and white matter hyperintensities (WMH). We hypothesized that these effects could be related to vascular damage. Fifty-three individuals in the suspected vascular cluster (Normal 2) were compared with 31 individuals from the cluster characterized as healthy/typical (Normal 1) on a variety of outcomes, including magnetic resonance imaging (MRI) and cerebrospinal fluid (CSF) biomarkers, vascular risk factors and outcomes, cognitive trajectory, and medications for vascular conditions. Normal 2 was significantly older but did not differ on ApoE4+ prevalence. Normal 2 differed significantly from Normal 1 on all MRI measures but not on Amyloid-Beta1-42 or total tau protein. Normal 2 had significantly higher body mass index (BMI), Hachinksi score, and creatinine levels, and took significantly more medications for vascular conditions. Normal 2 had marginally significantly higher triglycerides and blood glucose. Normal 2 had a worse cognitive trajectory on the Rey’s Auditory Verbal Learning Test (RAVLT) 30-min delay test and the Functional Activity Questionnaire (FAQ). Cerebral atrophy associated with multiple vascular risks is common among cognitively normal individuals, forming a distinct subgroup with significantly increased cognitive decline. Further studies are needed to determine the clinical impact of these findings. PMID:23527743
NASA Astrophysics Data System (ADS)
Wang, Shuo; Zhao, Weixiong; Xu, Xuezhe; Fang, Bo; Zhang, Qilei; Qian, Xiaodong; Zhang, Weijun; Chen, Weidong; Pu, Wei; Wang, Xin
2017-11-01
Seasonal dependence of the columnar aerosol optical and chemical properties on regional transport in Beijing over 10 years (from January 2005 to December 2014) were analyzed by using the ground-based remote sensing combined with backward trajectory analysis. Daily air mass backward trajectories terminated in Beijing were computed with HYSPLIT-4 model and were categorized into five clusters. The columnar mass concentrations of black carbon (BC), brown carbon (BrC), dust (DU), aerosol water content (AW), and ammonium sulfate like aerosol (AS) of each cluster were retrieved from the optical data obtained from the Aerosol Robotic NETwork (AERONET) with five-component model. It was found that the columnar aerosol properties in different seasons were changed, and they were related to the air mass origins. In spring, aerosol was dominated by coarse particles. Summer was characterized by higher single scattering albedo (SSA), lower real part of complex refractive index (n), and obvious hygroscopic growth due to humid air from the south. During autumn and winter, there was an observable increase in absorption aerosol optical thickness (AAOT) and the imaginary part of complex refraction (k), with high levels of retrieved BC and BrC. However, concentrations of BC showed less dependence on the clusters during the two seasons owing to the widely spread coal heating in north China.
Capturing Complexities of Relationship-Level Family Planning Trajectories in Malawi.
Furnas, Hannah E
2016-09-01
In a transitioning fertility climate, preferences and decisions surrounding family planning are constantly in flux. Malawi provides an ideal case study of family planning complexities as fertility preferences are flexible, the relationship context is unstable, and childbearing begins early. I use intensive longitudinal data from Tsogolo la Thanzi-a research project in Malawi that follows young adults in romantic partnerships through the course of their relationship. I examine two questions: (1) What are the typical patterns of family planning as young adults transition through a relationship? (2) How are family planning trajectories related to individual and relationship-level characteristics? I use sequence analysis to order family planning across time and to contextualize it within each relationship. I generate and cluster the family planning trajectories and find six distinct groups of young adults who engage in family planning in similar ways. I find that family planning is complex, dynamic, and unique to each relationship. I argue that (a) family planning research should use the relationship as the unit of analysis and (b) family planning behaviors and preferences should be sequenced over time for a better understanding of key concepts, such as unmet need. © 2016 The Population Council, Inc.
Capturing Complexities of Relationship-Level Family Planning Trajectories in Malawi
Furnas, Hannah E.
2017-01-01
In a transitioning fertility climate, preferences and decisions surrounding family planning are constantly in flux. Malawi provides an ideal case study of family planning complexities as fertility preferences are flexible, the relationship context is unstable, and childbearing begins early. I use intensive longitudinal data from Tsogolo la Thanzi—a research project in Malawi that follows young adults in romantic partnerships through the course of their relationship and allows me to ask two questions: (1) What are the typical patterns of family planning as young adults transition through a relationship? (2) How are family planning trajectories related to individual and relationship-level characteristics? I use sequence analysis to order family planning across time and to contextualize it within each relationship. I generate and cluster the family planning trajectories and find six distinct groups of young adults who engage in family planning in similar ways. I find that family planning is complex, dynamic, and unique to each relationship. I argue that (a) family planning research should use the relationship as the unit of analysis and (b) family planning behaviors and preferences should be sequenced over time for a better understanding of key concepts, such as unmet need. PMID:27517867
NASA Astrophysics Data System (ADS)
Giemsa, Esther; Jacobeit, Jucundus; Ries, Ludwig; Frank, Gabriele; Hachinger, Stephan; Meyer-Arnek, Julian
2016-04-01
In order to estimate the influence of Central European CO2 emissions, a new method to retrieve background concentrations based on statistics of radon-222 and backward trajectories is developed and applied to the CO2 observations at the alpine high-altitude research station Schneefernerhaus (2670 m a.s.l.). The reliable identification of baseline conditions is important for perceiving changes in time as well as in the sources and sinks of greenhouse gases and thereby assessing the efficiency of existing mitigation strategies. In the particular case of Central Europe, the analysis of background concentrations could add further insights on the question why background CO2 concentrations increased in the last few decades, despite a significant decrease in the reported emissions. Ongoing effort to define the baseline conditions has led to a variety of data selection techniques. In this diversity of data filtering concepts, a relatively recent data selection method effectively appropriates observations of radon-222 to reliably and unambiguously identify baseline air masses. Owing to its relatively constant emission rate from the ice-free land surface and its half-life of 3.8 days that is solely achieved through radioactive decay, the tropospheric background concentration of the inert radioactive gas is low and temporal variations caused by changes in atmospheric transport are precisely detectable. For defining the baseline air masses reaching the high alpine research station Schneefernerhaus, an objective analysis approach is applied to the two-hourly radon records. The CO2 values of days by the radon method associated with prevailing atmospheric background conditions result in the CO2 concentrations representing the least land influenced air masses. Additionally, three-dimensional back-trajectories were retrieved using the Lagrangian Particle Dispersion Model (LPDM) FLEXPART driven by analysis fields of the Global Forecast System (GFS) produced by the National Centers for Environmental Prediction (NCEP). For the past five years, every two hours a total of 10.000 particles was released and followed backward in time for ten days. The trajectory position was stored with a time step of two hours. Based on the thereby calculated residence time each trajectory spent in the European planetary boundary layer (PBL), a validation of the baseline values derived from the radon statistics is received. Only terms where back trajectories and radon agree in the baseline detection are selected as unpolluted. The ability to eliminate air masses contaminated by European pollution via combining these two filtering techniques permits to analyze the influence of different large-scale source regions to the receptor point Schneefernerhaus. In order to identify the different source regions, cluster analysis with the COST733 classification software is applied to the normalized position coordinates of each selected trajectory. This accounts for the variations in transport speed and direction in both horizontal and vertical directions simultaneously, yielding clusters of trajectories as homogeneous and as distinctly different from each other as possible. This methodology relates the variability in trace gas measurements to variations in synoptic-scale circulation facing a challenging task in the currently changing atmosphere.
Risk, Resiliency and Coping in National Guard Families
2015-10-01
future research and larger quantitative studies of injury trajectory. CONCLUSION This study increases our understanding of risk, resilience and coping... Solomon et al. 2008). This finding is supported by other research that found emotional numbing behaviors associated with the avoidance cluster to be...and effectively, all four symptomatic clusters of PTSD within a relational context. Research suggests that each cluster impacts veterans’ intimate
NASA Astrophysics Data System (ADS)
Lee, Tai Sik; Lee, Yoon-Sun; Lee, Jaeho; Chang, Byung Chul
2018-02-01
Human space exploration (HSE) is an interdisciplinary field composed of a range of subjects that have developed dramatically over the last few decades. This paper investigates the intellectual structure of HSE research with a focus on human related factors. A bibliometric approach with quantitative analytical techniques is applied to study the development and growth of the research. This study retrieves 1921 papers on HSE related to human factors from the year 1990 to the year 2016 from Web of Science and constructs a critical citation network composed of 336 papers. Edge-betweenness-based clustering is used to classify the citation network into twelve distinct research clusters based on four research themes: "biological risks from space radiation," "health and performance during long-duration spaceflight," "program and in-situ resources for HSE missions," and "habitat and life support systems in the space environment." These research themes are also similar to the classification results of a co-occurrence analysis on keywords for a total of 1921 papers. Papers with high centrality scores are identified as important papers in terms of knowledge flow. Moreover, the intermediary role of papers in exchanging knowledge between HSE sub-areas is identified using brokerage analysis. The key-route main path highlights the theoretical development trajectories. Due to the recent dramatic increase in investment by international governments and the private sector, the theoretical development trajectories of key research themes have been expanding from furthering scientific and technical knowledge to include various social and economic issues, thus encouraging massive public participation. This study contributes to an understanding of research trends and popular issues in the field of HSE by introducing a powerful way of determining major research themes and development trajectories. This study will help researchers seek the underlying knowledge diffusion flow from multifaceted aspects to establish future research directions.
NASA Astrophysics Data System (ADS)
Zakharov, Alexander
It is well-known that one can evaluate black hole (BH) parameters (including spin) analyz-ing trajectories of stars around BH. A bulk distribution of matter (dark matter (DM)+stellar cluster) inside stellar orbits modifies trajectories of stars, namely, generally there is a apoas-tron shift in direction which opposite to GR one, even now one could put constraints on DM distribution and BH parameters and constraints will more stringent in the future. Therefore, an analyze of bright star trajectories provides a relativistic test in a weak gravitational field approximation, but in the future one can test a strong gravitational field near the BH at the Galactic Center with the same technique due to a rapid progress in observational facilities. References A. Zakharov et al., Phys. Rev. D76, 062001 (2007). A.F. Zakharov et al., Space Sci. Rev. 148, 301313(2009).
NASA Astrophysics Data System (ADS)
Giemsa, Esther; Jacobeit, Jucundus; Ries, Ludwig; Frank, Gabriele; Hachinger, Stephan; Meyer-Arnek, Julian
2017-04-01
Carbon dioxide (CO2) and methane (CH4) represent the most important contributors to increased radiative forcing enhancing it together by contemporary 2.65 W/m2 on the global average (IPCC 2013). The unbroken increase of atmospheric greenhouse gases (GHG) has been unequivocally attributed to human emissions mainly coming from fossil fuel burning and land-use changes, while the oceans and terrestrial ecosystems slightly attenuate this rise with seasonally varying strength. Short-term fluctuations in the GHG concentrations that superimpose the seasonal cycle and the climate change driven trend reflect the presence of regional sources and sinks. A perfect place for investigating the comprehensive influence of these regional emissions is provided by the Environmental Research Station Schneefernerhaus (47.42°N, 10.98°E, 2.650m a.s.l.) situated in the eastern Alps at the southern side of Zugspitze mountain. Located just 300m below the highest peak of the German Alps, the exposed site is one of the currently 30 global core sites of the World Meteorological Organisation (WMO) Global Atmosphere Watch (GAW) programme and thus provides ideal conditions to study source-receptor relationships for greenhouse gases. We propose a stepwise statistical methodology for examining the relationship between synoptic-scale atmospheric transport patterns and climate gas mole fractions to finally receive a characterization of the sampling site with regard to the key processes driving CO2 and CH4 concentration levels. The first step entails a reliable radon-based filtering approach to subdivide the detected air masses according to their regional or 'background' origin. Simultaneously, a large number of ten-day back-trajectories from Schneefernerhaus every two hours over the entire study period 2011 - 2015 is calculated with the Lagrangian transport and dispersion model FLEXPART (Stohl et al. 2005) and subjected to cluster analysis. The weather- and emission strength-related (short-term) components of the regional CO2 and CH4 concentration time-series are assigned to the back-trajectory clusters. The significant differences in the greenhouse gases' distributions associated with each cluster are confirmed by the non-parametric Kruskal-Wallis test thereby delivering the prerequisites for further investigations, in particular by Potential Source Contribution Functions for the detection of probable locations of within-cluster emission sources. The advantages of this comprehensive approach are site-specificity (by considering trajectories arriving at Schneefernerhaus as well as a site-appropriate filter method) and concentration-specificity (each greenhouse gas has its own source regions) combined with granting the space and time scales related to the synoptic flow patterns in source attribution studies. This research received funding from the Bavarian State Ministry of the Environment and Consumer Protection.
Temporal variation of PM10 concentration and properties in Istanbul 2007-2015
NASA Astrophysics Data System (ADS)
Flores, Rosa M.; Kaya, Nefel; Eşer, Övgü; Saltan, Şehnaz
2017-04-01
The study of temporal variation of atmospheric aerosols is essential for a better understanding of sources, transport, and accumulation in the atmosphere. In addition, the study of aerosol properties is important for the understanding of their formation and potential impacts on ecosystems and climate change. Istanbul is a Megacity that often shows exceedance in particulate matter (PM) standard values, especially during the winter season. In this work, temporal variations of hourly ground-level PM10 concentrations, aerosol optical depth (AOD), aerosol index (AI), vertical distribution, and mineral dust loadings were investigated according to air mass trajectory clusters in Istanbul during 2007-2015. Aerosol properties (i.e., AOD, AI, and vertical distribution) and mineral dust loadings were retrieved from satellite observations and the BSC-DREAM8b model, respectively. Air mass backward trajectories and clustering were supplied by NOAA-HYSPLIT model. Mineral dust transport events were characterized according to the exceedance of a dust loading threshold value. The total number of mineral dust transport events ranged from 115 to 183 during the study period. The largest number of mineral dust transport events were observed in 2008 and 2014. However, the highest ground-level PM10 measurements were observed in 2012-2013 with approximately 70% of the daily average concentrations exceeding the air quality standard of 50 µg m-3. Overall, 5-6 air mass trajectory clusters were able to resolve over 85% of the total spatial variance. These trajectories vary in frequency and direction throughout the years, however, the main trajectories favor aerosol transport from N, NE, NNE, and S, and SE. Evaluation of mineral dust loading and PM10 concentrations is helpful for successful development and implementation of air quality management strategies on local levels.
Klijn, Sven L; Weijenberg, Matty P; Lemmens, Paul; van den Brandt, Piet A; Lima Passos, Valéria
2017-10-01
Background and objective Group-based trajectory modelling is a model-based clustering technique applied for the identification of latent patterns of temporal changes. Despite its manifold applications in clinical and health sciences, potential problems of the model selection procedure are often overlooked. The choice of the number of latent trajectories (class-enumeration), for instance, is to a large degree based on statistical criteria that are not fail-safe. Moreover, the process as a whole is not transparent. To facilitate class enumeration, we introduce a graphical summary display of several fit and model adequacy criteria, the fit-criteria assessment plot. Methods An R-code that accepts universal data input is presented. The programme condenses relevant group-based trajectory modelling output information of model fit indices in automated graphical displays. Examples based on real and simulated data are provided to illustrate, assess and validate fit-criteria assessment plot's utility. Results Fit-criteria assessment plot provides an overview of fit criteria on a single page, placing users in an informed position to make a decision. Fit-criteria assessment plot does not automatically select the most appropriate model but eases the model assessment procedure. Conclusions Fit-criteria assessment plot is an exploratory, visualisation tool that can be employed to assist decisions in the initial and decisive phase of group-based trajectory modelling analysis. Considering group-based trajectory modelling's widespread resonance in medical and epidemiological sciences, a more comprehensive, easily interpretable and transparent display of the iterative process of class enumeration may foster group-based trajectory modelling's adequate use.
Orpinas, Pamela; Nahapetyan, Lusine; Truszczynski, Natalia
2017-05-01
Understanding the interrelation among problem behaviors and their change over time is fundamental for prevention research. The Healthy Teens Longitudinal Study followed a cohort of adolescents from Grades 6-12. Prior research identified two distinct trajectories of perpetration of physical dating violence: Low and Increasing. The purpose of this study was to examine whether adolescents in these two trajectories differed longitudinally on other problem behaviors: (1) suicidal ideation and attempts, (2) weapon-carrying and threats with a weapon, and (3) substance use, particularly alcohol and marijuana. The sample consisted of 588 randomly-selected students (52% males; 49% White, 36% Black, 12% Latino). Students completed a self-reported, computer-based survey each spring from Grades 6-12. To examine significant differences by perpetration of physical dating violence trajectory, we used Chi-square test and generalized estimating equations modeling. Across most grades, significantly more students in Increasing than in the Low trajectory reported suicidal ideation and attempts, carried a weapon, and threatened someone with a weapon. Adolescents in the Increasing trajectory also had higher trajectories of alcohol use, being drunk, and marijuana use than those in the Low trajectory. All differences were already significant in Grade 6. The difference in the rate of change between groups was not significant. This longitudinal study highlights that problem behaviors-physical dating violence, suicidal ideation and attempts, weapon carrying and threats, marijuana and alcohol use-cluster together as early as sixth grade and the clustering persists over time. The combination of these behaviors poses a great public health concern and highlight the need for early interventions.
TOPTRAC: Topical Trajectory Pattern Mining
Kim, Younghoon; Han, Jiawei; Yuan, Cangzhou
2015-01-01
With the increasing use of GPS-enabled mobile phones, geo-tagging, which refers to adding GPS information to media such as micro-blogging messages or photos, has seen a surge in popularity recently. This enables us to not only browse information based on locations, but also discover patterns in the location-based behaviors of users. Many techniques have been developed to find the patterns of people's movements using GPS data, but latent topics in text messages posted with local contexts have not been utilized effectively. In this paper, we present a latent topic-based clustering algorithm to discover patterns in the trajectories of geo-tagged text messages. We propose a novel probabilistic model to capture the semantic regions where people post messages with a coherent topic as well as the patterns of movement between the semantic regions. Based on the model, we develop an efficient inference algorithm to calculate model parameters. By exploiting the estimated model, we next devise a clustering algorithm to find the significant movement patterns that appear frequently in data. Our experiments on real-life data sets show that the proposed algorithm finds diverse and interesting trajectory patterns and identifies the semantic regions in a finer granularity than the traditional geographical clustering methods. PMID:26709365
NASA Astrophysics Data System (ADS)
Lee, G.-S.; Kim, P.-R.; Han, Y.-J.; Holsen, T. M.; Seo, Y.-S.; Yi, S.-M.
2015-11-01
As a global pollutant, mercury (Hg) is of particular concern in East Asia where anthropogenic emissions are the largest. In this study, speciated Hg concentrations were measured in the western most island in Korea, located between China and the Korean mainland to identify the importance of local, regional and distant Hg sources. Various tools including correlations with other pollutants, conditional probability function, and back-trajectory based analysis consistently indicated that Korean sources were important for gaseous oxidized mercury (GOM) whereas, for total gaseous mercury (TGM) and particulate bound mercury (PBM), long-range and regional transport were also important. A trajectory cluster based approach considering both Hg concentration and the fraction of time each cluster was impacting the site was developed to quantify the effect of Korean sources and out-of-Korean source. This analysis suggests that Korean sources contributed approximately 55 % of the GOM and PBM while there were approximately equal contributions from Korean and out-of-Korean sources for the TGM measured at the site. The ratio of GOM / PBM decreased when the site was impacted by long-range transport, suggesting that this ratio may be a useful tool for identifying the relative significance of local sources vs. long-range transport. The secondary formation of PBM through gas-particle partitioning with GOM was found to be important at low temperatures and high relative humidity.
NASA Astrophysics Data System (ADS)
Lee, Gang-San; Kim, Pyung-Rae; Han, Young-Ji; Holsen, Thomas M.; Seo, Yong-Seok; Yi, Seung-Muk
2016-03-01
As a global pollutant, mercury (Hg) is of particular concern in East Asia, where anthropogenic emissions are the largest. In this study, speciated Hg concentrations were measured on Yongheung Island, the westernmost island in Korea, located between China and the Korean mainland to identify the importance of local and regional Hg sources. Various tools including correlations with other pollutants, conditional probability function, and back-trajectory-based analysis consistently indicated that Korean sources were important for gaseous oxidized mercury (GOM) whereas, for total gaseous mercury (TGM) and particulate bound mercury (PBM), regional transport was also important. A trajectory cluster based approach, considering both Hg concentration and the fraction of time each cluster was impacting the site, was developed to quantify the effect of Korean sources and out-of-Korean sources. This analysis suggests that contributions from out-of-Korean sources were similar to Korean sources for TGM whereas Korean sources contributed slightly more to the concentration variations of GOM and PBM compared to out-of-Korean sources. The ratio of GOM/PBM decreased when the site was impacted by regional transport, suggesting that this ratio may be a useful tool for identifying the relative significance of local sources vs. regional transport. The secondary formation of PBM through gas-particle partitioning with GOM was found to be important at low temperatures and high relative humidity.
Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI).
Fyffe, Denise; Kalpakjian, Claire Z; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C; Tulsky, David S; Jette, Alan M
2016-09-01
To provide validation of functional ability levels for the Spinal Cord Injury - Functional Index (SCI-FI). Cross-sectional. Inpatient rehabilitation hospital and community settings. A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Not Applicable. Spinal Cord Injury-Functional Index (SCI-FI). Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed.
NASA Astrophysics Data System (ADS)
Hanna, Sarah J.; Xu, Jun-Wei; Schroder, Jason C.; Wang, Qiaoqiao; McMeeking, Gavin R.; Hayden, Katherine; Leaitch, W. Richard; Macdonald, AnneMarie; von Salzen, Knut; Martin, Randall V.; Bertram, Allan K.
2018-05-01
Measurements of black carbon at remote and high altitude locations provide an important constraint for models. Here we present six months of refractory black carbon (rBC) data collected in July-August of 2009, June-July of 2010, and April-May of 2012 using a single particle soot photometer (SP2) at the remote Whistler High Elevation Research Site in the Coast Mountains of British Columbia (50.06°N, 122.96°W, 2182 m a.m.s.l). In order to reduce regional boundary layer influences, only measurements collected during the night (2000-0800 PST) were considered. Times impacted by local biomass burning were removed from the data set, as were periods of in-cloud sampling. Back trajectories and back trajectory cluster analysis were used to classify the sampled air masses as Southern Pacific, Northern Pacific, Western Pacific/Asian, or Northern Canadian in origin. The largest rBC mass median diameter (182 nm) was seen for air masses in the Southern Pacific cluster, and the smallest (156 nm) was seen for air masses in the Western Pacific/Asian cluster. Considering all the clusters, the median mass concentration of rBC was 25.0 ± 7.6 ng/m3-STP. The Northern Pacific, Southern Pacific, Western Pacific/Asian, and Northern Canada clusters had median mass concentrations of 25.0 ± 7.6, 21.3 ± 6.9, 25.0 ± 7.9, and 40.6 ± 12.9 ng/m3-STP, respectively. We compared these measurements with simulations from the global chemical transport model GEOS-Chem. The default GEOS-Chem simulations overestimated the median rBC mass concentrations for the different clusters by a factor of 1.2-2.2. The largest difference was observed for the Northern Pacific cluster (factor of 2.2) and the smallest difference was observed for the Northern Canada cluster (factor of 1.2). A sensitivity simulation that excluded Vancouver emissions still overestimated the median rBC mass concentrations for the different clusters by a factor of 1.1-2.0. After implementation of a revised wet scavenging scheme, the simulations overestimated the median rBC mass concentrations for the different clusters by a factor of 1.0-2.0.
Twarog, Nathaniel R.; Low, Jonathan A.; Currier, Duane G.; Miller, Greg; Chen, Taosheng; Shelat, Anang A.
2016-01-01
Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2’-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used. PMID:26886014
Twarog, Nathaniel R; Low, Jonathan A; Currier, Duane G; Miller, Greg; Chen, Taosheng; Shelat, Anang A
2016-01-01
Phenotypic screening through high-content automated microscopy is a powerful tool for evaluating the mechanism of action of candidate therapeutics. Despite more than a decade of development, however, high content assays have yielded mixed results, identifying robust phenotypes in only a small subset of compound classes. This has led to a combinatorial explosion of assay techniques, analyzing cellular phenotypes across dozens of assays with hundreds of measurements. Here, using a minimalist three-stain assay and only 23 basic cellular measurements, we developed an analytical approach that leverages informative dimensions extracted by linear discriminant analysis to evaluate similarity between the phenotypic trajectories of different compounds in response to a range of doses. This method enabled us to visualize biologically-interpretable phenotypic tracks populated by compounds of similar mechanism of action, cluster compounds according to phenotypic similarity, and classify novel compounds by comparing them to phenotypically active exemplars. Hierarchical clustering applied to 154 compounds from over a dozen different mechanistic classes demonstrated tight agreement with published compound mechanism classification. Using 11 phenotypically active mechanism classes, classification was performed on all 154 compounds: 78% were correctly identified as belonging to one of the 11 exemplar classes or to a different unspecified class, with accuracy increasing to 89% when less phenotypically active compounds were excluded. Importantly, several apparent clustering and classification failures, including rigosertib and 5-fluoro-2'-deoxycytidine, instead revealed more complex mechanisms or off-target effects verified by more recent publications. These results show that a simple, easily replicated, minimalist high-content assay can reveal subtle variations in the cellular phenotype induced by compounds and can correctly predict mechanism of action, as long as the appropriate analytical tools are used.
Using Clustering to Establish Climate Regimes from PCM Output
NASA Technical Reports Server (NTRS)
Oglesby, Robert; Arnold, James E. (Technical Monitor); Hoffman, Forrest; Hargrove, W. W.; Erickson, D.
2002-01-01
A multivariate statistical clustering technique--based on the k-means algorithm of Hartigan has been used to extract patterns of climatological significance from 200 years of general circulation model (GCM) output. Originally developed and implemented on a Beowulf-style parallel computer constructed by Hoffman and Hargrove from surplus commodity desktop PCs, the high performance parallel clustering algorithm was previously applied to the derivation of ecoregions from map stacks of 9 and 25 geophysical conditions or variables for the conterminous U.S. at a resolution of 1 sq km. Now applied both across space and through time, the clustering technique yields temporally-varying climate regimes predicted by transient runs of the Parallel Climate Model (PCM). Using a business-as-usual (BAU) scenario and clustering four fields of significance to the global water cycle (surface temperature, precipitation, soil moisture, and snow depth) from 1871 through 2098, the authors' analysis shows an increase in spatial area occupied by the cluster or climate regime which typifies desert regions (i.e., an increase in desertification) and a decrease in the spatial area occupied by the climate regime typifying winter-time high latitude perma-frost regions. The patterns of cluster changes have been analyzed to understand the predicted variability in the water cycle on global and continental scales. In addition, representative climate regimes were determined by taking three 10-year averages of the fields 100 years apart for northern hemisphere winter (December, January, and February) and summer (June, July, and August). The result is global maps of typical seasonal climate regimes for 100 years in the past, for the present, and for 100 years into the future. Using three-dimensional data or phase space representations of these climate regimes (i.e., the cluster centroids), the authors demonstrate the portion of this phase space occupied by the land surface at all points in space and time. Any single spot on the globe will exist in one of these climate regimes at any single point in time. By incrementing time, that same spot will trace out a trajectory or orbit between and among these climate regimes (or atmospheric states) in phase (or state) space. When a geographic region enters a state it never previously visited, a climatic change is said to have occurred. Tracing out the entire trajectory of a single spot on the globe yields a 'manifold' in state space representing the shape of its predicted climate occupancy. This sort of analysis enables a researcher to more easily grasp the multivariate behavior of the climate system.
NASA Astrophysics Data System (ADS)
Miura, Yasunari; Sugiyama, Yuki
2017-12-01
We present a general method for analyzing macroscopic collective phenomena observed in many-body systems. For this purpose, we employ diffusion maps, which are one of the dimensionality-reduction techniques, and systematically define a few relevant coarse-grained variables for describing macroscopic phenomena. The time evolution of macroscopic behavior is described as a trajectory in the low-dimensional space constructed by these coarse variables. We apply this method to the analysis of the traffic model, called the optimal velocity model, and reveal a bifurcation structure, which features a transition to the emergence of a moving cluster as a traffic jam.
Computational Approaches to Simulation and Optimization of Global Aircraft Trajectories
NASA Technical Reports Server (NTRS)
Ng, Hok Kwan; Sridhar, Banavar
2016-01-01
This study examines three possible approaches to improving the speed in generating wind-optimal routes for air traffic at the national or global level. They are: (a) using the resources of a supercomputer, (b) running the computations on multiple commercially available computers and (c) implementing those same algorithms into NASAs Future ATM Concepts Evaluation Tool (FACET) and compares those to a standard implementation run on a single CPU. Wind-optimal aircraft trajectories are computed using global air traffic schedules. The run time and wait time on the supercomputer for trajectory optimization using various numbers of CPUs ranging from 80 to 10,240 units are compared with the total computational time for running the same computation on a single desktop computer and on multiple commercially available computers for potential computational enhancement through parallel processing on the computer clusters. This study also re-implements the trajectory optimization algorithm for further reduction of computational time through algorithm modifications and integrates that with FACET to facilitate the use of the new features which calculate time-optimal routes between worldwide airport pairs in a wind field for use with existing FACET applications. The implementations of trajectory optimization algorithms use MATLAB, Python, and Java programming languages. The performance evaluations are done by comparing their computational efficiencies and based on the potential application of optimized trajectories. The paper shows that in the absence of special privileges on a supercomputer, a cluster of commercially available computers provides a feasible approach for national and global air traffic system studies.
Differential Decomposition Among Pig, Rabbit, and Human Remains.
Dautartas, Angela; Kenyhercz, Michael W; Vidoli, Giovanna M; Meadows Jantz, Lee; Mundorff, Amy; Steadman, Dawnie Wolfe
2018-03-30
While nonhuman animal remains are often utilized in forensic research to develop methods to estimate the postmortem interval, systematic studies that directly validate animals as proxies for human decomposition are lacking. The current project compared decomposition rates among pigs, rabbits, and humans at the University of Tennessee's Anthropology Research Facility across three seasonal trials that spanned nearly 2 years. The Total Body Score (TBS) method was applied to quantify decomposition changes and calculate the postmortem interval (PMI) in accumulated degree days (ADD). Decomposition trajectories were analyzed by comparing the estimated and actual ADD for each seasonal trial and by fuzzy cluster analysis. The cluster analysis demonstrated that the rabbits formed one group while pigs and humans, although more similar to each other than either to rabbits, still showed important differences in decomposition patterns. The decomposition trends show that neither nonhuman model captured the pattern, rate, and variability of human decomposition. © 2018 American Academy of Forensic Sciences.
Greater-than-bulk melting temperatures explained: Gallium melts Gangnam style
NASA Astrophysics Data System (ADS)
Gaston, Nicola; Steenbergen, Krista
2014-03-01
The experimental discovery of superheating in gallium clusters contradicted the clear and well-demonstrated paradigm that the melting temperature of a particle should decrease with its size. However the extremely sensitive dependence of melting temperature on size also goes to the heart of cluster science, and the interplay between the effects of electronic and geometric structure. We have performed extensive first-principles molecular dynamics calculations, incorporating parallel tempering for an efficient exploration of configurational phase space. This is necessary, due to the complicated energy landscape of gallium. In the nanoparticles, melting is preceded by a transitions between phases. A structural feature, referred to here as the Gangnam motif, is found to increase with the latent heat and appears throughout the observed phase changes of this curious metal. We will present our detailed analysis of the solid-state isomers, performed using extensive statistical sampling of the trajectory data for the assignment of cluster structures to known phases of gallium. Finally, we explain the greater-than-bulk melting through analysis of the factors that stabilise the liquid structures.
Collision-induced evaporation of water clusters and contribution of momentum transfer
NASA Astrophysics Data System (ADS)
Calvo, Florent; Berthias, Francis; Feketeová, Linda; Abdoul-Carime, Hassan; Farizon, Bernadette; Farizon, Michel
2017-05-01
The evaporation of water molecules from high-velocity argon atoms impinging on protonated water clusters has been computationally investigated using molecular dynamics simulations with the reactive OSS2 potential to model water clusters and the ZBL pair potential to represent their interaction with the projectile. Swarms of trajectories and an event-by-event analysis reveal the conditions under which a specific number of molecular evaporation events is found one nanosecond after impact, thereby excluding direct knockout events from the analysis. These simulations provide velocity distributions that exhibit two main features, with a major statistical component arising from a global redistribution of the collision energy into intermolecular degrees of freedom, and another minor but non-ergodic feature at high velocities. The latter feature is produced by direct impacts on the peripheral water molecules and reflects a more complete momentum transfer. These two components are consistent with recent experimental measurements and confirm that electronic processes are not explicitly needed to explain the observed non-ergodic behavior. Contribution to the Topical Issue "Dynamics of Systems at the Nanoscale", edited by Andrey Solov'yov and Andrei Korol.
Dental caries clusters among adolescents.
Warren, John J; Van Buren, John M; Levy, Steven M; Marshall, Teresa A; Cavanaugh, Joseph E; Curtis, Alexandra M; Kolker, Justine L; Weber-Gasparoni, Karin
2017-12-01
There have been very few longitudinal studies of dental caries in adolescents, and little study of the caries risk factors in this age group. The purpose of this study was to describe different caries trajectories and associated risk factors among members of the Iowa Fluoride Study (IFS) cohort. The IFS recruited a birth cohort from 1992 to 1995, and has gathered dietary, fluoride and behavioural data at least twice yearly since recruitment. Examinations for dental caries were completed when participants were ages 5, 9, 13 and 17 years. For this study, only participants with decayed and filled surface (DFS) caries data at ages 9, 13 and 17 were included (N=396). The individual DFS counts at age 13 and the DFS increment from 13 to 17 were used to identify distinct caries trajectories using Ward's hierarchical clustering algorithm. A number of multinomial logistic regression models were developed to predict trajectory membership, using longitudinal dietary, fluoride and demographic/behavioural data from 9 to 17 years. Model selection was based on the akaike information criterion (AIC). Several different trajectory schemes were considered, and a three-trajectory scheme-no DFS at age 17 (n=142), low DFS (n=145) and high DFS (n=109)-was chosen to balance sample sizes and interpretability. The model selection process resulted in use of an arithmetic average for dietary variables across the period from 9 to 17 years. The multinomial logistic regression model with the best fit included the variables maternal education level, 100% juice consumption, brushing frequency and sex. Other favoured models also included water and milk consumption and home water fluoride concentration. The high caries cluster was most consistently associated with lower maternal education level, lower 100% juice consumption, lower brushing frequency and being female. The use of a clustering algorithm and use of Akaike's Information Criterion (AIC) to determine the best representation of the data were useful means in presenting longitudinal caries data. Findings suggest that high caries incidence in adolescence is associated with lower maternal educational level, less frequent tooth brushing, lower 100% juice consumption and being female. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Study on the effect of sink moving trajectory on wireless sensor networks
NASA Astrophysics Data System (ADS)
Zhong, Peijun; Ruan, Feng
2018-03-01
Wireless sensor networks are developing very fast in recent years, due to their wide potential applications. However there exists the so-called hot spot problem, namely the nodes close to static sink node tend to die earlier than other nodes since they have heavier burden to forward. The introduction of mobile sink node can effectively alleviate this problem since sink node can move along certain trajectories, causing hot spot nodes more evenly distributed. In this paper, we make extensive experimental simulations for circular sensor network, with one mobile sink moving along different radius circumference. The whole network is divided into several clusters and there is one cluster head (CH) inside each cluster. The ordinary sensors communicate with CH and CHs construct a chain until the sink node. Simulation results show that the best network performance appears when sink moves along 0.25 R in terms of network lifetime.
Aerosols in Northern Morocco: Input pathways and their chemical fingerprint
NASA Astrophysics Data System (ADS)
Benchrif, A.; Guinot, B.; Bounakhla, M.; Cachier, H.; Damnati, B.; Baghdad, B.
2018-02-01
The Mediterranean basin is one of the most sensitive regions in the world regarding climate change and air quality. Deserts and marine aerosols combine with combustion aerosols from maritime traffic, large urban centers, and at a larger scale from populated industrialized regions in Europe. From Tetouan city located in the North of Morocco, we attempted to better figure out the main aerosol transport pathways and their respective aerosol load and chemical profile by examining air mass back trajectory patterns and aerosol chemical compositions from May 2011 to April 2012. The back trajectory analysis throughout the sampling period led to four clusters, for which meteorological conditions and aerosol chemical characteristics have been investigated. The most frequent cluster (CL3: 39%) corresponds to polluted air masses coming from the Mediterranean Basin, characterized by urban and marine vessels emissions out of Spain and of Northern Africa. Two other polluted clusters were characterized. One is of local origin (CL1: 22%), with a marked contribution from urban aerosols (Rabat, Casablanca) and from biomass burning aerosols. The second (CL2: 32%) defines air masses from the near Atlantic Ocean, affected by pollutants emitted from the Iberian coast. A fourth cluster (CL4: 7%) is characterized by rather clean, fast and rainy oceanic air masses, influenced during their last 24 h before reaching Tetouan by similar sources with those affecting CL2, but to a lesser extent. The chemical data show that carbonaceous species are found in the fine aerosols fraction and are generally from local primary sources (low OC/EC) rather than long-range transported. In addition to fresh traffic and maritime vessel aerosols, our results suggest the contribution of local biomass burning.
Scaling of cluster growth for coagulating active particles
NASA Astrophysics Data System (ADS)
Cremer, Peet; Löwen, Hartmut
2014-02-01
Cluster growth in a coagulating system of active particles (such as microswimmers in a solvent) is studied by theory and simulation. In contrast to passive systems, the net velocity of a cluster can have various scalings dependent on the propulsion mechanism and alignment of individual particles. Additionally, the persistence length of the cluster trajectory typically increases with size. As a consequence, a growing cluster collects neighboring particles in a very efficient way and thus amplifies its growth further. This results in unusual large growth exponents for the scaling of the cluster size with time and, for certain conditions, even leads to "explosive" cluster growth where the cluster becomes macroscopic in a finite amount of time.
Semantic-based surveillance video retrieval.
Hu, Weiming; Xie, Dan; Fu, Zhouyu; Zeng, Wenrong; Maybank, Steve
2007-04-01
Visual surveillance produces large amounts of video data. Effective indexing and retrieval from surveillance video databases are very important. Although there are many ways to represent the content of video clips in current video retrieval algorithms, there still exists a semantic gap between users and retrieval systems. Visual surveillance systems supply a platform for investigating semantic-based video retrieval. In this paper, a semantic-based video retrieval framework for visual surveillance is proposed. A cluster-based tracking algorithm is developed to acquire motion trajectories. The trajectories are then clustered hierarchically using the spatial and temporal information, to learn activity models. A hierarchical structure of semantic indexing and retrieval of object activities, where each individual activity automatically inherits all the semantic descriptions of the activity model to which it belongs, is proposed for accessing video clips and individual objects at the semantic level. The proposed retrieval framework supports various queries including queries by keywords, multiple object queries, and queries by sketch. For multiple object queries, succession and simultaneity restrictions, together with depth and breadth first orders, are considered. For sketch-based queries, a method for matching trajectories drawn by users to spatial trajectories is proposed. The effectiveness and efficiency of our framework are tested in a crowded traffic scene.
Recent increased identification and transmission of HIV-1 unique recombinant forms in Sweden.
Neogi, Ujjwal; Siddik, Abu Bakar; Kalaghatgi, Prabhav; Gisslén, Magnus; Bratt, Göran; Marrone, Gaetano; Sönnerborg, Anders
2017-07-25
A temporal increase in non-B subtypes has earlier been described in Sweden by us and we hypothesized that this increased viral heterogeneity may become a hotspot for the development of more complex and unique recombinant forms (URFs) if the epidemics converge. In the present study, we performed subtyping using four automated tools and phylogenetic analysis by RAxML of pol gene sequences (n = 5246) and HIV-1 near full-length genome (HIV-NFLG) sequences (n = 104). A CD4 + T-cell decline trajectory algorithm was used to estimate time of HIV infection. Transmission clusters were identified using the family-joining method. The analysis of HIV-NFLG and pol gene described 10.6% (11/104) and 2.6% (137/5246) of the strains as URFs, respectively. An increasing trend of URFs was observed in recent years by both approaches (p = 0·0082; p < 0·0001). Transmission cluster analysis using the pol gene of all URFs identified 14 clusters with two to eight sequences. Larger transmission clusters of URFs (BF1 and 01B) were observed among MSM who mostly were sero-diagnosed in recent time. Understanding the increased appearance and transmission of URFs in recent years could have importance for public health interventions and the use of HIV-NFLG would provide better statistical support for such assessments.
Terminal-Area Aircraft Intent Inference Approach Based on Online Trajectory Clustering.
Yang, Yang; Zhang, Jun; Cai, Kai-quan
2015-01-01
Terminal-area aircraft intent inference (T-AII) is a prerequisite to detect and avoid potential aircraft conflict in the terminal airspace. T-AII challenges the state-of-the-art AII approaches due to the uncertainties of air traffic situation, in particular due to the undefined flight routes and frequent maneuvers. In this paper, a novel T-AII approach is introduced to address the limitations by solving the problem with two steps that are intent modeling and intent inference. In the modeling step, an online trajectory clustering procedure is designed for recognizing the real-time available routes in replacing of the missed plan routes. In the inference step, we then present a probabilistic T-AII approach based on the multiple flight attributes to improve the inference performance in maneuvering scenarios. The proposed approach is validated with real radar trajectory and flight attributes data of 34 days collected from Chengdu terminal area in China. Preliminary results show the efficacy of the presented approach.
2018-01-01
Objectives We examine to what extent the effect of early-life conditions (health and socioeconomic status) on health in later life is mediated by educational attainment and life-course trajectories (fertility, partnership, employment). Methods Using data from the Survey of Health, Ageing and Retirement in Europe (N = 12,034), we apply, separately by gender, multichannel sequence analysis and cluster analysis to obtain groups of similar family and employment histories. The KHB method is used to disentangle direct and indirect effects of early-life conditions on health. Results Early-life-conditions indirectly impact on health in later life as result of their influence on education and family and employment trajectories. For example, between 22% and 42% of the effect of low parental socio-economic status at childhood on the three considered health outcomes at older age is explained by educational attainment for women. Even higher percentages are found for men (35% - 57%). On the contrary, the positive effect of poor health at childhood on poor health at older ages is not significantly mediated by education and life-course trajectories. Education captures most of the mediating effect of parental socio-economic status. More specifically, between 66% and 75% of the indirect effect of low parental socio-economic status at childhood on the three considered health outcomes at older age is explained by educational attainment for women. Again, higher percentages are found for men (86% - 93%). Early-life conditions, especially socioeconomic status, influence family and employment trajectories indirectly through their impact on education. We also find a persistent direct impact of early-life conditions on health at older ages. Conclusions Our findings demonstrate that early-life experiences influence education and life-course trajectories and health in later life, suggesting that public investments in children are expected to produce long lasting effects on people’s lives throughout the different phases of their life-course. PMID:29621290
Arpino, Bruno; Gumà, Jordi; Julià, Albert
2018-01-01
We examine to what extent the effect of early-life conditions (health and socioeconomic status) on health in later life is mediated by educational attainment and life-course trajectories (fertility, partnership, employment). Using data from the Survey of Health, Ageing and Retirement in Europe (N = 12,034), we apply, separately by gender, multichannel sequence analysis and cluster analysis to obtain groups of similar family and employment histories. The KHB method is used to disentangle direct and indirect effects of early-life conditions on health. Early-life-conditions indirectly impact on health in later life as result of their influence on education and family and employment trajectories. For example, between 22% and 42% of the effect of low parental socio-economic status at childhood on the three considered health outcomes at older age is explained by educational attainment for women. Even higher percentages are found for men (35% - 57%). On the contrary, the positive effect of poor health at childhood on poor health at older ages is not significantly mediated by education and life-course trajectories. Education captures most of the mediating effect of parental socio-economic status. More specifically, between 66% and 75% of the indirect effect of low parental socio-economic status at childhood on the three considered health outcomes at older age is explained by educational attainment for women. Again, higher percentages are found for men (86% - 93%). Early-life conditions, especially socioeconomic status, influence family and employment trajectories indirectly through their impact on education. We also find a persistent direct impact of early-life conditions on health at older ages. Our findings demonstrate that early-life experiences influence education and life-course trajectories and health in later life, suggesting that public investments in children are expected to produce long lasting effects on people's lives throughout the different phases of their life-course.
Clark, Caron A C; Fang, Hua; Espy, Kimberly Andrews; Filipek, Pauline A; Juranek, Jenifer; Bangert, Barbara; Hack, Maureen; Taylor, H Gerry
2013-05-01
This study examined the relation of cerebral tissue reductions associated with VLBW to patterns of growth in core academic domains. Children born <750 g, 750 to 1,499 g, or >2,500 g completed measures of calculation, mathematical problem solving, and word decoding at time points spanning middle childhood and adolescence. K. A. Espy, H. Fang, D. Charak, N. M. Minich, and H. G. Taylor (2009, Growth mixture modeling of academic achievement in children of varying birth weight risk, Neuropsychology, Vol. 23, pp. 460-474) used growth mixture modeling to identify two growth trajectories (clusters) for each academic domain: an average achievement trajectory and a persistently low trajectory. In this study, 97 of the same participants underwent magnetic resonance imaging (MRI) in late adolescence, and cerebral tissue volumes were used to predict the probability of low growth cluster membership for each domain. Adjusting for whole brain volume (wbv), each 1-cm(3) reduction in caudate volume was associated with a 1.7- to 2.1-fold increase in the odds of low cluster membership for each domain. Each 1-mm(2) decrease in corpus callosum surface area increased these odds approximately 1.02-fold. Reduced cerebellar white matter volume was associated specifically with low calculation and decoding growth, and reduced cerebral white matter volume was associated with low calculation growth. Findings were similar when analyses were confined to the VLBW groups. Reduced volume of structures involved in connectivity, executive attention, and motor control may contribute to heterogeneous academic trajectories among children with VLBW.
NASA Astrophysics Data System (ADS)
Mahura, A. G.; Baklanov, A. A.
2003-10-01
The probabilistic analysis of atmospheric transport patterns from most important nuclear risk sites in the Euro-Arctic region is performed employing the methodology developed within the "Arctic Risk" Project of the NARP Programme (Baklanov and Mahura, 2003). The risk sites are the nuclear power plants in the Northwest Russia, Finland, Sweden, Lithuania, United Kingdom, and Germany as well as the Novaya Zemlya test site of Russia. The geographical regions of interest are the Northern and Central European countries and Northwest Russia. In this study, the employed research tools are the trajectory model to calculate a multiyear dataset of forward trajectories that originated over the risk site locations, and a set of statistical methods (including exploratory, cluster, and probability fields analyses) for analysis of trajectory modelling results. The probabilistic analyses of trajectory modelling results for eleven sites are presented as a set of various indicators of the risk sites possible impact on geographical regions and countries of interest. The nuclear risk site possible impact (on a particular geographical region, territory, country, site, etc.) due to atmospheric transport from the site after hypothetical accidental release of radioactivity can be properly estimated based on a combined interpretation of the indicators (simple characteristics, atmospheric transport pathways, airflow and fast transport probability fields, maximum reaching distance and maximum possible impact zone, typical transport time and precipitation factor fields) for different time periods (annual, seasonal, and monthly) for any selected site (both separately for each site or grouped for several sites) in the Euro-Arctic region. Such estimation could be the useful input information for the decision-making process, risk assessment, and planning of emergency response systems for sites of nuclear, chemical, and biological danger.
A system for learning statistical motion patterns.
Hu, Weiming; Xiao, Xuejuan; Fu, Zhouyu; Xie, Dan; Tan, Tieniu; Maybank, Steve
2006-09-01
Analysis of motion patterns is an effective approach for anomaly detection and behavior prediction. Current approaches for the analysis of motion patterns depend on known scenes, where objects move in predefined ways. It is highly desirable to automatically construct object motion patterns which reflect the knowledge of the scene. In this paper, we present a system for automatically learning motion patterns for anomaly detection and behavior prediction based on a proposed algorithm for robustly tracking multiple objects. In the tracking algorithm, foreground pixels are clustered using a fast accurate fuzzy K-means algorithm. Growing and prediction of the cluster centroids of foreground pixels ensure that each cluster centroid is associated with a moving object in the scene. In the algorithm for learning motion patterns, trajectories are clustered hierarchically using spatial and temporal information and then each motion pattern is represented with a chain of Gaussian distributions. Based on the learned statistical motion patterns, statistical methods are used to detect anomalies and predict behaviors. Our system is tested using image sequences acquired, respectively, from a crowded real traffic scene and a model traffic scene. Experimental results show the robustness of the tracking algorithm, the efficiency of the algorithm for learning motion patterns, and the encouraging performance of algorithms for anomaly detection and behavior prediction.
NASA Astrophysics Data System (ADS)
Mozaffari, Ahmad; Vajedi, Mahyar; Azad, Nasser L.
2015-06-01
The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.
Species collapse via hybridization in Darwin's tree finches.
Kleindorfer, Sonia; O'Connor, Jody A; Dudaniec, Rachael Y; Myers, Steven A; Robertson, Jeremy; Sulloway, Frank J
2014-03-01
Species hybridization can lead to fitness costs, species collapse, and novel evolutionary trajectories in changing environments. Hybridization is predicted to be more common when environmental conditions change rapidly. Here, we test patterns of hybridization in three sympatric tree finch species (small tree finch Camarhynchus parvulus, medium tree finch Camarhynchus pauper, and large tree finch: Camarhynchus psittacula) that are currently recognized on Floreana Island, Galápagos Archipelago. Genetic analysis of microsatellite data from contemporary samples showed two genetic populations and one hybrid cluster in both 2005 and 2010; hybrid individuals were derived from genetic population 1 (small morph) and genetic population 2 (large morph). Females of the large and rare species were more likely to pair with males of the small common species. Finch populations differed in morphology in 1852-1906 compared with 2005/2010. An unsupervised clustering method showed (a) support for three morphological clusters in the historical tree finch sample (1852-1906), which is consistent with current species recognition; (b) support for two or three morphological clusters in 2005 with some (19%) hybridization; and (c) support for just two morphological clusters in 2010 with frequent (41%) hybridization. We discuss these findings in relation to species demarcations of Camarhynchus tree finches on Floreana Island.
Kasahara, Kota; Kinoshita, Kengo
2016-01-01
Ion conduction mechanisms of ion channels are a long-standing conundrum. Although the molecular dynamics (MD) method has been extensively used to simulate ion conduction dynamics at the atomic level, analysis and interpretation of MD results are not straightforward due to complexity of the dynamics. In our previous reports, we proposed an analytical method called ion-binding state analysis to scrutinize and summarize ion conduction mechanisms by taking advantage of a variety of analytical protocols, e.g., the complex network analysis, sequence alignment, and hierarchical clustering. This approach effectively revealed the ion conduction mechanisms and their dependence on the conditions, i.e., ion concentration and membrane voltage. Here, we present an easy-to-use computational toolkit for ion-binding state analysis, called IBiSA_tools. This toolkit consists of a C++ program and a series of Python and R scripts. From the trajectory file of MD simulations and a structure file, users can generate several images and statistics of ion conduction processes. A complex network named ion-binding state graph is generated in a standard graph format (graph modeling language; GML), which can be visualized by standard network analyzers such as Cytoscape. As a tutorial, a trajectory of a 50 ns MD simulation of the Kv1.2 channel is also distributed with the toolkit. Users can trace the entire process of ion-binding state analysis step by step. The novel method for analysis of ion conduction mechanisms of ion channels can be easily used by means of IBiSA_tools. This software is distributed under an open source license at the following URL: http://www.ritsumei.ac.jp/~ktkshr/ibisa_tools/.
Analysis of the structure and dynamics of human serum albumin.
Guizado, T R Cuya
2014-10-01
Human serum albumin (HSA) is a biologically relevant protein that binds a variety of drugs and other small molecules. No less than 50 structures are deposited in the RCSB Protein Data Bank (PDB). Based on these structures, we first performed a clustering analysis. Despite the diversity of ligands, only two well defined conformations are detected, with a deviation of 0.46 nm between the average structures of the two clusters, while deviations within each cluster are smaller than 0.08 nm. Those two conformations are representative of the apoprotein and the HSA-myristate complex already identified in previous literature. Considering the structures within each cluster as a representative sample of the dynamical states of the corresponding conformation, we scrutinize the structural and dynamical differences between both conformations. Analysis of the fluctuations within each cluster set reveals that domain II is the most rigid one and better matches both structures. Then, taking this domain as reference, we show that the structural difference between both conformations can be expressed in terms of twist and hinge motions of domains I and III, respectively. We also characterize the dynamical difference between conformations by computing correlations and principal components for each set of dynamical states. The two conformations display different collective motions. The results are compared with those obtained from the trajectories of short molecular dynamics simulations, giving consistent outcomes. Let us remark that, beyond the relevance of the results for the structural and dynamical characterization of HAS conformations, the present methodology could be extended to other proteins in the PDB archive.
Bricker, Jonathan B; Sridharan, Vasundhara; Zhu, Yifan; Mull, Kristin E; Heffner, Jaimee L; Watson, Noreen L; McClure, Jennifer B; Di, Chongzhi
2018-04-20
Little is known about how individuals engage with electronic health (eHealth) interventions over time and whether this engagement predicts health outcomes. The objectives of this study, by using the example of a specific type of eHealth intervention (ie, websites for smoking cessation), were to determine (1) distinct groups of log-in trajectories over a 12-month period, (2) their association with smoking cessation, and (3) baseline user characteristics that predict trajectory group membership. We conducted a functional clustering analysis of 365 consecutive days of log-in data from both arms of a large (N=2637) randomized trial of 2 website interventions for smoking cessation (WebQuit and Smokefree), with a primary outcome of 30-day point prevalence smoking abstinence at 12 months. We conducted analyses for each website separately. A total of 3 distinct trajectory groups emerged for each website. For WebQuit, participants were clustered into 3 groups: 1-week users (682/1240, 55.00% of the sample), 5-week users (399/1240, 32.18%), and 52-week users (159/1240, 12.82%). Compared with the 1-week users, the 5- and 52-week users had 57% higher odds (odds ratio [OR] 1.57, 95% CI 1.13-2.17; P=.007) and 124% higher odds (OR 2.24, 95% CI 1.45-3.43; P<.001), respectively, of being abstinent at 12 months. Smokefree users were clustered into 3 groups: 1-week users (645/1309, 49.27% of the sample), 4-week users (395/1309, 30.18%), and 5-week users (269/1309, 20.55%). Compared with the 1-week users, 5-week users (but not 4-week users; P=.99) had 48% higher odds (OR 1.48, 95% CI 1.05-2.07; P=.02) of being abstinent at 12 months. In general, the WebQuit intervention had a greater number of weekly log-ins within each of the 3 trajectory groups as compared with those of the Smokefree intervention. Baseline characteristics associated with trajectory group membership varied between websites. Patterns of 1-, 4-, and 5-week usage of websites may be common for how people engage in eHealth interventions. The 5-week usage of either website, and 52-week usage only of WebQuit, predicted a higher odds of quitting smoking. Strategies to increase eHealth intervention engagement for 4 more weeks (ie, from 1 week to 5 weeks) could be highly cost effective. ClinicalTrials.gov NCT01812278; https://www.clinicaltrials.gov/ct2/show/NCT01812278 (Archived by WebCite at http://www.webcitation.org/6yPO2OIKR). ©Jonathan B Bricker, Vasundhara Sridharan, Yifan Zhu, Kristin E Mull, Jaimee L Heffner, Noreen L Watson, Jennifer B McClure, Chongzhi Di. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 20.04.2018.
NASA Astrophysics Data System (ADS)
Guillen, George; Rainey, Gail; Morin, Michelle
2004-04-01
Currently, the Minerals Management Service uses the Oil Spill Risk Analysis model (OSRAM) to predict the movement of potential oil spills greater than 1000 bbl originating from offshore oil and gas facilities. OSRAM generates oil spill trajectories using meteorological and hydrological data input from either actual physical measurements or estimates generated from other hydrological models. OSRAM and many other models produce output matrices of average, maximum and minimum contact probabilities to specific landfall or target segments (columns) from oil spills at specific points (rows). Analysts and managers are often interested in identifying geographic areas or groups of facilities that pose similar risks to specific targets or groups of targets if a spill occurred. Unfortunately, due to the potentially large matrix generated by many spill models, this question is difficult to answer without the use of data reduction and visualization methods. In our study we utilized a multivariate statistical method called cluster analysis to group areas of similar risk based on potential distribution of landfall target trajectory probabilities. We also utilized ArcView™ GIS to display spill launch point groupings. The combination of GIS and multivariate statistical techniques in the post-processing of trajectory model output is a powerful tool for identifying and delineating areas of similar risk from multiple spill sources. We strongly encourage modelers, statistical and GIS software programmers to closely collaborate to produce a more seamless integration of these technologies and approaches to analyzing data. They are complimentary methods that strengthen the overall assessment of spill risks.
Arnold, L Eugene; Ganocy, Stephen J; Mount, Katherine; Youngstrom, Eric A; Frazier, Thomas; Fristad, Mary; Horwitz, Sarah M; Birmaher, Boris; Findling, Robert; Kowatch, Robert A; Demeter, Christine; Axelson, David; Gill, Mary Kay; Marsh, Linda
2014-07-01
This study aims to examine trajectories of attention-deficit/hyperactivity disorder (ADHD) symptoms in the Longitudinal Assessment of Manic Symptoms (LAMS) sample. The LAMS study assessed 684 children aged 6 to 12 years with the Kiddie-Schedule for Affective Disorders and Schizophrenia (K-SADS) and rating scales semi-annually for 3 years. Although they were selected for elevated manic symptoms, 526 children had baseline ADHD diagnoses. With growth mixture modeling (GMM), we separately analyzed inattentive and hyperactive/impulsive symptoms, covarying baseline age. Multiple standard methods determined optimal fit. The χ(2) and Kruskal-Wallis analysis of variance compared resulting latent classes/trajectories on clinical characteristics and medication. Three latent class trajectories best described inattentive symptoms, and 4 classes best described hyperactive/impulsive symptoms. Inattentive trajectories maintained their relative position over time. Hyperactive/impulsive symptoms had 2 consistent trajectories (least and most severe). A third trajectory (4.5%) started mild, then escalated; and a fourth (14%) started severe but improved dramatically. The improving trajectory was associated with the highest rate of ADHD and lowest rate of bipolar diagnoses. Three-fourths of the mildest inattention class were also in the mildest hyperactive/impulsive class; 72% of the severest inattentive class were in the severest hyperactive/impulsive class, but the severest inattention class also included 62% of the improving hyperactive-impulsive class. An ADHD rather than bipolar diagnosis prognosticates a better course of hyperactive/impulsive, but not inattentive, symptoms. High overlap of relative severity between inattention and hyperactivity/impulsivity confirms the link between these symptom clusters. Hyperactive/impulsive symptoms wane more over time. Group means are insufficient to understand individual ADHD prognosis. A small subgroup deteriorates over time in hyperactivity/impulsivity and needs better treatments than currently provided. Copyright © 2014 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.
Simulaid: a simulation facilitator and analysis program.
Mezei, Mihaly
2010-11-15
Simulaid performs a large number of simulation-related tasks: interconversion and modification of structure and trajectory files, optimization of orientation, and a large variety of analysis functions. The program can handle structures in PDB (Berman et al., Nucleic Acids Res 2000, 28, 235), Charmm (Brooks et al., J Comput Chem 4, 187) CRD, Amber (Case et al.), Macromodel (Mohamadi et al., J Comput Chem 1990, 11, 440), Gromos/Gromacs (Hess et al.), InsightII (InsightII. Accelrys Inc.: San Diego, 2005), Grasp (Nicholls et al., Proteins: Struct Funct Genet 1991, 11, 281) .crg, Tripos (Tripos International, S. H. R., St. Louis, MO) .mol2 (input only), and in the MMC (Mezei, M.; MMC: Monte Carlo program for molecular assemblies. Available at: http://inka.mssm.edu/~mezei/mmc) formats; and trajectories in the formats of Charmm, Amber, Macromodel, and MMC. Analysis features include (but are not limited to): (1) simple distance calculations and hydrogen-bond analysis, (2) calculation of 2-D RMSD maps (produced both as text file with the data and as a color-coded matrix) and cross RMSD maps between trajectories, (3) clustering based on RMSD maps, (4) analysis of torsion angles, Ramachandran (Ramachandran and Sasiskharan, Adv Protein Chem 1968, 23, 283) angles, proline kink (Visiers et al., Protein Eng 2000, 13, 603) angles, pseudorotational (Altona and Sundaralingam, J Am Chem Soc 1972, 94, 8205; Cremer and Pople, J Am Chem Soc 1975, 97, 1354) angles, and (5) analysis based on circular variance (Mezei, J Mol Graphics Model 2003, 21, 463). Torsion angle evolutions are presented in dial plots (Ravishanker et al., J Biomol Struct Dyn 1989, 6, 669). Several of these features are unique to Simulaid. 2010 Wiley Periodicals, Inc.
NASA Astrophysics Data System (ADS)
Laura, Jason; Skinner, James A.; Hunter, Marc A.
2017-08-01
In this paper we present the Large Crater Clustering (LCC) tool set, an ArcGIS plugin that supports the quantitative approximation of a primary impact location from user-identified locations of possible secondary impact craters or the long-axes of clustered secondary craters. The identification of primary impact craters directly supports planetary geologic mapping and topical science studies where the chronostratigraphic age of some geologic units may be known, but more distant features have questionable geologic ages. Previous works (e.g., McEwen et al., 2005; Dundas and McEwen, 2007) have shown that the source of secondary impact craters can be estimated from secondary impact craters. This work adapts those methods into a statistically robust tool set. We describe the four individual tools within the LCC tool set to support: (1) processing individually digitized point observations (craters), (2) estimating the directional distribution of a clustered set of craters, back projecting the potential flight paths (crater clusters or linearly approximated catenae or lineaments), (3) intersecting projected paths, and (4) intersecting back-projected trajectories to approximate the local of potential source primary craters. We present two case studies using secondary impact features mapped in two regions of Mars. We demonstrate that the tool is able to quantitatively identify primary impacts and supports the improved qualitative interpretation of potential secondary crater flight trajectories.
Cazade, Pierre-André; Berezovska, Ganna; Meuwly, Markus
2015-05-01
The nature of ligand motion in proteins is difficult to characterize directly using experiment. Specifically, it is unclear to what degree these motions are coupled. All-atom simulations are used to sample ligand motion in truncated Hemoglobin N. A transition network analysis including ligand- and protein-degrees of freedom is used to analyze the microscopic dynamics. Clustering of two different subsets of MD trajectories highlights the importance of a diverse and exhaustive description to define the macrostates for a ligand-migration network. Monte Carlo simulations on the transition matrices from one particular clustering are able to faithfully capture the atomistic simulations. Contrary to clustering by ligand positions only, including a protein degree of freedom yields considerably improved coarse grained dynamics. Analysis with and without imposing detailed balance agree closely which suggests that the underlying atomistic simulations are converged with respect to sampling transitions between neighboring sites. Protein and ligand dynamics are not independent from each other and ligand migration through globular proteins is not passive diffusion. Transition network analysis is a powerful tool to analyze and characterize the microscopic dynamics in complex systems. This article is part of a Special Issue entitled Recent developments of molecular dynamics. Copyright © 2014 Elsevier B.V. All rights reserved.
A parsimonious characterization of change in global age-specific and total fertility rates
2018-01-01
This study aims to understand trends in global fertility from 1950-2010 though the analysis of age-specific fertility rates. This approach incorporates both the overall level, as when the total fertility rate is modeled, and different patterns of age-specific fertility to examine the relationship between changes in age-specific fertility and fertility decline. Singular value decomposition is used to capture the variation in age-specific fertility curves while reducing the number of dimensions, allowing curves to be described nearly fully with three parameters. Regional patterns and trends over time are evident in parameter values, suggesting this method provides a useful tool for considering fertility decline globally. The second and third parameters were analyzed using model-based clustering to examine patterns of age-specific fertility over time and place; four clusters were obtained. A country’s demographic transition can be traced through time by membership in the different clusters, and regional patterns in the trajectories through time and with fertility decline are identified. PMID:29377899
Clinical interpretation of the Spinal Cord Injury Functional Index (SCI-FI)
Fyffe, Denise; Kalpakjian, Claire Z.; Slavin, Mary; Kisala, Pamela; Ni, Pengsheng; Kirshblum, Steven C.; Tulsky, David S.; Jette, Alan M.
2016-01-01
Objective: To provide validation of functional ability levels for the Spinal Cord Injury – Functional Index (SCI-FI). Design: Cross-sectional. Setting: Inpatient rehabilitation hospital and community settings. Participants: A sample of 855 individuals with traumatic spinal cord injury enrolled in 6 rehabilitation centers participating in the National Spinal Cord Injury Model Systems Network. Interventions: Not Applicable. Main Outcome Measures: Spinal Cord Injury-Functional Index (SCI-FI). Results: Cluster analyses identified three distinct groups that represent low, mid-range and high SCI-FI functional ability levels. Comparison of clusters on personal and other injury characteristics suggested some significant differences between groups. Conclusions: These results strongly support the use of SCI-FI functional ability levels to document the perceived functional abilities of persons with SCI. Results of the cluster analysis suggest that the SCI-FI functional ability levels capture function by injury characteristics. Clinical implications regarding tracking functional activity trajectories during follow-up visits are discussed. PMID:26781769
Huang, Yangxin; Lu, Xiaosun; Chen, Jiaqing; Liang, Juan; Zangmeister, Miriam
2017-10-27
Longitudinal and time-to-event data are often observed together. Finite mixture models are currently used to analyze nonlinear heterogeneous longitudinal data, which, by releasing the homogeneity restriction of nonlinear mixed-effects (NLME) models, can cluster individuals into one of the pre-specified classes with class membership probabilities. This clustering may have clinical significance, and be associated with clinically important time-to-event data. This article develops a joint modeling approach to a finite mixture of NLME models for longitudinal data and proportional hazard Cox model for time-to-event data, linked by individual latent class indicators, under a Bayesian framework. The proposed joint models and method are applied to a real AIDS clinical trial data set, followed by simulation studies to assess the performance of the proposed joint model and a naive two-step model, in which finite mixture model and Cox model are fitted separately.
Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions
NASA Astrophysics Data System (ADS)
Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard
2014-09-01
Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.
Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G., E-mail: yannis@princeton.edu, E-mail: gerhard.hummer@biophys.mpg.de
Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlapmore » with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space.« less
Cognitive Clusters in Specific Learning Disorder.
Poletti, Michele; Carretta, Elisa; Bonvicini, Laura; Giorgi-Rossi, Paolo
The heterogeneity among children with learning disabilities still represents a barrier and a challenge in their conceptualization. Although a dimensional approach has been gaining support, the categorical approach is still the most adopted, as in the recent fifth edition of the Diagnostic and Statistical Manual of Mental Disorders. The introduction of the single overarching diagnostic category of specific learning disorder (SLD) could underemphasize interindividual clinical differences regarding intracategory cognitive functioning and learning proficiency, according to current models of multiple cognitive deficits at the basis of neurodevelopmental disorders. The characterization of specific cognitive profiles associated with an already manifest SLD could help identify possible early cognitive markers of SLD risk and distinct trajectories of atypical cognitive development leading to SLD. In this perspective, we applied a cluster analysis to identify groups of children with a Diagnostic and Statistical Manual-based diagnosis of SLD with similar cognitive profiles and to describe the association between clusters and SLD subtypes. A sample of 205 children with a diagnosis of SLD were enrolled. Cluster analyses (agglomerative hierarchical and nonhierarchical iterative clustering technique) were used successively on 10 core subtests of the Wechsler Intelligence Scale for Children-Fourth Edition. The 4-cluster solution was adopted, and external validation found differences in terms of SLD subtype frequencies and learning proficiency among clusters. Clinical implications of these findings are discussed, tracing directions for further studies.
Diffusion maps, clustering and fuzzy Markov modeling in peptide folding transitions
Nedialkova, Lilia V.; Amat, Miguel A.; Kevrekidis, Ioannis G.; Hummer, Gerhard
2014-01-01
Using the helix-coil transitions of alanine pentapeptide as an illustrative example, we demonstrate the use of diffusion maps in the analysis of molecular dynamics simulation trajectories. Diffusion maps and other nonlinear data-mining techniques provide powerful tools to visualize the distribution of structures in conformation space. The resulting low-dimensional representations help in partitioning conformation space, and in constructing Markov state models that capture the conformational dynamics. In an initial step, we use diffusion maps to reduce the dimensionality of the conformational dynamics of Ala5. The resulting pretreated data are then used in a clustering step. The identified clusters show excellent overlap with clusters obtained previously by using the backbone dihedral angles as input, with small—but nontrivial—differences reflecting torsional degrees of freedom ignored in the earlier approach. We then construct a Markov state model describing the conformational dynamics in terms of a discrete-time random walk between the clusters. We show that by combining fuzzy C-means clustering with a transition-based assignment of states, we can construct robust Markov state models. This state-assignment procedure suppresses short-time memory effects that result from the non-Markovianity of the dynamics projected onto the space of clusters. In a comparison with previous work, we demonstrate how manifold learning techniques may complement and enhance informed intuition commonly used to construct reduced descriptions of the dynamics in molecular conformation space. PMID:25240340
Reactive Collision Avoidance Algorithm
NASA Technical Reports Server (NTRS)
Scharf, Daniel; Acikmese, Behcet; Ploen, Scott; Hadaegh, Fred
2010-01-01
The reactive collision avoidance (RCA) algorithm allows a spacecraft to find a fuel-optimal trajectory for avoiding an arbitrary number of colliding spacecraft in real time while accounting for acceleration limits. In addition to spacecraft, the technology can be used for vehicles that can accelerate in any direction, such as helicopters and submersibles. In contrast to existing, passive algorithms that simultaneously design trajectories for a cluster of vehicles working to achieve a common goal, RCA is implemented onboard spacecraft only when an imminent collision is detected, and then plans a collision avoidance maneuver for only that host vehicle, thus preventing a collision in an off-nominal situation for which passive algorithms cannot. An example scenario for such a situation might be when a spacecraft in the cluster is approaching another one, but enters safe mode and begins to drift. Functionally, the RCA detects colliding spacecraft, plans an evasion trajectory by solving the Evasion Trajectory Problem (ETP), and then recovers after the collision is avoided. A direct optimization approach was used to develop the algorithm so it can run in real time. In this innovation, a parameterized class of avoidance trajectories is specified, and then the optimal trajectory is found by searching over the parameters. The class of trajectories is selected as bang-off-bang as motivated by optimal control theory. That is, an avoiding spacecraft first applies full acceleration in a constant direction, then coasts, and finally applies full acceleration to stop. The parameter optimization problem can be solved offline and stored as a look-up table of values. Using a look-up table allows the algorithm to run in real time. Given a colliding spacecraft, the properties of the collision geometry serve as indices of the look-up table that gives the optimal trajectory. For multiple colliding spacecraft, the set of trajectories that avoid all spacecraft is rapidly searched on-line. The optimal avoidance trajectory is implemented as a receding-horizon model predictive control law. Therefore, at each time step, the optimal avoidance trajectory is found and the first time step of its acceleration is applied. At the next time step of the control computer, the problem is re-solved and the new first time step is again applied. This continual updating allows the RCA algorithm to adapt to a colliding spacecraft that is making erratic course changes.
Network-based study of Lagrangian transport and mixing
NASA Astrophysics Data System (ADS)
Padberg-Gehle, Kathrin; Schneide, Christiane
2017-10-01
Transport and mixing processes in fluid flows are crucially influenced by coherent structures and the characterization of these Lagrangian objects is a topic of intense current research. While established mathematical approaches such as variational methods or transfer-operator-based schemes require full knowledge of the flow field or at least high-resolution trajectory data, this information may not be available in applications. Recently, different computational methods have been proposed to identify coherent behavior in flows directly from Lagrangian trajectory data, that is, numerical or measured time series of particle positions in a fluid flow. In this context, spatio-temporal clustering algorithms have been proven to be very effective for the extraction of coherent sets from sparse and possibly incomplete trajectory data. Inspired by these recent approaches, we consider an unweighted, undirected network, where Lagrangian particle trajectories serve as network nodes. A link is established between two nodes if the respective trajectories come close to each other at least once in the course of time. Classical graph concepts are then employed to analyze the resulting network. In particular, local network measures such as the node degree, the average degree of neighboring nodes, and the clustering coefficient serve as indicators of highly mixing regions, whereas spectral graph partitioning schemes allow us to extract coherent sets. The proposed methodology is very fast to run and we demonstrate its applicability in two geophysical flows - the Bickley jet as well as the Antarctic stratospheric polar vortex.
Clark, Caron A. C.; Fang, Hua; Espy, Kimberly Andrews; Filipek, Pauline A.; Juranek, Jenifer; Bangert, Barbara; Hack, Maureen; Taylor, H. Gerry
2013-01-01
Objective Children with very low birth weight (VLBW; <1500g) are at risk for academic underachievement, although less is known regarding the developmental course of these difficulties or their neural basis. This study examined whether cerebral tissue reductions related to VLBW are associated with poor patterns of growth in core academic skills. Method Children born <750 g, 750–1499 g or >2500 g completed measures of calculation, mathematical problem solving and word decoding at several time points spanning middle childhood and adolescence. Espy, Fang, Charak, Minich and Taylor (2009) used growth mixture modeling to identify two distinct growth trajectories (growth clusters) for each academic domain: an average achievement trajectory and a persistently low achievement trajectory. In this study, 97 of the same participants underwent MRI in late adolescence. MRI measures of cerebral tissue volume were used to predict the probability of low growth cluster membership for each domain. Results After adjusting for whole brain volume, each 1cm3 reduction in caudate volume was associated with a 1.7 – 2.1 fold increase in the odds of low cluster membership for each academic domain. Each 1mm2 decrease in corpus callosum surface area increased these odds approximately 1.02 fold. Reductions in cerebellar white matter volume were associated specifically with low calculation and decoding growth while reduced cerebral white matter volume was associated with low calculation growth. Findings were similar when analyses were confined to the VLBW groups. Conclusions Volumetric reductions in neural regions involved in connectivity, executive attention and motor control may help to explain heterogeneous academic growth trajectories amongst children with VLBW. PMID:23688218
Carstens, J K P; Shaw, W S; Boersma, K; Reme, S E; Pransky, G; Linton, S J
2014-02-01
Expectations for recovery are a known predictor for returning to work. Most studies seem to conclude that the higher the expectancy the better the outcome. However, the development of expectations over time is rarely researched and experimental studies show that realistic expectations rather than high expectancies are the most adaptive. This study aims to explore patterns of stability and change in expectations for recovery during the first weeks of a back-pain episode and how these patterns relate to other psychological variables and outcome. The study included 496 volunteer patients seeking treatment for work-related, acute back pain. The participants were measured with self-report scales of depression, fear of pain, life impact of pain, catastrophizing and expectations for recovery at two time points. A follow-up focusing on recovery and return to work was conducted 3 months later. A cluster analysis was conducted, categorizing the data on the trajectories of recovery expectations. Cluster analysis revealed four clusters regarding the development of expectations for recovery during a 2-week period after pain onset. Three out of four clusters showed stability in their expectations as well as corresponding levels of proximal psychological factors. The fourth cluster showed increases in distress and a decrease in expectations for recovery. This cluster also has poor odds ratios for returning to work and recovery. Decreases in expectancies for recovery seem as important as baseline values in terms of outcome, which has clinical and theoretical implications. © 2013 European Pain Federation - EFIC®
A biologically inspired neural net for trajectory formation and obstacle avoidance.
Glasius, R; Komoda, A; Gielen, S C
1996-06-01
In this paper we present a biologically inspired two-layered neural network for trajectory formation and obstacle avoidance. The two topographically ordered neural maps consist of analog neurons having continuous dynamics. The first layer, the sensory map, receives sensory information and builds up an activity pattern which contains the optimal solution (i.e. shortest path without collisions) for any given set of current position, target positions and obstacle positions. Targets and obstacles are allowed to move, in which case the activity pattern in the sensory map will change accordingly. The time evolution of the neural activity in the second layer, the motor map, results in a moving cluster of activity, which can be interpreted as a population vector. Through the feedforward connections between the two layers, input of the sensory map directs the movement of the cluster along the optimal path from the current position of the cluster to the target position. The smooth trajectory is the result of the intrinsic dynamics of the network only. No supervisor is required. The output of the motor map can be used for direct control of an autonomous system in a cluttered environment or for control of the actuators of a biological limb or robot manipulator. The system is able to reach a target even in the presence of an external perturbation. Computer simulations of a point robot and a multi-joint manipulator illustrate the theory.
Gray and white matter changes and their relation to illness trajectory in first episode psychosis.
Keymer-Gausset, Alejandro; Alonso-Solís, Anna; Corripio, Iluminada; Sauras-Quetcuti, Rosa B; Pomarol-Clotet, Edith; Canales-Rodriguez, Erick J; Grasa-Bello, Eva; Álvarez, Enric; Portella, Maria J
2018-03-01
Previous works have studied structural brain characteristics in first-episode psychosis (FEP), but few have focused on the relation between brain differences and illness trajectories. The aim of this study is to analyze gray and white matter changes in FEP patients and their relation with one-year clinical outcomes. A sample of 41 FEP patients and 41 healthy controls (HC), matched by age and educational level was scanned with a 3T MRI during the first month of illness onset. One year later, patients were assigned to two illness trajectories (schizophrenia and non-schizophrenia). Voxel-based morphometry (VBM) was used for gray matter and Tract-based spatial statistics (TBSS) was used for white matter data analysis. VBM revealed significant and widespread bilateral gray matter density differences between FEP and HC groups in areas that included the right insular Cortex, the inferior frontal gyrus and orbito-frontal cortices, and segments of the occipital cortex. TBSS showed a significant lower fractional anisotropy (FA) in 8 clusters that included segments of the anterior thalamic radiation, the left body and forceps minor of corpus callosum, the right anterior segment of the inferior fronto-occipital fasciculus and the anterior segments of the cingulum. The sub-groups comparison revealed significant lower FA in the schizophrenia sub-group in two clusters: the anterior thalamic radiation and the anterior segment of left cingulum. These findings are coherent with previous morphology studies. The results suggest that gray and white matter abnormalities are present at early stages of the disease, and white matter differences may distinguish different illness prognosis. Copyright © 2018 Elsevier B.V. and ECNP. All rights reserved.
Ibrahim, George M; Morgan, Benjamin R; Lee, Wayne; Smith, Mary Lou; Donner, Elizabeth J; Wang, Frank; Beers, Craig A; Federico, Paolo; Taylor, Margot J; Doesburg, Sam M; Rutka, James T; Snead, O Carter
2014-11-01
Typical childhood development is characterized by the emergence of intrinsic connectivity networks (ICNs) by way of internetwork segregation and intranetwork integration. The impact of childhood epilepsy on the maturation of ICNs is, however, poorly understood. The developmental trajectory of ICNs in 26 children (8-17 years) with localization-related epilepsy and 28 propensity-score matched controls was evaluated using graph theoretical analysis of whole brain connectomes from resting-state functional magnetic resonance imaging (fMRI) data. Children with epilepsy demonstrated impaired development of regional hubs in nodes of the salience and default mode networks (DMN). Seed-based connectivity and hierarchical clustering analysis revealed significantly decreased intranetwork connections, and greater internetwork connectivity in children with epilepsy compared to controls. Significant interactions were identified between epilepsy duration and the expected developmental trajectory of ICNs, indicating that prolonged epilepsy may cause progressive alternations in large-scale networks throughout childhood. DMN integration was also associated with better working memory, whereas internetwork segregation was associated with higher full-scale intelligence quotient scores. Furthermore, subgroup analyses revealed the thalamus, hippocampus, and caudate were weaker hubs in children with secondarily generalized seizures, relative to other patient subgroups. Our findings underscore that epilepsy interferes with the developmental trajectory of brain networks underlying cognition, providing evidence supporting the early treatment of affected children. Copyright © 2014 Wiley Periodicals, Inc.
Evaluation of bacterial run and tumble motility parameters through trajectory analysis
NASA Astrophysics Data System (ADS)
Liang, Xiaomeng; Lu, Nanxi; Chang, Lin-Ching; Nguyen, Thanh H.; Massoudieh, Arash
2018-04-01
In this paper, a method for extraction of the behavior parameters of bacterial migration based on the run and tumble conceptual model is described. The methodology is applied to the microscopic images representing the motile movement of flagellated Azotobacter vinelandii. The bacterial cells are considered to change direction during both runs and tumbles as is evident from the movement trajectories. An unsupervised cluster analysis was performed to fractionate each bacterial trajectory into run and tumble segments, and then the distribution of parameters for each mode were extracted by fitting mathematical distributions best representing the data. A Gaussian copula was used to model the autocorrelation in swimming velocity. For both run and tumble modes, Gamma distribution was found to fit the marginal velocity best, and Logistic distribution was found to represent better the deviation angle than other distributions considered. For the transition rate distribution, log-logistic distribution and log-normal distribution, respectively, was found to do a better job than the traditionally agreed exponential distribution. A model was then developed to mimic the motility behavior of bacteria at the presence of flow. The model was applied to evaluate its ability to describe observed patterns of bacterial deposition on surfaces in a micro-model experiment with an approach velocity of 200 μm/s. It was found that the model can qualitatively reproduce the attachment results of the micro-model setting.
O’Connor, Erin Eileen; Supplee, Lauren
2017-01-01
The present study identified trajectories of teacher-child relationship conflict and closeness from first through sixth grades, and associations between these trajectories and externalizing and internalizing behaviors at age 11 among low-income, urban males (N = 262). There were three main findings. Nagin cluster analyses indicated five trajectories for conflict with all children evidencing increases in conflict, and four trajectories for closeness with all children demonstrating decreases in closeness. Trajectories with higher levels of conflict and lower levels of closeness were associated with higher levels of externalizing and internalizing behavior problems at age 11. Moreover, conflictual teacher-child relationships exacerbated the effects of externalizing and internalizing behavior problems in early childhood; children with conflictual teacher-child relationships had higher levels of behavior problems in middle childhood relative to children with low conflictual teacher-child relationships. Implications of targeting teacher-child relationships as interventions to help prevent behavior problems are discussed. PMID:29170565
Ultrafast photochemistry of methyl hydroperoxide on ice particles
Kamboures, M. A.; Nizkorodov, S. A.; Gerber, R. B.
2009-01-01
Simulations show that photodissociation of methyl hydroperoxide, CH3OOH, on water clusters produces a surprisingly wide range of products on a subpicosecond time scale, pointing to the possibility of complex photodegradation pathways for organic peroxides on aerosols and water droplets. Dynamics are computed at several excitation energies at 50 K using a semiempirical PM3 potential surface. CH3OOH is found to prefer the exterior of the cluster, with the CH3O group sticking out and the OH group immersed within the cluster. At atmospherically relevant photodissociation wavelengths the OH and CH3O photofragments remain at the surface of the cluster or embedded within it. However, none of the 25 completed trajectories carried out at the atmospherically relevant photodissociation energies led to recombination of OH and CH3O to form CH3OOH. Within the limited statistics of the available trajectories the predicted yield for the recombination is zero. Instead, various reactions involving the initial fragments and water promptly form a wide range of stable molecular products such as CH2O, H2O, H2, CO, CH3OH, and H2O2. PMID:19846778
Inherent structure versus geometric metric for state space discretization.
Liu, Hanzhong; Li, Minghai; Fan, Jue; Huo, Shuanghong
2016-05-30
Inherent structure (IS) and geometry-based clustering methods are commonly used for analyzing molecular dynamics trajectories. ISs are obtained by minimizing the sampled conformations into local minima on potential/effective energy surface. The conformations that are minimized into the same energy basin belong to one cluster. We investigate the influence of the applications of these two methods of trajectory decomposition on our understanding of the thermodynamics and kinetics of alanine tetrapeptide. We find that at the microcluster level, the IS approach and root-mean-square deviation (RMSD)-based clustering method give totally different results. Depending on the local features of energy landscape, the conformations with close RMSDs can be minimized into different minima, while the conformations with large RMSDs could be minimized into the same basin. However, the relaxation timescales calculated based on the transition matrices built from the microclusters are similar. The discrepancy at the microcluster level leads to different macroclusters. Although the dynamic models established through both clustering methods are validated approximately Markovian, the IS approach seems to give a meaningful state space discretization at the macrocluster level in terms of conformational features and kinetics. © 2016 Wiley Periodicals, Inc.
Pedersen, Pernille; Lund, Thomas; Lindholdt, Louise; Nohr, Ellen A; Jensen, Chris; Søgaard, Hans Jørgen; Labriola, Merete
2016-04-16
To investigate differences in return to work (RTW) and employment trajectories in individuals on sick leave for either mental health reasons or other health related reasons. This study was based on 2036 new sickness absence cases who completed a questionnaire on social characteristics, expectations for RTW and reasons for sickness absence. They were divided into two exposure groups according to their self-reported sickness absence reason: mental health reasons or other health reasons. The outcome was employment status during the following 51 weeks and was measured both as time-to-event analysis and with sequence analysis. Individuals with mental health reasons for sickness absence had a higher risk of not having returned to work (RR 0.87 (0.80;0.93)). Adjusting for gender, age, education and employment did not change the estimate, however, after adding RTW expectations to the model, the excess risk was no longer present (RR 1.01 (0.95;1.08)). In relation to the sequence analysis, individuals with mental health related absence had significantly higher odds of being in the sickness absence cluster and significantly lower odds for being in the fast RTW cluster, but when adjusting for RTW expectations, the odds were somewhat attenuated and no longer significant. Employees on sick leave due to self-reported mental health problems spent more weeks in sickness absence and temporary benefits and had a higher risk of not having returned to work within a year compared to employees on sick leave due to other health reasons. The difference could be explained by their lower RTW expectations at baseline. This emphasises the need to develop suitable and specific interventions to facilitate RTW for this group of sickness absentees.
Watts, C R; Mezei, M; Murphy, R F; Lovas, S
2001-04-01
The conformational space available to GnRH and lGnRH-III was compared using 5.2 ns constant temperature and pressure molecular dynamics simulations with explicit TIP3P solvation and the AMBER v. 5.0 force field. Cluster analysis of both trajectories resulted in two groups of conformations. Results of free energy calculations, in agreement with previous experimental data, indicate that a conformation with a turn from residues 5 through 8 is preferred for GnRH in an aqueous environment. By contrast, a conformation with a helix from residues 2 through 7 with a bend from residues 6 through 10 is preferred for lGnRH-III in an aqueous environment. The side chains of His2 and Trp3 in lGnRH-III occupy different regions of phase space and participate in weakly polar interactions different from those in GnRH. The unique conformational properties of lGnRH-III may account for its specific anti cancer activity.
Advanced multivariate analysis to assess remediation of hydrocarbons in soils.
Lin, Deborah S; Taylor, Peter; Tibbett, Mark
2014-10-01
Accurate monitoring of degradation levels in soils is essential in order to understand and achieve complete degradation of petroleum hydrocarbons in contaminated soils. We aimed to develop the use of multivariate methods for the monitoring of biodegradation of diesel in soils and to determine if diesel contaminated soils could be remediated to a chemical composition similar to that of an uncontaminated soil. An incubation experiment was set up with three contrasting soil types. Each soil was exposed to diesel at varying stages of degradation and then analysed for key hydrocarbons throughout 161 days of incubation. Hydrocarbon distributions were analysed by Principal Coordinate Analysis and similar samples grouped by cluster analysis. Variation and differences between samples were determined using permutational multivariate analysis of variance. It was found that all soils followed trajectories approaching the chemical composition of the unpolluted soil. Some contaminated soils were no longer significantly different to that of uncontaminated soil after 161 days of incubation. The use of cluster analysis allows the assignment of a percentage chemical similarity of a diesel contaminated soil to an uncontaminated soil sample. This will aid in the monitoring of hydrocarbon contaminated sites and the establishment of potential endpoints for successful remediation.
NASA Astrophysics Data System (ADS)
Berta, Maristella; Bellomo, Lucio; Griffa, Annalisa; Gatimu Magaldi, Marcello; Marmain, Julien; Molcard, Anne; Taillandier, Vincent
2013-04-01
The Lagrangian assimilation algorithm LAVA (LAgrangian Variational Analysis) is customized for coastal areas in the framework of the TOSCA (Tracking Oil Spills & Coastal Awareness network) Project, to improve the response to maritime accidents in the Mediterranean Sea. LAVA assimilates drifters' trajectories in the velocity fields which may come from either coastal radars or numerical models. In the present study, LAVA is applied to the coastal area in front of Toulon (France). Surface currents are available from a WERA radar network (2km spatial resolution, every 20 minutes) and from the GLAZUR model (1/64° spatial resolution, every hour). The cluster of drifters considered is constituted by 7 buoys, transmitting every 15 minutes for a period of 5 days. Three assimilation cases are considered: i) correction of the radar velocity field, ii) correction of the model velocity field and iii) reconstruction of the velocity field from drifters only. It is found that drifters' trajectories compare well with the ones obtained by the radar and the correction to radar velocity field is therefore minimal. Contrarily, observed and numerical trajectories separate rapidly and the correction to the model velocity field is substantial. For the reconstruction from drifters only, the velocity fields obtained are similar to the radar ones, but limited to the neighbor of the drifter paths.
Scale dependence of the 200-mb divergence inferred from EOLE data.
NASA Technical Reports Server (NTRS)
Morel, P.; Necco, G.
1973-01-01
The EOLE experiment with 480 constant-volume balloons distributed over the Southern Hemisphere approximately at the 200-mb level, has provided a unique, highly accurate set of tracer trajectories in the general westerly circulation. The trajectories of neighboring balloons are analyzed to estimate the horizontal divergence from the Lagrangian derivative of the area of one cluster. The variance of the divergence estimates results from two almost comparable effects: the true divergence of the horizontal flow and eddy diffusion due to small-scale, two-dimensional turbulence. Taking this into account, the rms divergence is found to be of the order of 0.00001 per sec and decreases logarithmically with cluster size. This scale dependence is shown to be consistent with the quasi-geostrophic turbulence model of the general circulation in midlatitudes.
Combinatorial pattern discovery approach for the folding trajectory analysis of a beta-hairpin.
Parida, Laxmi; Zhou, Ruhong
2005-06-01
The study of protein folding mechanisms continues to be one of the most challenging problems in computational biology. Currently, the protein folding mechanism is often characterized by calculating the free energy landscape versus various reaction coordinates, such as the fraction of native contacts, the radius of gyration, RMSD from the native structure, and so on. In this paper, we present a combinatorial pattern discovery approach toward understanding the global state changes during the folding process. This is a first step toward an unsupervised (and perhaps eventually automated) approach toward identification of global states. The approach is based on computing biclusters (or patterned clusters)-each cluster is a combination of various reaction coordinates, and its signature pattern facilitates the computation of the Z-score for the cluster. For this discovery process, we present an algorithm of time complexity c in RO((N + nm) log n), where N is the size of the output patterns and (n x m) is the size of the input with n time frames and m reaction coordinates. To date, this is the best time complexity for this problem. We next apply this to a beta-hairpin folding trajectory and demonstrate that this approach extracts crucial information about protein folding intermediate states and mechanism. We make three observations about the approach: (1) The method recovers states previously obtained by visually analyzing free energy surfaces. (2) It also succeeds in extracting meaningful patterns and structures that had been overlooked in previous works, which provides a better understanding of the folding mechanism of the beta-hairpin. These new patterns also interconnect various states in existing free energy surfaces versus different reaction coordinates. (3) The approach does not require calculating the free energy values, yet it offers an analysis comparable to, and sometimes better than, the methods that use free energy landscapes, thus validating the choice of reaction coordinates. (An abstract version of this work was presented at the 2005 Asia Pacific Bioinformatics Conference [1].).
Pandini, Alessandro; Fraccalvieri, Domenico; Bonati, Laura
2013-01-01
The biological function of proteins is strictly related to their molecular flexibility and dynamics: enzymatic activity, protein-protein interactions, ligand binding and allosteric regulation are important mechanisms involving protein motions. Computational approaches, such as Molecular Dynamics (MD) simulations, are now routinely used to study the intrinsic dynamics of target proteins as well as to complement molecular docking approaches. These methods have also successfully supported the process of rational design and discovery of new drugs. Identification of functionally relevant conformations is a key step in these studies. This is generally done by cluster analysis of the ensemble of structures in the MD trajectory. Recently Artificial Neural Network (ANN) approaches, in particular methods based on Self-Organising Maps (SOMs), have been reported performing more accurately and providing more consistent results than traditional clustering algorithms in various data-mining problems. In the specific case of conformational analysis, SOMs have been successfully used to compare multiple ensembles of protein conformations demonstrating a potential in efficiently detecting the dynamic signatures central to biological function. Moreover, examples of the use of SOMs to address problems relevant to other stages of the drug-design process, including clustering of docking poses, have been reported. In this contribution we review recent applications of ANN algorithms in analysing conformational and structural ensembles and we discuss their potential in computer-based approaches for medicinal chemistry.
Quantum trajectories for time-dependent adiabatic master equations
NASA Astrophysics Data System (ADS)
Yip, Ka Wa; Albash, Tameem; Lidar, Daniel A.
2018-02-01
We describe a quantum trajectories technique for the unraveling of the quantum adiabatic master equation in Lindblad form. By evolving a complex state vector of dimension N instead of a complex density matrix of dimension N2, simulations of larger system sizes become feasible. The cost of running many trajectories, which is required to recover the master equation evolution, can be minimized by running the trajectories in parallel, making this method suitable for high performance computing clusters. In general, the trajectories method can provide up to a factor N advantage over directly solving the master equation. In special cases where only the expectation values of certain observables are desired, an advantage of up to a factor N2 is possible. We test the method by demonstrating agreement with direct solution of the quantum adiabatic master equation for 8-qubit quantum annealing examples. We also apply the quantum trajectories method to a 16-qubit example originally introduced to demonstrate the role of tunneling in quantum annealing, which is significantly more time consuming to solve directly using the master equation. The quantum trajectories method provides insight into individual quantum jump trajectories and their statistics, thus shedding light on open system quantum adiabatic evolution beyond the master equation.
NASA Astrophysics Data System (ADS)
McPartland, Conor; Ebeling, Harald; Roediger, Elke; Blumenthal, Kelly
2016-01-01
We investigate the observational signatures and physical origin of ram-pressure stripping (RPS) in 63 massive galaxy clusters at z = 0.3-0.7, based on images obtained with the Hubble Space Telescope. Using a training set of a dozen `jellyfish' galaxies identified earlier in the same imaging data, we define morphological criteria to select 211 additional, less obvious cases of RPS. Spectroscopic follow-up observations of 124 candidates so far confirmed 53 as cluster members. For the brightest and most favourably aligned systems, we visually derive estimates of the projected direction of motion based on the orientation of apparent compression shocks and debris trails. Our findings suggest that the onset of these events occurs primarily at large distances from the cluster core (>400 kpc), and that the trajectories of the affected galaxies feature high-impact parameters. Simple models show that such trajectories are highly improbable for galaxy infall along filaments but common for infall at high velocities, even after observational biases are accounted for, provided the duration of the resulting RPS events is ≲500 Myr. We thus tentatively conclude that extreme RPS events are preferentially triggered by cluster mergers, an interpretation that is supported by the disturbed dynamical state of many of the host clusters. This hypothesis implies that extreme RPS might occur also near the cores of merging poor clusters or even merging groups of galaxies. Finally, we present nine additional `jellyfish" galaxies at z > 0.3 discovered by us, thereby doubling the number of such systems known at intermediate redshift.
Simulating protein folding initiation sites using an alpha-carbon-only knowledge-based force field
Buck, Patrick M.; Bystroff, Christopher
2015-01-01
Protein folding is a hierarchical process where structure forms locally first, then globally. Some short sequence segments initiate folding through strong structural preferences that are independent of their three-dimensional context in proteins. We have constructed a knowledge-based force field in which the energy functions are conditional on local sequence patterns, as expressed in the hidden Markov model for local structure (HMMSTR). Carbon-alpha force field (CALF) builds sequence specific statistical potentials based on database frequencies for α-carbon virtual bond opening and dihedral angles, pairwise contacts and hydrogen bond donor-acceptor pairs, and simulates folding via Brownian dynamics. We introduce hydrogen bond donor and acceptor potentials as α-carbon probability fields that are conditional on the predicted local sequence. Constant temperature simulations were carried out using 27 peptides selected as putative folding initiation sites, each 12 residues in length, representing several different local structure motifs. Each 0.6 μs trajectory was clustered based on structure. Simulation convergence or representativeness was assessed by subdividing trajectories and comparing clusters. For 21 of the 27 sequences, the largest cluster made up more than half of the total trajectory. Of these 21 sequences, 14 had cluster centers that were at most 2.6 Å root mean square deviation (RMSD) from their native structure in the corresponding full-length protein. To assess the adequacy of the energy function on nonlocal interactions, 11 full length native structures were relaxed using Brownian dynamics simulations. Equilibrated structures deviated from their native states but retained their overall topology and compactness. A simple potential that folds proteins locally and stabilizes proteins globally may enable a more realistic understanding of hierarchical folding pathways. PMID:19137613
Sobanski, E; Leppämäki, S; Bushe, C; Berggren, L; Casillas, M; Deberdt, W
2015-11-01
Atomoxetine is a well-established pharmacotherapy for adult ADHD. Long-term studies show incremental reductions in symptoms over time. However, clinical experience suggests that patients differ in their response patterns. From 13 Eli Lilly-sponsored studies, we pooled and analyzed data for adults with ADHD who completed atomoxetine treatment at long-term (24 weeks; n=1443) and/or short-term (12 weeks; n=2830) time-points, and had CAARS-Inv:SV total and CGI-S data up to or after these time-points and at Week 0 (i.e. at baseline, when patients first received atomoxetine). The goal was to identify and describe distinct trajectories of response to atomoxetine using hierarchical clustering methods and linear mixed modelling. Based on the homogeneity of changes in CAARS-Inv:SV total scores, 5 response clusters were identified for patients who completed long-term (24 weeks) treatment with atomoxetine, and 4 clusters were identified for patients who completed short-term (12 weeks) treatment. Four of the 5 long-term clusters (comprising 95% of completer patients) showed positive trajectories: 2 faster responding clusters (L1 and L2), and 2 more gradually responding clusters (L3 and L4). Responses (i.e.≥30% reduction in CAARS-Inv:SV total score, and CGI-S score≤3) were observed at 8 and 24 weeks in 80% and 95% of completers in Cluster L1, versus 5% and 48% in Cluster L4. While many adults with ADHD responded relatively rapidly to atomoxetine, others responded more gradually without a clear plateau at 24 weeks. Longer-term treatment may be associated with greater numbers of responders. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
Sun, Yu; Lee, Renick; Chen, Yu; Collinson, Simon; Thakor, Nitish; Bezerianos, Anastasios; Sim, Kang
2015-01-01
Sexual dimorphism in the brain maturation during childhood and adolescence has been repeatedly documented, which may underlie the differences in behaviors and cognitive performance. However, our understanding of how gender modulates the development of structural connectome in healthy adults is still not entirely clear. Here we utilized graph theoretical analysis of longitudinal diffusion tensor imaging data over a five-year period to investigate the progressive gender differences of brain network topology. The brain networks of both genders showed prominent economical "small-world" architecture (high local clustering and short paths between nodes). Additional analysis revealed a more economical "small-world" architecture in females as well as a greater global efficiency in males regardless of scan time point. At the regional level, both increased and decreased efficiency were found across the cerebral cortex for both males and females, indicating a compensation mechanism of cortical network reorganization over time. Furthermore, we found that weighted clustering coefficient exhibited significant gender-time interactions, implying different development trends between males and females. Moreover, several specific brain regions (e.g., insula, superior temporal gyrus, cuneus, putamen, and parahippocampal gyrus) exhibited different development trajectories between males and females. Our findings further prove the presence of sexual dimorphism in brain structures that may underlie gender differences in behavioral and cognitive functioning. The sex-specific progress trajectories in brain connectome revealed in this work provide an important foundation to delineate the gender related pathophysiological mechanisms in various neuropsychiatric disorders, which may potentially guide the development of sex-specific treatments for these devastating brain disorders.
A Lagrangian analysis of cold cloud clusters and their life cycles with satellite observations
Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong
2018-01-01
Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi-coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Niño. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics. PMID:29744257
A Lagrangian analysis of cold cloud clusters and their life cycles with satellite observations.
Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong
2016-10-16
Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi-coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Niño. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics.
A Lagrangian Analysis of Cold Cloud Clusters and Their Life Cycles With Satellite Observations
NASA Technical Reports Server (NTRS)
Esmaili, Rebekah Bradley; Tian, Yudong; Vila, Daniel Alejandro; Kim, Kyu-Myong
2016-01-01
Cloud movement and evolution signify the complex water and energy transport in the atmosphere-ocean-land system. Detecting, clustering, and tracking clouds as semi coherent cluster objects enables study of their evolution which can complement climate model simulations and enhance satellite retrieval algorithms, where there are large gaps between overpasses. Using an area-overlap cluster tracking algorithm, in this study we examine the trajectories, horizontal extent, and brightness temperature variations of millions of individual cloud clusters over their lifespan, from infrared satellite observations at 30-minute, 4-km resolution, for a period of 11 years. We found that the majority of cold clouds were both small and short-lived and that their frequency and location are influenced by El Nino. More importantly, this large sample of individually tracked clouds shows their horizontal size and temperature evolution. Longer lived clusters tended to achieve their temperature and size maturity milestones at different times, while these stages often occurred simultaneously in shorter lived clusters. On average, clusters with this lag also exhibited a greater rainfall contribution than those where minimum temperature and maximum size stages occurred simultaneously. Furthermore, by examining the diurnal cycle of cluster development over Africa and the Indian subcontinent, we observed differences in the local timing of the maximum occurrence at different life cycle stages. Over land there was a strong diurnal peak in the afternoon while over the ocean there was a semi-diurnal peak composed of longer-lived clusters in the early morning hours and shorter-lived clusters in the afternoon. Building on regional specific work, this study provides a long-term, high-resolution, and global survey of object-based cloud characteristics.
Fast large-scale clustering of protein structures using Gauss integrals.
Harder, Tim; Borg, Mikael; Boomsma, Wouter; Røgen, Peter; Hamelryck, Thomas
2012-02-15
Clustering protein structures is an important task in structural bioinformatics. De novo structure prediction, for example, often involves a clustering step for finding the best prediction. Other applications include assigning proteins to fold families and analyzing molecular dynamics trajectories. We present Pleiades, a novel approach to clustering protein structures with a rigorous mathematical underpinning. The method approximates clustering based on the root mean square deviation by first mapping structures to Gauss integral vectors--which were introduced by Røgen and co-workers--and subsequently performing K-means clustering. Compared to current methods, Pleiades dramatically improves on the time needed to perform clustering, and can cluster a significantly larger number of structures, while providing state-of-the-art results. The number of low energy structures generated in a typical folding study, which is in the order of 50,000 structures, can be clustered within seconds to minutes.
NASA Astrophysics Data System (ADS)
MacKenzie, Rob; Fawole, Olusegun Gabriel; Levine, James; Cai, Xiaoming
2016-04-01
Gas flaring, the disposal of gas through stacks in an open-air flame, is a common feature in the processing of crude oil, especially in oil-rich regions of the world. Gas flaring is a prominent source of volatile organic compounds (VOCs), polycyclic aromatic hydrocarbons (PAH), CO, CO2, nitrogen oxides (NOx), SO2 (in "sour" gas only), and soot (black carbon), as well as the release of locally significant amounts of heat. The rates of emission of these pollutants from gas flaring depend on a number of factors including, but not limited to, fuel composition and quantity, stack geometry, flame/combustion characteristics, and prevailing meteorological conditions. Here, we derive new estimated emission factors (EFs) for carbon-containing pollutants (excluding PAH). The air pollution dispersion model, ADMS5, is used to simulate the dispersion of the pollutants from flaring stacks in the Niger delta. A seasonal variation of the dispersion pattern of the pollutant within a year is studied in relation to the movements of the West Africa Monsoon (WAM) and other prevailing meteorological factors. Further, we have clustered AERONET aerosol signals using trajectory analysis to identify dominant aerosol sources at the Ilorin site in West Africa (4.34 oE, 8.32 oN). A 10-year trajectory-based analysis was undertaken (2005-2015, excluding 2010). Of particular interest are air masses that have passed through the gas flaring region in the Niger Delta area en-route the AERONET site. 7-day back trajectories were calculated using the UK Universities Global Atmospheric Modelling Programme (UGAMP) trajectory model which is driven by analyses from the European Centre for Medium-Range Weather Forecasts (ECMWF). From the back-trajectory calculations, dominant sources are identified, using literature classifications: desert dust (DD); Biomass burning (BB); and Urban-Industrial (UI). We use a combination of synoptic trajectories and aerosol optical properties to distinguish a fourth source: that due to gas flaring. We discuss the relative impact of these different aerosol sources on the overall radiative forcing at Ilorin AERONET site.
a Web-Based Platform for Visualizing Spatiotemporal Dynamics of Big Taxi Data
NASA Astrophysics Data System (ADS)
Xiong, H.; Chen, L.; Gui, Z.
2017-09-01
With more and more vehicles equipped with Global Positioning System (GPS), access to large-scale taxi trajectory data has become increasingly easy. Taxis are valuable sensors and information associated with taxi trajectory can provide unprecedented insight into many aspects of city life. But analysing these data presents many challenges. Visualization of taxi data is an efficient way to represent its distributions and structures and reveal hidden patterns in the data. However, Most of the existing visualization systems have some shortcomings. On the one hand, the passenger loading status and speed information cannot be expressed. On the other hand, mono-visualization form limits the information presentation. In view of these problems, this paper designs and implements a visualization system in which we use colour and shape to indicate passenger loading status and speed information and integrate various forms of taxi visualization. The main work as follows: 1. Pre-processing and storing the taxi data into MongoDB database. 2. Visualization of hotspots for taxi pickup points. Through DBSCAN clustering algorithm, we cluster the extracted taxi passenger's pickup locations to produce passenger hotspots. 3. Visualizing the dynamic of taxi moving trajectory using interactive animation. We use a thinning algorithm to reduce the amount of data and design a preloading strategyto load the data smoothly. Colour and shape are used to visualize the taxi trajectory data.
Constructing an Indoor Floor Plan Using Crowdsourcing Based on Magnetic Fingerprinting
Zhao, Fang; Jiang, Mengling; Ma, Hao; Zhang, Yuexia
2017-01-01
A large number of indoor positioning systems have recently been developed to cater for various location-based services. Indoor maps are a prerequisite of such indoor positioning systems; however, indoor maps are currently non-existent for most indoor environments. Construction of an indoor map by external experts excludes quick deployment and prevents widespread utilization of indoor localization systems. Here, we propose an algorithm for the automatic construction of an indoor floor plan, together with a magnetic fingerprint map of unmapped buildings using crowdsourced smartphone data. For floor plan construction, our system combines the use of dead reckoning technology, an observation model with geomagnetic signals, and trajectory fusion based on an affinity propagation algorithm. To obtain the indoor paths, the magnetic trajectory data obtained through crowdsourcing were first clustered using dynamic time warping similarity criteria. The trajectories were inferred from odometry tracing, and those belonging to the same cluster in the magnetic trajectory domain were then fused. Fusing these data effectively eliminates the inherent tracking errors originating from noisy sensors; as a result, we obtained highly accurate indoor paths. One advantage of our system is that no additional hardware such as a laser rangefinder or wheel encoder is required. Experimental results demonstrate that our proposed algorithm successfully constructs indoor floor plans with 0.48 m accuracy, which could benefit location-based services which lack indoor maps. PMID:29156639
The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog.
Girdhar, Kiran; Gruebele, Martin; Chemla, Yann R
2015-01-01
How simple is the underlying control mechanism for the complex locomotion of vertebrates? We explore this question for the swimming behavior of zebrafish larvae. A parameter-independent method, similar to that used in studies of worms and flies, is applied to analyze swimming movies of fish. The motion itself yields a natural set of fish "eigenshapes" as coordinates, rather than the experimenter imposing a choice of coordinates. Three eigenshape coordinates are sufficient to construct a quantitative "postural space" that captures >96% of the observed zebrafish locomotion. Viewed in postural space, swim bouts are manifested as trajectories consisting of cycles of shapes repeated in succession. To classify behavioral patterns quantitatively and to understand behavioral variations among an ensemble of fish, we construct a "behavioral space" using multi-dimensional scaling (MDS). This method turns each cycle of a trajectory into a single point in behavioral space, and clusters points based on behavioral similarity. Clustering analysis reveals three known behavioral patterns-scoots, turns, rests-but shows that these do not represent discrete states, but rather extremes of a continuum. The behavioral space not only classifies fish by their behavior but also distinguishes fish by age. With the insight into fish behavior from postural space and behavioral space, we construct a two-channel neural network model for fish locomotion, which produces strikingly similar postural space and behavioral space dynamics compared to real zebrafish.
The Behavioral Space of Zebrafish Locomotion and Its Neural Network Analog
Girdhar, Kiran; Gruebele, Martin; Chemla, Yann R.
2015-01-01
How simple is the underlying control mechanism for the complex locomotion of vertebrates? We explore this question for the swimming behavior of zebrafish larvae. A parameter-independent method, similar to that used in studies of worms and flies, is applied to analyze swimming movies of fish. The motion itself yields a natural set of fish "eigenshapes" as coordinates, rather than the experimenter imposing a choice of coordinates. Three eigenshape coordinates are sufficient to construct a quantitative "postural space" that captures >96% of the observed zebrafish locomotion. Viewed in postural space, swim bouts are manifested as trajectories consisting of cycles of shapes repeated in succession. To classify behavioral patterns quantitatively and to understand behavioral variations among an ensemble of fish, we construct a "behavioral space" using multi-dimensional scaling (MDS). This method turns each cycle of a trajectory into a single point in behavioral space, and clusters points based on behavioral similarity. Clustering analysis reveals three known behavioral patterns—scoots, turns, rests—but shows that these do not represent discrete states, but rather extremes of a continuum. The behavioral space not only classifies fish by their behavior but also distinguishes fish by age. With the insight into fish behavior from postural space and behavioral space, we construct a two-channel neural network model for fish locomotion, which produces strikingly similar postural space and behavioral space dynamics compared to real zebrafish. PMID:26132396
Mid-Term Probabilistic Forecast of Oil Spill Trajectories
NASA Astrophysics Data System (ADS)
Castanedo, S.; Abascal, A. J.; Cardenas, M.; Medina, R.; Guanche, Y.; Mendez, F. J.; Camus, P.
2012-12-01
There is increasing concern about the threat posed by oil spills to the coastal environment. This is reflected in the promulgation of various national and international standards among which are those that require companies whose activities involves oil spill risk, to have oil pollution emergency plans or similar arrangements for responding promptly and effectively to oil pollution incidents. Operational oceanography systems (OOS) that provide decision makers with oil spill trajectory forecasting, have demonstrated their usefulness in recent accidents (Castanedo et al., 2006). In recent years, many national and regional OOS have been setup focusing on short-term oil spill forecast (up to 5 days). However, recent accidental marine oil spills (Prestige in Spain, Deep Horizon in Gulf of Mexico) have revealed the importance of having larger prediction horizons (up to 15 days) in regional-scale areas. In this work, we have developed a methodology to provide probabilistic oil spill forecast based on numerical modelling and statistical methods. The main components of this approach are: (1) Use of high resolution long-term (1948-2009) historical hourly data bases of wind, wind-induced currents and astronomical tide currents obtained using state-of-the-art numerical models; (2) classification of representative wind field patterns (n=100) using clustering techniques based on PCA and K-means algorithms (Camus et al., 2011); (3) determination of the cluster occurrence probability and the stochastic matrix (matrix of transition of probability or Markov matrix), p_ij, (probability of moving from a cluster "i" to a cluster "j" in one time step); (4) Initial state for mid-term simulations is obtained from available wind forecast using nearest-neighbors analog method; (5) 15-days Stochastic Markov Chain simulations (m=1000) are launched; (6) Corresponding oil spill trajectories are carried out by TESEO Lagrangian transport model (Abascal et al., 2009); (7) probability maps are delivered using an user friendly Web App. The application of the method to the Gulf of Biscay (North Spain) will show the ability of this approach. References Abascal, A.J., Castanedo, S., Mendez, F.J., Medina, R., Losada, I.J., 2009. Calibration of a Lagrangian transport model using drifting buoys deployed during the Prestige oil spill. J. Coast. Res. 25 (1), 80-90.. Camus, P., Méndez, F.J., Medina, R., 2011. Analysis of clustering and selection algorithms for the study of multivariate wave climate. Coastal Engineering, doi:10.1016/j.coastaleng.2011.02.003. Castanedo, S., Medina, R., Losada, I.J., Vidal, C., Méndez, F.J., Osorio, A., Juanes, J.A., Puente, A., 2006. The Prestige oil spill in Cantabria (Bay of Biscay). Part I: operational forecasting system for quick response, risk assessment and protection of natural resources. J. Coast. Res. 22 (6), 1474-1489.
Duncan, Robert; Washburn, Isaac J; Lewis, Kendra M; Bavarian, Niloofar; DuBois, David L; Acock, Alan C; Vuchinich, Samuel; Flay, Brian R
2017-02-01
Behavioral trajectories during middle childhood are predictive of consequential outcomes later in life (e.g., substance abuse, violence). Social and emotional learning (SEL) programs are designed to promote trajectories that reflect both growth in positive behaviors and inhibited development of negative behaviors. The current study used growth mixture models to examine effects of the Positive Action (PA) program on behavioral trajectories of social-emotional and character development (SECD) and misconduct using data from a cluster-randomized trial that involved 14 schools and a sample of predominately low-income, urban youth followed from 3rd through 8th grade. For SECD, findings indicated that PA was similarly effective at improving trajectories within latent classes characterized as "high/declining" and "low/stable". Favorable program effects were likewise evident to a comparable degree for misconduct across observed latent classes that reflected "low/rising" and "high/rising" trajectories. These findings suggest that PA and perhaps other school-based universal SEL programs have the potential to yield comparable benefits across subgroups of youth with differing trajectories of positive and negative behaviors, making them promising strategies for achieving the intended goal of school-wide improvements in student outcomes.
COLAcode: COmoving Lagrangian Acceleration code
NASA Astrophysics Data System (ADS)
Tassev, Svetlin V.
2016-02-01
COLAcode is a serial particle mesh-based N-body code illustrating the COLA (COmoving Lagrangian Acceleration) method; it solves for Large Scale Structure (LSS) in a frame that is comoving with observers following trajectories calculated in Lagrangian Perturbation Theory (LPT). It differs from standard N-body code by trading accuracy at small-scales to gain computational speed without sacrificing accuracy at large scales. This is useful for generating large ensembles of accurate mock halo catalogs required to study galaxy clustering and weak lensing; such catalogs are needed to perform detailed error analysis for ongoing and future surveys of LSS.
September epsilon Perseid cluster as a result of orbital fragmentation
NASA Astrophysics Data System (ADS)
Koten, P.; Čapek, D.; Spurný, P.; Vaubaillon, J.; Popek, M.; Shrbený, L.
2017-04-01
Context. A bright fireball was observed above the Czech Republic on September 9, 2016, at 23:06:59 UT. Moreover, the video cameras at two different stations recorded eight fainter meteors flying on parallel atmospheric trajectories within less than 2 s. All the meteors belong to the September epsilon Perseid meteor shower. The measured proximity of all meteors during a very low activity meteor shower suggests that a cluster of meteors was observed. Aims: The goal of the paper is first to determine whether this event was a random occurrence or a real meteor cluster and second, if it was a cluster, to determine the epoch and at what distance from the Earth the separation of the particles occurred. Methods: The atmospheric trajectories of the observed meteors, masses, and relative distances of individual particles were determined using a double-station observation. According to the distances and masses of the particles, the most probable distance and time of fragmentation is determined. Results: The observed group of meteors is interpreted as the result of the orbital fragmentation of a bigger meteoroid. The fragmentation happened no earlier than 2 or 3 days before the encounter with the Earth at a distance smaller than 0.08 AU from the Earth.
NASA Astrophysics Data System (ADS)
Brankov, Elvira
This thesis presents a methodology for examining the relationship between synoptic-scale atmospheric transport patterns and observed pollutant concentration levels. It involves calculating a large number of back-trajectories from the observational site and subjecting them to cluster analysis. The pollutant concentration data observed at that site are then segregated according to the back-trajectory clusters. If the pollutant observations extend over several seasons, it is important to filter out seasonal and long-term components from the time series data before pollutant cluster-segregation, because only the short-term component of the time series data is related to the synoptic-scale transport. Multiple comparison procedures are used to test for significant differences in the chemical composition of pollutant data associated with each cluster. This procedure is useful in indicating potential pollutant source regions and isolating meteorological regimes associated with pollutant transport from those regions. If many observational sites are available, the spatial and temporal scales of the pollution transport from a given direction can be extracted through the time-lagged inter- site correlation analysis of pollutant concentrations. The proposed methodology is applicable to any pollutant at any site if sufficiently abundant data set is available. This is illustrated through examination of five-year long time series data of ozone concentrations at several sites in the Northeast. The results provide evidence of ozone transport to these sites, revealing the characteristic spatial and temporal scales involved in the transport and identifying source regions for this pollutant. Problems related to statistical analyses of censored data are addressed in the second half of this thesis. Although censoring (reporting concentrations in a non-quantitative way) is typical for trace-level measurements, methods for statistical analysis, inference and interpretation of such data are complex and still under development. In this study, multiple comparison of censored data sets was required in order to examine the influence of synoptic- scale circulations on concentration levels of several trace-level toxic pollutants observed in the Northeast (e.g., As, Se, Mn, V, etc.). Since the traditional multiple comparison procedures are not readily applicable to such data sets, a Monte Carlo simulation study was performed to assess several nonparametric methods for multiple comparison of censored data sets. Application of an appropriate comparison procedure to clusters of toxic trace elements observed in the Northeast led to the identification of potential source regions and atmospheric patterns associated with the long-range transport of these pollutants. A method for comparison of proportions and elemental ratio calculations were used to confirm/clarify these inferences with a greater degree of confidence.
Liu, Xian; Engel, Charles C
2012-12-20
Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.
On the association between synoptic circulation and wildfires in the Eastern Mediterranean
NASA Astrophysics Data System (ADS)
Papadopoulos, A.; Paschalidou, A. K.; Kassomenos, P. A.; McGregor, G.
2014-02-01
In the present paper cluster analysis of 2-month air mass back-trajectories for three contrasting fire and non-fire events is conducted (high, low, and zero burnt area). The large fire event displays an air mass history dissimilar to other events whereby a 39-day period of warm and dry chiefly northerly anticyclonic conditions is evident, before a week of warmer predominantly southwesterly cyclonic activity, immediately prior to ignition. The pressure level of these anticyclonic air masses is above 800 hPa for more than 75 % of the trajectory length; this region is above the principal moisture transport regime of 800 hPa altitude. Analysis of variance on the mean rate of change of potential temperature identified weak statistically significant differences between two air mass pairs regarding the large fire: anticyclonic and cyclonic air masses in both cases ( p = 0.038 and p = 0.020). Such regularity of type and occurrence, approach pressure levels and statistically significant differences are not evident for the small and non-fire event air masses. Such understanding is expected to permit appropriate steps to be undertaken including superior prediction and improved suppression strategy.
Kobak, Roger; Zajac, Kristyn; Smith, Clare
2014-01-01
Adolescents’ trajectories of impulsive and hostile behaviors provide a dynamic index of risk for the emergence of Cluster B (Anti-social and Borderline) personality disorders in early adulthood. In the current study, we tested the hypothesis that Preoccupied states of mind in the Adult Attachment Interview would increase both the level and rate of growth in adolescents’ trajectories of aggressive and sexual risk-taking behaviors measured at ages 13, 15, and 17. Overall, Preoccupied states of mind predicted higher levels of sexual risk-taking and aggressive behaviors across all three assessments as well as higher rates of growth in sexual-risk taking and caregiver-reported aggression over time. In addition, Preoccupied females showed slower rates of decline in self-reported hostile emotions than did Preoccupied males. The effects of gender as a moderator of the relations between Preoccupied status and risk trajectories for personality disorders are discussed. PMID:19583886
White, Alec F.; Epifanovsky, Evgeny; McCurdy, C. William; ...
2017-06-21
The method of complex basis functions is applied to molecular resonances at correlated levels of theory. Møller-Plesset perturbation theory at second order and equation-of-motion electron attachment coupled-cluster singles and doubles (EOM-EA-CCSD) methods based on a non-Hermitian self-consistent-field reference are used to compute accurate Siegert energies for shape resonances in small molecules including N 2 - , CO - , CO 2 - , and CH 2 O - . Analytic continuation of complex θ-trajectories is used to compute Siegert energies, and the θ-trajectories of energy differences are found to yield more consistent results than those of total energies.more » Furthermore, the ability of such methods to accurately compute complex potential energy surfaces is investigated, and the possibility of using EOM-EA-CCSD for Feshbach resonances is explored in the context of e-helium scattering.« less
A study of QM/Langevin-MD simulation for oxygen-evolving center of photosystem II
DOE Office of Scientific and Technical Information (OSTI.GOV)
Uchida, Waka; Kimura, Yoshiro; Wakabayashi, Masamitsu
2013-12-10
We have performed three QM/Langevin-MD simulations for oxygen-evolving complex (OEC) and surrounding residues, which are different configurations of the oxidation numbers on Mn atoms in the Mn{sub 4}O{sub 5}Ca cluster. By analyzing these trajectories, we have observed sensitivity of the change to the configuration of Mn oxidation state on O atoms of carboxyl on three amino acids, Glu354, Ala344, and Glu333. The distances from Mn to O atoms in residues contacting with the Mn{sub 4}O{sub 5}Ca cluster were analyzed for the three trajectories. We found the good correlation of the distances among the simulations. However, the distances with Glu354, Ala344,more » and Glu333 have not shown the correlation. These residues can be sensitive index of the changes of Mn oxidation numbers.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
White, Alec F.; Epifanovsky, Evgeny; McCurdy, C. William
The method of complex basis functions is applied to molecular resonances at correlated levels of theory. Møller-Plesset perturbation theory at second order and equation-of-motion electron attachment coupled-cluster singles and doubles (EOM-EA-CCSD) methods based on a non-Hermitian self-consistent-field reference are used to compute accurate Siegert energies for shape resonances in small molecules including N 2 - , CO - , CO 2 - , and CH 2 O - . Analytic continuation of complex θ-trajectories is used to compute Siegert energies, and the θ-trajectories of energy differences are found to yield more consistent results than those of total energies.more » Furthermore, the ability of such methods to accurately compute complex potential energy surfaces is investigated, and the possibility of using EOM-EA-CCSD for Feshbach resonances is explored in the context of e-helium scattering.« less
Cluster flight control for fractionated spacecraft on an elliptic orbit
NASA Astrophysics Data System (ADS)
Xu, Ming; Liang, Yuying; Tan, Tian; Wei, Lixin
2016-08-01
This paper deals with the stabilization of cluster flight on an elliptic reference orbit by the Hamiltonian structure-preserving control using the relative position measurement only. The linearized Melton's relative equation is utilized to derive the controller and then the full nonlinear relative dynamics are employed to numerically evaluate the controller's performance. In this paper, the hyperbolic and elliptic eigenvalues and their manifolds are treated without distinction notations. This new treatment not only contributes to solving the difficulty in feedback of the unfixed-dimensional manifolds, but also allows more opportunities to set the controlled frequencies of foundational motions or to optimize control gains. Any initial condition can be stabilized on a Kolmogorov-Arnold-Moser torus near a controlled elliptic equilibrium. The motions are stabilized around the natural relative trajectories rather than track a reference relative configuration. In addition, the bounded quasi-periodic trajectories generated by the controller have advantages in rapid reconfiguration and unpredictable evolution.
Early Environment and Neurobehavioral Development Predict Adult Temperament Clusters
Congdon, Eliza; Service, Susan; Wessman, Jaana; Seppänen, Jouni K.; Schönauer, Stefan; Miettunen, Jouko; Turunen, Hannu; Koiranen, Markku; Joukamaa, Matti; Järvelin, Marjo-Riitta; Veijola, Juha; Mannila, Heikki; Paunio, Tiina; Freimer, Nelson B.
2012-01-01
Background Investigation of the environmental influences on human behavioral phenotypes is important for our understanding of the causation of psychiatric disorders. However, there are complexities associated with the assessment of environmental influences on behavior. Methods/Principal Findings We conducted a series of analyses using a prospective, longitudinal study of a nationally representative birth cohort from Finland (the Northern Finland 1966 Birth Cohort). Participants included a total of 3,761 male and female cohort members who were living in Finland at the age of 16 years and who had complete temperament scores. Our initial analyses (Wessman et al., in press) provide evidence in support of four stable and robust temperament clusters. Using these temperament clusters, as well as independent temperament dimensions for comparison, we conducted a data-driven analysis to assess the influence of a broad set of life course measures, assessed pre-natally, in infancy, and during adolescence, on adult temperament. Results Measures of early environment, neurobehavioral development, and adolescent behavior significantly predict adult temperament, classified by both cluster membership and temperament dimensions. Specifically, our results suggest that a relatively consistent set of life course measures are associated with adult temperament profiles, including maternal education, characteristics of the family’s location and residence, adolescent academic performance, and adolescent smoking. Conclusions Our finding that a consistent set of life course measures predict temperament clusters indicate that these clusters represent distinct developmental temperament trajectories and that information about a subset of life course measures has implications for adult health outcomes. PMID:22815688
Automated tracking, segmentation and trajectory classification of pelvic organs on dynamic MRI.
Nekooeimehr, Iman; Lai-Yuen, Susana; Bao, Paul; Weitzenfeld, Alfredo; Hart, Stuart
2016-08-01
Pelvic organ prolapse is a major health problem in women where pelvic floor organs (bladder, uterus, small bowel, and rectum) fall from their normal position and bulge into the vagina. Dynamic Magnetic Resonance Imaging (DMRI) is presently used to analyze the organs' movements from rest to maximum strain providing complementary support for diagnosis. However, there is currently no automated or quantitative approach to measure the movement of the pelvic organs and their correlation with the severity of prolapse. In this paper, a two-stage method is presented to automatically track and segment pelvic organs on DMRI followed by a multiple-object trajectory classification method to improve the diagnosis of pelvic organ prolapse. Organs are first tracked using particle filters and K-means clustering with prior information. Then, they are segmented using the convex hull of the cluster of particles. Finally, the trajectories of the pelvic organs are modeled using a new Coupled Switched Hidden Markov Model (CSHMM) to classify the severity of pelvic organ prolapse. The tracking and segmentation results are validated using Dice Similarity Index (DSI) whereas the classification results are compared with two manual clinical measurements. Results demonstrate that the presented method is able to automatically track and segment pelvic organs with a DSI above 82% for 26 out of 46 cases and DSI above 75% for all 46 tested cases. The accuracy of the trajectory classification model is also better than current manual measurements.
Ascent trajectory dispersion analysis for WTR heads-up space shuttle trajectory
NASA Technical Reports Server (NTRS)
1986-01-01
The results of a Space Transportation System ascent trajectory dispersion analysis are discussed. The purpose is to provide critical trajectory parameter values for assessing the Space Shuttle in a heads-up configuration launched from the Western Test Range (STR). This analysis was conducted using a trajectory profile based on a launch from the WTR in December. The analysis consisted of the following steps: (1) nominal trajectories were simulated under the conditions as specified by baseline reference mission guidelines; (2) dispersion trajectories were simulated using predetermined parametric variations; (3) requirements for a system-related composite trajectory were determined by a root-sum-square (RSS) analysis of the positive deviations between values of the aerodynamic heating indicator (AHI) generated by the dispersion and nominal trajectories; (4) using the RSS assessment as a guideline, the system related composite trajectory was simulated by combinations of dispersion parameters which represented major contributors; (5) an assessment of environmental perturbations via a RSS analysis was made by the combination of plus or minus 2 sigma atmospheric density variation and 95% directional design wind dispersions; (6) maximum aerodynamic heating trajectories were simulated by variation of dispersion parameters which would emulate the summation of the system-related RSS and environmental RSS values of AHI. The maximum aerodynamic heating trajectories were simulated consistent with the directional winds used in the environmental analysis.
Duncan, Robert; Washburn, Isaac J.; Lewis, Kendra M.; Bavarian, Niloofar; DuBois, David L.; Acock, Alan C.; Vuchinich, Samuel; Flay, Brian R.
2016-01-01
Behavioral trajectories during middle childhood are predictive of consequential outcomes later in life (e.g., substance abuse, violence). Social and emotional learning (SEL) programs are designed to promote trajectories that reflect both growth in positive behaviors and inhibited development of negative behaviors. The current study used growth mixture models to examine effects of the Positive Action program (PA) on behavioral trajectories of social-emotional and character development (SECD) and misconduct using data from a cluster-randomized trial that involved 14 schools and a sample of predominately low-income, urban youth followed from 3rd through 8th grade. For SECD, findings indicated that PA was similarly effective at improving trajectories within latent classes characterized as “High/declining” and “Low/stable”. Favorable program effects were likewise evident to a comparable degree for misconduct across observed latent classes that reflected “Low/rising” and “High/rising” trajectories. These findings suggest that PA and perhaps other school-based universal SEL programs have the potential to yield comparable benefits across subgroups of youth with differing trajectories of positive and negative behaviors, making them promising strategies for achieving the intended goal of school-wide improvements in student outcomes. PMID:28028741
NASA Astrophysics Data System (ADS)
Conor, McPartland; Ebeling, Harald; Roediger, Elke
2015-08-01
We investigate the physical origin and observational signatures of extreme ram-pressure stripping (RPS) in 63 massive galaxy clusters at z=0.3-0.7, based on data in the F606W passband obtained with the Advanced Camera for Surveys aboard the Hubble Space Telescope. Using a training set of a dozen ``jellyfish" galaxies identified earlier in the same imaging data, we define quantitative morphological criteria to select candidate galaxies which are similar to known cases of RPS. Considering a sample of 16 ``jellyfish" galaxies (10 of which we present for the first time), we visually derive estimates of the projected direction of motion based on dynamical features such as apparent compression shocks and debris trails. Our findings suggest that the observed events occur primarily at large distances from the cluster core and involve infall trajectories featuring high impact parameters. Simple models of cluster growth show that such trajectories are consistent with two scenarios: 1) galaxy infall along filaments; and 2) infall at high velocities (≥1000 km/s) characteristic of cluster mergers. The observed distribution of events is best described by timescales of ˜few Myr in agreement with recent numerical simulations of RPS. The broader areal coverage of the Hubble Frontier Fields should provide an even larger sample of RPS events to determine the relative contributions of infall and cluster mergers. Prompted by the discovery of several jellyfish galaxies whose brightness in the F606W passband rivals or exceeds that of the respective brightest cluster galaxy, we attempt to constrain the luminosity function of galaxies undergoing RPS. The observed significant excess at the bright end compared to the luminosity functions of blue cluster members strongly suggests enhanced star formation, thus challenging theoretical and numerical studies according to which RPS merely displaces existing star-forming regions. In-depth studies of individual objects will help test our conclusions and allow a quantitative comparison with predictions of theoretical and numerical models of ram-pressure stripping.
Spatiotemporal Interpolation Methods for Solar Event Trajectories
NASA Astrophysics Data System (ADS)
Filali Boubrahimi, Soukaina; Aydin, Berkay; Schuh, Michael A.; Kempton, Dustin; Angryk, Rafal A.; Ma, Ruizhe
2018-05-01
This paper introduces four spatiotemporal interpolation methods that enrich complex, evolving region trajectories that are reported from a variety of ground-based and space-based solar observatories every day. Our interpolation module takes an existing solar event trajectory as its input and generates an enriched trajectory with any number of additional time–geometry pairs created by the most appropriate method. To this end, we designed four different interpolation techniques: MBR-Interpolation (Minimum Bounding Rectangle Interpolation), CP-Interpolation (Complex Polygon Interpolation), FI-Interpolation (Filament Polygon Interpolation), and Areal-Interpolation, which are presented here in detail. These techniques leverage k-means clustering, centroid shape signature representation, dynamic time warping, linear interpolation, and shape buffering to generate the additional polygons of an enriched trajectory. Using ground-truth objects, interpolation effectiveness is evaluated through a variety of measures based on several important characteristics that include spatial distance, area overlap, and shape (boundary) similarity. To our knowledge, this is the first research effort of this kind that attempts to address the broad problem of spatiotemporal interpolation of solar event trajectories. We conclude with a brief outline of future research directions and opportunities for related work in this area.
Ruiz, Duncan D. A.; Norberto de Souza, Osmar
2015-01-01
Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward’s, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes. PMID:26218832
De Paris, Renata; Quevedo, Christian V; Ruiz, Duncan D A; Norberto de Souza, Osmar
2015-01-01
Protein receptor conformations, obtained from molecular dynamics (MD) simulations, have become a promising treatment of its explicit flexibility in molecular docking experiments applied to drug discovery and development. However, incorporating the entire ensemble of MD conformations in docking experiments to screen large candidate compound libraries is currently an unfeasible task. Clustering algorithms have been widely used as a means to reduce such ensembles to a manageable size. Most studies investigate different algorithms using pairwise Root-Mean Square Deviation (RMSD) values for all, or part of the MD conformations. Nevertheless, the RMSD only may not be the most appropriate gauge to cluster conformations when the target receptor has a plastic active site, since they are influenced by changes that occur on other parts of the structure. Hence, we have applied two partitioning methods (k-means and k-medoids) and four agglomerative hierarchical methods (Complete linkage, Ward's, Unweighted Pair Group Method and Weighted Pair Group Method) to analyze and compare the quality of partitions between a data set composed of properties from an enzyme receptor substrate-binding cavity and two data sets created using different RMSD approaches. Ensembles of representative MD conformations were generated by selecting a medoid of each group from all partitions analyzed. We investigated the performance of our new method for evaluating binding conformation of drug candidates to the InhA enzyme, which were performed by cross-docking experiments between a 20 ns MD trajectory and 20 different ligands. Statistical analyses showed that the novel ensemble, which is represented by only 0.48% of the MD conformations, was able to reproduce 75% of all dynamic behaviors within the binding cavity for the docking experiments performed. Moreover, this new approach not only outperforms the other two RMSD-clustering solutions, but it also shows to be a promising strategy to distill biologically relevant information from MD trajectories, especially for docking purposes.
A Segment-Based Trajectory Similarity Measure in the Urban Transportation Systems.
Mao, Yingchi; Zhong, Haishi; Xiao, Xianjian; Li, Xiaofang
2017-03-06
With the rapid spread of built-in GPS handheld smart devices, the trajectory data from GPS sensors has grown explosively. Trajectory data has spatio-temporal characteristics and rich information. Using trajectory data processing techniques can mine the patterns of human activities and the moving patterns of vehicles in the intelligent transportation systems. A trajectory similarity measure is one of the most important issues in trajectory data mining (clustering, classification, frequent pattern mining, etc.). Unfortunately, the main similarity measure algorithms with the trajectory data have been found to be inaccurate, highly sensitive of sampling methods, and have low robustness for the noise data. To solve the above problems, three distances and their corresponding computation methods are proposed in this paper. The point-segment distance can decrease the sensitivity of the point sampling methods. The prediction distance optimizes the temporal distance with the features of trajectory data. The segment-segment distance introduces the trajectory shape factor into the similarity measurement to improve the accuracy. The three kinds of distance are integrated with the traditional dynamic time warping algorithm (DTW) algorithm to propose a new segment-based dynamic time warping algorithm (SDTW). The experimental results show that the SDTW algorithm can exhibit about 57%, 86%, and 31% better accuracy than the longest common subsequence algorithm (LCSS), and edit distance on real sequence algorithm (EDR) , and DTW, respectively, and that the sensitivity to the noise data is lower than that those algorithms.
Hurricane and Monsoon Tracking with Driftsondes
NASA Astrophysics Data System (ADS)
Drobinski, Philippe; Cocquerez, Philippe; Doerenbecher, A.; Hock, Terrence; Lavaysse, C.; Parsons, D.; Redelsperger, J. L.
Tropical cyclones (TCs) are a typical weather threat. The threat can apply to humans, their properties, and activities. Their prediction, particularly their trajectory and intensity, remains difficult. In addition, TCs develop above the tropical oceans where the coverage by in situ observations is poor and within cloud clusters (mesoscale convective systems MCS) that limit the ability of numerical weather prediction (NWP) models to assimilate satellite data [18]. Improved forecast of TCs trajectories is a huge benefit in terms of material costs of evacuations and damage, not being able to quantify saved life.
Hughes, Jan N.; Liew, Jeffrey; Kwok, Oiman
2008-01-01
Based on a sample of 480 academically at-risk first graders, we used a cluster analysis involving multimethod assessment (i.e., teacher-report, peer-evaluation, and self-report) of behavioral and psychological engagement to identify subtypes of academic engagement. Four theoretically and practically meaningful clusters were identified and labeled as cooperative (n = 95), resistive (n =96), enthusiastic (n = 188), and disaffected (n = 101). The four types did not differ in IQ measured with the Universal Nonverbal Intelligence Test. The cooperative group consisted of more female and Hispanic students, whereas the resistive group consisted of more male and African American students. The cooperative group was the most popular among peers, followed by the enthusiastic group. The disaffected and resistive groups had more emotional symptoms than the cooperative and enthusiastic groups. Academic engagement types also differed in growth trajectories of academic achievement measured with Woodcock Johnson III Tests of Achievement from second to fourth grade. For reading, the cooperative and enthusiastic groups outperformed the resistive and disaffected groups at the beginning. However, the growth rate was similar across engagement types. For math, the engagement types did not differ at the beginning. However, the cooperative group developed at a faster rate and had higher math achievement by fourth grade than the other types. The findings support the importance of teaching temperament-based regulatory skills and of providing a positive psychological climate for children's academic learning. PMID:19343104
Large-scale atomistic calculations of clusters in intense x-ray pulses
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ho, Phay J.; Knight, Chris
Here, we present the methodology of our recently developed Monte-Carlo/ Molecular-Dynamics method for studying the fundamental ultrafast dynamics induced by high-fluence, high-intensity x-ray free electron laser (XFEL) pulses in clusters. The quantum nature of the initiating ionization process is accounted for by a Monte Carlo method to calculate probabilities of electronic transitions, including photo absorption, inner-shell relaxation, photon scattering, electron collision and recombination dynamics, and thus track the transient electronic configurations explicitly. The freed electrons and ions are followed by classical particle trajectories using a molecular dynamics algorithm. These calculations reveal the surprising role of electron-ion recombination processes that leadmore » to the development of nonuniform spatial charge density profiles in x-ray excited clusters over femtosecond timescales. In the high-intensity limit, it is important to include the recombination dynamics in the calculated scattering response even for a 2- fs pulse. We also demonstrate that our numerical codes and algorithms can make e!cient use of the computational power of massively parallel supercomputers to investigate the intense-field dynamics in systems with increasing complexity and size at the ultrafast timescale and in non-linear x-ray interaction regimes. In particular, picosecond trajectories of XFEL clusters with attosecond time resolution containing millions of particles can be e!ciently computed on upwards of 262,144 processes.« less
Large-scale atomistic calculations of clusters in intense x-ray pulses
Ho, Phay J.; Knight, Chris
2017-04-28
Here, we present the methodology of our recently developed Monte-Carlo/ Molecular-Dynamics method for studying the fundamental ultrafast dynamics induced by high-fluence, high-intensity x-ray free electron laser (XFEL) pulses in clusters. The quantum nature of the initiating ionization process is accounted for by a Monte Carlo method to calculate probabilities of electronic transitions, including photo absorption, inner-shell relaxation, photon scattering, electron collision and recombination dynamics, and thus track the transient electronic configurations explicitly. The freed electrons and ions are followed by classical particle trajectories using a molecular dynamics algorithm. These calculations reveal the surprising role of electron-ion recombination processes that leadmore » to the development of nonuniform spatial charge density profiles in x-ray excited clusters over femtosecond timescales. In the high-intensity limit, it is important to include the recombination dynamics in the calculated scattering response even for a 2- fs pulse. We also demonstrate that our numerical codes and algorithms can make e!cient use of the computational power of massively parallel supercomputers to investigate the intense-field dynamics in systems with increasing complexity and size at the ultrafast timescale and in non-linear x-ray interaction regimes. In particular, picosecond trajectories of XFEL clusters with attosecond time resolution containing millions of particles can be e!ciently computed on upwards of 262,144 processes.« less
HIGH-ENERGY NEUTRINOS FROM SOURCES IN CLUSTERS OF GALAXIES
DOE Office of Scientific and Technical Information (OSTI.GOV)
Fang, Ke; Olinto, Angela V.
2016-09-01
High-energy cosmic rays can be accelerated in clusters of galaxies, by mega-parsec scale shocks induced by the accretion of gas during the formation of large-scale structures, or by powerful sources harbored in clusters. Once accelerated, the highest energy particles leave the cluster via almost rectilinear trajectories, while lower energy ones can be confined by the cluster magnetic field up to cosmological time and interact with the intracluster gas. Using a realistic model of the baryon distribution and the turbulent magnetic field in clusters, we studied the propagation and hadronic interaction of high-energy protons in the intracluster medium. We report themore » cumulative cosmic-ray and neutrino spectra generated by galaxy clusters, including embedded sources, and demonstrate that clusters can contribute a significant fraction of the observed IceCube neutrinos above 30 TeV while remaining undetected in high-energy cosmic rays and γ rays for reasonable choices of parameters and source scenarios.« less
Analysis of Chemical, REP, and SEP missions to the Trojan asteroids
NASA Technical Reports Server (NTRS)
Bonfiglio, Eugene P.; Oh, David; Yen, Chen-Wan
2005-01-01
Recent studies suggest significant benefits from using 1st and 2nd generation Radioisotope Power Systems (RPS) as a power source for electric propulsion (EP) missions to the outer planets. This study focuses on trajectories to the Trojan asteroids. A high level analysis is performed with chemical trajectories to determine potential canidates for REP trajectory optimization. Extensive analysis of direct trajectories using REP is performed on these candidates. Solar Electric Propulsion (SEP) trajectories are also considered for comparison against REP trajectories.
NASA Astrophysics Data System (ADS)
Tarasova, O. A.; Staehelin, J.; Senik, I. A.; Sosonkin, M. G.; Cui, J.; Prevot, A. S.
2008-12-01
An analysis of the atmospheric transport influence on the seasonal variations and trends of the surface ozone for two mountain sites, namely Kislovodsk High Mountain Station (KHMS) in Caucasus, Russia (43.7°N, 42.7°E, 2070 m asl.) and Jungfraujoch (JFJ) in Switzerland (46.5°N, 7.9°E, 3580 m asl) will be presented. Transport patterns are analyzed using 3D LAGRANTO trajectories. Main transport directions are obtained with the help of k-means trajectories clustering for the period 1990-2006. For each selected cluster average seasonal cycle and trends at two mountain locations are analyzed. Due to non-monotonous behavior of the trend the entire period is divided into two subsets (1991-2001 and 1997- 2006) which are studied separately. For both sites (JFJ and KHMS) the highest spring maximum is observed in May in the cluster, originating in East Asia and traveling to both sites with the longest contact with the upper free troposphere. Moreover, for both locations the excess of the summer maximum above the spring one is observed in the cluster of the local/regional transport due to ozone photochemical production in the polluted continental PBL. Trend of the surface ozone concentration at JFJ in 1991-2001 is connected with increased ozone concentrations in the free troposphere of mid latitude over West Atlantic/USA influenced by stratospheric concentration increase (most positive spring trend in trans-Atlantic clusters). The response to the regional European emission decrease observed in the local/regional advection cluster is less important but it is contributing to the seasonality of the trend. In 1997-2006 the trends at JFJ are more connected with European emissions regulations (the strongest trend are in the cluster of local/regional advection). The strong negative trends of the surface ozone concentrations at KHMS during both considered periods (1991-2001 and 1996-2007) are likely to be associated with different regime of emission (both of the local and regional scale), with abrupt emissions reduction in the beginning of 1990s in Former USSR and economical recovery during more recent period. The mentioned trends are best seen in the cluster with local/regional transport. Other reasons are also discussed in the presentation. The work is financially supported by the Swiss National Science Foundation (JRP IB7320-110831), European Commission (Marie-Curie IIF project N 039905 - FP6-2005-Mobility-7) and Russian Foundation for Basic Research (projects 06-05-64427 and 06-05-65308) and contributes to ACCENT T&TP project.
Interactions between tropical cyclones and mid-latitude systems in the Northeastern Pacific
NASA Astrophysics Data System (ADS)
Lugo, A.; Abarca, S. F.; Raga, G. B.; Vargas, D. C.
2014-12-01
Major challenges in tropical meteorology include the short-term forecast of tropical cyclone (TC) intensity, which is defined as the maximum tangential wind. Several efforts have been made in order to reach this goal over the last decade: Among these efforts, the study of lightning in the TC inner core (the region inside a disc of 100 km radius from the center) as a proxy to deep convection, has the potential to be used as a predictor to forecast intensity (DeMaria et al, 2012, Mon. Wea. Rev., 140, 1828-1842).While most studies focus their objectives in studying the lightning flash density in the inner core, we study the probability of flash occurrence for intensifying and weakening cyclones. We have analyzed the trajectories of the observed 62 tropical cyclones that developed in the basin from 2006 to 2009, and classified them into separate clusters according to their trajectories. These clusters can broadly be described as having trajectories mostly oriented: East-West, towards the central Pacific, NW far from the Mexican coast, parallel to the Mexican coast and recurving towards the Mexican coast.We estimate that probability of inner core lightning occurrence increases as cyclones intensify but the probability rapidly decrease as the systems weaken. This is valid for cyclones in most of the clusters. However, the cyclones that exhibit trajectories that recurve towards the Mexican coast, do not present the same relationship between intensity and inner-core lightning probability, these cyclones show little or no decrease in the lightning occurrence probability as they weaken.We hypothesize that one of the reasons for this anomalous behavior is likely the fact that these cyclones interact with mid-latitude systems. Mid-latitude systems are important in determining the recurving trajectory but they may also influence the TC by advecting mid-level moisture towards the TC inner core. This additional supply of moisture as the system is approaching land may enhance deep convection in the inner core and result in increases of lightning probability even though the cyclones are weakening. We use a Lagrangian approach similar to the used by Rutherford and Montgomery (2012, Atmos. Chem. Phys., 12, 11355-11381, 2012), to study moisture fluxes between intensifying and weakening in recurving tropical cyclones.
Masiol, Mauro; Centanni, Elena; Squizzato, Stefania; Hofer, Angelika; Pecorari, Eliana; Rampazzo, Giancarlo; Pavoni, Bruno
2012-09-01
This study presents a procedure to differentiate the local and remote sources of particulate-bound polycyclic aromatic hydrocarbons (PAHs). Data were collected during an extended PM(2.5) sampling campaign (2009-2010) carried out for 1 year in Venice-Mestre, Italy, at three stations with different emissive scenarios: urban, industrial, and semirural background. Diagnostic ratios and factor analysis were initially applied to point out the most probable sources. In a second step, the areal distribution of the identified sources was studied by applying the discriminant analysis on factor scores. Third, samples collected in days with similar atmospheric circulation patterns were grouped using a cluster analysis on wind data. Local contributions to PM(2.5) and PAHs were then assessed by interpreting cluster results with chemical data. Results evidenced that significantly lower levels of PM(2.5) and PAHs were found when faster winds changed air masses, whereas in presence of scarce ventilation, locally emitted pollutants were trapped and concentrations increased. This way, an estimation of pollutant loads due to local sources can be derived from data collected in days with similar wind patterns. Long-range contributions were detected by a cluster analysis on the air mass back-trajectories. Results revealed that PM(2.5) concentrations were relatively high when air masses had passed over the Po Valley. However, external sources do not significantly contribute to the PAHs load. The proposed procedure can be applied to other environments with minor modifications, and the obtained information can be useful to design local and national air pollution control strategies.
Wickrama, Kandauda K A S; Lee, Tae Kyoung; O'Neal, Catherine Walker; Kwon, Josephine A
2015-05-01
Although research has established the impact of early stress, including stressful life contexts, and early resources, such as educational attainment, on various adolescent health outcomes, previous research has not adequately investigated "integrative models" incorporating both stress and resource mediational pathways to explain how early socioeconomic adversity impacts physical health outcomes, particularly in early life stages. Data on early childhood/adolescent stress and socioeconomic resources as well as biomarkers indicating physical health status in young adulthood were collected from 11,798 respondents (54 % female) over a 13-year period from youth participating in the National Study of Adolescent Health (Add Health). Physical health risk in young adulthood was measured using a composite index of nine regulatory biomarkers of cardiovascular and metabolic systems. Heterogeneity in stress and socioeconomic resource pathways was assessed using latent class analysis to identify clusters, or classes, of stress and socioeconomic resource trajectories. The influence of early socioeconomic adversity on young adults' physical health risk, as measured by biomarkers, was estimated, and the role of stress and socioeconomic resource trajectory classes as linking mechanisms was assessed. There was evidence for the influence of early socioeconomic adversity on young adults' physical health risk directly and indirectly through stress and socioeconomic resource trajectory classes over the early life course. These findings suggest that health models should be broadened to incorporate both stress and resource experiences simultaneously. Furthermore, these findings have prevention and intervention implications, including the importance of early socioeconomic adversity and key intervention points for "turning" the trajectories of at-risk youth.
Spatiotemporal Analysis of Corn Phenoregions in the Continental United States
NASA Astrophysics Data System (ADS)
Konduri, V. S.; Kumar, J.; Hoffman, F. M.; Ganguly, A. R.; Hargrove, W. W.
2017-12-01
The delineation of regions exhibiting similar crop performance has potential benefits for agricultural planning and management, policymaking and natural resource conservation. Studies of natural ecosystems have used multivariate clustering algorithms based on environmental characteristics to identify ecoregions for species range prediction and habitat conservation. However, few studies have used clustering to delineate regions based on crop phenology. The aim of this study was to perform a spatiotemporal analysis of phenologically self-similar clusters, or phenoregions, for the major corn growing areas in the Continental United States (CONUS) for the period 2008-2016. Annual trajectories of remotely sensed normalized difference vegetation index (NDVI), a useful proxy for land surface phenology, derived from Moderate Resolution Spectroradiometer (MODIS) instruments at 8-day intervals and 250 m resolution was used as the phenological metric. Because of the large data volumes involved, the phenoregion delineation was performed using a highly scalable, unsupervised clustering technique with the help of high performance computing. These phenoregions capture the spatial variability in the timing of important crop phenological stages (like emergence and maturity dates) and thus could be used to develop more accurate parameterizations for crop models applied at regional to global scales. Moreover, historical crop performance from phenoregions, in combination with climate and soils data, could be used to improve production forecasts. The temporal variability in NDVI at each location could also be used to develop an early warning system to identify locations where the crop deviates from its expected phenological behavior. Such deviations may indicate a need for irrigation or fertilization or suggest where pest outbreaks or other disturbances have occurred.
Bringing Clouds into Our Lab! - The Influence of Turbulence on the Early Stage Rain Droplets
NASA Astrophysics Data System (ADS)
Yavuz, Mehmet Altug; Kunnen, Rudie; Heijst, Gertjan; Clercx, Herman
2015-11-01
We are investigating a droplet-laden flow in an air-filled turbulence chamber, forced by speaker-driven air jets. The speakers are running in a random manner; yet they allow us to control and define the statistics of the turbulence. We study the motion of droplets with tunable size (Stokes numbers ~ 0.13 - 9) in a turbulent flow, mimicking the early stages of raindrop formation. 3D Particle Tracking Velocimetry (PTV) together with Laser Induced Fluorescence (LIF) methods are chosen as the experimental method to track the droplets and collect data for statistical analysis. Thereby it is possible to study the spatial distribution of the droplets in turbulence using the so-called Radial Distribution Function (RDF), a statistical measure to quantify the clustering of particles. Additionally, 3D-PTV technique allows us to measure velocity statistics of the droplets and the influence of the turbulence on droplet trajectories, both individually and collectively. In this contribution, we will present the clustering probability quantified by the RDF for different Stokes numbers. We will explain the physics underlying the influence of turbulence on droplet cluster behavior. This study supported by FOM/NWO Netherlands.
Defining clusters in APT reconstructions of ODS steels.
Williams, Ceri A; Haley, Daniel; Marquis, Emmanuelle A; Smith, George D W; Moody, Michael P
2013-09-01
Oxide nanoclusters in a consolidated Fe-14Cr-2W-0.3Ti-0.3Y₂O₃ ODS steel and in the alloy powder after mechanical alloying (but before consolidation) are investigated by atom probe tomography (APT). The maximum separation method is a standard method to define and characterise clusters from within APT data, but this work shows that the extent of clustering between the two materials is sufficiently different that the nanoclusters in the mechanically alloyed powder and in the consolidated material cannot be compared directly using the same cluster selection parameters. As the cluster selection parameters influence the size and composition of the clusters significantly, a procedure to optimise the input parameters for the maximum separation method is proposed by sweeping the d(max) and N(min) parameter space. By applying this method of cluster parameter selection combined with a 'matrix correction' to account for trajectory aberrations, differences in the oxide nanoclusters can then be reliably quantified. Copyright © 2012 Elsevier B.V. All rights reserved.
Kannampallil, Thomas; Galanter, William L; Falck, Suzanne; Gaunt, Michael J; Gibbons, Robert D; McNutt, Robert; Odwazny, Richard; Schiff, Gordon; Vaida, Allen J; Wilkie, Diana J; Lambert, Bruce L
2016-12-01
Pain care for hospitalized patients is often suboptimal. Representing pain scores as a graphical trajectory may provide insights into the understanding and treatment of pain. We describe a 1-year, retrospective, observational study to characterize pain trajectories of hospitalized adults during the first 48 hours after admission at an urban academic medical center. Using a subgroup of patients who presented with significant pain (pain score >4; n = 7762 encounters), we characterized pain trajectories and measured area under the curve, slope of the trajectory for the first 2 hours after admission, and pain intensity at plateau. We used mixed-effects regression to assess the association between pain score and sociodemographics (age, race, and gender), pain medication orders (opioids, nonopioids, and no medications), and medical service (obstetrics, psychiatry, surgery, sickle cell, intensive care unit, and medicine). K-means clustering was used to identify patient subgroups with similar trajectories. Trajectories showed differences based on race, gender, service, and initial pain score. Patients presumed to have dissimilar pain experiences (eg, sickle vs obstetrical) had markedly different pain trajectories. Patients with higher initial pain had a more rapid reduction during their first 2 hours of treatment. Pain reduction achieved in the 48 hours after admission was approximately 50% of the initial pain, regardless of the initial pain. Most patients' pain failed to fully resolve, plateauing at a pain score of 4 or greater. Visualizing pain scores as graphical trajectories illustrates the dynamic variability in pain, highlighting pain responses over a period of observation, and may yield new insights for quality improvement and research.
NASA Astrophysics Data System (ADS)
Biswas, Sohag; Dasgupta, Teesta; Mallik, Bhabani S.
2016-09-01
We present the reactivity of an organic intermediate by studying the proton transfer process from water to ketyl radical anion using gas phase electronic structure calculations and the metadynamics method based first principles molecular dynamics (FPMD) simulations. Our results indicate that during the micro solvation of anion by water molecules systematically, the presence of minimum three water molecules in the gas phase cluster is sufficient to observe the proton transfer event. The analysis of trajectories obtained from initial FPMD simulation of an aqueous solution of the anion does not show any evident of complete transfer of the proton from water. The cooperativity of water molecules and the relatively weak anion-water interaction in liquid state prohibit the full release of the proton. Using biasing potential through first principles metadynamics simulations, we report the observation of proton transfer reaction from water to ketyl radical anion with a barrier height of 16.0 kJ/mol.
Nakar, Orit; Brunner, Romuald; Schilling, Oliver; Chanen, Andrew; Fischer, Gloria; Parzer, Peter; Carli, Vladimir; Wasserman, Danuta; Sarchiapone, Marco; Wasserman, Camilla; Hoven, Christina W; Resch, Franz; Kaess, Michael
2016-06-01
Adolescent risk-taking and self-harm behaviors are associated with affect dysregulation and impulsivity, both core features of borderline personality disorder (BPD). We hypothesized that the developmental courses of these behaviors i) tend to cluster rather than appear individually, and ii) might indicate adolescent BPD pathology. Therefore, we explored the developmental trajectories of self-injurious behavior (SIB), suicidal behavior (SB) and substance misuse (SM) in a community sample of adolescents; and we investigated the trajectories' overlap and its associations with BPD traits. 513 adolescents, aged 15-17 years, were followed for two years as part of the Saving and Empowering Young Lives in Europe study and its subsequent follow-up. Distinct developmental trajectories were explored using general growth mixture modeling. Three distinct classes were identified within each of the harmful behaviors SIB, SB and SM. Both the high-risk SIB trajectory and the high-risk SB trajectory demonstrated elevated initial degree of engagement, followed by a gradual decrease. The SM high-risk trajectory had a medium initial degree of engagement, which increased over time. There was a high degree of overlap (80-90%) among the high-risk trajectories for the three behaviors (SIB, SB and SM), and this overlap was significantly associated with elevated levels of BPD pathology. The data collection was based on participants' self-report. The findings indicate a similar pattern of reduction over time between SIB and SB for the high-risk trajectories, whereas the high-risk trajectories for SM show a pattern of increase over time. The observed symptom shift is associated with borderline personality pathology in adolescents. Therefore these behaviors might represent early indicators of risk supporting potential early detection. Copyright © 2016 Elsevier B.V. All rights reserved.
Post-processing interstitialcy diffusion from molecular dynamics simulations
NASA Astrophysics Data System (ADS)
Bhardwaj, U.; Bukkuru, S.; Warrier, M.
2016-01-01
An algorithm to rigorously trace the interstitialcy diffusion trajectory in crystals is developed. The algorithm incorporates unsupervised learning and graph optimization which obviate the need to input extra domain specific information depending on crystal or temperature of the simulation. The algorithm is implemented in a flexible framework as a post-processor to molecular dynamics (MD) simulations. We describe in detail the reduction of interstitialcy diffusion into known computational problems of unsupervised clustering and graph optimization. We also discuss the steps, computational efficiency and key components of the algorithm. Using the algorithm, thermal interstitialcy diffusion from low to near-melting point temperatures is studied. We encapsulate the algorithms in a modular framework with functionality to calculate diffusion coefficients, migration energies and other trajectory properties. The study validates the algorithm by establishing the conformity of output parameters with experimental values and provides detailed insights for the interstitialcy diffusion mechanism. The algorithm along with the help of supporting visualizations and analysis gives convincing details and a new approach to quantifying diffusion jumps, jump-lengths, time between jumps and to identify interstitials from lattice atoms.
Post-processing interstitialcy diffusion from molecular dynamics simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bhardwaj, U., E-mail: haptork@gmail.com; Bukkuru, S.; Warrier, M.
2016-01-15
An algorithm to rigorously trace the interstitialcy diffusion trajectory in crystals is developed. The algorithm incorporates unsupervised learning and graph optimization which obviate the need to input extra domain specific information depending on crystal or temperature of the simulation. The algorithm is implemented in a flexible framework as a post-processor to molecular dynamics (MD) simulations. We describe in detail the reduction of interstitialcy diffusion into known computational problems of unsupervised clustering and graph optimization. We also discuss the steps, computational efficiency and key components of the algorithm. Using the algorithm, thermal interstitialcy diffusion from low to near-melting point temperatures ismore » studied. We encapsulate the algorithms in a modular framework with functionality to calculate diffusion coefficients, migration energies and other trajectory properties. The study validates the algorithm by establishing the conformity of output parameters with experimental values and provides detailed insights for the interstitialcy diffusion mechanism. The algorithm along with the help of supporting visualizations and analysis gives convincing details and a new approach to quantifying diffusion jumps, jump-lengths, time between jumps and to identify interstitials from lattice atoms. -- Graphical abstract:.« less
Trajectory-Based Loads for the Ares I-X Test Flight Vehicle
NASA Technical Reports Server (NTRS)
Vause, Roland F.; Starr, Brett R.
2011-01-01
In trajectory-based loads, the structural engineer treats each point on the trajectory as a load case. Distributed aero, inertial, and propulsion forces are developed for the structural model which are equivalent to the integrated values of the trajectory model. Free-body diagrams are then used to solve for the internal forces, or loads, that keep the applied aero, inertial, and propulsion forces in dynamic equilibrium. There are several advantages to using trajectory-based loads. First, consistency is maintained between the integrated equilibrium equations of the trajectory analysis and the distributed equilibrium equations of the structural analysis. Second, the structural loads equations are tied to the uncertainty model for the trajectory systems analysis model. Atmosphere, aero, propulsion, mass property, and controls uncertainty models all feed into the dispersions that are generated for the trajectory systems analysis model. Changes in any of these input models will affect structural loads response. The trajectory systems model manages these inputs as well as the output from the structural model over thousands of dispersed cases. Large structural models with hundreds of thousands of degrees of freedom would execute too slowly to be an efficient part of several thousand system analyses. Trajectory-based loads provide a means for the structures discipline to be included in the integrated systems analysis. Successful applications of trajectory-based loads methods for the Ares I-X vehicle are covered in this paper. Preliminary design loads were based on 2000 trajectories using Monte Carlo dispersions. Range safety loads were tied to 8423 malfunction turn trajectories. In addition, active control system loads were based on 2000 preflight trajectories using Monte Carlo dispersions.
Uniform deposition of size-selected clusters using Lissajous scanning
DOE Office of Scientific and Technical Information (OSTI.GOV)
Beniya, Atsushi; Watanabe, Yoshihide, E-mail: e0827@mosk.tytlabs.co.jp; Hirata, Hirohito
2016-05-15
Size-selected clusters can be deposited on the surface using size-selected cluster ion beams. However, because of the cross-sectional intensity distribution of the ion beam, it is difficult to define the coverage of the deposited clusters. The aggregation probability of the cluster depends on coverage, whereas cluster size on the surface depends on the position, despite the size-selected clusters are deposited. It is crucial, therefore, to deposit clusters uniformly on the surface. In this study, size-selected clusters were deposited uniformly on surfaces by scanning the cluster ions in the form of Lissajous pattern. Two sets of deflector electrodes set in orthogonalmore » directions were placed in front of the sample surface. Triangular waves were applied to the electrodes with an irrational frequency ratio to ensure that the ion trajectory filled the sample surface. The advantages of this method are simplicity and low cost of setup compared with raster scanning method. The authors further investigated CO adsorption on size-selected Pt{sub n} (n = 7, 15, 20) clusters uniformly deposited on the Al{sub 2}O{sub 3}/NiAl(110) surface and demonstrated the importance of uniform deposition.« less
NASA Astrophysics Data System (ADS)
Schlueter-Kuck, Kristy; Dabiri, John
2017-11-01
In recent years, there has been a proliferation of techniques that aim to characterize fluid flow kinematics on the basis of Lagrangian trajectories of collections of tracer particles. Most of these techniques depend on presence of tracer particles that are initially closely-spaced, in order to compute local gradients of their trajectories. In many applications, the requirement of close tracer spacing cannot be satisfied, especially when the tracers are naturally occurring and their distribution is dictated by the underlying flow. Moreover, current methods often focus on determination of the boundaries of coherent sets, whereas in practice it is often valuable to identify the complete set of trajectories that are coherent with an individual trajectory of interest. We extend the concept of Coherent Structure Coloring to achieve identification of the coherent set associated with individual Lagrangian trajectories. This algorithm is proven successful in identifying coherent structures of varying complexities in canonical unsteady flows. Importantly, although the method is demonstrated here in the context of fluid flow kinematics, the generality of the approach allows for its potential application to other unsupervised clustering problems in dynamical systems. This work was supported by the Department of Defense (DoD) through the National Defense Science & Engineering Graduate Fellowship (NDSEG) Program.
Symptom Clusters Change over Time in Women Receiving Adjuvant Chemotherapy for Breast Cancer
Albusoul, Randa M.; Berger, Ann M.; Gay, Caryl L.; Janson, Susan L.; Lee, Kathryn A.
2017-01-01
Context Patients with breast cancer receiving chemotherapy (CTX) experience multiple concurrent symptoms, but little is known about how symptoms change during and after treatment. Knowledge of the identity and trajectory of symptom clusters (SCs) would enhance measurement and management. Objectives We aimed to identify SCs and their change over time from baseline to completion of breast cancer CTX. Methods SCs were identified and assessed for change in 219 women from Nebraska at four times: baseline, during cycles #3 and #4 of CTX, and one-month after finishing CTX. Ten symptoms were measured: two using the Hospital Anxiety and Depression Scale and eight using the Symptom Experience Scale. Exploratory factor analysis was conducted at each time point, then changes in SCs were evaluated at different times. Results Two SCs were identified before and after initiating CTX: Gastrointestinal (GI) and Treatment-related (Tr). The number and type of symptoms in each cluster differed over time. Clusters were dynamic during CTX with changes in the number and type of symptoms. Only one Tr SC, which consisted of fatigue, pain, and sleep disturbance, was identified after CTX completion. Conclusion SCs during CTX appear to be dynamic, changing over time from before until after CTX completion. Repeated assessments of SCs reveal symptoms that are present and when patients are most burdened and in need of additional support. PMID:28062343
Rapid, directed transport of DC-SIGN clusters in the plasma membrane
Liu, Ping; Weinreb, Violetta; Ridilla, Marc; Betts, Laurie; Patel, Pratik; de Silva, Aravinda M.; Thompson, Nancy L.; Jacobson, Ken
2017-01-01
C-type lectins, including dendritic cell–specific intercellular adhesion molecule-3–grabbing nonintegrin (DC-SIGN), are all-purpose pathogen receptors that exist in nanoclusters in plasma membranes of dendritic cells. A small fraction of these clusters, obvious from the videos, can undergo rapid, directed transport in the plane of the plasma membrane at average speeds of more than 1 μm/s in both dendritic cells and MX DC-SIGN murine fibroblasts ectopically expressing DC-SIGN. Surprisingly, instantaneous speeds can be considerably greater. In MX DC-SIGN cells, many cluster trajectories are colinear with microtubules that reside close to the ventral membrane, and the microtubule-depolymerizing drug, nocodazole, markedly reduced the areal density of directed movement trajectories, suggesting a microtubule motor–driven transport mechanism; by contrast, latrunculin A, which affects the actin network, did not depress this movement. Rapid, retrograde movement of DC-SIGN may be an efficient mechanism for bringing bound pathogen on the leading edge and projections of dendritic cells to the perinuclear region for internalization and processing. Dengue virus bound to DC-SIGN on dendritic projections was rapidly transported toward the cell center. The existence of this movement within the plasma membrane points to an unexpected lateral transport mechanism in mammalian cells and challenges our current concepts of cortex-membrane interactions. PMID:29134199
NASA Astrophysics Data System (ADS)
Li, Lili; Liu, Yihong; Wang, Yunpeng
2017-07-01
Urban air pollution is influenced not only by local emission sources including industry and vehicles, but also greatly by regional atmospheric pollutant transportation from the surrounding areas, especially in developed city clusters, like the Pearl River Delta (PRD). Taking an air pollution episode in Shenzhen as an example, this paper investigates the occurrence and evolution of the pollution episode and identifies the transport pathways of air pollutants in Shenzhen by combining MODIS satellite images and HYSPLIT back trajectory analysis. Results show that this pollution episode is mainly caused by the local emission of pollutants in PRD and oceanic air masses under specific weather conditions.
Synchronization of relativistic particles in the hyperbolic Kuramoto model
NASA Astrophysics Data System (ADS)
Ritchie, Louis M.; Lohe, M. A.; Williams, Anthony G.
2018-05-01
We formulate a noncompact version of the Kuramoto model by replacing the invariance group SO(2) of the plane rotations by the noncompact group SO(1, 1). The N equations of the system are expressed in terms of hyperbolic angles αi and are similar to those of the Kuramoto model, except that the trigonometric functions are replaced by hyperbolic functions. Trajectories are generally unbounded, nevertheless synchronization occurs for any positive couplings κi, arbitrary positive multiplicative parameters λi and arbitrary exponents ωi. There are no critical values for the coupling constants. We measure the onset of synchronization by means of several order and disorder parameters. We show numerically and by means of exact solutions for N = 2 that solutions can develop singularities if the coupling constants are negative, or if the initial values are not suitably restricted. We describe a physical interpretation of the system as a cluster of interacting relativistic particles in 1 + 1 dimensions, subject to linear repulsive forces with space-time trajectories parametrized by the rapidity αi. The trajectories synchronize provided that the particle separations remain predominantly time-like, and the synchronized cluster can be viewed as a bound state of N relativistic particle constituents. We extend the defining equations of the system to higher dimensions by means of vector equations which are covariant with respect to SO(p, q).
Moritsugu, Kei; Koike, Ryotaro; Yamada, Kouki; Kato, Hiroaki; Kidera, Akinori
2015-01-01
Molecular dynamics (MD) simulations of proteins provide important information to understand their functional mechanisms, which are, however, likely to be hidden behind their complicated motions with a wide range of spatial and temporal scales. A straightforward and intuitive analysis of protein dynamics observed in MD simulation trajectories is therefore of growing significance with the large increase in both the simulation time and system size. In this study, we propose a novel description of protein motions based on the hierarchical clustering of fluctuations in the inter-atomic distances calculated from an MD trajectory, which constructs a single tree diagram, named a “Motion Tree”, to determine a set of rigid-domain pairs hierarchically along with associated inter-domain fluctuations. The method was first applied to the MD trajectory of substrate-free adenylate kinase to clarify the usefulness of the Motion Tree, which illustrated a clear-cut dynamics picture of the inter-domain motions involving the ATP/AMP lid and the core domain together with the associated amplitudes and correlations. The comparison of two Motion Trees calculated from MD simulations of ligand-free and -bound glutamine binding proteins clarified changes in inherent dynamics upon ligand binding appeared in both large domains and a small loop that stabilized ligand molecule. Another application to a huge protein, a multidrug ATP binding cassette (ABC) transporter, captured significant increases of fluctuations upon binding a drug molecule observed in both large scale inter-subunit motions and a motion localized at a transmembrane helix, which may be a trigger to the subsequent structural change from inward-open to outward-open states to transport the drug molecule. These applications demonstrated the capabilities of Motion Trees to provide an at-a-glance view of various sizes of functional motions inherent in the complicated MD trajectory. PMID:26148295
Tracking career performance of successful triathletes.
Malcata, Rita M; Hopkins, Will G; Pearson, Simon N
2014-06-01
Tracking athletes' performances over time is important but problematic for sports with large environmental effects. Here we have developed career performance trajectories for elite triathletes, investigating changes in swim, cycle, run stages, and total performance times while accounting for environmental and other external factors. Performance times of 337 female and 427 male triathletes competing in 419 international races between 2000 and 2012 were obtained from triathlon.org. Athletes were categorized according to any top 16 placing at World Championships or Olympics between 2008 and 2012. A mixed linear model accounting for race distance (sprint and Olympic), level of competition, calendar-year trend, athlete's category, and clustering of times within athletes and races was used to derive athletes' individual quadratic performance trajectories. These trajectories provided estimates of age of peak performance and predictions for the 2012 London Olympic Games. By markedly reducing the scatter of individual race times, the model produced well-fitting trajectories suitable for comparison of triathletes. Trajectories for top 16 triathletes showed different patterns for race stages and differed more among women than among men, but ages of peak total performance were similar for men and women (28 ± 3 yr, mean ± SD). Correlations between observed and predicted placings at Olympics were slightly higher than those provided by placings in races before the Olympics. Athletes' trajectories will help identify talented athletes and their weakest and strongest stages. The wider range of trajectories among women should be taken into account when setting talent identification criteria. Trajectories offer a small advantage over usual race placings for predicting men's performance. Further refinements, such as accounting for individual responses to race conditions, may improve utility of performance trajectories.
Osofsky, Joy D; Osofsky, Howard J; Weems, Carl F; King, Lucy S; Hansel, Tonya C
2015-12-01
Theorists and researchers have demonstrated multiple trajectories of symptoms following disasters (Ecology and Society, 13, 2008, 9), highlighting the importance of obtaining more knowledge about exposed youth who demonstrate resilience as well as those who suffer chronic difficulties. This paper examines trajectories of post-traumatic stress disorder (PTSD) symptoms following exposure to hurricanes and the Deepwater Horizon Oil Spill to increase understanding of resilience and chronic reactions to both natural and technological disasters. A multiwave longitudinal design was used to follow N = 4,619 youth who were evaluated for PTSD symptoms, hurricane exposure, and oil spill exposure/stress at four time points over a period of 4 years. Trajectories were identified with cluster analyses and multilevel modeling. Individual trajectories were statistically identified consistent with theory. The largest group exhibited stable-low symptoms (52%), a second group showed steep declines following initial symptoms (21%), a third group exhibited increasing symptoms (18%), and a fourth group showed stable-high symptoms (9%). Both hurricane exposure and oil spill stress predicted trajectories and overall levels of PTSD symptoms. Results identified an effect of oil spill stress and hurricane exposure on symptom levels and trajectories of exposed youth. Results provide prospective data to support theories of multiple symptom trajectories following disasters and reinforce the importance of research that utilizes a developmental perspective to consider the long-term effects of disasters in youth. Findings highlight the importance of identifying symptoms and predictors of resilience as well as factors that contribute to resilience. © 2015 Association for Child and Adolescent Mental Health.
Analysis of Spatio-Temporal Traffic Patterns Based on Pedestrian Trajectories
NASA Astrophysics Data System (ADS)
Busch, S.; Schindler, T.; Klinger, T.; Brenner, C.
2016-06-01
For driver assistance and autonomous driving systems, it is essential to predict the behaviour of other traffic participants. Usually, standard filter approaches are used to this end, however, in many cases, these are not sufficient. For example, pedestrians are able to change their speed or direction instantly. Also, there may be not enough observation data to determine the state of an object reliably, e.g. in case of occlusions. In those cases, it is very useful if a prior model exists, which suggests certain outcomes. For example, it is useful to know that pedestrians are usually crossing the road at a certain location and at certain times. This information can then be stored in a map which then can be used as a prior in scene analysis, or in practical terms to reduce the speed of a vehicle in advance in order to minimize critical situations. In this paper, we present an approach to derive such a spatio-temporal map automatically from the observed behaviour of traffic participants in everyday traffic situations. In our experiments, we use one stationary camera to observe a complex junction, where cars, public transportation and pedestrians interact. We concentrate on the pedestrians trajectories to map traffic patterns. In the first step, we extract trajectory segments from the video data. These segments are then clustered in order to derive a spatial model of the scene, in terms of a spatially embedded graph. In the second step, we analyse the temporal patterns of pedestrian movement on this graph. We are able to derive traffic light sequences as well as the timetables of nearby public transportation. To evaluate our approach, we used a 4 hour video sequence. We show that we are able to derive traffic light sequences as well as time tables of nearby public transportation.
Kwon, Soyang; Janz, Kathleen F; Letuchy, Elena M; Burns, Trudy L; Levy, Steven M
2015-07-01
The diverse developmental patterns of obesogenic behaviors during childhood and adolescence can be better understood by using new analytic approaches to assess the heterogeneity in variation during growth and development and to map the clustering of behavior patterns. To identify distinct trajectories of daily time spent in moderate- to vigorous-intensity physical activity (MVPA) from ages 5 to 19 years and to examine the associations of MVPA trajectories with sports participation and television viewing trajectories. Cohort members in the prospective population-based Iowa Bone Development Study participated in MVPA assessments via accelerometry from September 16, 1998, to December 9, 2013, at ages 5, 8, 11, 13, 15, 17, and 19 years and completed a questionnaire every 6 months on sports participation and daily time spent in television viewing. Trajectories of MVPA (minutes per day), participation in organized sports (yes or no), and television viewing time (hours per day). Based on the data from 537 participants (50.1% females; 94.6% white), we identified 4 MVPA trajectories: consistently inactive (14.9%), consistently active (18.1%), decreasing moderate physical activity (52.9%), and substantially decreasing high physical activity (14.1%). All participants in the consistently inactive trajectory also followed a trajectory of no participation in sports. The consistently active trajectory was associated with decreasing an already low television viewing trajectory (P < .001). This study provided a nuanced look at the known decrease in MVPA during childhood and adolescence. Sports participation could be a critical way to avoid the consistently inactive pattern. Most important, we identified a subset of participants who maintained a seemingly healthy level of MVPA from childhood to young adulthood. The developmental pathways of physical activity and television viewing behaviors could be related. Additional studies should examine the determinants and health consequences of these specific MVPA trajectories.
Collective Emotions Online and Their Influence on Community Life
Chmiel, Anna; Sienkiewicz, Julian; Thelwall, Mike; Paltoglou, Georgios; Buckley, Kevan; Kappas, Arvid; Hołyst, Janusz A.
2011-01-01
Background E-communities, social groups interacting online, have recently become an object of interdisciplinary research. As with face-to-face meetings, Internet exchanges may not only include factual information but also emotional information – how participants feel about the subject discussed or other group members. Emotions in turn are known to be important in affecting interaction partners in offline communication in many ways. Could emotions in Internet exchanges affect others and systematically influence quantitative and qualitative aspects of the trajectory of e-communities? The development of automatic sentiment analysis has made large scale emotion detection and analysis possible using text messages collected from the web. However, it is not clear if emotions in e-communities primarily derive from individual group members' personalities or if they result from intra-group interactions, and whether they influence group activities. Methodology/Principal Findings Here, for the first time, we show the collective character of affective phenomena on a large scale as observed in four million posts downloaded from Blogs, Digg and BBC forums. To test whether the emotions of a community member may influence the emotions of others, posts were grouped into clusters of messages with similar emotional valences. The frequency of long clusters was much higher than it would be if emotions occurred at random. Distributions for cluster lengths can be explained by preferential processes because conditional probabilities for consecutive messages grow as a power law with cluster length. For BBC forum threads, average discussion lengths were higher for larger values of absolute average emotional valence in the first ten comments and the average amount of emotion in messages fell during discussions. Conclusions/Significance Overall, our results prove that collective emotional states can be created and modulated via Internet communication and that emotional expressiveness is the fuel that sustains some e-communities. PMID:21818302
Rohlman, C E; Blanco, M R; Walter, N G
2016-01-01
The spliceosome is a biomolecular machine that, in all eukaryotes, accomplishes site-specific splicing of introns from precursor messenger RNAs (pre-mRNAs) with high fidelity. Operating at the nanometer scale, where inertia and friction have lost the dominant role they play in the macroscopic realm, the spliceosome is highly dynamic and assembles its active site around each pre-mRNA anew. To understand the structural dynamics underlying the molecular motors, clocks, and ratchets that achieve functional accuracy in the yeast spliceosome (a long-standing model system), we have developed single-molecule fluorescence resonance energy transfer (smFRET) approaches that report changes in intra- and intermolecular interactions in real time. Building on our work using hidden Markov models (HMMs) to extract kinetic and conformational state information from smFRET time trajectories, we recognized that HMM analysis of individual state transitions as independent stochastic events is insufficient for a biomolecular machine as complex as the spliceosome. In this chapter, we elaborate on the recently developed smFRET-based Single-Molecule Cluster Analysis (SiMCAn) that dissects the intricate conformational dynamics of a pre-mRNA through the splicing cycle in a model-free fashion. By leveraging hierarchical clustering techniques developed for Bioinformatics, SiMCAn efficiently analyzes large datasets to first identify common molecular behaviors. Through a second level of clustering based on the abundance of dynamic behaviors exhibited by defined functional intermediates that have been stalled by biochemical or genetic tools, SiMCAn then efficiently assigns pre-mRNA FRET states and transitions to specific splicing complexes, with the potential to find heretofore undescribed conformations. SiMCAn thus arises as a general tool to analyze dynamic cellular machines more broadly. © 2016 Elsevier Inc. All rights reserved.
Hoekstra, Femke; van Offenbeek, Marjolein A G; Dekker, Rienk; Hettinga, Florentina J; Hoekstra, Trynke; van der Woude, Lucas H V; van der Schans, Cees P
2017-12-01
Although the importance of evaluating implementation fidelity is acknowledged, little is known about heterogeneity in fidelity over time. This study aims to generate insight into the heterogeneity in implementation fidelity trajectories of a health promotion program in multidisciplinary settings and the relationship with changes in patients' health behavior. This study used longitudinal data from the nationwide implementation of an evidence-informed physical activity promotion program in Dutch rehabilitation care. Fidelity scores were calculated based on annual surveys filled in by involved professionals (n = ± 70). Higher fidelity scores indicate a more complete implementation of the program's core components. A hierarchical cluster analysis was conducted on the implementation fidelity scores of 17 organizations at three different time points. Quantitative and qualitative data were used to explore organizational and professional differences between identified trajectories. Regression analyses were conducted to determine differences in patient outcomes. Three trajectories were identified as the following: 'stable high fidelity' (n = 9), 'moderate and improving fidelity' (n = 6), and 'unstable fidelity' (n = 2). The stable high fidelity organizations were generally smaller, started earlier, and implemented the program in a more structured way compared to moderate and improving fidelity organizations. At the implementation period's start and end, support from physicians and physiotherapists, professionals' appreciation, and program compatibility were rated more positively by professionals working in stable high fidelity organizations as compared to the moderate and improving fidelity organizations (p < .05). Qualitative data showed that the stable high fidelity organizations had often an explicit vision and strategy about the implementation of the program. Intriguingly, the trajectories were not associated with patients' self-reported physical activity outcomes (adjusted model β = - 651.6, t(613) = - 1032, p = .303). Differences in organizational-level implementation fidelity trajectories did not result in outcome differences at patient-level. This suggests that an effective implementation fidelity trajectory is contingent on the local organization's conditions. More specifically, achieving stable high implementation fidelity required the management of tensions: realizing a localized change vision, while safeguarding the program's standardized core components and engaging the scarce physicians throughout the process. When scaling up evidence-informed health promotion programs, we propose to tailor the management of implementation tensions to local organizations' starting position, size, and circumstances. The Netherlands National Trial Register NTR3961 . Registered 18 April 2013.
TrackTable Trajectory Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wilson, Andrew T.
Tracktable is designed for analysis and rendering of the trajectories of moving objects such as planes, trains, automobiles and ships. Its purpose is to operate on large sets of trajectories (millions) to help a user detect, analyze and display patterns. It will also be used to disseminate trajectory research results from Sandia's PANTHER Grand Challenge LDRD.
Performance Analysis and Design Synthesis (PADS) computer program. Volume 3: User manual
NASA Technical Reports Server (NTRS)
1972-01-01
The two-fold purpose of the Performance Analysis and Design Synthesis (PADS) computer program is discussed. The program can size launch vehicles in conjunction with calculus-of-variations optimal trajectories and can also be used as a general purpose branched trajectory optimization program. For trajectory optimization alone or with sizing, PADS has two trajectory modules. The first trajectory module uses the method of steepest descent. The second module uses the method of quasi-linearization, which requires a starting solution from the first trajectory module.
NASA Astrophysics Data System (ADS)
Dimitriou, Konstantinos; Kassomenos, Pavlos
2013-11-01
Particulate air pollution is associated with adverse health effects to the population exposed. The aim of this paper is the identification of local and regional sources, affecting PM10 and PM2.5 levels in four large cities of southern Europe, namely: Lisbon, Madrid, Marseille, and Rome. Air pollution data from seven sampling sites of the European Union network were used. These stations were selected due to their ability of monitoring PM2.5 concentrations and providing reliable series of data. Each station's background was also taken into account. Pearson correlation coefficients and primal component analysis components were extracted separately for cold and warm periods in order to define the relationships among particle matters (PMs) and gaseous pollutants (CO, NO2, SO2, and O3) and evaluate the contributions of local sources. Possible seasonal variations of PM2.5/PM10 ratio daily values were also used as markers of PM sources, influencing particulate size distribution. Particle emissions were primarily attributed to traffic and secondarily to natural sources. Minimum daily values of PM2.5/PM10 ratio were observed during warm periods, particularly at suburban stations with rural background, due to dust resuspension and also due to the increase of biogenic coarse PM (pollen, dust, etc.). Hybrid Single-Particle Lagrangian Integrated Trajectory Model trajectory model was used in order to compute the 4-day backward trajectories of the air masses that affected the four cities which are under study during days with recorded PM10 exceedances, within a 5-year period (2003-2007), at 300, 750, and 1,500 m above ground level (AGL). The trajectories were then divided to clusters with a K-means analysis. In all four cities, the influence of slow-moving air masses was associated with a large fraction of PM10 exceedances and with high average and maximum daily mean PM10 concentrations, principally at the 300 m AGL analysis. As far the issue of the increased PM10 concentrations, the results were weaker in Marseille and particularly in Rome, probably due to their greater distance from Northwest Africa, in comparison to Madrid and Lisbon. Dust intrusions from the Sahara desert and transportation of Mediterranean/Atlantic sea spray, were characterized as primary regional sources of exogenous PM10 in all four cities. Continental trajectories from the industrialized northern Italy affected PM10 levels particularly in Marseille and Rome, due to their more eastern geographical position.
Water network-mediated, electron-induced proton transfer in [C5H5N ṡ (H2O)n]- clusters
NASA Astrophysics Data System (ADS)
DeBlase, Andrew F.; Wolke, Conrad T.; Weddle, Gary H.; Archer, Kaye A.; Jordan, Kenneth D.; Kelly, John T.; Tschumper, Gregory S.; Hammer, Nathan I.; Johnson, Mark A.
2015-10-01
The role of proton-assisted charge accommodation in electron capture by a heterocyclic electron scavenger is investigated through theoretical analysis of the vibrational spectra of cold, gas phase [Py ṡ (H2O)n=3-5]- clusters. These radical anions are formed when an excess electron is attached to water clusters containing a single pyridine (Py) molecule in a supersonic jet ion source. Under these conditions, the cluster ion distribution starts promptly at n = 3, and the photoelectron spectra, combined with vibrational predissociation spectra of the Ar-tagged anions, establish that for n > 3, these species are best described as hydrated hydroxide ions with the neutral pyridinium radical, PyH(0), occupying one of the primary solvation sites of the OH-. The n = 3 cluster appears to be a special case where charge localization on Py and hydroxide is nearly isoenergetic, and the nature of this species is explored with ab initio molecular dynamics calculations of the trajectories that start from metastable arrangements of the anion based on a diffuse, essentially dipole-bound electron. These calculations indicate that the reaction proceeds via a relatively slow rearrangement of the water network to create a favorable hydration configuration around the water molecule that eventually donates a proton to the Py nitrogen atom to yield the product hydroxide ion. The correlation between the degree of excess charge localization and the evolving shape of the water network revealed by this approach thus provides a microscopic picture of the "solvent coordinate" at the heart of a prototypical proton-coupled electron transfer reaction.
Gujt, Jure; Podlipnik, Črtomir; Bešter-Rogač, Marija; Spohr, Eckhard
2014-09-28
The relative position of the hydroxylic and the carboxylic group in the isomeric hydroxybenzoate (HB) anions is known to have a large impact on transport properties of this species. It also influences crucially the self-organisation of cationic surfactants. In this article a systematic investigation of aqueous solutions of the ortho, meta, and para isomers of the HB anion is presented. Molecular dynamics simulations of all three HB isomers were conducted for two different concentrations at 298.15 K and using two separate water models. From the resulting trajectories we calculated the self-diffusion coefficient of each isomer. According to the calculated self-diffusion coefficients, isomers were ranked in the order o-HB > m-HB > p-HB at both concentrations for both the used SPC and SPC/E water models, which agrees very well with the experiment. The structural analysis revealed that at lower concentration, where the tendency for dimerisation or cluster formation is low, hydrogen bonding with water determines the mobility of the HB anion. o-HB forms the least hydrogen bonds and is therefore the most mobile, and p-HB, which forms the most hydrogen bonds with water, is the least mobile isomer. At higher concentration the formation of clusters also needs to be considered. The ortho isomer predominantly forms dimers with 2 hydrogen bonds per dimer between one OH and one carboxylate group of each anion. m-HB mostly forms clusters of sizes around 5 and p-HB forms clusters of sizes even larger than 10, which can be either rings or chains.
3D Tracking of Diatom Motion in Turbulent Flow
NASA Astrophysics Data System (ADS)
Variano, E. A.; Brandt, L.; Sardina, G.; Ardekani, M.; Pujara, N.; Ayers, S.; Du Clos, K.; Karp-Boss, L.; Jumars, P. A.
2016-02-01
We present laboratory measurements of single-celled and chain forming diatom motion in a stirred turbulence tank. The overarching goal is to explore whether diatoms track flow with fidelity (passive tracers) or whether interactions with cell density and shape result in biased trajectories that alter settling velocities. Diatom trajectories are recorded in 3D using a stereoscopic, calibrated tracking tool. Turbulence is created in a novel stirred tank, designed to create motions that match those found in the ocean surface mixed layer at scales less than 10 cm. The data are analyzed for evidence of enhanced particle clustering, an indicator of turbulently altered settling rates
Hysteresis phenomena of the intelligent driver model for traffic flow
NASA Astrophysics Data System (ADS)
Dahui, Wang; Ziqiang, Wei; Ying, Fan
2007-07-01
We present hysteresis phenomena of the intelligent driver model for traffic flow in a circular one-lane roadway. We show that the microscopic structure of traffic flow is dependent on its initial state by plotting the fraction of congested vehicles over the density, which shows a typical hysteresis loop, and by investigating the trajectories of vehicles on the velocity-over-headway plane. We find that the trajectories of vehicles on the velocity-over-headway plane, which usually show a hysteresis loop, include multiple loops. We also point out the relations between these hysteresis loops and the congested jams or high-density clusters in traffic flow.
Diffusion maps for high-dimensional single-cell analysis of differentiation data.
Haghverdi, Laleh; Buettner, Florian; Theis, Fabian J
2015-09-15
Single-cell technologies have recently gained popularity in cellular differentiation studies regarding their ability to resolve potential heterogeneities in cell populations. Analyzing such high-dimensional single-cell data has its own statistical and computational challenges. Popular multivariate approaches are based on data normalization, followed by dimension reduction and clustering to identify subgroups. However, in the case of cellular differentiation, we would not expect clear clusters to be present but instead expect the cells to follow continuous branching lineages. Here, we propose the use of diffusion maps to deal with the problem of defining differentiation trajectories. We adapt this method to single-cell data by adequate choice of kernel width and inclusion of uncertainties or missing measurement values, which enables the establishment of a pseudotemporal ordering of single cells in a high-dimensional gene expression space. We expect this output to reflect cell differentiation trajectories, where the data originates from intrinsic diffusion-like dynamics. Starting from a pluripotent stage, cells move smoothly within the transcriptional landscape towards more differentiated states with some stochasticity along their path. We demonstrate the robustness of our method with respect to extrinsic noise (e.g. measurement noise) and sampling density heterogeneities on simulated toy data as well as two single-cell quantitative polymerase chain reaction datasets (i.e. mouse haematopoietic stem cells and mouse embryonic stem cells) and an RNA-Seq data of human pre-implantation embryos. We show that diffusion maps perform considerably better than Principal Component Analysis and are advantageous over other techniques for non-linear dimension reduction such as t-distributed Stochastic Neighbour Embedding for preserving the global structures and pseudotemporal ordering of cells. The Matlab implementation of diffusion maps for single-cell data is available at https://www.helmholtz-muenchen.de/icb/single-cell-diffusion-map. fbuettner.phys@gmail.com, fabian.theis@helmholtz-muenchen.de Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Exploring the importance of quantum effects in nucleation: The archetypical Nen case
NASA Astrophysics Data System (ADS)
Unn-Toc, Wesley; Halberstadt, Nadine; Meier, Christoph; Mella, Massimo
2012-07-01
The effect of quantum mechanics (QM) on the details of the nucleation process is explored employing Ne clusters as test cases due to their semi-quantal nature. In particular, we investigate the impact of quantum mechanics on both condensation and dissociation rates in the framework of the microcanonical ensemble. Using both classical trajectories and two semi-quantal approaches (zero point averaged dynamics, ZPAD, and Gaussian-based time dependent Hartree, G-TDH) to model cluster and collision dynamics, we simulate the dissociation and monomer capture for Ne8 as a function of the cluster internal energy, impact parameter and collision speed. The results for the capture probability Ps(b) as a function of the impact parameter suggest that classical trajectories always underestimate capture probabilities with respect to ZPAD, albeit at most by 15%-20% in the cases we studied. They also do so in some important situations when using G-TDH. More interestingly, dissociation rates kdiss are grossly overestimated by classical mechanics, at least by one order of magnitude. We interpret both behaviours as mainly due to the reduced amount of kinetic energy available to a quantum cluster for a chosen total internal energy. We also find that the decrease in monomer dissociation energy due to zero point energy effects plays a key role in defining dissociation rates. In fact, semi-quantal and classical results for kdiss seem to follow a common "corresponding states" behaviour when the proper definition of internal and dissociation energies are used in a transition state model estimation of the evaporation rate constants.
Clustering of neural code words revealed by a first-order phase transition
NASA Astrophysics Data System (ADS)
Huang, Haiping; Toyoizumi, Taro
2016-06-01
A network of neurons in the central nervous system collectively represents information by its spiking activity states. Typically observed states, i.e., code words, occupy only a limited portion of the state space due to constraints imposed by network interactions. Geometrical organization of code words in the state space, critical for neural information processing, is poorly understood due to its high dimensionality. Here, we explore the organization of neural code words using retinal data by computing the entropy of code words as a function of Hamming distance from a particular reference codeword. Specifically, we report that the retinal code words in the state space are divided into multiple distinct clusters separated by entropy-gaps, and that this structure is shared with well-known associative memory networks in a recallable phase. Our analysis also elucidates a special nature of the all-silent state. The all-silent state is surrounded by the densest cluster of code words and located within a reachable distance from most code words. This code-word space structure quantitatively predicts typical deviation of a state-trajectory from its initial state. Altogether, our findings reveal a non-trivial heterogeneous structure of the code-word space that shapes information representation in a biological network.
Kangaslampi, Samuli; Punamäki, Raija-Leena; Qouta, Samir; Diab, Marwan; Peltonen, Kirsi
2016-12-01
Cognitive theories point to reduction in dysfunctional posttraumatic cognitions (PTCs) as one mechanism involved in recovery from posttraumatic stress symptoms (PTSS), yet research findings have shown individual differences in the recovery process. We tested the cognitive mediation hypothesis above in a previously published psychosocial group intervention among war-affected children. We also examined heterogeneity in children's PTCs during the intervention. We used a cluster randomized trial of Smith et al.'s (2002) teaching recovery techniques (TRT) intervention among 482 Palestinians 10-13 years of age (n = 242 for intervention group, n = 240 for control group). Children reported PTSS, PTCs, and depressive symptoms at baseline, midpoint, postintervention, and at 6-month follow-up. Path analysis results showed that TRT was not effective in reducing dysfunctional PTCs, and the reductions did not mediate intervention effects on PTSS. Using latent class growth analysis, we chose the model with 3 differing trajectories in the intervention group: high, decreasing, moderate, downward trending, and severe, stable levels of PTCs. Higher PTSS and depressive symptoms at baseline were associated with membership in the severe, stable trajectory. The intervention did not produce the kind of beneficial cognitive change needed in the cognitive mediation conceptualization. Nevertheless, cognitive changes differed substantially across children during the intervention, and were associated with their preintervention mental health status. These findings call for more detailed examination of the process of cognitive mediation. Copyright © 2016 International Society for Traumatic Stress Studies.
NASA Technical Reports Server (NTRS)
White, Richard E.; Bally, John
1993-01-01
A large emission 'cavity' whose bright rims extend about 5 deg eastward from the Pleiades, and is pressurized by the soft-UV radiation of the cluster, has been revealed by a mosaic of IRAS images; the emission cavity delineates the wake of the Pleiades as it moves supersonically through the ISM. Photoelectric heating is identified as the most likely agent of the cluster-cloud interaction generating a shock wave, and prompts the hypothesis that transverse expansion of heated gas near the cluster plays a crucial role in driving the shock. The cloud trajectory can be traced back to an origin in Gould's Belt some 15 Myr ago, in a blowout of gas into the Galactic halo.
Parent and child cigarette use: a longitudinal, multigenerational study.
Vuolo, Mike; Staff, Jeremy
2013-09-01
Using longitudinal data from the multigenerational Youth Development Study (YDS), this article documents how parents' long-term smoking trajectories are associated with adolescent children's likelihood of smoking. Prospective data from the parents (from age 14-38 years) enable unique comparisons of the parents' and children's smoking behavior, as well as that of siblings. Smoking trajectories are constructed using latent class analysis for the original YDS cohort (n = 1010). Multigenerational longitudinal data from 214 parents and 314 offspring ages 11 years and older are then analyzed by using logistic regression with cluster-corrected SEs. Four latent smoking trajectories emerged among the original cohort: stable nonsmokers (54%), early-onset light smokers who quit/reduce (16%), late-onset persistent smokers (14%), and early-onset persistent heavy smokers (16%). Although 8% of children of stable nonsmokers smoked in the last year, the other groups' children had much higher percentages, ranging from 23% to 29%. Multivariate logistic regression models confirm that these significant differences were robust to the inclusion of myriad child- and parent-level measures (for which child age and grade point average [GPA] are significant predictors). Older sibling smoking, however, mediated the link between parental heavy smoking and child smoking. Even in an era of declining rates of teenage cigarette use in the United States, children of current and former smokers face an elevated risk of smoking. Prevention efforts to weaken intergenerational associations should consider parents' long-term cigarette use, as well as the smoking behavior of older siblings in the household.
Dark energy in six nearby galaxy flows: Synthetic phase diagrams and self-similarity
NASA Astrophysics Data System (ADS)
Chernin, A. D.; Teerikorpi, P.; Dolgachev, V. P.; Kanter, A. A.; Domozhilova, L. M.; Valtonen, M. J.; Byrd, G. G.
2012-09-01
Outward flows of galaxies are observed around groups of galaxies on spatial scales of about 1 Mpc, and around galaxy clusters on scales of 10 Mpc. Using recent data from the Hubble Space Telescope (HST), we have constructed two synthetic velocity-distance phase diagrams: one for four flows on galaxy-group scales and the other for two flows on cluster scales. It has been shown that, in both cases, the antigravity produced by the cosmic dark-energy background is stronger than the gravity produced by the matter in the outflow volume. The antigravity accelerates the flows and introduces a phase attractor that is common to all scales, corresponding to a linear velocity-distance relation (the local Hubble law). As a result, the bundle of outflow trajectories mostly follow the trajectory of the attractor. A comparison of the two diagrams reveals the universal self-similar nature of the outflows: their gross phase structure in dimensionless variables is essentially independent of their physical spatial scales, which differ by approximately a factor of 10 in the two diagrams.
Uncovering urban human mobility from large scale taxi GPS data
NASA Astrophysics Data System (ADS)
Tang, Jinjun; Liu, Fang; Wang, Yinhai; Wang, Hua
2015-11-01
Taxi GPS trajectories data contain massive spatial and temporal information of urban human activity and mobility. Taking taxi as mobile sensors, the information derived from taxi trips benefits the city and transportation planning. The original data used in study are collected from more than 1100 taxi drivers in Harbin city. We firstly divide the city area into 400 different transportation districts and analyze the origin and destination distribution in urban area on weekday and weekend. The Density-Based Spatial Clustering of Applications with Noise (DBSCAN) algorithm is used to cluster pick-up and drop-off locations. Furthermore, four spatial interaction models are calibrated and compared based on trajectories in shopping center of Harbin city to study the pick-up location searching behavior. By extracting taxi trips from GPS data, travel distance, time and average speed in occupied and non-occupied status are then used to investigate human mobility. Finally, we use observed OD matrix of center area in Harbin city to model the traffic distribution patterns based on entropy-maximizing method, and the estimation performance verify its effectiveness in case study.
NASA Astrophysics Data System (ADS)
Pradas, Marc; Pumir, Alain; Huber, Greg; Wilkinson, Michael
2017-07-01
Chaos is widely understood as being a consequence of sensitive dependence upon initial conditions. This is the result of an instability in phase space, which separates trajectories exponentially. Here, we demonstrate that this criterion should be refined. Despite their overall intrinsic instability, trajectories may be very strongly convergent in phase space over extremely long periods, as revealed by our investigation of a simple chaotic system (a realistic model for small bodies in a turbulent flow). We establish that this strong convergence is a multi-facetted phenomenon, in which the clustering is intense, widespread and balanced by lacunarity of other regions. Power laws, indicative of scale-free features, characterize the distribution of particles in the system. We use large-deviation and extreme-value statistics to explain the effect. Our results show that the interpretation of the ‘butterfly effect’ needs to be carefully qualified. We argue that the combination of mixing and clustering processes makes our specific model relevant to understanding the evolution of simple organisms. Lastly, this notion of convergent chaos, which implies the existence of conditions for which uncertainties are unexpectedly small, may also be relevant to the valuation of insurance and futures contracts.
Identification of linearised RMS-voltage dip patterns based on clustering in renewable plants
DOE Office of Scientific and Technical Information (OSTI.GOV)
García-Sánchez, Tania; Gómez-Lázaro, Emilio; Muljadi, Edward
Generation units connected to the grid are currently required to meet low-voltage ride-through (LVRT) requirements. In most developed countries, these requirements also apply to renewable sources, mainly wind power plants and photovoltaic installations connected to the grid. This study proposes an alternative characterisation solution to classify and visualise a large number of collected events in light of current limits and requirements. The authors' approach is based on linearised root-mean-square-(RMS)-voltage trajectories, taking into account LRVT requirements, and a clustering process to identify the most likely pattern trajectories. The proposed solution gives extensive information on an event's severity by providing a simplemore » but complete visualisation of the linearised RMS-voltage patterns. In addition, these patterns are compared to current LVRT requirements to determine similarities or discrepancies. A large number of collected events can then be automatically classified and visualised for comparative purposes. Real disturbances collected from renewable sources in Spain are used to assess the proposed solution. Extensive results and discussions are also included in this study.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
García-Sánchez, Tania; Gómez-Lázaro, Emilio; Muljadi, E.
An alternative approach to characterise real voltage dips is proposed and evaluated in this study. The proposed methodology is based on voltage-space vector solutions, identifying parameters for ellipses trajectories by using the least-squares algorithm applied on a sliding window along the disturbance. The most likely patterns are then estimated through a clustering process based on the k-means algorithm. The objective is to offer an efficient and easily implemented alternative to characterise faults and visualise the most likely instantaneous phase-voltage evolution during events through their corresponding voltage-space vector trajectories. This novel solution minimises the data to be stored but maintains extensivemore » information about the dips including starting and ending transients. The proposed methodology has been applied satisfactorily to real voltage dips obtained from intensive field-measurement campaigns carried out in a Spanish wind power plant up to a time period of several years. A comparison to traditional minimum root mean square-voltage and time-duration classifications is also included in this study.« less
NASA Technical Reports Server (NTRS)
Glenn, G. M.
1977-01-01
A preflight analysis of the ALT separation reference trajectories for the tailcone on, forward, and aft cg orbiter configurations is documented. The ALT separation reference trajectories encompass the time from physical separation of the orbiter from the carrier to orbiter attainment of the maximum ALT interface airspeed. The trajectories include post separation roll maneuvers by both vehicles and are generated using the final preflight data base. The trajectories so generated satisfy all known separation design criteria and violate no known constraints. The requirement for this analysis is given along with the specifications, assumptions, and analytical approach used to generate the separation trajectories. The results of the analytical approach are evaluated, and conclusions and recommendations are summarized.
Time-Hierarchical Clustering and Visualization of Weather Forecast Ensembles.
Ferstl, Florian; Kanzler, Mathias; Rautenhaus, Marc; Westermann, Rudiger
2017-01-01
We propose a new approach for analyzing the temporal growth of the uncertainty in ensembles of weather forecasts which are started from perturbed but similar initial conditions. As an alternative to traditional approaches in meteorology, which use juxtaposition and animation of spaghetti plots of iso-contours, we make use of contour clustering and provide means to encode forecast dynamics and spread in one single visualization. Based on a given ensemble clustering in a specified time window, we merge clusters in time-reversed order to indicate when and where forecast trajectories start to diverge. We present and compare different visualizations of the resulting time-hierarchical grouping, including space-time surfaces built by connecting cluster representatives over time, and stacked contour variability plots. We demonstrate the effectiveness of our visual encodings with forecast examples of the European Centre for Medium-Range Weather Forecasts, which convey the evolution of specific features in the data as well as the temporally increasing spatial variability.
A fast parallel clustering algorithm for molecular simulation trajectories.
Zhao, Yutong; Sheong, Fu Kit; Sun, Jian; Sander, Pedro; Huang, Xuhui
2013-01-15
We implemented a GPU-powered parallel k-centers algorithm to perform clustering on the conformations of molecular dynamics (MD) simulations. The algorithm is up to two orders of magnitude faster than the CPU implementation. We tested our algorithm on four protein MD simulation datasets ranging from the small Alanine Dipeptide to a 370-residue Maltose Binding Protein (MBP). It is capable of grouping 250,000 conformations of the MBP into 4000 clusters within 40 seconds. To achieve this, we effectively parallelized the code on the GPU and utilize the triangle inequality of metric spaces. Furthermore, the algorithm's running time is linear with respect to the number of cluster centers. In addition, we found the triangle inequality to be less effective in higher dimensions and provide a mathematical rationale. Finally, using Alanine Dipeptide as an example, we show a strong correlation between cluster populations resulting from the k-centers algorithm and the underlying density. © 2012 Wiley Periodicals, Inc. Copyright © 2012 Wiley Periodicals, Inc.
Highly efficient, very low-thrust transfer to geosynchronous orbit - Exact and approximate solutions
NASA Astrophysics Data System (ADS)
Redding, D. C.
1984-04-01
An overview is provided of the preflight, postflight, and accuracy analysis of the Titan IIIC launch vehicle that injects payloads into geosynchronous orbits. The postflight trajectory reconstruction plays an important role in determining payload injection accuracy. Furthermore, the postflight analysis provides useful information about the characteristics of measuring instruments subjected to a flight environment. Suitable approaches for meeting mission specifications, trajectory requirements, and instrument constraints are considered, taking into account the importance of preflight trajectory analysis activities. Gimbal flip avoidance algorithms in the flight software, and considerable beta gimbal analysis ensures a singularity-free trajectory.
A Lagrangian description of motion in Northern California coastal transition filaments
NASA Astrophysics Data System (ADS)
Paduan, Jeffrey D.; Niiler, Pearn P.
1990-10-01
Lagrangian drifters deployed during May 1987 as part of the Coastal Transition Zone experiment were used to examine the motion in cold-water features seen in satellite AVHRR imagery. The drifters were drogued at 15 m depth and had temperature sensors at 0 m, 12 m, and 18 m. Drogue positions were obtained via service ARGOS at an average of 8 times per day. A cluster of nine drifters was deployed on May 18 near the base of a cold-water feature off Pt. Reyes. Drifter trajectories confirm the presence of strong (> 50 cm s-1) currents along the axis of the feature. Six of the drifters moved northward following a cyclonic circulation pattern between the Pt. Reyes jet and another feature originating near Pt. Arena. The remaining three drifters, together with three more deployed on May 20, moved offshore in the positive vorticity portion of the Reyes jet. Cluster analysis of the northern tracks indicates large convergence (˜0.5f;), but because relative vorticity during the same few-day period is found to be constant (˜-0.2f), a simple vorticity balance does not emerge. This is attributed to insufficient resolution of divergence of the water parcel by the small number in the cluster. Drifters reside on the negative vorticity side of the jet while the flow is upwind but on the positive vorticity side while the flow is downwind. Such behavior is consistent with the convergence or divergence patterns expected when along-jet winds blow over such strong and narrow ocean currents producing significant advection of relative vorticity. Temperature-salinity data from CTD surveys during the experiment show how the jets that were revealed in both the imagery and the drifter trajectories were advecting different water masses. In the nearshore area where the drifters were deployed a column of cold and salty water had upwelled about 80 m since leaving the source region far offshore. Within the offshore extension of the jets as traced by the drifters, this same water is found about 20 m deeper than it is in the nearshore area. We thus observe that cold filaments seen in AVHRR transport upwelled water offshore through the coastal transition zone. That water subducts in the offshore extension of the filaments. Analysis of the high-frequency motion from a cluster of five drifters in the Reyes jet shows a multitude of mixing scales. For periods shorter than a day, the cluster shows coherent oscillations of tidal/inertial period whose motions lead to excursions on the order of 2 to 4 km. This suggests that motions on these scales are organized and not random or turbulent. Conversely, motions at scales of 1 km and less appear turbulent. Over longer time periods (several days), the particles exchange places over the cross-jet scale of the feature (10 to 20 km).
Hypervelocity Inflight Trajectory Scatter (HITS) Code. User’s Manual
1976-04-01
referred to as skewness. The fourth central moment is referred to as kurtosis and provides an additional measure of the clustering of the distribution... clustering of data points in the resulting "scatter diagram" would indicate correlation. The correlation can be quantified by fit- ting a straight line...10- *4 U* 0%.0 Coo IX wV~ Z de *I *- 0 On Wa )I GMX Ŕ.~ Ot. *P0 WX #- % OW- W 00WIj u +,- >ot o-O- oW cbok~ o*9 lWI $ Wld6 0000000N000 0 4 00 6 6
Donovan, Kera L; Brassard, Marla R
2011-10-01
The primary research objective was to explore the relationship between trajectories of maternal verbal aggression (VA) experienced by low-income, community middle school students across a three-year period and outcomes that have been found to be related to VA in previous work, including a negative view of self and social problems. Longitudinal data were collected from 421 youth (51.8% male) attending two middle schools over 3 years using a multiple-informant survey design. K-means cluster analysis was used to identify trajectories of VA using youth ratings of the Conflict Tactics Scale: Parent-Child (Straus, Hamby, Finkelhor, Moore, & Runyan, 1998). Dependent variables were self-reported depression, self-esteem, delinquency, and peer victimization as well as peer-rated aggression and sensitive-isolated reputation. Four trajectory groups of VA were identified: Low Stable, Increasing, Decreasing, and High Stable. The 3-year average occurrence of VA was: 1.31, 9.18, 10.24, and 31.14 instances, respectively. Gender-specific MANOVAs revealed dramatic differences between the High Stable and Low Stable groups. High Stable boys reported significantly more depressive symptoms, delinquency, peer overt and relational victimization, and were less likely to have a sensitive/isolated reputation than Low Stable boys. High Stable girls reported significantly more depressive symptoms, low self-esteem, delinquency, peer overt and relational victimization and were rated by peers as having more aggressive/disruptive and relationally aggressive reputations than Low Stable girls. Girls in the High Stable group were more likely than other youth to report levels of depressive symptoms and delinquency >1 SD above the mean, while boys in the High Stable group were more likely to report levels of delinquency >1 SD above the mean. The Increasing and Decreasing groups also demonstrated significantly poorer functioning than the Low Stable group on most outcomes. Growth curve analysis revealed that VA showed a contemporaneous association with self-reported delinquency suggesting these factors are closely related. Any level of VA greater than the 1-2 instances per year reported by youth in the Low Stable group was associated with less favorable outcomes. Copyright © 2011 Elsevier Ltd. All rights reserved.
NASA Technical Reports Server (NTRS)
Glenn, G. M.
1976-01-01
Details of the generation of the separation trajectories are discussed. The analysis culminated in definition of separation trajectories between physical separation and orbiter/carrier vortex clearance. Specifications, assumptions and analytical approach used to generate the separation trajectories are presented. Results of the analytical approach are evaluated. Conclusions and recommendations are summarized. Supporting references are listed.
Dimitriou, Konstantinos; Kassomenos, Pavlos
2017-11-01
The main objective of this study was to examine the levels of four heavy metals (As, Cd, Pb and Ni) in PM 10 samples collected in two urban background stations in Dortmund and Bielefeld, in relation to atmospheric circulation. Pollution roses, Conditional Probability Function (CPF) roses and backward air mass trajectory clusters were used to identify air currents associated with the importation of PM 10 and of the included metal constituents. In addition, PM 10 , NO 2 , SO 2 , O 3 , As, Cd, Ni and Pb concentrations were analyzed by a Principal Component Analysis (PCA) to reveal major local emission sources of PM 10 metal content. Traffic was the main emitter of PM 10 , As, Cd, and Pb in both cities, highlighting the existence of non-negligible lead quantities in unleaded gasoline, whilst nickel emissions were associated with heavy fuel oil combustion in industries and primarily for domestic heating. The created CPF roses and trajectory clusters were in good agreement, clearly revealing that eastern air currents enriched the locally produced PM 10 load with additional aerosols from Eastern Europe. The concentrations of arsenic and cadmium were also enhanced by the arrival of air parcels from the East, indicating the anthropogenic origin of the exogenous aerosols due to combustion. The induced cancer risk (CR inh ) for adults, due to inhalation of individual metal constituents, was also estimated in terms of atmospheric circulation, indicating higher risk in Dortmund than in Bielefeld. CR inh values for arsenic exceeded the limit of 1 × 10 -6 in both cities, primarily during the influence of eastern circulation. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Wu, Hao; Nüske, Feliks; Paul, Fabian; Klus, Stefan; Koltai, Péter; Noé, Frank
2017-04-01
Markov state models (MSMs) and master equation models are popular approaches to approximate molecular kinetics, equilibria, metastable states, and reaction coordinates in terms of a state space discretization usually obtained by clustering. Recently, a powerful generalization of MSMs has been introduced, the variational approach conformation dynamics/molecular kinetics (VAC) and its special case the time-lagged independent component analysis (TICA), which allow us to approximate slow collective variables and molecular kinetics by linear combinations of smooth basis functions or order parameters. While it is known how to estimate MSMs from trajectories whose starting points are not sampled from an equilibrium ensemble, this has not yet been the case for TICA and the VAC. Previous estimates from short trajectories have been strongly biased and thus not variationally optimal. Here, we employ the Koopman operator theory and the ideas from dynamic mode decomposition to extend the VAC and TICA to non-equilibrium data. The main insight is that the VAC and TICA provide a coefficient matrix that we call Koopman model, as it approximates the underlying dynamical (Koopman) operator in conjunction with the basis set used. This Koopman model can be used to compute a stationary vector to reweight the data to equilibrium. From such a Koopman-reweighted sample, equilibrium expectation values and variationally optimal reversible Koopman models can be constructed even with short simulations. The Koopman model can be used to propagate densities, and its eigenvalue decomposition provides estimates of relaxation time scales and slow collective variables for dimension reduction. Koopman models are generalizations of Markov state models, TICA, and the linear VAC and allow molecular kinetics to be described without a cluster discretization.
NASA Astrophysics Data System (ADS)
Chantara, Somporn; Sillapapiromsuk, Sopittaporn; Wiriya, Wan
2012-12-01
Monitoring and analysis of the chemical composition of air pollutants were conducted over a five-year period (2005-2009) in the sub-urban area of Chiang Mai, Thailand. This study aims to determine the seasonal variation of atmospheric ion species and gases, examine their correlations, identify possible sources and assess major air-flow patterns to the receptor. The dominant gas and particulate pollutants were NH3 (43-58%) and SO42- (39-48%), respectively. The annual mean concentrations of NH3 (μg m-3) in descending order were 4.08 (2009) > 3.32 (2007) > 2.68 (2008) > 2.47 (2006) and 1.87 (2005), while those of SO42- (μg m-3) were 2.60 (2007) > 2.20 (2006) > 1.95 (2009) > 1.75 (2008) and 1.26 (2005). Concentrations of particulate ions were analyzed by principle component analysis to find out the possible sources of air pollutants in this area. The first component of each year had a high loading of SO42- and NH4+, which probably came from fuel combustion and agricultural activity, respectively. K+, a tracer of biomass burning, also contributed to the first or the second components of each year. Concentrations of NH4+ and SO42- were well correlated (r > 0.777, p < 0.01), which lead to the conclusion that (NH4)2SO4 was a major compound present in this area. The 3-day backward trajectories of air mass arriving at Chiang Mai from 2005 to 2009 were analyzed using the hybrid single particle langrangian integrated trajectory (HYSPLIT) model and grouped by cluster analysis. The air mass data was analyzed for the dry season (n = 18; 100%). The trajectory of air mass in 2005 mainly originated locally (67%). In 2006, the recorded data showed that 56% of air mass was emitted from the western continental region of Thailand. In 2007, the percent ratios from the western and eastern continental areas were equal (39%). In 2008, 67% originated from the western continental area. In 2009, the recorded air mass mainly came from the western continental area (72%). In conclusion, the major trajectories of air mass from 2006 to 2009 originated from the southwest direction of the receptor, but in 2005, the air mass appeared to be locally originated.
Monteiro, Baltazar Ricardo; Candoso, Fátima; Reis, Magda; Bastos, Sónia
2017-03-01
Reforms started in 1996 intended that Regional Health Administrations (ARS) should play a relevant role in the process of transforming an integrated model towards a contractual health care model. The essential tool of this transformation would be the Contractualization Agency, established in each ARS. Its role in the new contractualization culture was to negotiate prospective budgets with health care institutions, which included Primary Health Care (PHC). This paper is a longitudinal analysis of the development of a set of nine PHC contractualization indicators in three Health Center Clusters (ACeS) of the Regional Health Administration of Lisbon and Tagus Valley (ARSLVT). We have noticed that the setting of goals, in terms of external contractualization and its monitoring and follow-up are decisive and help health professionals to define trajectories and performance goals. We also recognize the need to revise baseline indicators by developing them into outcome indicators.
NASA Astrophysics Data System (ADS)
Giorgino, Toni; Laio, Alessandro; Rodriguez, Alex
2017-08-01
Molecular dynamics (MD) simulations allow the exploration of the phase space of biopolymers through the integration of equations of motion of their constituent atoms. The analysis of MD trajectories often relies on the choice of collective variables (CVs) along which the dynamics of the system is projected. We developed a graphical user interface (GUI) for facilitating the interactive choice of the appropriate CVs. The GUI allows: defining interactively new CVs; partitioning the configurations into microstates characterized by similar values of the CVs; calculating the free energies of the microstates for both unbiased and biased (metadynamics) simulations; clustering the microstates in kinetic basins; visualizing the free energy landscape as a function of a subset of the CVs used for the analysis. A simple mouse click allows one to quickly inspect structures corresponding to specific points in the landscape.
An Examination of "The Martian" Trajectory
NASA Technical Reports Server (NTRS)
Burke, Laura
2015-01-01
This analysis was performed to support a request to examine the trajectory of the Hermes vehicle in the novel "The Martian" by Andy Weir. Weir developed his own tool to perform the analysis necessary to provide proper trajectory information for the novel. The Hermes vehicle is the interplanetary spacecraft that shuttles the crew to and from Mars. It is notionally a Nuclear powered vehicle utilizing VASIMR engines for propulsion. The intent of this analysis was the determine whether the trajectory as it was outlined in the novel is consistent with the rules of orbital mechanics.
Pteros: fast and easy to use open-source C++ library for molecular analysis.
Yesylevskyy, Semen O
2012-07-15
An open-source Pteros library for molecular modeling and analysis of molecular dynamics trajectories for C++ programming language is introduced. Pteros provides a number of routine analysis operations ranging from reading and writing trajectory files and geometry transformations to structural alignment and computation of nonbonded interaction energies. The library features asynchronous trajectory reading and parallel execution of several analysis routines, which greatly simplifies development of computationally intensive trajectory analysis algorithms. Pteros programming interface is very simple and intuitive while the source code is well documented and easily extendible. Pteros is available for free under open-source Artistic License from http://sourceforge.net/projects/pteros/. Copyright © 2012 Wiley Periodicals, Inc.
Barbas, J P; Leahy, T; Horta, A E; García-Herreros, M
2018-03-20
Sperm cryopreservation in goats has been a challenge for many years due to the detrimental effects of seminal plasma enzymes produced by the bulbo-urethral glands which catalyse the hydrolysis of lecithins in egg yolk to fatty acids and lysolecithins which are deleterious to spermatozoa. This fact implies to carry out additional processing steps during sperm cryopreservation for seminal plasma removal triggering different sperm responses which may affect sperm functionality. The objective of the present study was to determine specific sperm subpopulation responses in different handling steps during the cryopreservation process by using functional sperm kinematic descriptors in caprine ejaculates. Buck ejaculates (n = 40) were analysed for sperm concentration, viability, morphology and acrosome integrity. Moreover, sperm motility was assessed using a computer-assisted sperm analysis (CASA) system after five different handling steps (fresh sperm, 1st washing, 2nd washing, cooling and frozen-thawed sperm) during a standard cryopreservation protocol for goat semen. The results were analysed using Principal Component Analysis (PCA) and multivariate clustering procedures to establish the relationship between the distribution of the subpopulations found and the functional sperm motility in each step. Except for the 1st and 4th steps, four sperm kinematic subpopulations were observed explaining more than 75% of the variance. Based on velocity and linearity parameters and the subpopulations disclosed, the kinematic response varies among processing steps modifying sperm movement trajectories in a subpopulation-specific and handling step-dependent manner (p < 0.001). The predominant motile subpopulation in freshly ejaculated buck sperm had very fast velocity characteristics and a non-linear trajectory (41.1%). Washing buck sperm twice altered the subpopulation structure as well as cooling which resulted in a dramatic reduction in sperm velocities (p < 0.01). Frozen-thawed spermatozoa showed similar characteristics to cooled sperm except there was a further increase in linearity with a large proportion of sperm attributed to new slow, linear cluster (32.5%). In conclusion, this study confirms the variability and heterogeneity of goat sperm kinematic patterns throughout the cryopreservation process and suggests that the predominant motility pattern (assayed in vitro via CASA) of high quality spermatozoa might be typified by high speed and a non-linear trajectory. The relationships among the number and distribution of sperm subpopulations and the different handling steps were particularlly relevant, specially after the cooling and the post-thawing steps, when effects derived from these critical handling steps were evident and altered drastically the sperm motion patterns. Copyright © 2018 Elsevier Inc. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
DeBlase, Andrew F.; Wolke, Conrad T.; Johnson, Mark A., E-mail: jordan@pitt.edu, E-mail: nhammer@olemiss.edu, E-mail: mark.johnson@yale.edu
2015-10-14
The role of proton-assisted charge accommodation in electron capture by a heterocyclic electron scavenger is investigated through theoretical analysis of the vibrational spectra of cold, gas phase [Py ⋅ (H{sub 2}O){sub n=3−5}]{sup −} clusters. These radical anions are formed when an excess electron is attached to water clusters containing a single pyridine (Py) molecule in a supersonic jet ion source. Under these conditions, the cluster ion distribution starts promptly at n = 3, and the photoelectron spectra, combined with vibrational predissociation spectra of the Ar-tagged anions, establish that for n > 3, these species are best described as hydrated hydroxidemore » ions with the neutral pyridinium radical, PyH{sup (0)}, occupying one of the primary solvation sites of the OH{sup −}. The n = 3 cluster appears to be a special case where charge localization on Py and hydroxide is nearly isoenergetic, and the nature of this species is explored with ab initio molecular dynamics calculations of the trajectories that start from metastable arrangements of the anion based on a diffuse, essentially dipole-bound electron. These calculations indicate that the reaction proceeds via a relatively slow rearrangement of the water network to create a favorable hydration configuration around the water molecule that eventually donates a proton to the Py nitrogen atom to yield the product hydroxide ion. The correlation between the degree of excess charge localization and the evolving shape of the water network revealed by this approach thus provides a microscopic picture of the “solvent coordinate” at the heart of a prototypical proton-coupled electron transfer reaction.« less
NASA Technical Reports Server (NTRS)
1972-01-01
The Performance Analysis and Design Synthesis (PADS) computer program has a two-fold purpose. It can size launch vehicles in conjunction with calculus-of-variations optimal trajectories and can also be used as a general-purpose branched trajectory optimization program. In the former use, it has the Space Shuttle Synthesis Program as well as a simplified stage weight module for optimally sizing manned recoverable launch vehicles. For trajectory optimization alone or with sizing, PADS has two trajectory modules. The first trajectory module uses the method of steepest descent; the second employs the method of quasilinearization, which requires a starting solution from the first trajectory module. For Volume 1 see N73-13199.
NASA Astrophysics Data System (ADS)
Zhang, Haiying; Bai, Jiaojiao; Li, Zhengjie; Liu, Yan; Liu, Kunhong
2017-06-01
The detection and discrimination of infrared small dim targets is a challenge in automatic target recognition (ATR), because there is no salient information of size, shape and texture. Many researchers focus on mining more discriminative information of targets in temporal-spatial. However, such information may not be available with the change of imaging environments, and the targets size and intensity keep changing in different imaging distance. So in this paper, we propose a novel research scheme using density-based clustering and backtracking strategy. In this scheme, the speeded up robust feature (SURF) detector is applied to capture candidate targets in single frame at first. And then, these points are mapped into one frame, so that target traces form a local aggregation pattern. In order to isolate the targets from noises, a newly proposed density-based clustering algorithm, fast search and find of density peak (FSFDP for short), is employed to cluster targets by the spatial intensive distribution. Two important factors of the algorithm, percent and γ , are exploited fully to determine the clustering scale automatically, so as to extract the trace with highest clutter suppression ratio. And at the final step, a backtracking algorithm is designed to detect and discriminate target trace as well as to eliminate clutter. The consistence and continuity of the short-time target trajectory in temporal-spatial is incorporated into the bounding function to speed up the pruning. Compared with several state-of-arts methods, our algorithm is more effective for the dim targets with lower signal-to clutter ratio (SCR). Furthermore, it avoids constructing the candidate target trajectory searching space, so its time complexity is limited to a polynomial level. The extensive experimental results show that it has superior performance in probability of detection (Pd) and false alarm suppressing rate aiming at variety of complex backgrounds.
NASA Technical Reports Server (NTRS)
Byrnes, D. V.; Carney, P. C.; Underwood, J. W.; Vogt, E. D.
1974-01-01
The six month effort was responsible for the development, test, conversion, and documentation of computer software for the mission analysis of missions to halo orbits about libration points in the earth-sun system. The software consisting of two programs called NOMNAL and ERRAN is part of the Space Trajectories Error Analysis Programs. The program NOMNAL targets a transfer trajectory from earth on a given launch date to a specified halo orbit on a required arrival date. Either impulsive or finite thrust insertion maneuvers into halo orbit are permitted by the program. The transfer trajectory is consistent with a realistic launch profile input by the user. The second program ERRAN conducts error analyses of the targeted transfer trajectory. Measurements including range, doppler, star-planet angles, and apparent planet diameter are processed in a Kalman-Schmidt filter to determine the trajectory knowledge uncertainty.
Lynch, Brian A; Rutten, Lila J Finney; Ebbert, Jon O; Kumar, Seema; Yawn, Barbara P; Jacobson, Debra; Sauver, Jennifer St
2017-10-01
The prevalence of childhood obesity has increased over the past 3 decades. This study was designed to understand how childhood body mass index (BMI) influences later risk of obesity. We calculated BMIs for children residing in Olmsted County, Minnesota, between January 1, 2005 and December 31, 2012 using medical records data. We defined homogenous BMI trajectory clusters using a nonparametric hill-climbing algorithm. Overall, 16,538 (47%) children had >3 weight assessments at least 1 year apart and were included in the analyses. Within the 8-year follow-up period, children who were younger than 2 years and overweight had a 3- fold increase of obesity (adjusted hazard ratio [HR] = 3.24; 95% confidence interval [CI] = 2.69-3.89) and those aged 5 years and overweight had a 10-fold increased risk of obesity (adjusted HR = 9.97, 95% CI = 8.55-11.62). Three distinct BMI trajectories could be distinguished prior to 5 years of age. The risk of developing obesity in those who are overweight increased dramatically with increasing age. Interventions to prevent obesity need to occur prior to school age to prevent children from entering unhealthy BMI trajectories.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Su, Kuan-Hao; Hu, Lingzhi; Traughber, Melanie
Purpose: MR-based pseudo-CT has an important role in MR-based radiation therapy planning and PET attenuation correction. The purpose of this study is to establish a clinically feasible approach, including image acquisition, correction, and CT formation, for pseudo-CT generation of the brain using a single-acquisition, undersampled ultrashort echo time (UTE)-mDixon pulse sequence. Methods: Nine patients were recruited for this study. For each patient, a 190-s, undersampled, single acquisition UTE-mDixon sequence of the brain was acquired (TE = 0.1, 1.5, and 2.8 ms). A novel method of retrospective trajectory correction of the free induction decay (FID) signal was performed based on point-spreadmore » functions of three external MR markers. Two-point Dixon images were reconstructed using the first and second echo data (TE = 1.5 and 2.8 ms). R2{sup ∗} images (1/T2{sup ∗}) were then estimated and were used to provide bone information. Three image features, i.e., Dixon-fat, Dixon-water, and R2{sup ∗}, were used for unsupervised clustering. Five tissue clusters, i.e., air, brain, fat, fluid, and bone, were estimated using the fuzzy c-means (FCM) algorithm. A two-step, automatic tissue-assignment approach was proposed and designed according to the prior information of the given feature space. Pseudo-CTs were generated by a voxelwise linear combination of the membership functions of the FCM. A low-dose CT was acquired for each patient and was used as the gold standard for comparison. Results: The contrast and sharpness of the FID images were improved after trajectory correction was applied. The mean of the estimated trajectory delay was 0.774 μs (max: 1.350 μs; min: 0.180 μs). The FCM-estimated centroids of different tissue types showed a distinguishable pattern for different tissues, and significant differences were found between the centroid locations of different tissue types. Pseudo-CT can provide additional skull detail and has low bias and absolute error of estimated CT numbers of voxels (−22 ± 29 HU and 130 ± 16 HU) when compared to low-dose CT. Conclusions: The MR features generated by the proposed acquisition, correction, and processing methods may provide representative clustering information and could thus be used for clinical pseudo-CT generation.« less
Neck/shoulder and back pain in new graduate nurses: A growth mixture modeling analysis.
Lövgren, Malin; Gustavsson, Petter; Melin, Bo; Rudman, Ann
2014-04-01
Although it is well known that musculoskeletal disorders are common among registered nurses, little longitudinal research has been conducted to examine this problem from nursing education to working life. The aim was to investigate the prevalence and incidence of neck/shoulder and back pain in nursing students in their final semester, and one and two years after graduation. Furthermore, to identify common trajectories of neck/shoulder and back pain, and explore sociodemographic and lifestyle-related factors, contextual factors and health outcome that might be characteristic of individuals in the various trajectories. Longitudinal study following nursing students from their final year of studies, with follow-ups one and two years after graduation. Nursing students who graduated from the 26 universities providing undergraduate nursing education in Sweden 2002 were invited to participate (N=1700). Of those asked, 1153 gave their informed consent. The participants answered postal surveys at yearly intervals. Descriptive statistics were used to analyze prevalence and incidence of pain, and growth mixture modeling was applied to identify different homogeneous clusters of individuals following similar trajectories in pain development across time. The prevalence of neck/shoulder and back pain remained constant over time (around 50% for neck/shoulder pain and just over 40% for back pain). Six different development trajectories for each symptom were found, reflecting patterns of stable pain levels or variation in levels over time: one symptom-free group, two decreasing pain groups, two increasing pain groups, and one chronic pain group. With few exceptions, the same factors (sex, children, chronic disease, working overtime, work absence, sickness presence, physical load, depression, self-rated health, sleep quality and muscular tension) were associated with neck/shoulder and back pain trajectories. Different types of physical load characterized new nurses with neck/shoulder pain and back pain respectively. The high prevalence of pain among nursing students and among new graduate nurses, suggests that it would be effective to implement preventive strategies already during nursing education, but they should also preferably continue after graduation. Many factors associated with pain in the neck/shoulder and back seem to be modifiable, and thereby constitute targets for preventive strategies. Copyright © 2013 Elsevier Ltd. All rights reserved.
Precisely and Accurately Inferring Single-Molecule Rate Constants
Kinz-Thompson, Colin D.; Bailey, Nevette A.; Gonzalez, Ruben L.
2017-01-01
The kinetics of biomolecular systems can be quantified by calculating the stochastic rate constants that govern the biomolecular state versus time trajectories (i.e., state trajectories) of individual biomolecules. To do so, the experimental signal versus time trajectories (i.e., signal trajectories) obtained from observing individual biomolecules are often idealized to generate state trajectories by methods such as thresholding or hidden Markov modeling. Here, we discuss approaches for idealizing signal trajectories and calculating stochastic rate constants from the resulting state trajectories. Importantly, we provide an analysis of how the finite length of signal trajectories restrict the precision of these approaches, and demonstrate how Bayesian inference-based versions of these approaches allow rigorous determination of this precision. Similarly, we provide an analysis of how the finite lengths and limited time resolutions of signal trajectories restrict the accuracy of these approaches, and describe methods that, by accounting for the effects of the finite length and limited time resolution of signal trajectories, substantially improve this accuracy. Collectively, therefore, the methods we consider here enable a rigorous assessment of the precision, and a significant enhancement of the accuracy, with which stochastic rate constants can be calculated from single-molecule signal trajectories. PMID:27793280
Latent trajectory studies: the basics, how to interpret the results, and what to report.
van de Schoot, Rens
2015-01-01
In statistics, tools have been developed to estimate individual change over time. Also, the existence of latent trajectories, where individuals are captured by trajectories that are unobserved (latent), can be evaluated (Muthén & Muthén, 2000). The method used to evaluate such trajectories is called Latent Growth Mixture Modeling (LGMM) or Latent Class Growth Modeling (LCGA). The difference between the two models is whether variance within latent classes is allowed for (Jung & Wickrama, 2008). The default approach most often used when estimating such models begins with estimating a single cluster model, where only a single underlying group is presumed. Next, several additional models are estimated with an increasing number of clusters (latent groups or classes). For each of these models, the software is allowed to estimate all parameters without any restrictions. A final model is chosen based on model comparison tools, for example, using the BIC, the bootstrapped chi-square test, or the Lo-Mendell-Rubin test. To ease the use of LGMM/LCGA step by step in this symposium (Van de Schoot, 2015) guidelines are presented which can be used for researchers applying the methods to longitudinal data, for example, the development of posttraumatic stress disorder (PTSD) after trauma (Depaoli, van de Schoot, van Loey, & Sijbrandij, 2015; Galatzer-Levy, 2015). The guidelines include how to use the software Mplus (Muthén & Muthén, 1998-2012) to run the set of models needed to answer the research question: how many latent classes exist in the data? The next step described in the guidelines is how to add covariates/predictors to predict class membership using the three-step approach (Vermunt, 2010). Lastly, it described what essentials to report in the paper. When applying LGMM/LCGA models for the first time, the guidelines presented can be used to guide what models to run and what to report.
Samuel A. Cushman; Kevin McGarigal
2007-01-01
Integrating temporal variabilily into spatial analyses is one of the abiding challenges in landscape ecology. In this chapter we use landscape trajectory analysis to assess changes in landscape patterns over time. Landscape trajectory analysis is an approach to quantify changes in landscape structure over time. There are three key concepts which underlie the...
Leung, Cherry Y; Leung, Gabriel M; Schooling, C Mary
2018-07-01
Prospectively childhood behavioral problems and low self-esteem are associated with depression. However, these mental health changes over time have never been examined. This study assessed the association of childhood behavioral trajectories and self-esteem changes over time with adolescent depressive symptoms. Parent-reported Rutter behavioral assessments and self-reported Culture-Free Self-Esteem Inventories (SEI) were obtained via record linkage from the Student Health Service, Department of Health (Hong Kong), and the Patient Health Questionnaire-9 (PHQ-9) depressive symptom scores were obtained via active follow-up of the Hong Kong's Children of 1997" Chinese birth cohort. Partitional clustering was used to generate homogenous trajectories between ~ 7 and ~ 11 years for Rutter scores. Changes in low self-esteem between ~ 10 and ~ 12 years were obtained from the SEI. Multiple linear regression was used to estimate their associations with depressive symptom scores at ~ 13 years. Four trajectories/groups (stable low, declining, rising, and stable high) of Rutter score and self-esteem groups were created. The stable low behavioral trajectory was associated with the fewest depressive symptoms while the stable high trajectory had 1.23 more depressive symptoms [95% confidence interval (CI) 0.84 to 1.61] than the stable low trajectory. Consistently low self-esteem (stable low) was associated with 2.96 more depressive symptoms (95% CI 2.35-3.57) compared to consistently high self-esteem (stable high). Sustained or worsening childhood behavioral problems and low self-esteem were precursors of adolescent depressive symptoms, and as such could be an early indicator of the need for intervention.
Parent and Child Cigarette Use: A Longitudinal, Multigenerational Study
Staff, Jeremy
2013-01-01
OBJECTIVES: Using longitudinal data from the multigenerational Youth Development Study (YDS), this article documents how parents’ long-term smoking trajectories are associated with adolescent children’s likelihood of smoking. Prospective data from the parents (from age 14–38 years) enable unique comparisons of the parents’ and children’s smoking behavior, as well as that of siblings. METHODS: Smoking trajectories are constructed using latent class analysis for the original YDS cohort (n = 1010). Multigenerational longitudinal data from 214 parents and 314 offspring ages 11 years and older are then analyzed by using logistic regression with cluster-corrected SEs. RESULTS: Four latent smoking trajectories emerged among the original cohort: stable nonsmokers (54%), early-onset light smokers who quit/reduce (16%), late-onset persistent smokers (14%), and early-onset persistent heavy smokers (16%). Although 8% of children of stable nonsmokers smoked in the last year, the other groups’ children had much higher percentages, ranging from 23% to 29%. Multivariate logistic regression models confirm that these significant differences were robust to the inclusion of myriad child- and parent-level measures (for which child age and grade point average [GPA] are significant predictors). Older sibling smoking, however, mediated the link between parental heavy smoking and child smoking. CONCLUSIONS: Even in an era of declining rates of teenage cigarette use in the United States, children of current and former smokers face an elevated risk of smoking. Prevention efforts to weaken intergenerational associations should consider parents’ long-term cigarette use, as well as the smoking behavior of older siblings in the household. PMID:23918887
A Seasonal Air Transport Climatology for Kenya
NASA Technical Reports Server (NTRS)
Gatebe, C. K.; Tyson, P. D.; Annegarn, H.; Piketh, S.; Helas, G.
1998-01-01
A climatology of air transport to and from Kenya has been developed using kinematic trajectory modeling. Significant months for trajectory analysis have been determined from a classification of synoptic circulation fields. Five-point back and forward trajectory clusters to and from Kenya reveal that the transport corridors to Kenya are clearly bounded and well defined. Air reaching the country originates mainly from the Saharan region and northwestern Indian Ocean of the Arabian Sea in the northern hemisphere and from the Madagascan region of the Indian Ocean in the southern hemisphere. Transport from each of these source regions show distinctive annual cycles related to the northeasterly Asian monsoon and the southeasterly trade wind maximum over Kenya in May. The Saharan transport in the lower troposphere is at a maximum when the subtropical high over northern Africa is strongly developed in the boreal winter. Air reaching Kenya between 700 and 500 hPa is mainly from Sahara and northwest India Ocean flows in the months of January and March, which gives way to southwest Indian Ocean flow in May and November. In contrast, air reaching Kenya at 400 hPa is mainly from southwest Indian Ocean in January and March, which is replaced by Saharan transport in May and November. Transport of air from Kenya is invariant, both spatially and temporally, in the tropical easterlies to the Congo Basin and Atlantic Ocean in comparison to the transport to the country. Recirculation of air has also been observed, but on a limited and often local scale and not to the extent reported in southern Africa.
Gribble, Matthew O; Bartell, Scott M; Kannan, Kurunthachalam; Wu, Qian; Fair, Patricia A; Kamen, Diane L
2015-11-01
Charleston Harbor has elevated concentrations of PFAS in dolphins, but local human exposure data are limited. We sought to describe PFAS serum concentrations' temporal trends among Gullah African American residents of coastal South Carolina. Longitudinal measures of PFAS in blood serum from a Gullah clinical sample, without lupus, were examined using spaghetti plots and visit-to-visit change scores (e.g., differences in concentrations between visits) among the 68 participants with repeated measures available. We also modeled population-level trends among the 71 participants with any data using proportionate percentile models, accounting for clustering through robust standard errors. In a post-hoc analysis we examined heterogeneity of temporal trends by age through mixed-effects models for the log-transformed PFAS compounds. Population concentrations of PFOS dropped approximately 9 (95% CI: 8, 10) percent each year over 2003-2013. This was concordant with individual PFOS trajectories (median PFOS change score -21.7 ng/g wet weight, interquartile range of PFOS change scores: -32.8, -14.9) and reports for other populations over this time period. Several other compounds including PFOA, PFHxS, and PFuNDA also showed a population-level decrease. However, examination of individual trajectories suggested substantial heterogeneity. Post-hoc analyses indicated that PFAS trajectories were heterogeneous by age. Many PFAS compounds are decreasing in a sample of Gullah African Americans from coastal South Carolina. There may be age differences in the elimination kinetics of PFASs. The possible role of age as a modifier of PFAS serum trends merits further research. Copyright © 2015 Elsevier Inc. All rights reserved.
Time-resolved microrheology of actively remodeling actomyosin networks
NASA Astrophysics Data System (ADS)
Silva, Marina Soares e.; Stuhrmann, Björn; Betz, Timo; Koenderink, Gijsje H.
2014-07-01
Living cells constitute an extraordinary state of matter since they are inherently out of thermal equilibrium due to internal metabolic processes. Indeed, measurements of particle motion in the cytoplasm of animal cells have revealed clear signatures of nonthermal fluctuations superposed on passive thermal motion. However, it has been difficult to pinpoint the exact molecular origin of this activity. Here, we employ time-resolved microrheology based on particle tracking to measure nonequilibrium fluctuations produced by myosin motor proteins in a minimal model system composed of purified actin filaments and myosin motors. We show that the motors generate spatially heterogeneous contractile fluctuations, which become less frequent with time as a consequence of motor-driven network remodeling. We analyze the particle tracking data on different length scales, combining particle image velocimetry, an ensemble analysis of the particle trajectories, and finally a kymograph analysis of individual particle trajectories to quantify the length and time scales associated with active particle displacements. All analyses show clear signatures of nonequilibrium activity: the particles exhibit random motion with an enhanced amplitude compared to passive samples, and they exhibit sporadic contractile fluctuations with ballistic motion over large (up to 30 μm) distances. This nonequilibrium activity diminishes with sample age, even though the adenosine triphosphate level is held constant. We propose that network coarsening concentrates motors in large clusters and depletes them from the network, thus reducing the occurrence of contractile fluctuations. Our data provide valuable insight into the physical processes underlying stress generation within motor-driven actin networks and the analysis framework may prove useful for future microrheology studies in cells and model organisms.
Atomic Scale Imaging of Nucleation and Growth Trajectories of an Interfacial Bismuth Nanodroplet.
Li, Yingxuan; Bunes, Benjamin R; Zang, Ling; Zhao, Jie; Li, Yan; Zhu, Yunqing; Wang, Chuanyi
2016-02-23
Because of the lack of experimental evidence, much confusion still exists on the nucleation and growth dynamics of a nanostructure, particularly of metal. The situation is even worse for nanodroplets because it is more difficult to induce the formation of a nanodroplet while imaging the dynamic process with atomic resolution. Here, taking advantage of an electron beam to induce the growth of Bi nanodroplets on a SrBi2Ta2O9 platelet under a high resolution transmission electron microscope (HRTEM), we directly observed the detailed growth pathways of Bi nanodroplets from the earliest stage of nucleation that were previously inaccessible. Atomic scale imaging reveals that the dynamics of nucleation involves a much more complex trajectory than previously predicted based on classical nucleation theory (CNT). The monatomic Bi layer was first formed in the nucleation process, which induced the formation of the prenucleated clusters. Following that, critical nuclei for the nanodroplets formed both directly from the addition of atoms to the prenucleated clusters by the classical growth process and indirectly through transformation of an intermediate liquid film based on the Stranski-Krastanov growth mode, in which the liquid film was induced by the self-assembly of the prenucleated clusters. Finally, the growth of the Bi nanodroplets advanced through the classical pathway and sudden droplet coalescence. This study allows us to visualize the critical steps in the nucleation process of an interfacial nanodroplet, which suggests a revision of the perspective of CNT.
NASA Technical Reports Server (NTRS)
Byrnes, D. V.; Carney, P. C.; Underwood, J. W.; Vogt, E. D.
1974-01-01
Development, test, conversion, and documentation of computer software for the mission analysis of missions to halo orbits about libration points in the earth-sun system is reported. The software consisting of two programs called NOMNAL and ERRAN is part of the Space Trajectories Error Analysis Programs (STEAP). The program NOMNAL targets a transfer trajectory from Earth on a given launch date to a specified halo orbit on a required arrival date. Either impulsive or finite thrust insertion maneuvers into halo orbit are permitted by the program. The transfer trajectory is consistent with a realistic launch profile input by the user. The second program ERRAN conducts error analyses of the targeted transfer trajectory. Measurements including range, doppler, star-planet angles, and apparent planet diameter are processed in a Kalman-Schmidt filter to determine the trajectory knowledge uncertainty. Execution errors at injection, midcourse correction and orbit insertion maneuvers are analyzed along with the navigation uncertainty to determine trajectory control uncertainties and fuel-sizing requirements. The program is also capable of generalized covariance analyses.
Cullati, Stéphane
2014-07-01
Self-rated health (SRH) trajectories tend to decline over a lifetime. Moreover, the Cumulative Advantage and Disadvantage (CAD) model indicates that SRH trajectories are known to consistently diverge along socioeconomic positions (SEP) over the life course. However, studies of working adults to consider the influence of work and family conflict (WFC) on SRH trajectories are scarce. We test the CAD model and hypothesise that SRH trajectories diverge over time according to socioeconomic positions and WFC trajectories accentuate this divergence. Using longitudinal data from the Swiss Household Panel (N = 2327 working respondents surveyed from 2004 to 2010), we first examine trajectories of SRH and potential divergence over time across age, gender, SEP and family status using latent growth curve analysis. Second, we assess changes in SRH trajectories in relation to changes in WFC trajectories and divergence in SRH trajectories according to gender, SEP and family status using parallel latent growth curve analysis. Three measures of WFC are used: exhaustion after work, difficulty disconnecting from work, and work interference in private family obligations. The results show that SRH trajectories slowly decline over time and that the rate of change is not influenced by age, gender or SEP, a result which does not support the CAD model. SRH trajectories are significantly correlated with exhaustion after work trajectories but not the other two WFC measures. When exhaustion after work trajectories are taken into account, SRH trajectories of higher educated people decline slower compared to less educated people, supporting the CAD hypothesis. Copyright © 2014 Elsevier Ltd. All rights reserved.
Folio, Les R; Fischer, Tatjana; Shogan, Paul; Frew, Michael; Dwyer, Andrew; Provenzale, James M
2011-08-01
The purpose of this study is to determine the agreement with which radiologists identify wound paths in vivo on MDCT and calculate missile trajectories on the basis of Cartesian coordinates using a Cartesian positioning system (CPS). Three radiologists retrospectively identified 25 trajectories on MDCT in 19 casualties who sustained penetrating trauma in Iraq. Trajectories were described qualitatively in terms of directional path descriptors and quantitatively as trajectory vectors. Directional descriptors, trajectory angles, and angles between trajectories were calculated based on Cartesian coordinates of entrance and terminus or exit recorded in x, y image and table space (z) using a Trajectory Calculator created using spreadsheet software. The consistency of qualitative descriptor determinations was assessed in terms of frequency of observer agreement and multirater kappa statistics. Consistency of trajectory vectors was evaluated in terms of distribution of magnitude of the angles between vectors and the differences between their paraaxial and parasagittal angles. In 68% of trajectories, the observers' visual assessment of qualitative descriptors was congruent. Calculated descriptors agreed across observers in 60% of the trajectories. Estimated kappa also showed good agreement (0.65-0.79, p < 0.001); 70% of calculated paraaxial and parasagittal angles were within 20° across observers, and 61.3% of angles between trajectory vectors were within 20° across observers. Results show agreement of visually assessed and calculated qualitative descriptors and trajectory angles among observers. The Trajectory Calculator describes trajectories qualitatively similar to radiologists' visual assessment, showing the potential feasibility of automated trajectory analysis.
NASA Astrophysics Data System (ADS)
Swinburne, Thomas D.; Perez, Danny
2018-05-01
A massively parallel method to build large transition rate matrices from temperature-accelerated molecular dynamics trajectories is presented. Bayesian Markov model analysis is used to estimate the expected residence time in the known state space, providing crucial uncertainty quantification for higher-scale simulation schemes such as kinetic Monte Carlo or cluster dynamics. The estimators are additionally used to optimize where exploration is performed and the degree of temperature acceleration on the fly, giving an autonomous, optimal procedure to explore the state space of complex systems. The method is tested against exactly solvable models and used to explore the dynamics of C15 interstitial defects in iron. Our uncertainty quantification scheme allows for accurate modeling of the evolution of these defects over timescales of several seconds.
Linear growth trajectories in Zimbabwean infants12
Gough, Ethan K; Moodie, Erica EM; Prendergast, Andrew J; Ntozini, Robert; Moulton, Lawrence H; Humphrey, Jean H; Manges, Amee R
2016-01-01
Background: Undernutrition in early life underlies 45% of child deaths globally. Stunting malnutrition (suboptimal linear growth) also has long-term negative effects on childhood development. Linear growth deficits accrue in the first 1000 d of life. Understanding the patterns and timing of linear growth faltering or recovery during this period is critical to inform interventions to improve infant nutritional status. Objective: We aimed to identify the pattern and determinants of linear growth trajectories from birth through 24 mo of age in a cohort of Zimbabwean infants. Design: We performed a secondary analysis of longitudinal data from a subset of 3338 HIV-unexposed infants in the Zimbabwe Vitamin A for Mothers and Babies trial. We used k-means clustering for longitudinal data to identify linear growth trajectories and multinomial logistic regression to identify covariates that were associated with each trajectory group. Results: For the entire population, the mean length-for-age z score declined from −0.6 to −1.4 between birth and 24 mo of age. Within the population, 4 growth patterns were identified that were each characterized by worsening linear growth restriction but varied in the timing and severity of growth declines. In our multivariable model, 1-U increments in maternal height and education and infant birth weight and length were associated with greater relative odds of membership in the least–growth restricted groups (A and B) and reduced odds of membership in the more–growth restricted groups (C and D). Male infant sex was associated with reduced odds of membership in groups A and B but with increased odds of membership in groups C and D. Conclusion: In this population, all children were experiencing growth restriction but differences in magnitude were influenced by maternal height and education and infant sex, birth weight, and birth length, which suggest that key determinants of linear growth may already be established by the time of birth. This trial was registered at clinicaltrials.gov as NCT00198718. PMID:27806980
DOE Office of Scientific and Technical Information (OSTI.GOV)
Turi, László, E-mail: turi@chem.elte.hu
2016-04-21
We evaluate the applicability of a hierarchy of quantum models in characterizing the binding energy of excess electrons to water clusters. In particular, we calculate the vertical detachment energy of an excess electron from water cluster anions with methods that include one-electron pseudopotential calculations, density functional theory (DFT) based calculations, and ab initio quantum chemistry using MP2 and eom-EA-CCSD levels of theory. The examined clusters range from the smallest cluster size (n = 2) up to nearly nanosize clusters with n = 1000 molecules. The examined cluster configurations are extracted from mixed quantum-classical molecular dynamics trajectories of cluster anions withmore » n = 1000 water molecules using two different one-electron pseudopotenial models. We find that while MP2 calculations with large diffuse basis set provide a reasonable description for the hydrated electron system, DFT methods should be used with precaution and only after careful benchmarking. Strictly tested one-electron psudopotentials can still be considered as reasonable alternatives to DFT methods, especially in large systems. The results of quantum chemistry calculations performed on configurations, that represent possible excess electron binding motifs in the clusters, appear to be consistent with the results using a cavity structure preferring one-electron pseudopotential for the hydrated electron, while they are in sharp disagreement with the structural predictions of a non-cavity model.« less
NASA Astrophysics Data System (ADS)
Turi, László
2016-04-01
We evaluate the applicability of a hierarchy of quantum models in characterizing the binding energy of excess electrons to water clusters. In particular, we calculate the vertical detachment energy of an excess electron from water cluster anions with methods that include one-electron pseudopotential calculations, density functional theory (DFT) based calculations, and ab initio quantum chemistry using MP2 and eom-EA-CCSD levels of theory. The examined clusters range from the smallest cluster size (n = 2) up to nearly nanosize clusters with n = 1000 molecules. The examined cluster configurations are extracted from mixed quantum-classical molecular dynamics trajectories of cluster anions with n = 1000 water molecules using two different one-electron pseudopotenial models. We find that while MP2 calculations with large diffuse basis set provide a reasonable description for the hydrated electron system, DFT methods should be used with precaution and only after careful benchmarking. Strictly tested one-electron psudopotentials can still be considered as reasonable alternatives to DFT methods, especially in large systems. The results of quantum chemistry calculations performed on configurations, that represent possible excess electron binding motifs in the clusters, appear to be consistent with the results using a cavity structure preferring one-electron pseudopotential for the hydrated electron, while they are in sharp disagreement with the structural predictions of a non-cavity model.
Dynamical evolution of galaxies in dense cluster environment.
NASA Astrophysics Data System (ADS)
Gnedin, O. Y.
1997-12-01
I present the results of study of the dynamics of galaxies in clusters of galaxies. The effects of the galaxy environment could be quite dramatic. The time-varying gravitational potential of the cluster subjects the galaxies to strong tidal effects. The tidal density cutoff effectively strips the dark matter halos and leads to highly concentrated structures in the galactic centers. The fast gravitational tidal shocks raise the random motion of stars in the galaxies, transforming the thin disks into the kinematically hot thick configurations. The tidal shocks also cause relaxation of stellar energies that enhances the rate of accretion onto the galactic centers. These effects of the time-varying cluster potential have not been consistently taken into account before. I present numerical N-body simulations of galaxies using the Self-Consistent Field code with 10(7) - 10(8) particles. The code is coupled with the PM code that provides a fully dynamic simulation of the cluster potential. The tidal field of the cluster along the galaxy trajectories is imposed as an external perturbation on the galaxies in the SCF scheme. Recent HST observations show that the high-redshift (z > 0.4) clusters contain numerous bright blue spirals, often with distorted profiles, whereas the nearby clusters are mostly populated by featureless ellipticals. The goal of my study is to understand whether dynamics is responsible for the observed strong evolution of galaxies in clusters.
ERIC Educational Resources Information Center
Clements, Douglas H.; Sarama, Julie; Wolfe, Christopher B.; Spitler, Mary Elaine
2013-01-01
Using a cluster randomized trial design, we evaluated the persistence of effects of a research-based model for scaling up educational interventions. The model was implemented in 42 schools in two city districts serving low-resource communities, randomly assigned to three conditions. In pre-kindergarten, the two experimental interventions were…
Romantic Relationship Patterns in Young Adulthood and Their Developmental Antecedents
Rauer, Amy J.; Pettit, Gregory S.; Lansford, Jennifer E.; Bates, John E.; Dodge, Kenneth A.
2013-01-01
The delayed entry into marriage that characterizes modern society raises questions about young adults' romantic relationship trajectories and whether patterns found to characterize adolescent romantic relationships persist into young adulthood. The current study traced developmental transitions into and out of romantic relationships from age 18 through age 25 in a sample of 511 young adults. The developmental antecedents of these different romantic relationship experiences in both distal and proximal family and peer domains were also examined. Analyses included both person-oriented and variable-oriented approaches. Findings show 5 distinct clusters varying in timing, duration, and frequency of participation in romantic relationships that range from those who had only recently entered into a romantic relationship to those who had been in the same relationship from age 18 to age 25. These relationship outcome trajectory clusters were predicted by variations in competence in early relationships with family and peers. Interpersonal experiences in family and peer contexts in early childhood through adolescence thus may form a scaffold on which later competence in romantic relationships develops. Findings shed light on both normative and nonnormative developmental transitions of romantic relationships in young adulthood. PMID:23421803
Iso-chemical potential trajectories in the P-T plane for He II
NASA Technical Reports Server (NTRS)
Maytal, B.; Nissen, J. A.; Van Sciver, S. W.
1990-01-01
Trajectories of constant chemical potential in the P-T plane serve as an integral formulation of London's equation. The trajectories are useful for analysis and synthesis of fountain effect pump performance. A family of trajectories is generated from available numerical codes.
A Robot Trajectory Optimization Approach for Thermal Barrier Coatings Used for Free-Form Components
NASA Astrophysics Data System (ADS)
Cai, Zhenhua; Qi, Beichun; Tao, Chongyuan; Luo, Jie; Chen, Yuepeng; Xie, Changjun
2017-10-01
This paper is concerned with a robot trajectory optimization approach for thermal barrier coatings. As the requirements of high reproducibility of complex workpieces increase, an optimal thermal spraying trajectory should not only guarantee an accurate control of spray parameters defined by users (e.g., scanning speed, spray distance, scanning step, etc.) to achieve coating thickness homogeneity but also help to homogenize the heat transfer distribution on the coating surface. A mesh-based trajectory generation approach is introduced in this work to generate path curves on a free-form component. Then, two types of meander trajectories are generated by performing a different connection method. Additionally, this paper presents a research approach for introducing the heat transfer analysis into the trajectory planning process. Combining heat transfer analysis with trajectory planning overcomes the defects of traditional trajectory planning methods (e.g., local over-heating), which helps form the uniform temperature field by optimizing the time sequence of path curves. The influence of two different robot trajectories on the process of heat transfer is estimated by coupled FEM models which demonstrates the effectiveness of the presented optimization approach.
On Integral Invariants for Effective 3-D Motion Trajectory Matching and Recognition.
Shao, Zhanpeng; Li, Youfu
2016-02-01
Motion trajectories tracked from the motions of human, robots, and moving objects can provide an important clue for motion analysis, classification, and recognition. This paper defines some new integral invariants for a 3-D motion trajectory. Based on two typical kernel functions, we design two integral invariants, the distance and area integral invariants. The area integral invariants are estimated based on the blurred segment of noisy discrete curve to avoid the computation of high-order derivatives. Such integral invariants for a motion trajectory enjoy some desirable properties, such as computational locality, uniqueness of representation, and noise insensitivity. Moreover, our formulation allows the analysis of motion trajectories at a range of scales by varying the scale of kernel function. The features of motion trajectories can thus be perceived at multiscale levels in a coarse-to-fine manner. Finally, we define a distance function to measure the trajectory similarity to find similar trajectories. Through the experiments, we examine the robustness and effectiveness of the proposed integral invariants and find that they can capture the motion cues in trajectory matching and sign recognition satisfactorily.
IRVE-II Post-Flight Trajectory Reconstruction
NASA Technical Reports Server (NTRS)
O'Keefe, Stephen A.; Bose, David M.
2010-01-01
NASA s Inflatable Re-entry Vehicle Experiment (IRVE) II successfully demonstrated an inflatable aerodynamic decelerator after being launched aboard a sounding rocket from Wallops Flight Facility (WFF). Preliminary day of flight data compared well with pre-flight Monte Carlo analysis, and a more complete trajectory reconstruction performed with an Extended Kalman Filter (EKF) approach followed. The reconstructed trajectory and comparisons to an attitude solution provided by NASA Sounding Rocket Operations Contract (NSROC) personnel at WFF are presented. Additional comparisons are made between the reconstructed trajectory and pre and post-flight Monte Carlo trajectory predictions. Alternative observations of the trajectory are summarized which leverage flight accelerometer measurements, the pre-flight aerodynamic database, and on-board flight video. Finally, analysis of the payload separation and aeroshell deployment events are presented. The flight trajectory is reconstructed to fidelity sufficient to assess overall project objectives related to flight dynamics and overall, IRVE-II flight dynamics are in line with expectations
Kim, Sang-Hee; Byun, Youngsoon
Symptom clusters must be identified in patients with high-grade brain cancers for effective symptom management during cancer-related therapy. The aims of this study were to identify symptom clusters in patients with high-grade brain cancers and to determine the relationship of each cluster with the performance status and quality of life (QOL) during concurrent chemoradiotherapy (CCRT). Symptoms were assessed using the Memorial Symptom Assessment Scale, and the performance status was evaluated using the Karnofsky Performance Scale. Quality of life was assessed using the Functional Assessment of Cancer Therapy-General. This prospective longitudinal survey was conducted before CCRT and at 2 to 3 weeks and 4 to 6 weeks after the initiation of CCRT. A total of 51 patients with newly diagnosed primary malignant brain cancer were included. Six symptom clusters were identified, and 2 symptom clusters were present at each time point (ie, "negative emotion" and "neurocognitive" clusters before CCRT, "negative emotion and decreased vitality" and "gastrointestinal and decreased sensory" clusters at 2-3 weeks, and "body image and decreased vitality" and "gastrointestinal" clusters at 4-6 weeks). The symptom clusters at each time point demonstrated a significant relationship with the performance status or QOL. Differences were observed in symptom clusters in patients with high-grade brain cancers during CCRT. In addition, the symptom clusters were correlated with the performance status and QOL of patients, and these effects could change during CCRT. The results of this study will provide suggestions for interventions to treat or prevent symptom clusters in patients with high-grade brain cancer during CCRT.
Overview of the Development for a Suite of Low-Thrust Trajectory Analysis Tools
NASA Technical Reports Server (NTRS)
Kos, Larry D.; Polsgrove, Tara; Hopkins, Randall; Thomas, Dan; Sims, Jon A.
2006-01-01
A NASA intercenter team has developed a suite of low-thrust trajectory analysis tools to make a significant improvement in three major facets of low-thrust trajectory and mission analysis. These are: 1) ease of use, 2) ability to more robustly converge to solutions, and 3) higher fidelity modeling and accuracy of results. Due mostly to the short duration of the development, the team concluded that a suite of tools was preferred over having one integrated tool. This tool-suite, their characteristics, and their applicability will be described. Trajectory analysts can read this paper and determine which tool is most appropriate for their problem.
Sanchez Sorzano, Carlos Oscar; Alvarez-Cabrera, Ana Lucia; Kazemi, Mohsen; Carazo, Jose María; Jonić, Slavica
2016-04-26
Single-particle electron microscopy (EM) has been shown to be very powerful for studying structures and associated conformational changes of macromolecular complexes. In the context of analyzing conformational changes of complexes, distinct EM density maps obtained by image analysis and three-dimensional (3D) reconstruction are usually analyzed in 3D for interpretation of structural differences. However, graphic visualization of these differences based on a quantitative analysis of elastic transformations (deformations) among density maps has not been done yet due to a lack of appropriate methods. Here, we present an approach that allows such visualization. This approach is based on statistical analysis of distances among elastically aligned pairs of EM maps (one map is deformed to fit the other map), and results in visualizing EM maps as points in a lower-dimensional distance space. The distances among points in the new space can be analyzed in terms of clusters or trajectories of points related to potential conformational changes. The results of the method are shown with synthetic and experimental EM maps at different resolutions. Copyright © 2016 Biophysical Society. Published by Elsevier Inc. All rights reserved.
NASA Astrophysics Data System (ADS)
Pawar, Harshita; Sachan, Himanshu; Garg, Saryu; Arya, Ruhani; Singh, Nitin Kumar; Sinha, Baerbel; Sinha, Vinayak
2013-04-01
We investigate the climatology of air masses arriving at the IISER Mohali Atmospheric Chemistry facility (30.67°N, 76.73°E; 310 m amsl) through 3-day backtrajectories arriving at 20 m above ground level for the period August 2011-November 2012. IISER Mohali is a suburban site in the North-Western Indo Gangetic Basin. The trajectories are computed in ensemble mode twice daily with an arrival time of 2:30 pm local time (daytime) and 4:30 am local time (nighttime) using the HYSPLIT 4 model with the National Oceanic and Atmospheric Administration's GDAS file as meterological input data. Due to the close proximity of the site to the Himalayan mountain range the trajectory output is found to be very sensitive to the models input data. IISER Air Quality station is located in the IGB at an altitude of 310 m amsl approximately 20 km south west of the Shivalik hills, but the model terrain height for the site in the ensemble run output varies between 200 m amsl and 3500 m amsl for the GDAS dataset and 200 m amsl to 5000 m amsl for the reanalysis dataset. We conclude that the GDAS dataset performs better than than reanalysis dataset for our site and selected only those trajectories from the trajectory ensemble for cluster analysis, for which the terrain height in the model output was < 400 m amsl for IISER Mohali (in the IGB) and > 400 m amsl for Shimla (a site located at an altitude of 1000 m amsl in the mountains 60 km north east of Mohali). We subjected the trajectories to hierarchical, and non-hierarchical (K-means) clustering and found that the air mass transport to our station can be characterised by 10 distinct airflow patterns; 3 of which occur only during the monsoon season. For pre-monsoon season (March-June), post-monsoon season (Sept-Nov) and winter season (Dec-Feb), air mass transport to our site is predominantly from the west. Direct transport of north westerly air masses to our site is subdivided into three clusters (slow, medium and rapid) while other clusters are attributed to south westerly air currents or arise from the fact that westerly air masses are deflected and descend along the slope of the Himalayan mountain range and reach our site from the north or south-east. A local recirculation cluster is found to occur particularly during wintertime when stagnant conditions with windspeeds < 1 m/s can presist for several days. We find that several air pollutants measured at the IISER Mohali air quality station are significantly influenced by regional transport and long range transport during pre-monsoon (March-June) and post-monsoon (Sept-Nov) season. This is particularly true for PM10 where the highest loadings (730 μg/m3) are found in air masses with rapid air mass transport from a north western direction during pre-monsoon season. In medium and slow transport from the NW we observe 260 μg/m3 and 210 μg/m3 PM10 respectively. The lowest PM10 loading during pre-monsoon season are associated with local recirculation of air masses (170 μg/m3) and air masses with a long residence time over the eastern IGB (190μg/m3). For NOx, SO2 and CO the lowest concentrations are observed in air masses influenced by rapid long range transport from the NW (4.7, 2.6 and 220 ppbv respectively) while the highest NOx, SO2 and concentrations are observed in air masses transported with slow or medium speed from the NW (7.1, 5.2 and 380 ppbv respectively). During winter season local and regional sources are found to dominate over long range transport, with long range transport accounting for less than 30 % of the observed variablity in the chemical composition of the air masses. During monsoon season removal of pollutants through wet deposition dominates the measured concentrations. Acknowledgement: We thank the IISER Mohali Atmospheric Chemistry Facility for data and the Ministry of Human Resource Development (MHRD), India and IISER Mohali for funding the facility. Chinmoy Sarkar is acknowledged for technical support, SG thanks the Max Planck-DST India Partner Group on Tropospheric OH reactivity and VOCs for funding the research, H. Panwar, H. Sachan and N. K. Singh acknowledge the DST-INSPIRE Fellowship program and R. Arya thanks IISER Mohali for providing an IISER Summer Research Fellowship.
Essential dynamics/factor analysis for the interpretation of molecular dynamics trajectories
NASA Astrophysics Data System (ADS)
Kaźmierkiewicz, R.; Czaplewski, C.; Lammek, B.; Ciarkowski, J.
1999-01-01
Subject of this work is the analysis of molecular dynamics (MD) trajectories of neurophysins I (NPI) and II (NPII) and their complexes with the neurophyseal nonapeptide hormones oxytocin (OT) and vasopresssin (VP), respectively, simulated in water. NPs serve in the neurosecretory granules as carrier proteins for the hormones before their release to the blood. The starting data consisted of two pairs of different trajectories for each of the (NPII/VP)2 and (NPI/OT)2 heterotetramers and two more trajectories for the NPII2 and NPI2 homodimers (six trajectories in total). Using essential dynamics which, to our judgement, is equivalent to factor analysis, we found that only about 10 degrees of freedom per trajectory are necessary and sufficient to describe in full the motions relevant for the function of the protein. This is consistent with these motions to explain about 90% of the total variance of the system. These principal degrees of freedom represent slow anharmonic motional modes, clearly pointing at distinguished mobility of the atoms involved in the protein's functionality.
Educational Aspirations Trajectories in England
ERIC Educational Resources Information Center
McCulloch, Andrew
2017-01-01
This study used latent class analysis to examine the trajectories followed by young people's educational aspirations in England over the age range from 13 to 16 years and their relationship to educational achievement. The results suggested that young people's aspirations followed six trajectories. Four trajectories showed overall patterns of…
Automated Sensitivity Analysis of Interplanetary Trajectories
NASA Technical Reports Server (NTRS)
Knittel, Jeremy; Hughes, Kyle; Englander, Jacob; Sarli, Bruno
2017-01-01
This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.
Optimal solar sail planetocentric trajectories
NASA Technical Reports Server (NTRS)
Sackett, L. L.
1977-01-01
The analysis of solar sail planetocentric optimal trajectory problem is described. A computer program was produced to calculate optimal trajectories for a limited performance analysis. A square sail model is included and some consideration is given to a heliogyro sail model. Orbit to a subescape point and orbit to orbit transfer are considered. Trajectories about the four inner planets can be calculated and shadowing, oblateness, and solar motion may be included. Equinoctial orbital elements are used to avoid the classical singularities, and the method of averaging is applied to increase computational speed. Solution of the two-point boundary value problem which arises from the application of optimization theory is accomplished with a Newton procedure. Time optimal trajectories are emphasized, but a penalty function has been considered to prevent trajectories which intersect a planet's surface.
Cselényi, Zsolt; Lundberg, Johan; Halldin, Christer; Farde, Lars; Gulyás, Balázs
2004-10-01
Positron emission tomography (PET) has proved to be a highly successful technique in the qualitative and quantitative exploration of the human brain's neurotransmitter-receptor systems. In recent years, the number of PET radioligands, targeted to different neuroreceptor systems of the human brain, has increased considerably. This development paves the way for a simultaneous analysis of different receptor systems and subsystems in the same individual. The detailed exploration of the versatility of neuroreceptor systems requires novel technical approaches, capable of operating on huge parametric image datasets. An initial step of such explorative data processing and analysis should be the development of novel exploratory data-mining tools to gain insight into the "structure" of complex multi-individual, multi-receptor data sets. For practical reasons, a possible and feasible starting point of multi-receptor research can be the analysis of the pre- and post-synaptic binding sites of the same neurotransmitter. In the present study, we propose an unsupervised, unbiased data-mining tool for this task and demonstrate its usefulness by using quantitative receptor maps, obtained with positron emission tomography, from five healthy subjects on (pre-synaptic) serotonin transporters (5-HTT or SERT) and (post-synaptic) 5-HT(1A) receptors. Major components of the proposed technique include the projection of the input receptor maps to a feature space, the quasi-clustering and classification of projected data (neighbourhood formation), trans-individual analysis of neighbourhood properties (trajectory analysis), and the back-projection of the results of trajectory analysis to normal space (creation of multi-receptor maps). The resulting multi-receptor maps suggest that complex relationships and tendencies in the relationship between pre- and post-synaptic transporter-receptor systems can be revealed and classified by using this method. As an example, we demonstrate the regional correlation of the serotonin transporter-receptor systems. These parameter-specific multi-receptor maps can usefully guide the researchers in their endeavour to formulate models of multi-receptor interactions and changes in the human brain.
Predicting Reading Disability: Early Cognitive Risk and Protective Factors
ERIC Educational Resources Information Center
Eklund, Kenneth Mikael; Torppa, Minna; Lyytinen, Heikki
2013-01-01
This longitudinal study examined early cognitive risk and protective factors for Grade 2 reading disability (RD). We first examined the reading outcome of 198 children in four developmental cognitive subgroups that were identified in our previous analysis: dysfluent trajectory, declining trajectory, unexpected trajectory and typical trajectory. We…
Trajectory selection for the Mariner Jupiter/Saturn 1977 project
NASA Technical Reports Server (NTRS)
Dyer, J. S.; Miles, R. F., Jr.
1974-01-01
The use of decision analysis to facilitate a group decision-making problem in the selection of trajectories for the two spacecraft of the Mariner Jupiter/Saturn 1977 Project. A set of 32 candidate trajectory pairs was developed. Cardinal utility function values were assigned to the trajectory pairs, and the data and statistics derived from collective choice rules were used in selecting the science-preferred trajectory pair.
NASA Astrophysics Data System (ADS)
Salvador, P.; Artíñano, B.; Pio, C. A.; Afonso, J.; Puxbaum, H.; Legrand, M.; Hammer, S.; Kaiser, A.
2009-04-01
During the last years, the analysis of a great number of back-trajectories from receptor sites has turned out to be a valuable tool to identify sources and sinks areas of atmospheric particulate matter (PM) or to reconstruct their average spatial distribution. A number of works have applied different trajectory statistical methods (TSM), which allow working simultaneously with back-trajectories computed from one or several receptor points and PM concentration values registered there. In spite of these methods have many limitations, they are simple and effective methods to detect the relevant source regions and the air flow regimes which are connected with regional and large-scale air pollution transport. In this study 5-day backward air trajectories arriving over 3 monitoring sites, were utilised and analysed simultaneously with the PM levels and chemical composition values registered there. These sites are located in the centre of Europe and can be classified into natural continental background (Schauinsland-SIL in Germany (1205 m asl), Puy de Dôme-PDD in France (1450 m asl) and Sonnblick-SBO in Austria (3106 m asl)). In the framework of the CARBOSOL European project, weekly aerosol samples were collected with High Volume Samplers (DIGITEL DH77) and PM10 (SIL and PDD) or PM2.5 (SBO) inlets, on quartz fibre filters. Filter samples were treated and analyzed for determining the levels of major organic fractions (OC, EC) and inorganic ions. Additionally, analyses for specific organic compounds were also carried out whenever was possible (Pio et al., 2007). For each day of the sampling period, four trajectories ending at 00:00, 06:00, 12:00 and 18:00 h UTC have been computed by the Norwegian Institute for Air Research NILU (SIL and PDD) and the Central Institute for Meteorology and Geophysics of Austria (SBO) using the FLEXTRA model (Stohl et al., 1995). In all, more than 8000 complete trajectories were available for analysis, each with 40 endpoints. Firstly air mass back-trajectories have been grouped into clusters, each one representing a characteristic meteorological scenario. Some common features have been detected for the clusters obtained in the three monitoring sites. A clear seasonal pattern has been observed with marked fast westerly and northerly Atlantic flows during the winter, to low speed air circulation flows in summertime. The transition period between the occurrence of the longest trajectories in winter and the shortest ones in summer has been characterised by the advection of moderate flows from the north-eastern and eastern European mainland areas. Meteorological scenarios represented by trajectories coming from the Mediterranean basin and North-African regions, have also occurred during the summer months. Then, Redistribution Concentration Fields (RCF, Stohl, 1996) have been computed for each single station and for SIL and PDD together with the aim to obtain more reliable information on PM10 sources, for the whole sampling period and also for the summer and winter seasons. With this methodology, it is possible to obtain spatial distributions of concentrations for specific tracers of PM sources. High concentration values of the element C obtained over a geographical region means that, on average, air parcels passing over that region result in high concentrations of the element C at the receptor site. The main results obtained with this analysis, suggests that current carbonaceous aerosol concentrations in central Europe are likely to be influenced significantly during the winter and autumn months by long-range transport of PM from the north-eastern and eastern regions of Europe. Emissions produced by fossil-fuel and biomass burning processes in these areas, are probably the main sources contributing to the transported aerosol. In contrast, in summer there is a higher contribution of the emissions from local and regional sources on the OC and EC levels at these background sites (Germany, Poland and the Baltic countries). Secondary organic aerosol carbon formed by the photo-oxidation of biogenic emissions mainly from Germany, seems to be predominant in this season. This seasonal cycle is mainly driven by the winter/summer contrast of the regional-scale vertical mixing. During the warm season the vertical air mass exchange is enhanced by a more efficient upward transport from the boundary layer to the mountain sites. During the winter months, the vertical mixing intensity is reduced. In this season the mean levels obtained for OC and EC were lower than those recorded during the summer. Their spatiotemporal variability was mainly governed by air mass transport from distant regions, especially from Eastern Europe regions, where significant amounts of fossil fuels and biomass are currently consumed. Furthermore, emissions from desert regions in North Africa seemed to significantly influence the central European background mineral aerosol concentrations throughout the year. References: Pio C. A., M. Legrand, T. Oliveira, J. Afonso, C. Santos, A. Caseiro, P. Fialho, F. Barata, H. Puxbaum, A. Sanchez-Ochoa, A. Kasper-Giebl, A. Gelencsér, S. Preunkert, and M. Schock (2007), Climatology of aerosol composition (organic versus inorganic) at nonurban sites on a west-east transect across Europe. J. Geophys. Res., 112, D23S02, doi:10.1029/2006JD008038. Stohl A., G. Wotawa, P. Seibert and H. Kromp-Kolb (1995), Interpolation errors in wind fields as a function of spatial and temporal resolution and their impact on different types of kinematic trajectories. J. Appl. Meteorol., 34, 2149-2165. Stohl A. (1996), Trajectory statistics-a new method to establish source-receptor relationships of air pollutants and its application to the transport of particulate sulfate in Europe. Atmos. Environ., 30(4), 579-587.
Loprinzi, Paul D; Walker, Jerome F
2016-01-01
To our knowledge, no longitudinal epidemiological study among daily smokers has examined the effects of physical activity change/ trajectory on smoking cessation. The purpose of this study was to examine the longitudinal effects of changes in physical activity on smoking cessation among a national sample of young (16-24 y) daily smokers. Data from the 2003-2005 National Youth Smoking Cessation Survey were used (N = 1178). Using hierarchical agglomerative cluster analysis, 5 distinct self-reported physical activity trajectories over 3 time periods (baseline, 12-month, and 24-month follow-up) were observed, including stable low physical activity, decreasing physical activity, curvilinear physical activity, stable high physical activity, and increasing physical activity. Nicotine dependence (Heaviness of Smoking Index) and demographic parameters were assessed via survey. With stable low physical activity (16.2% quit smoking) serving as the referent group, those in the stable high physical activity (24.8% quit smoking) group had 1.8 greater odds of not smoking at the 24-month follow-up period (odds ratio = 1.81; 95% confidence interval, 1.12-2.91) after adjusting for nicotine dependence, age, gender, race-ethnicity, and education. Maintenance of regular physical activity among young daily smokers may help to facilitate smoking cessation.
Krüger, Dennis M; Ahmed, Aqeel; Gohlke, Holger
2012-07-01
The NMSim web server implements a three-step approach for multiscale modeling of protein conformational changes. First, the protein structure is coarse-grained using the FIRST software. Second, a rigid cluster normal-mode analysis provides low-frequency normal modes. Third, these modes are used to extend the recently introduced idea of constrained geometric simulations by biasing backbone motions of the protein, whereas side chain motions are biased toward favorable rotamer states (NMSim). The generated structures are iteratively corrected regarding steric clashes and stereochemical constraint violations. The approach allows performing three simulation types: unbiased exploration of conformational space; pathway generation by a targeted simulation; and radius of gyration-guided simulation. On a data set of proteins with experimentally observed conformational changes, the NMSim approach has been shown to be a computationally efficient alternative to molecular dynamics simulations for conformational sampling of proteins. The generated conformations and pathways of conformational transitions can serve as input to docking approaches or more sophisticated sampling techniques. The web server output is a trajectory of generated conformations, Jmol representations of the coarse-graining and a subset of the trajectory and data plots of structural analyses. The NMSim webserver, accessible at http://www.nmsim.de, is free and open to all users with no login requirement.
Transport pathway and source area for Artemisia pollen in Beijing, China
NASA Astrophysics Data System (ADS)
Qin, Xiaoxin; Li, Yiyin; Sun, Xu; Meng, Ling; Wang, Xiaoke
2017-12-01
Artemisia pollen is an important allergen responsible for allergic rhinitis in Beijing, China. To explore the transport pathways and source areas of Artemisia pollen, we used Burkard 7-day traps to monitor daily pollen concentrations in 2016 in an urban and suburban locality. Backward trajectories of 24- and 96-h and their cluster analysis were performed to identify transport pathways of Artemisia pollen using the HYSPLIT model on 0.5° × 0.5° GADS meteorological data. The potential source contribution function (PSCF) and concentration weighted trajectory (CWT) were calculated to further identify the major potential source areas at local, regional, and long-range scales. Our results showed significant differences in Artemisia pollen concentration between urban and suburban areas, attributed to differences in plant distribution and altitude of the sampling locality. Such differences arisen from both pollen emission and air mass movements, hence pollen dispersal. At local or regional scales, source area of northwestern parts of Beijing City, Hebei Province and northern and northwestern parts of Inner Mongolia influenced the major transport pathways of Artemisia pollen. Transport pathway at a long-range scale and its corresponding source area extended to northwestern parts of Mongolia. The regional-scale transport affected by wind and altitude is more profound for Artemisia pollen at the suburban than at the urban station.
NASA Astrophysics Data System (ADS)
Masiol, Mauro; Benetello, Francesca; Harrison, Roy M.; Formenton, Gianni; De Gaspari, Francesco; Pavoni, Bruno
2015-09-01
The Veneto region lies in the eastern part of the Po Valley (Italy). This is one of the hotspots in Europe for air quality, where efforts to meet the European standard for PM2.5 according to current and future legislation have been generally unsuccessful. Recent data indicating that ammonium, nitrate and sulphate account for about one third of total PM2.5 mass show that secondary inorganic aerosol (SIA) plays a key role in the exceedence of the standards. A sampling campaign for PM2.5 was carried out simultaneously in six major cities (2012-2013). The water soluble inorganic ions were quantified and data processed to: (1) investigate the seasonal trends and the spatial variations of the ionic component of aerosol; (2) identify chemical characteristics at the regional-scale and (3) assess the potential effects of long-range transport using back-trajectory cluster analysis and concentration-weighted trajectory (CWT) models. Results indicated that PM2.5 and SIA ions have an increasing gradient in concentrations from North (mountain) to South (lowland) and from East (coastal) to West (more continental), whereas K+ and Ca2+ levels are quite uniformly distributed. Similar seasonal trends in PM2.5 and ions are seen across the region. Simultaneous daily changes were observed and interpreted as a consequence of similar emission sources, secondary pollutant generation and accumulation/removal processes. Sulphate and nitrate were not directly related to the concentrations of their precursor gases and were generally largely, but not completely, neutralised by ammonium. The clustering of back-trajectories and CWT demonstrate that the long-range movement of the air masses has a major impact upon PM2.5 and ion concentrations: an area spreading from Eastern to Central Europe was identified as a main potential source for most ions. The valley sites are also heavily influenced by local emissions in slow moving northerly air masses. Finally, two episodes of high nitrate levels were investigated to explain why some sites are experiencing much higher concentrations than others. This study identifies some key features in the generation of SIA in the Po Valley, demonstrating that SIA generation is a regional pollution phenomenon and mitigation policies are required at regional, national and even European scales.
NASA Technical Reports Server (NTRS)
Kanzawa, Hiroshi; Fujii, Ryoichi; Yamazaki, Koji; Yamanaka, Manabu D.
1994-01-01
Actual trajectories of two PPB's which flew in the Antarctic stratosphere in austral summer and spring are compared with those calculated based on objective analysis data of Japan Meteorological Agency (JMA). The differences between the actual and calculated trajectories are discussed to check reliability of the JMA objective analysis data for the stratosphere, and to detect subsynoptic scale variability due to gravity waves and others.
Automated Sensitivity Analysis of Interplanetary Trajectories for Optimal Mission Design
NASA Technical Reports Server (NTRS)
Knittel, Jeremy; Hughes, Kyle; Englander, Jacob; Sarli, Bruno
2017-01-01
This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.
Variation in Trajectories of Women's Marital Quality
James, Spencer L.
2014-01-01
I examine variation in trajectories of women's marital quality across the life course. The analysis improves upon earlier research in three ways: (1) the analysis uses a sequential cohort design and data from the first 35 years of marriage; (2) I analyze rich data from a national sample; (3) I examine multiple dimensions of marital quality. Latent class growth analyses estimated on data from women in the National Longitudinal Survey of Youth-1979 (N = 2604) suggest multiple trajectories for each of three dimensions of marital quality, including two trajectories of marital happiness, two trajectories of marital communication, and three trajectories of marital conflict. Socioeconomic and demographic covariates are then used to illustrate how factors such as income, cohabitation, and race-ethnicity set individuals at risk of poor marital quality throughout the life course by differentiating between high and low trajectories of marital quality. Women on low marital quality trajectories are, as expected, at much greater risk of divorce. Taken together, these findings show how fundamental socioeconomic and demographic characteristics contribute to subsequent marital outcomes via their influence on trajectories of marital quality as well as providing a better picture of the complexity in contemporary patterns of marital quality. PMID:25432600
Friendship networks and trajectories of adolescent tobacco use.
Pollard, Michael S; Tucker, Joan S; Green, Harold D; Kennedy, David; Go, Myong-Hyun
2010-07-01
This article examines how friendship networks in adolescence are linked to tobacco use trajectories through a combination of analytic techniques that traditionally are located in separate literatures: social network analysis and developmental trajectory analysis. Using six years of longitudinal data from the National Longitudinal Study of Adolescent Health, we identify a set of six unique developmental trajectories of smoking (never smokers, steady lows, delayed increasers, early increasers, decreasers, and steady highs). Individuals' locations in their friendship networks were then linked to their trajectory group membership. Adolescents with a greater number of smoking friends were more likely to belong to the higher use trajectories. Beyond this exposure to smoking peers, individuals who at baseline were either members of a smoking group or liaisons to a smoking group were more likely than members of a nonsmoking group to belong to the higher use trajectories. Liaisons to a smoking group were particularly likely to belong to the delayed increaser trajectory group. Trajectory group membership for adolescents who belonged to a nonsmoking group did not significantly differ from those who were isolates or liaisons to a nonsmoking group. The study suggests features of an individual's social network have long-lasting associations with smoking behaviors. 2010 Elsevier Ltd. All rights reserved.
Accuracy and Repeatability of Trajectory Rod Measurement Using Laser Scanners.
Liscio, Eugene; Guryn, Helen; Stoewner, Daniella
2017-12-22
Three-dimensional (3D) technologies contribute greatly to bullet trajectory analysis and shooting reconstruction. There are few papers which address the errors associated with utilizing laser scanning for bullet trajectory documentation. This study examined the accuracy and precision of laser scanning for documenting trajectory rods in drywall for angles between 25° and 90°. The inherent error range of 0.02°-2.10° was noted while the overall error for laser scanning ranged between 0.04° and 1.98°. The inter- and intraobserver errors for trajectory rod placement and virtual trajectory marking showed that the range of variation for rod placement was between 0.1°-1° in drywall and 0.05°-0.5° in plywood. Virtual trajectory marking accuracy tests showed that 75% of data values were below 0.91° and 0.61° on azimuth and vertical angles, respectively. In conclusion, many contributing factors affect bullet trajectory analysis, and the use of 3D technologies can aid in reduction of errors associated with documentation. © 2017 American Academy of Forensic Sciences.
Aeroassisted orbit transfer vehicle trajectory analysis
NASA Technical Reports Server (NTRS)
Braun, Robert D.; Suit, William T.
1988-01-01
The emphasis in this study was on the use of multiple pass trajectories for aerobraking. However, for comparison, single pass trajectories, trajectories using ballutes, and trajectories corrupted by atmospheric anomolies were run. A two-pass trajectory was chosen to determine the relation between sensitivity to errors and payload to orbit. Trajectories that used only aerodynamic forces for maneuvering could put more weight into the target orbits but were very sensitive to variations from the planned trajectors. Using some thrust control resulted in less payload to orbit, but greatly reduced the sensitivity to variations from nominal trajectories. When compared to the non-thrusting trajectories investigated, the judicious use of thrusting resulted in multiple pass trajectories that gave 97 percent of the payload to orbit with almost none of the sensitivity to variations from the nominal.
NASA Astrophysics Data System (ADS)
Saroglou, Charalampos; Asteriou, Pavlos; Zekkos, Dimitrios; Tsiambaos, George; Clark, Marin; Manousakis, John
2018-01-01
We present field evidence and a kinematic study of a rock block mobilized in the Ponti area by a Mw = 6.5 earthquake near the island of Lefkada on 17 November 2015. A detailed survey was conducted using an unmanned aerial vehicle (UAV) with an ultrahigh definition (UHD) camera, which produced a high-resolution orthophoto and a digital terrain model (DTM). The sequence of impact marks from the rock trajectory on the ground surface was identified from the orthophoto and field verified. Earthquake characteristics were used to estimate the acceleration of the rock slope and the initial condition of the detached block. Using the impact points from the measured rockfall trajectory, an analytical reconstruction of the trajectory was undertaken, which led to insights on the coefficients of restitution (CORs). The measured trajectory was compared with modeled rockfall trajectories using recommended parameters. However, the actual trajectory could not be accurately predicted, revealing limitations of existing rockfall analysis software used in engineering practice.
Trajectory analyses of sickness absence among industrial and municipal employees.
Virtanen, P; Siukola, A; Lipiäinen, L; Liukkonen, V; Pentti, J; Vahtera, J
2017-03-01
Compared with the public sector, the private sector is more susceptible to changes in the economic environment and associated threats of downsizing, outsourcing and transfers of production. This might be assumed to be associated with more restrictive sickness absence practices. To investigate whether this difference is reflected in higher sickness absence rates in the public sector and to explore the potential of trajectory analysis in researching such absences. The sample consisted of industrial and municipal employees. Latent groups of differential sickness absence during a 6-year study period were searched with a two-response trajectory analysis that jointly captured the spells and the days. Multinomial logistic regressions were used to assess associations of the labour market sector with the set of trajectories obtained. There were 2207 industrial and 3477 municipal employees in the study group. The analysis assigned the employees to three trajectory groups, the 'low-level', 'middle-range' and 'high-range' groups. The relative risk ratios for the middle-range and the high-range trajectories of public sector employees were not higher after controlling for age, gender and occupational. In this study, the labour market sector was not a major independent determinant of sickness absence practices. Trajectory analysis can be recommended as a way to determine differential absence practices. The trajectory approach might help occupational health services to identify more accurately the employees who need support to maintain their work ability. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com
14 CFR 417.207 - Trajectory analysis.
Code of Federal Regulations, 2011 CFR
2011-01-01
... after lift-off, the limits of a launch vehicle's normal flight, as defined by the nominal trajectory and... straight-up trajectory for any time after lift-off until the straight-up time that would result if the...
14 CFR 417.207 - Trajectory analysis.
Code of Federal Regulations, 2010 CFR
2010-01-01
... after lift-off, the limits of a launch vehicle's normal flight, as defined by the nominal trajectory and... straight-up trajectory for any time after lift-off until the straight-up time that would result if the...
Yadav, Rajeev; Lu, H Peter
2018-03-28
The N-methyl-d-aspartate (NMDA) receptor ion-channel is activated by the binding of ligands, along with the application of action potential, important for synaptic transmission and memory functions. Despite substantial knowledge of the structure and function, the gating mechanism of the NMDA receptor ion channel for electric on-off signals is still a topic of debate. We investigate the NMDA receptor partition distribution and the associated channel's open-close electric signal trajectories using a combined approach of correlating single-molecule fluorescence photo-bleaching, single-molecule super-resolution imaging, and single-channel electric patch-clamp recording. Identifying the compositions of NMDA receptors, their spatial organization and distributions over live cell membranes, we observe that NMDA receptors are organized inhomogeneously: nearly half of the receptor proteins are individually dispersed; whereas others exist in heterogeneous clusters of around 50 nm in size as well as co-localized within the diffraction limited imaging area. We demonstrate that inhomogeneous interactions and partitions of the NMDA receptors can be a cause of the heterogeneous gating mechanism of NMDA receptors in living cells. Furthermore, comparing the imaging results with the ion-channel electric current recording, we propose that the clustered NMDA receptors may be responsible for the variation in the current amplitude observed in the on-off two-state ion-channel electric signal trajectories. Our findings shed new light on the fundamental structure-function mechanism of NMDA receptors and present a conceptual advancement of the ion-channel mechanism in living cells.
Trajectories of the healthy ageing phenotype among middle-aged and older Britons, 2004-2013.
Tampubolon, Gindo
2016-06-01
Since the ageing population demands a response to ensure older people remain healthy and active, we studied the dynamics of a recently proposed healthy ageing phenotype. We drew the phenotype's trajectories and tested whether their levels and rates of change are influenced by health behaviours, comorbidities and socioeconomic positions earlier in the life course. The English Longitudinal Ageing Study, a prospective, nationally representative sample of people aged ≥50 years, measured a set of eight biomarkers which make up the outcome of the healthy ageing phenotype three times over nearly a decade (N2004=5009, N2008=5301, N2013=4455). A cluster of health behaviours, comorbidities and socioeconomic positions were also measured repeatedly. We assessed the phenotype's distribution non-parametrically, then fitted linear mixed models to phenotypic change and further examined time interactions with gender and socioeconomic position. We ran additional analyses to test robustness. Women had a wider distribution of the healthy ageing phenotype than men had. The phenotype declined annually by -0.242 (95% confidence interval [CI]: -0.352, -0.131). However, there was considerable heterogeneity in the levels and rates of phenotypic change. Women started at higher levels, then declined more steeply by -0.293 (CI: -0.403, -0.183) annually, leading to crossover in the trajectories. Smoking and physical activity assessed on the Allied Dunbar scale were strongly associated with the trajectories. Though marked by secular decline, the trajectories of the healthy ageing phenotype showed distinct socioeconomic gradients. The trajectories were also susceptible to variations in health behaviours, strengthening the case for serial interventions to attain healthy and active ageing. Copyright © 2016 The Author. Published by Elsevier Ireland Ltd.. All rights reserved.
Detecting New Pedestrian Facilities from VGI Data Sources
NASA Astrophysics Data System (ADS)
Zhong, S.; Xie, Z.
2017-12-01
Pedestrian facility (e.g. footbridge, pedestrian crossing and underground passage) information is an important basic data of location based service (LBS) for pedestrians. However, timely updating pedestrian facility information challenges due to facilities change frequently. Previous pedestrian facility information collecting and updating tasks are mainly completed by highly trained specialized persons. However, this conventional approach has several disadvantages such as high cost, long update cycle and so on. Volunteered Geographic Information (VGI) has proven efficiency to provide new, free and fast growing spatial data. Pedestrian trajectory, which can be seen as measurements of real pedestrian road, is one of the most valuable information of VGI data. Although the accuracy of the trajectories is not too high, due to the large number of measurements, an improvement of quality of the road information can be achieved. Thus, we develop a method for detecting new pedestrian facilities based on the current road network and pedestrian trajectories. Specifically, 1) by analyzing speed, distance and direction, those outliers of pedestrian trajectories are removed, 2) a road network matching algorithm is developed for eliminating redundant trajectories, and 3) a space-time cluster algorithm is adopted for detecting new walking facilities. The performance of the method is evaluated with a series of experiments conducted on a part of the road network of Heifei and a large number of real pedestrian trajectories, and verified the results by using Tencent Street map. The results show that the proposed method is able to detecting new pedestrian facilities from VGI data accurately. We believe that the proposed method provides an alternative way for general road data acquisition, and can improve the quality of LBS for pedestrians.
Survey of optimization techniques for nonlinear spacecraft trajectory searches
NASA Technical Reports Server (NTRS)
Wang, Tseng-Chan; Stanford, Richard H.; Sunseri, Richard F.; Breckheimer, Peter J.
1988-01-01
Mathematical analysis of the optimal search of a nonlinear spacecraft trajectory to arrive at a set of desired targets is presented. A high precision integrated trajectory program and several optimization software libraries are used to search for a converged nonlinear spacecraft trajectory. Several examples for the Galileo Jupiter Orbiter and the Ocean Topography Experiment (TOPEX) are presented that illustrate a variety of the optimization methods used in nonlinear spacecraft trajectory searches.
Failure detection in high-performance clusters and computers using chaotic map computations
Rao, Nageswara S.
2015-09-01
A programmable media includes a processing unit capable of independent operation in a machine that is capable of executing 10.sup.18 floating point operations per second. The processing unit is in communication with a memory element and an interconnect that couples computing nodes. The programmable media includes a logical unit configured to execute arithmetic functions, comparative functions, and/or logical functions. The processing unit is configured to detect computing component failures, memory element failures and/or interconnect failures by executing programming threads that generate one or more chaotic map trajectories. The central processing unit or graphical processing unit is configured to detect a computing component failure, memory element failure and/or an interconnect failure through an automated comparison of signal trajectories generated by the chaotic maps.
Monte Carlo Analysis as a Trajectory Design Driver for the TESS Mission
NASA Technical Reports Server (NTRS)
Nickel, Craig; Lebois, Ryan; Lutz, Stephen; Dichmann, Donald; Parker, Joel
2016-01-01
The Transiting Exoplanet Survey Satellite (TESS) will be injected into a highly eccentric Earth orbit and fly 3.5 phasing loops followed by a lunar flyby to enter a mission orbit with lunar 2:1 resonance. Through the phasing loops and mission orbit, the trajectory is significantly affected by lunar and solar gravity. We have developed a trajectory design to achieve the mission orbit and meet mission constraints, including eclipse avoidance and a 30-year geostationary orbit avoidance requirement. A parallelized Monte Carlo simulation was performed to validate the trajectory after injecting common perturbations, including launch dispersions, orbit determination errors, and maneuver execution errors. The Monte Carlo analysis helped identify mission risks and is used in the trajectory selection process.
Gribble, Matthew O.; Bartell, Scott M.; Kannan, Kurunthachalam; Wu, Qian; Fair, Patricia A.; Kamen, Diane L.
2015-01-01
Background Charleston Harbor has elevated concentrations of PFAS in dolphins, but local human exposure data are limited. Objectives We sought to describe PFAS serum concentrations’ temporal trends among Gullah African American residents of coastal South Carolina. Methods Longitudinal measures of PFAS in blood serum from a Gullah clinical sample, without lupus, were examined using spaghetti plots and visit-to-visit change scores (e.g., differences in concentrations between visits) among the 68 participants with repeated measures available. We also modeled population-level trends among the 71 participants with any data using proportionate percentile models, accounting for clustering through robust standard errors. In a post-hoc analysis we examined heterogeneity of temporal trends by age through mixed-effects models for the log-transformed PFAS compounds. Results Population concentrations of PFOS dropped approximately 9 (95% CI: 8, 10) percent each year over 2003–2013. This was concordant with individual PFOS trajectories (median PFOS change score −21.7 ng/g wet weight, interquartile range of PFOS change scores: −32.8, −14.9) and reports for other populations over this time period. Several other compounds including PFOA, PFHxS, and PFuNDA also showed a population-level decrease. However, examination of individual trajectories suggested substantial heterogeneity. Post-hoc analyses indicated that PFAS trajectories were heterogeneous by age. Conclusions Many PFAS compounds are decreasing in a sample of Gullah African Americans from coastal South Carolina. There may be age differences in the elimination kinetics of PFASs. The possible role of age as a modifier of PFAS serum trends merits further research. PMID:25819541
Lima Passos, Valéria; Klijn, Sven; van Zandvoort, Kevin; Abidi, Latifa; Lemmens, Paul
2017-04-01
The cardio-protective effect of alcohol has been the subject of a long-standing scientific controversy. Emerging evidence remains equivocal, as the validity of the dose-dependent J-shape association is tainted by conceptual, theoretical and methodological problems. A major impediment for a resolution on the matter is the lack of a life-long developmental approach to pinpoint alcohol's specific impact on the risk for cardio-vascular events (CVE). Using retrospective and prospective individual-level data of alcohol consumption (AC) we applied a model-based clustering technique to uncover life-course trajectories of AC and explored their links to CVE. Data stemmed from a random sub-cohort of a large-scale, longitudinal study conducted in the Netherlands (N=2288). Group Based Trajectory Model (GBTM) was applied to extract distinct progressions of AC over time. Stratified by sex, the association between the developmental trajectories and CVE was examined with multiple logistic regression models, with adjustment for traditional risk factors. GBTM analysis laid bare the heterogeneity of AC dynamics over the life-course, reiterating sex differences in drinking habits and CVE risk. AC temporal behaviors during adolescence and adulthood were diverse, but showed relative stability in in middle-age and elderly years. For males, adjusted odds for CVE differed among the uncovered developmental classes. The findings elicited supportive evidence for a J-shape, but with a new twist. Besides moderation the results indicate that onset, timing, duration and stability of AC over the life-course are major aspects to be accounted for when attempting to elucidate alcohol's cardio-vascular role. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Chambers, S. D.; Choi, T.; Park, S.-J.; Williams, A. G.; Hong, S.-B.; Tositti, L.; Griffiths, A. D.; Crawford, J.; Pereira, E.
2017-12-01
We report on the first summer of high-sensitivity radon measurements from a two-filter detector at Jang Bogo Station (Terra Nova Bay) and contrast them with simultaneous observations at King Sejong Station (King George Island). King Sejong radon concentrations were characteristic of a marine baseline station (0.02-0.3 Bq m-3), whereas Jang Bogo values were highly variable (0.06-5.2 Bq m-3), mainly due to emissions from exposed coastal ground (estimated mean flux 0.09-0.11 atoms cm-2 s-1) and shallow atmospheric mixing depths. For wind speeds of ≤3.5 m s-1 the influence of local radon emissions became increasingly more prominent at both sites. A cluster analysis of back trajectories from King Sejong (62°S) revealed a fairly even distribution between air masses that had passed recently over South America, the Southern Ocean, and Antarctica, whereas at Jang Bogo (75°S) 80% of events had recently passed over the Ross Ice Shelf and West Antarctica, 12% were synoptically forced over Cape Adare, and 8% were associated with subsidence over the Antarctic interior and katabatic flow to the station. When cross-checked against radon concentrations, only half of the back trajectories ending at Jang Bogo that had indicated distant contact with nonpolar southern hemisphere continents within the past 10 days showed actual signs of terrestrial influence. A simple-to-implement technique based on high-pass filtered absolute humidity is developed to distinguish between predominantly katabatic, oceanic, and near-coastal air masses for characterization of trace gas and aerosol measurements at coastal East Antarctic sites.
Online Calibration of the TPC Drift Time in the ALICE High Level Trigger
NASA Astrophysics Data System (ADS)
Rohr, David; Krzewicki, Mikolaj; Zampolli, Chiara; Wiechula, Jens; Gorbunov, Sergey; Chauvin, Alex; Vorobyev, Ivan; Weber, Steffen; Schweda, Kai; Lindenstruth, Volker
2017-06-01
A Large Ion Collider Experiment (ALICE) is one of the four major experiments at the Large Hadron Collider (LHC) at CERN. The high level trigger (HLT) is a compute cluster, which reconstructs collisions as recorded by the ALICE detector in real-time. It employs a custom online data-transport framework to distribute data and workload among the compute nodes. ALICE employs subdetectors that are sensitive to environmental conditions such as pressure and temperature, e.g., the time projection chamber (TPC). A precise reconstruction of particle trajectories requires calibration of these detectors. Performing calibration in real time in the HLT improves the online reconstructions and renders certain offline calibration steps obsolete speeding up offline physics analysis. For LHC Run 3, starting in 2020 when data reduction will rely on reconstructed data, online calibration becomes a necessity. Reconstructed particle trajectories build the basis for the calibration making a fast online-tracking mandatory. The main detectors used for this purpose are the TPC and Inner Tracking System. Reconstructing the trajectories in the TPC is the most compute-intense step. We present several improvements to the ALICE HLT developed to facilitate online calibration. The main new development for online calibration is a wrapper that can run ALICE offline analysis and calibration tasks inside the HLT. In addition, we have added asynchronous processing capabilities to support long-running calibration tasks in the HLT framework, which runs event-synchronously otherwise. In order to improve the resiliency, an isolated process performs the asynchronous operations such that even a fatal error does not disturb data taking. We have complemented the original loop-free HLT chain with ZeroMQ data-transfer components. The ZeroMQ components facilitate a feedback loop that inserts the calibration result created at the end of the chain back into tracking components at the beginning of the chain, after a short delay. All these new features are implemented in a general way, such that they have use-cases aside from online calibration. In order to gather sufficient statistics for the calibration, the asynchronous calibration component must process enough events per time interval. Since the calibration is valid only for a certain time period, the delay until the feedback loop provides updated calibration data must not be too long. A first full-scale test of the online calibration functionality was performed during 2015 heavy-ion run under real conditions. Since then, online calibration is enabled and benchmarked in 2016 proton-proton data taking. We present a timing analysis of this first online-calibration test, which concludes that the HLT is capable of online TPC drift time calibration fast enough to calibrate the tracking via the feedback loop. We compare the calibration results with the offline calibration and present a comparison of the residuals of the TPC cluster coordinates with respect to offline reconstruction.
Quantifying ataxia: ideal trajectory analysis--a technical note
NASA Technical Reports Server (NTRS)
McPartland, M. D.; Krebs, D. E.; Wall, C. 3rd
2000-01-01
We describe a quantitative method to assess repeated stair stepping stability. In both the mediolateral (ML) and anterioposterior (AP) directions, the trajectory of the subject's center of mass (COM) was compared to an ideal sinusoid. The two identified sinusoids were unique in each direction but coupled. Two dimensionless numbers-the mediolateral instability index (IML) and AP instability index (IAP)-were calculated using the COM trajectory and ideal sinusoids for each subject with larger index values resulting from less stable performance. The COM trajectories of nine nonimpaired controls and six patients diagnosed with unilateral or bilateral vestibular labyrinth hypofunction were analyzed. The average IML and IAP values of labyrinth disorder patients were respectively 127% and 119% greater than those of controls (p<0.014 and 0.006, respectively), indicating that the ideal trajectory analysis distinguishes persons with labyrinth disorder from those without. The COM trajectories also identify movement inefficiencies attributable to vestibulopathy.
NASA Astrophysics Data System (ADS)
Piras, Paolo; Torromeo, Concetta; Re, Federica; Evangelista, Antonietta; Gabriele, Stefano; Esposito, Giuseppe; Nardinocchi, Paola; Teresi, Luciano; Madeo, Andrea; Chialastri, Claudia; Schiariti, Michele; Varano, Valerio; Uguccioni, Massimo; Puddu, Paolo E.
2016-10-01
The analysis of full Left Atrium (LA) deformation and whole LA deformational trajectory in time has been poorly investigated and, to the best of our knowledge, seldom discussed in patients with Hypertrophic Cardiomyopathy. Therefore, we considered 22 patients with Hypertrophic Cardiomyopathy (HCM) and 46 healthy subjects, investigated them by three-dimensional Speckle Tracking Echocardiography, and studied the derived landmark clouds via Geometric Morphometrics with Parallel Transport. Trajectory shape and trajectory size were different in Controls versus HCM and their classification powers had high AUC (Area Under the Receiving Operator Characteristic Curve) and accuracy. The two trajectories were much different at the transition between LA conduit and booster pump functions. Full shape and deformation analyses with trajectory analysis enabled a straightforward perception of pathophysiological consequences of HCM condition on LA functioning. It might be worthwhile to apply these techniques to look for novel pathophysiological approaches that may better define atrio-ventricular interaction.
Direct Method Transcription for a Human-Class Translunar Injection Trajectory Optimization
NASA Technical Reports Server (NTRS)
Witzberger, Kevin E.; Zeiler, Tom
2012-01-01
This paper presents a new trajectory optimization software package developed in the framework of a low-to-high fidelity 3 degrees-of-freedom (DOF)/6-DOF vehicle simulation program named Mission Analysis Simulation Tool in Fortran (MASTIF) and its application to a translunar trajectory optimization problem. The functionality of the developed optimization package is implemented as a new "mode" in generalized settings to make it applicable for a general trajectory optimization problem. In doing so, a direct optimization method using collocation is employed for solving the problem. Trajectory optimization problems in MASTIF are transcribed to a constrained nonlinear programming (NLP) problem and solved with SNOPT, a commercially available NLP solver. A detailed description of the optimization software developed is provided as well as the transcription specifics for the translunar injection (TLI) problem. The analysis includes a 3-DOF trajectory TLI optimization and a 3-DOF vehicle TLI simulation using closed-loop guidance.
NASA Astrophysics Data System (ADS)
Tarasova, O. A.; Staehelin, J.; Prevot, A. S.; Senik, I. A.; Sosonkin, M. G.; Cui, J.
2007-12-01
Analysis of the long-term surface ozone records of two mountain sites, namely Kislovodsk High Mountain Station (KHMS) in Caucasus, Russia (43.7°N, 42.7°E, 2070 asl.) and Jungfraujoch (JFJ) in Switzerland (46.5°N, 7.9°E, 3580m asl) will be presented. A strong increase in ozone concentration (up +0.46±0.11ppb/year) was found at JFJ while ozone significantly deceased at KHMS (-0.65 ±0.09 ppb/year) during 1990-2005. We will compare trends values for earlier years (1990-2001) and for the latter ones (1993-2005). Among the possible reasons of the trends difference the impact of atmospheric transport is studied. Both vertical and horizontal components are considered in connection with ozone concentration trends. Transport analysis is based on 3D trajectories using LAGRANTO. There was no substantial difference in trends detected for different PV-levels or PBL filtered cases, while the main difference has been found in the source areas of the air masses at the two locations and inside different advection sectors at the each particular site. Trends will be compared (for the two receptor sites and two periods) for filtered subsets of upper tropospheric/stratospheric cases (based on PV and trajectory altitude), cases impacted by Planetary Boundary Layer (based on PBL height) and in different horizontal advection clusters. The work is financially supported by the Swiss National Science Foundation (JRP IB7320-110831), European Commission (Marie-Curie IIF project N 039905 - FP6-2005-Mobility-7) and Russian Foundation for Basic Research (projects 06-05-64427 and 06-05-65308) and contributes to ACCENT T&TP project.
High Speed Solution of Spacecraft Trajectory Problems Using Taylor Series Integration
NASA Technical Reports Server (NTRS)
Scott, James R.; Martini, Michael C.
2008-01-01
Taylor series integration is implemented in a spacecraft trajectory analysis code-the Spacecraft N-body Analysis Program (SNAP) - and compared with the code s existing eighth-order Runge-Kutta Fehlberg time integration scheme. Nine trajectory problems, including near Earth, lunar, Mars and Europa missions, are analyzed. Head-to-head comparison at five different error tolerances shows that, on average, Taylor series is faster than Runge-Kutta Fehlberg by a factor of 15.8. Results further show that Taylor series has superior convergence properties. Taylor series integration proves that it can provide rapid, highly accurate solutions to spacecraft trajectory problems.
A Smoluchowski model of crystallization dynamics of small colloidal clusters
NASA Astrophysics Data System (ADS)
Beltran-Villegas, Daniel J.; Sehgal, Ray M.; Maroudas, Dimitrios; Ford, David M.; Bevan, Michael A.
2011-10-01
We investigate the dynamics of colloidal crystallization in a 32-particle system at a fixed value of interparticle depletion attraction that produces coexisting fluid and solid phases. Free energy landscapes (FELs) and diffusivity landscapes (DLs) are obtained as coefficients of 1D Smoluchowski equations using as order parameters either the radius of gyration or the average crystallinity. FELs and DLs are estimated by fitting the Smoluchowski equations to Brownian dynamics (BD) simulations using either linear fits to locally initiated trajectories or global fits to unbiased trajectories using Bayesian inference. The resulting FELs are compared to Monte Carlo Umbrella Sampling results. The accuracy of the FELs and DLs for modeling colloidal crystallization dynamics is evaluated by comparing mean first-passage times from BD simulations with analytical predictions using the FEL and DL models. While the 1D models accurately capture dynamics near the free energy minimum fluid and crystal configurations, predictions near the transition region are not quantitatively accurate. A preliminary investigation of ensemble averaged 2D order parameter trajectories suggests that 2D models are required to capture crystallization dynamics in the transition region.
Space shuttle booster multi-engine base flow analysis
NASA Technical Reports Server (NTRS)
Tang, H. H.; Gardiner, C. R.; Anderson, W. A.; Navickas, J.
1972-01-01
A comprehensive review of currently available techniques pertinent to several prominent aspects of the base thermal problem of the space shuttle booster is given along with a brief review of experimental results. A tractable engineering analysis, capable of predicting the power-on base pressure, base heating, and other base thermal environmental conditions, such as base gas temperature, is presented and used for an analysis of various space shuttle booster configurations. The analysis consists of a rational combination of theoretical treatments of the prominent flow interaction phenomena in the base region. These theories consider jet mixing, plume flow, axisymmetric flow effects, base injection, recirculating flow dynamics, and various modes of heat transfer. Such effects as initial boundary layer expansion at the nozzle lip, reattachment, recompression, choked vent flow, and nonisoenergetic mixing processes are included in the analysis. A unified method was developed and programmed to numerically obtain compatible solutions for the various flow field components in both flight and ground test conditions. Preliminary prediction for a 12-engine space shuttle booster base thermal environment was obtained for a typical trajectory history. Theoretical predictions were also obtained for some clustered-engine experimental conditions. Results indicate good agreement between the data and theoretical predicitons.
BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data
Hospital, Adam; Andrio, Pau; Cugnasco, Cesare; Codo, Laia; Becerra, Yolanda; Dans, Pablo D.; Battistini, Federica; Torres, Jordi; Goñi, Ramón; Orozco, Modesto; Gelpí, Josep Ll.
2016-01-01
Molecular dynamics simulation (MD) is, just behind genomics, the bioinformatics tool that generates the largest amounts of data, and that is using the largest amount of CPU time in supercomputing centres. MD trajectories are obtained after months of calculations, analysed in situ, and in practice forgotten. Several projects to generate stable trajectory databases have been developed for proteins, but no equivalence exists in the nucleic acids world. We present here a novel database system to store MD trajectories and analyses of nucleic acids. The initial data set available consists mainly of the benchmark of the new molecular dynamics force-field, parmBSC1. It contains 156 simulations, with over 120 μs of total simulation time. A deposition protocol is available to accept the submission of new trajectory data. The database is based on the combination of two NoSQL engines, Cassandra for storing trajectories and MongoDB to store analysis results and simulation metadata. The analyses available include backbone geometries, helical analysis, NMR observables and a variety of mechanical analyses. Individual trajectories and combined meta-trajectories can be downloaded from the portal. The system is accessible through http://mmb.irbbarcelona.org/BIGNASim/. Supplementary Material is also available on-line at http://mmb.irbbarcelona.org/BIGNASim/SuppMaterial/. PMID:26612862
Heidari, Zahra; Roe, Daniel R; Galindo-Murillo, Rodrigo; Ghasemi, Jahan B; Cheatham, Thomas E
2016-07-25
Long time scale molecular dynamics (MD) simulations of biological systems are becoming increasingly commonplace due to the availability of both large-scale computational resources and significant advances in the underlying simulation methodologies. Therefore, it is useful to investigate and develop data mining and analysis techniques to quickly and efficiently extract the biologically relevant information from the incredible amount of generated data. Wavelet analysis (WA) is a technique that can quickly reveal significant motions during an MD simulation. Here, the application of WA on well-converged long time scale (tens of μs) simulations of a DNA helix is described. We show how WA combined with a simple clustering method can be used to identify both the physical and temporal locations of events with significant motion in MD trajectories. We also show that WA can not only distinguish and quantify the locations and time scales of significant motions, but by changing the maximum time scale of WA a more complete characterization of these motions can be obtained. This allows motions of different time scales to be identified or ignored as desired.
CFD Analysis of Swing of Cricket Ball and Trajectory Prediction
NASA Astrophysics Data System (ADS)
G, Jithin; Tom, Josin; Ruishikesh, Kamat; Jose, Jyothish; Kumar, Sanjay
2013-11-01
This work aims to understand the aerodynamics associated with the flight and swing of a cricket ball and predict its flight trajectory over the course of the game: at start (smooth ball) and as the game progresses (rough ball). Asymmetric airflow over the ball due to seam orientation and surface roughness can cause flight deviation (swing). The values of Drag, Lift and Side forces which are crucial for determining the trajectory of the ball were found with the help of FLUENT using the standard K- ɛ model. Analysis was done to study how the ball velocity, spin imparted to be ball and the tilt of the seam affects the movement of the ball through air. The governing force balance equations in 3 dimensions in combination a MATLAB code which used Heun's method was used for obtaining the trajectory of the ball. The conditions for the conventional swing and reverse swing to occur were deduced from the analysis and found to be in alignment with the real life situation. Critical seam angle for maximum swing and transition speed for normal to reverse swing were found out. The obtained trajectories were compared to real life hawk eye trajectories for validation. The analysis results were in good agreement with the real life situation.
Two-year trajectory of fall risk in people with Parkinson’s disease: a latent class analysis
Paul, Serene S; Thackeray, Anne; Duncan, Ryan P; Cavanaugh, James T; Ellis, Theresa D; Earhart, Gammon M; Ford, Matthew P; Foreman, K Bo; Dibble, Leland E
2015-01-01
Objective To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson’s disease (PD). Design Latent class analysis, specifically growth mixture modeling (GMM) of longitudinal fall risk trajectories. Setting Not applicable. Participants 230 community-dwelling PD participants of a longitudinal cohort study who attended at least two of five assessments over a two year period. Interventions Not applicable. Main Outcome Measures Fall risk trajectory (low, medium or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6-monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. Results The GMM optimally grouped participants into three fall risk trajectories that closely mirrored baseline fall risk status (p=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium risk trajectories (p<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. Conclusions Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over two years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD. PMID:26606871
The effects of cation–anion clustering on defect migration in MgAl 2O 4
Zamora, Richard J.; Voter, Arthur F.; Perez, Danny; ...
2016-06-28
Magnesium aluminate spinel (MgAl 2O 4), like many other ceramic materials, offers a range of technological applications, from nuclear reactor materials to military body armor. For many of these applications, it is critical to understand both the formation and evolution of lattice defects throughout the lifetime of the material. We use the Speculatively Parallel Temperature Accelerated Dynamics (SpecTAD) method to investigate the effects of di-vacancy and di-interstitial formation on the mobility of the component defects. From long-time trajectories of the state-to-state dynamics, we characterize the migration pathways of defect clusters, and calculate their self-diffusion constants across a range of temperatures.more » We find that the clustering of Al and O vacancies drastically reduces the mobility of both defects, while the clustering of Mg and O vacancies completely immobilizes them. For interstitials, we find that the clustering of Mg and O defects greatly reduces O interstitial mobility, but has only a weak effect on Mg. Lastly, these findings illuminate important new details regarding defect kinetics relevant to the application of MgAl 2O 4 in extreme environments.« less
The persistent clustering of adult body mass index by school attended in adolescence.
Evans, Clare Rosenfeld; Lippert, Adam M; Subramanian, S V
2016-03-01
It is well known that adolescent body mass index (BMI) shows school-level clustering. We explore whether school-level clustering of BMI persists into adulthood. Multilevel models nesting young adults in schools they attended as adolescents are fit for 3 outcomes: adolescent BMI, self-report adult BMI and measured adult BMI. Sex-stratified and race/ethnicity-stratified (black, Hispanic, white, other) analyses were also conducted. School-level clustering (wave 1 intraclass correlation coefficient (ICC)=1.3%) persists over time (wave 4 ICC=2%), and results are comparable across stratified analyses of both sexes and all racial/ethnic groups (except for Hispanics when measured BMIs are used). Controlling for BMI in adolescence partially attenuates this effect. School-level clustering of BMI persists into young adulthood. Possible explanations include the salience of school environments in establishing behaviours and trajectories, the selection of adult social networks that resemble adolescent networks and reinforce previous behaviours, and characteristics of school catchment areas associated with BMI. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/
Yang, Huan; Goudeli, Eirini; Hogan, Christopher J.
2018-04-24
In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-Molecular Dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients; we use this approach to examine atomic condensation onto 6-56 atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity ( v) between atom and cluster andmore » the initial impact parameter ( b). In all cases there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms, and for 14 atom and 28 atom Mg clusters, as cluster equilibration temperature increases the condensation rate coefficient drops to values below the hard sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (> 1000 m s -1) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). In conclusion, the presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.« less
Yang, Huan; Goudeli, Eirini; Hogan, Christopher J
2018-04-28
In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard-sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-molecular dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients. We use this approach to examine atomic condensation onto 6-56-atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity (v) between atom and cluster and the initial impact parameter (b). In all cases, there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard-sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms and for 14- and 28-atom Mg clusters, as cluster equilibration temperature increases, the condensation rate coefficient drops to values below the hard-sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (>1000 m s -1 ) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). The presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Huan; Goudeli, Eirini; Hogan, Christopher J.
In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-Molecular Dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients; we use this approach to examine atomic condensation onto 6-56 atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity ( v) between atom and cluster andmore » the initial impact parameter ( b). In all cases there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms, and for 14 atom and 28 atom Mg clusters, as cluster equilibration temperature increases the condensation rate coefficient drops to values below the hard sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (> 1000 m s -1) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). In conclusion, the presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.« less
NASA Astrophysics Data System (ADS)
Yang, Huan; Goudeli, Eirini; Hogan, Christopher J.
2018-04-01
In gas phase synthesis systems, clusters form and grow via condensation, in which a monomer binds to an existing cluster. While a hard-sphere equation is frequently used to predict the condensation rate coefficient, this equation neglects the influences of potential interactions and cluster internal energy on the condensation process. Here, we present a collision rate theory-molecular dynamics simulation approach to calculate condensation probabilities and condensation rate coefficients. We use this approach to examine atomic condensation onto 6-56-atom Au and Mg clusters. The probability of condensation depends upon the initial relative velocity (v) between atom and cluster and the initial impact parameter (b). In all cases, there is a well-defined region of b-v space where condensation is highly probable, and outside of which the condensation probability drops to zero. For Au clusters with more than 10 atoms, we find that at gas temperatures in the 300-1200 K range, the condensation rate coefficient exceeds the hard-sphere rate coefficient by a factor of 1.5-2.0. Conversely, for Au clusters with 10 or fewer atoms and for 14- and 28-atom Mg clusters, as cluster equilibration temperature increases, the condensation rate coefficient drops to values below the hard-sphere rate coefficient. Calculations also yield the self-dissociation rate coefficient, which is found to vary considerably with gas temperature. Finally, calculations results reveal that grazing (high b) atom-cluster collisions at elevated velocity (>1000 m s-1) can result in the colliding atom rebounding (bounce) from the cluster surface or binding while another atom dissociates (replacement). The presented method can be applied in developing rate equations to predict material formation and growth rates in vapor phase systems.
Galatzer-Levy, Isaac R.; Ankri, Yael; Freedman, Sara; Israeli-Shalev, Yossi; Roitman, Pablo; Gilad, Moran; Shalev, Arieh Y.
2013-01-01
Context Uncovering heterogeneities in the progression of early PTSD symptoms can improve our understanding of the disorder's pathogenesis and prophylaxis. Objectives To describe discrete symptom trajectories and examine their relevance for preventive interventions. Design Latent Growth Mixture Modeling (LGMM) of data from a randomized controlled study of early treatment. LGMM identifies latent longitudinal trajectories by exploring discrete mixture distributions underlying observable data. Setting Hadassah Hospital unselectively receives trauma survivors from Jerusalem and vicinity. Participants Adult survivors of potentially traumatic events consecutively admitted to the hospital's emergency department (ED) were assessed ten days and one-, five-, nine- and fifteen months after ED admission. Participants with data at ten days and at least two additional assessments (n = 957) were included; 125 received cognitive behavioral therapy (CBT) between one and nine months. Approach We used LGMM to identify latent parameters of symptom progression and tested the effect of CBT on these parameters. CBT consisted of 12 weekly sessions of either cognitive therapy (n = 41) or prolonged exposure (PE, n = 49), starting 29.8±5.7 days after ED admission, or delayed PE (n = 35) starting at 151.8±42.4 days. CBT effectively reduced PTSD symptoms in the entire sample. Main Outcome Measure Latent trajectories of PTSD symptoms; effects of CBT on these trajectories. Results Three trajectories were identified: Rapid Remitting (rapid decrease in symptoms from 1- to 5-months; 56% of the sample), Slow Remitting (progressive decrease in symptoms over 15 months; 27%) and Non-Remitting (persistently elevated symptoms; 17%). CBT accelerated the recovery of the Slow Remitting class but did not affect the other classes. Conclusions The early course of PTSD symptoms is characterized by distinct and diverging response patterns that are centrally relevant to understanding the disorder and preventing its occurrence. Studies of the pathogenesis of PTSD may benefit from using clustered symptom trajectories as their dependent variables. PMID:23990895
Enhanced Trajectory Based Similarity Prediction with Uncertainty Quantification
2014-10-02
challenge by obtaining the highest score by using a data-driven prognostics method to predict the RUL of a turbofan engine (Saxena & Goebel, PHM08...process for multi-regime health assessment. To illustrate multi-regime partitioning, the “ Turbofan Engine Degradation simulation” data set from...hence the name k- means. Figure 3 shows the results of the k-means clustering algorithm on the “ Turbofan Engine Degradation simulation” data set. As
Gruebner, Oliver; Lowe, Sarah R; Tracy, Melissa; Cerdá, Magdalena; Joshi, Spruha; Norris, Fran H; Galea, Sandro
2016-04-01
To demonstrate a spatial epidemiologic approach that could be used in the aftermath of disasters to (1) detect spatial clusters and (2) explore geographic heterogeneity in predictors for mental health and general wellness. We used a cohort study of Hurricane Ike survivors (n=508) to assess the spatial distribution of postdisaster mental health wellness (most likely resilience trajectory for posttraumatic stress symptoms [PTSS] and depression) and general wellness (most likely resilience trajectory for PTSS, depression, functional impairment, and days of poor health) in Galveston, Texas. We applied the spatial scan statistic (SaTScan) and geographically weighted regression. We found spatial clusters of high likelihood wellness in areas north of Texas City and spatial concentrations of low likelihood wellness in Galveston Island. Geographic variation was found in predictors of wellness, showing increasing associations with both forms of wellness the closer respondents were located to Galveston City in Galveston Island. Predictors for postdisaster wellness may manifest differently across geographic space with concentrations of lower likelihood wellness and increased associations with predictors in areas of higher exposure. Our approach could be used to inform geographically targeted interventions to promote mental health and general wellness in disaster-affected communities.
Tay, A K; Jayasuriya, R; Jayasuriya, D; Silove, D
2017-01-01
We conducted a 12-month follow-up of a population sample of adults from districts (Mannar, Killinochi, Mullaitivu and Jaffna) exposed to high levels of mass conflict in Sri Lanka, the aim of the present analysis being to identify trajectories of depression and anxiety symptoms and their associations with exposure to psychological trauma and ongoing living adversities. The cohort of 1275 adults (response 86%) followed-up in 2015 was a structured subsample drawn from the baseline nationally representative survey conducted in 2014 across 25 districts in Sri Lanka. Interviews were conducted using electronic tablets by field workers applying contextually adapted indices of trauma exposure, ongoing adversities and symptoms of depression and anxiety. Latent transition analysis revealed a three-class longitudinal model from which four composite trajectories were derived, comprising a persistent symptom trajectory (n=555, 43.5%), an incident or new onset trajectory (n=170, 13.3%), a recovery trajectory (n=299, 23.5%) and a persistently low-symptom trajectory (n=251, 19.7%). Factors associated with both the persistent symptom and incident trajectories were female gender, past trauma exposure and lack of access to health services. Loss of a job was uniquely associated with the persisting trajectory at follow-up. The recovery trajectory comprised a higher proportion of men, older persons and those without risk factors. Our findings assist in translating epidemiologic data into public policy and practice by indicating the importance of stable employment and the provision of healthcare as key factors that may act to reduce anxiety and depressive symptoms in the post-conflict phase. The findings also confirm that women are at high risk of mental distress. Brief screening for trauma exposure in populations with high levels of exposure to mass conflict may assist in defining those at risk of ongoing symptoms of anxiety and depression. PMID:28786977
ERIC Educational Resources Information Center
Hardonk, Stefan; Desnerck, Greetje; Loots, Gerrit; Van Hove, Geert; Van Kerschaver, Erwin; Sigurjonsdottir, Hanna Bjorg; Vanroelen, Christophe; Louckx, Fred
2011-01-01
The objective of this study is to examine the early care trajectories of congenitally deaf children from a parental perspective, starting with universal neonatal hearing screenings. The analysis using a three-dimensional care trajectory concept is aimed at developing a basic typology of postscreening care trajectories. Children with…
NASA Astrophysics Data System (ADS)
Xie, Lingwang; Zhang, Xingwei; Luo, Pan; Huang, Panpan
2017-10-01
The optimization designs and dynamic analysis on the driving mechanism of flapping-wing air vehicles on base of flapping trajectory patterns is carried out in this study. Three different driving mechanisms which are spatial double crank-rocker, plane five-bar and gear-double slider, are systematically optimized and analysed by using the Mat lab and Adams software. After a series debugging on the parameter, the comparatively ideal flapping trajectories are obtained by the simulation of Adams. Present results indicate that different drive mechanisms output different flapping trajectories and have their unique characteristic. The spatial double crank-rocker mechanism can only output the arc flapping trajectory and it has the advantages of small volume, high flexibility and efficient space utilization. Both planar five-bar mechanism and gear-double slider mechanism can output the oval, figure of eight and double eight flapping trajectories. Nevertheless, the gear-double slider mechanism has the advantage of convenient parameter setting and better performance in output double eight flapping trajectory. This study can provide theoretical basis and helpful reference for the design of the drive mechanisms of flapping-wing air vehicles with different output flapping trajectories.
Trajectory Design Considerations for Exploration Mission 1
NASA Technical Reports Server (NTRS)
Dawn, Timothy F.; Gutkowski, Jeffrey P.; Batcha, Amelia L.; Williams, Jacob; Pedrotty, Samuel M.
2018-01-01
Exploration Mission 1 (EM-1) will be the first mission to send an uncrewed Orion Multi-Purpose Crew Vehicle (MPCV) to cislunar space in the fall of 2019. EM-1 was originally conceived as a lunar free-return mission, but was later changed to a Distant Retrograde Orbit (DRO) mission as a precursor to the Asteroid Redirect Mission. To understand the required mission performance (i.e., propellant requirement), a series of trajectory optimization runs was conducted using JSC's Copernicus spacecraft trajectory optimization tool. In order for the runs to be done in a timely manner, it was necessary to employ a parallelization approach on a computing cluster using a new trajectory scan tool written in Python. Details of the scan tool are provided and how it is used to perform the scans and post-process the results. Initially, a scan of daily due east launched EM-1 DRO missions in 2018 was made. Valid mission opportunities are ones that do not exceed the useable propellant available to perform the required burns. The initial scan data showed the propellant and delta-V performance patterns for each launch period. As questions were raised from different subsystems (e.g., power, thermal, communications, flight operations, etc.), the mission parameters or data that were of interest to them were added to the scan output data file. The additional data includes: (1) local launch and landing times in relation to sunrise and sunset, (2) length of eclipse periods during the in-space portion of the mission, (3) Earth line of sight from cislunar space, (4) Deep Space Network field of view looking towards cislunar space, and (5) variation of the downrange distance from Earth entry interface to splashdown. Mission design trades can also be performed based on the information that the additional data shows. For example, if the landing is in darkness, but the recovery operations team desires a landing in daylight, then an analysis is performed to determine how to change the mission design to meet this request. Also, subsystems request feasibility of alternate or contingency mission designs, such as adding an Orion main engine checkout burn or Orion completing all of its burns using only its auxiliary thrusters. This paper examines and presents the evolving trade studies that incorporate subsystem feedback and demonstrate the feasibility of these constrained mission trajectory designs and contingencies.
Investigating the mechanism of aggregation of colloidal particles during electrophoretic deposition
NASA Astrophysics Data System (ADS)
Guelcher, Scott Arthur
Charged particles deposited near an electrode aggregate to form ordered clusters in the presence of both dc and ac applied electric fields. The aggregation process could have important applications in areas such as coatings technology and ceramics processing. This thesis has sought to identify the phenomena driving the aggregation process. According to the electroosmotic flow developed by Solomentsev et al. (1997), aggregation in dc electric fields is caused by convection in the electroosmotic flow about deposited particles, and it is therefore an electrokinetic phenomenon which scales linearly with the electric field and the zeta-potential of the particles. Trajectories of pairs of particles aggregating to form doublets have been shown to scale linearly with the electric field and the zeta-potential of the particles, as predicted by the electroosmotic flow model. Furthermore, quantitative agreement has been demonstrated between the experimental and calculated trajectories for surface-to-surface separation distances between the particles ranging from one to two radii. The trajectories were calculated from the electroosmotic flow model with no fitting parameters; the only inputs to the model were the mobility of the deposited particles, the zeta- potential of the particles, and the applied electric field, all of which were measured independently. Clustering of colloidal particles deposited near an electrode in ac fields has also been observed, but a suitable model for the aggregation process has not been proposed and quantitative data in the literature are scarce. Trajectories of pairs of particles aggregating to form doublets in an ac field have been shown to scale with the root-mean-square (rms) electric field raised to the power 1.4 over the range of electric fields 10-35 V/cm (100-Hz sine and square waves). The aggregation is also frequency dependent; the doublets aggregate fastest at 30 Hz (square wave) and slowest at 500 Hz (square wave), while the interaction is repulsive at 1 kHz (square wave). The advantage of ac fields is that the process can operated at frequencies sufficiently high to avoid the negative effects of electrochemical reactions.
NASA Technical Reports Server (NTRS)
Nickel, Craig; Parker, Joel; Dichmann, Don; Lebois, Ryan; Lutz, Stephen
2016-01-01
The Transiting Exoplanet Survey Satellite (TESS) will be injected into a highly eccentric Earth orbit and fly 3.5 phasing loops followed by a lunar flyby to enter a mission orbit with lunar 2:1 resonance. Through the phasing loops and mission orbit, the trajectory is significantly affected by lunar and solar gravity. We have developed a trajectory design to achieve the mission orbit and meet mission constraints, including eclipse avoidance and a 30-year geostationary orbit avoidance requirement. A parallelized Monte Carlo simulation was performed to validate the trajectory after injecting common perturbations, including launch dispersions, orbit determination errors, and maneuver execution errors. The Monte Carlo analysis helped identify mission risks and is used in the trajectory selection process.
The Best Estimated Trajectory Analysis for Pad Abort One
NASA Technical Reports Server (NTRS)
Kutty, Prasad; Noonan, Meghan; Karlgaard, Christopher; Beck, Roger
2011-01-01
I. Best Estimated Trajectory (BET) objective: a) Produce reconstructed trajectory of the PA-1 flight to understand vehicle dynamics and aid other post flight analyses. b) Leverage all measurement sources taken of vehicle during flight to produce the most accurate estimate of vehicle trajectory. c) Generate trajectory reconstructions of the Crew Module (CM), Launch Abort System (LAS), and Forward Bay Cover (FBC). II. BET analysis was started immediately following the PA-1 mission and was completed in September, 2010 a) Quick look version of BET released 5/25/2010: initial repackaging of SIGI data. b) Preliminary version of BET released 7/6/2010: first blended solution using available sources of external measurements. c) Final version of BET released 9/1/2010: final blended solution using all available sources of data.
Oceanic Flights and Airspace: Improving Efficiency by Trajectory-Based Operations
NASA Technical Reports Server (NTRS)
Fernandes, Alicia Borgman; Rebollo, Juan; Koch, Michael
2016-01-01
Oceanic operations suffer from multiple inefficiencies, including pre-departure planning that does not adequately consider uncertainty in the proposed trajectory, restrictions on the routes that a flight operator can choose for an oceanic crossing, time-consuming processes and procedures for amending en route trajectories, and difficulties exchanging data between Flight Information Regions (FIRs). These inefficiencies cause aircraft to fly suboptimal trajectories, burning fuel and time that could be conserved. A concept to support integration of existing and emerging capabilities and concepts is needed to transition to an airspace system that employs Trajectory Based Operations (TBO) to improve efficiency and safety in oceanic operations. This paper describes such a concept and the results of preliminary activities to evaluate the concept, including a stakeholder feedback activity, user needs analysis, and high level benefits analysis.
Performance Analysis and Design Synthesis (PADS) computer program. Volume 1: Formulation
NASA Technical Reports Server (NTRS)
1972-01-01
The program formulation for PADS computer program is presented. It can size launch vehicles in conjunction with calculus-of-variations optimal trajectories and can also be used as a general-purpose branched trajectory optimization program. In the former use, it has the Space Shuttle Synthesis Program as well as a simplified stage weight module for optimally sizing manned recoverable launch vehicles. For trajectory optimization alone or with sizing, PADS has two trajectory modules. The first trajectory module uses the method of steepest descent; the second employs the method of quasilinearization, which requires a starting solution from the first trajectory module.
Trajectory-based heating analysis for the European Space Agency/Rosetta Earth Return Vehicle
NASA Technical Reports Server (NTRS)
Henline, William D.; Tauber, Michael E.
1994-01-01
A coupled, trajectory-based flowfield and material thermal-response analysis is presented for the European Space Agency proposed Rosetta comet nucleus sample return vehicle. The probe returns to earth along a hyperbolic trajectory with an entry velocity of 16.5 km/s and requires an ablative heat shield on the forebody. Combined radiative and convective ablating flowfield analyses were performed for the significant heating portion of the shallow ballistic entry trajectory. Both quasisteady ablation and fully transient analyses were performed for a heat shield composed of carbon-phenolic ablative material. Quasisteady analysis was performed using the two-dimensional axisymmetric codes RASLE and BLIMPK. Transient computational results were obtained from the one-dimensional ablation/conduction code CMA. Results are presented for heating, temperature, and ablation rate distributions over the probe forebody for various trajectory points. Comparison of transient and quasisteady results indicates that, for the heating pulse encountered by this probe, the quasisteady approach is conservative from the standpoint of predicted surface recession.
Ernst, Dominique; Köhler, Jürgen
2013-01-21
We provide experimental results on the accuracy of diffusion coefficients obtained by a mean squared displacement (MSD) analysis of single-particle trajectories. We have recorded very long trajectories comprising more than 1.5 × 10(5) data points and decomposed these long trajectories into shorter segments providing us with ensembles of trajectories of variable lengths. This enabled a statistical analysis of the resulting MSD curves as a function of the lengths of the segments. We find that the relative error of the diffusion coefficient can be minimized by taking an optimum number of points into account for fitting the MSD curves, and that this optimum does not depend on the segment length. Yet, the magnitude of the relative error for the diffusion coefficient does, and achieving an accuracy in the order of 10% requires the recording of trajectories with about 1000 data points. Finally, we compare our results with theoretical predictions and find very good qualitative and quantitative agreement between experiment and theory.
Creating drag and lift curves from soccer trajectories
NASA Astrophysics Data System (ADS)
Goff, John Eric; Kelley, John; Hobson, Chad M.; Seo, Kazuya; Asai, Takeshi; Choppin, S. B.
2017-07-01
Trajectory analysis is an alternative to using wind tunnels to measure a soccer ball’s aerodynamic properties. It has advantages over wind tunnel testing such as being more representative of game play. However, previous work has not presented a method that produces complete, speed-dependent drag and lift coefficients. Four high-speed cameras in stereo-calibrated pairs were used to measure the spatial co-ordinates for 29 separate soccer trajectories. Those trajectories span a range of launch speeds from 9.3 to 29.9 m s-1. That range encompasses low-speed laminar flow of air over a soccer ball, through the drag crises where air flow is both laminar and turbulent, and up to high-speed turbulent air flow. Results from trajectory analysis were combined to give speed-dependent drag and lift coefficient curves for the entire range of speeds found in the 29 trajectories. The average root mean square error between the measured and modelled trajectory was 0.028 m horizontally and 0.034 m vertically. The drag and lift crises can be observed in the plots of drag and lift coefficients respectively.
Clustering method for counting passengers getting in a bus with single camera
NASA Astrophysics Data System (ADS)
Yang, Tao; Zhang, Yanning; Shao, Dapei; Li, Ying
2010-03-01
Automatic counting of passengers is very important for both business and security applications. We present a single-camera-based vision system that is able to count passengers in a highly crowded situation at the entrance of a traffic bus. The unique characteristics of the proposed system include, First, a novel feature-point-tracking- and online clustering-based passenger counting framework, which performs much better than those of background-modeling-and foreground-blob-tracking-based methods. Second, a simple and highly accurate clustering algorithm is developed that projects the high-dimensional feature point trajectories into a 2-D feature space by their appearance and disappearance times and counts the number of people through online clustering. Finally, all test video sequences in the experiment are captured from a real traffic bus in Shanghai, China. The results show that the system can process two 320×240 video sequences at a frame rate of 25 fps simultaneously, and can count passengers reliably in various difficult scenarios with complex interaction and occlusion among people. The method achieves high accuracy rates up to 96.5%.
Network Analysis of Protein Adaptation: Modeling the Functional Impact of Multiple Mutations
Beleva Guthrie, Violeta; Masica, David L; Fraser, Andrew; Federico, Joseph; Fan, Yunfan; Camps, Manel; Karchin, Rachel
2018-01-01
Abstract The evolution of new biochemical activities frequently involves complex dependencies between mutations and rapid evolutionary radiation. Mutation co-occurrence and covariation have previously been used to identify compensating mutations that are the result of physical contacts and preserve protein function and fold. Here, we model pairwise functional dependencies and higher order interactions that enable evolution of new protein functions. We use a network model to find complex dependencies between mutations resulting from evolutionary trade-offs and pleiotropic effects. We present a method to construct these networks and to identify functionally interacting mutations in both extant and reconstructed ancestral sequences (Network Analysis of Protein Adaptation). The time ordering of mutations can be incorporated into the networks through phylogenetic reconstruction. We apply NAPA to three distantly homologous β-lactamase protein clusters (TEM, CTX-M-3, and OXA-51), each of which has experienced recent evolutionary radiation under substantially different selective pressures. By analyzing the network properties of each protein cluster, we identify key adaptive mutations, positive pairwise interactions, different adaptive solutions to the same selective pressure, and complex evolutionary trajectories likely to increase protein fitness. We also present evidence that incorporating information from phylogenetic reconstruction and ancestral sequence inference can reduce the number of spurious links in the network, whereas preserving overall network community structure. The analysis does not require structural or biochemical data. In contrast to function-preserving mutation dependencies, which are frequently from structural contacts, gain-of-function mutation dependencies are most commonly between residues distal in protein structure. PMID:29522102
NASA Astrophysics Data System (ADS)
Li, D.; Liu, J.; Li, S.; Wang, C.; Zhou, S.
2018-04-01
This study used the HYSPLIT-4 model combined with cluster analysis, potential source pollution contribution functions and other methods to analyse the ground air pollution monitoring data and meteorological data in Zhengzhou during 2016. The results showed that: 1) the level of PM2.5 reached the low value in summer. The PM2.5 concentration reached the highest level in December and reached the lowest level in August. The daily variation characteristics of PM2.5 concentration in different seasons were roughly the same, and it had an obviously "double-peak" structure. 2) The annual PM2.5 concentration was positively correlated with atmospheric pressure and relative humidity. The annual PM2.5 concentration was negatively correlated with temperature, visibility, precipitation, and wind speed. 3) In winter, the air mass trajectory that through the northern Sichuan - Gansu - Shaanxi - Hubei was polluted seriously, and the level of PM2.5 was the highest which reached to 202.13 μg/m3. In summer, the air mass trajectory that came from Hubei was the lowest level with the value is 40.17 μg/m3. 4) The potential source areas located in northwest of Zhengzhou, Gansu, Hubei and Beijing-Tianjin-Hebei region in spring. The surrounding of Zhengzhou contributed to the pollution of Zhengzhou. The potential source areas appeared in Shaanxi, Sichuan, and Qinghai, the border between Ningxia and Inner Mongolia in autumn. In winter the potential source areas located in Jiangsu, Hubei, Henan, eastern of Shanxi, southern of Shanxi, Ningxia and the area of Yellow Sea, etc.
Chen, Xinguang; Lunn, Sonya; Deveaux, Lynette; Li, Xioaming; Brathwaite, Nanika; Cottrell, Lesley; Stanton, Bonita
2014-01-01
Background Behavioral interventions based on the Protection Motivation Theory (PMT) have been demonstrated to reduce HIV risk behavior among mid- and older adolescents in different settings across the globe but have not been evaluated among Caribbean nations and have received limited evaluation among pre-adolescents. Objective To determine 1) the effectiveness among pre-adolescents in The Bahamas of a PMT-based HIV prevention program “Focus on Youth in the Caribbean” (FOYC) and 2) the role of the targeted PMT constructs in intervention effect. Methods 1,360 sixth grade youth (10-11 years of age) from 15 urban schools in New Providence, The Bahamas were randomized by school to receive either FOYC or a control condition. Data collected at baseline, six and 12 months post intervention were analyzed. A five-step scheme was used to assess sexual behavior progression, ranging from “1” = “a virgin without intention to have sex” to” 5″ = “having sex without a condom”. Group-based trajectory analysis was utilized in assessing the program effect. Results Two sexual behavior progression patterns were detected: slow progressors and quick progressors. Receiving FOYC reduced the likelihood for adolescents to become quick progressors (adjusted OR = 0.77, 95% CI: 0.64-1.00). The observed effectiveness was especially impacted by a subset of the targeted PMT constructs. Conclusion FOYC effectively delays sexual risk among Bahamian pre-adolescents. The group-based trajectory analysis provides an analytical approach for assessing interventions among adolescents with low rates and diverse progression patterns of sexual activity. PMID:19116781
Outer-Planet Mission Analysis Using Solar-Electric Ion Propulsion
NASA Technical Reports Server (NTRS)
Woo, Byoungsam; Coverstone, Victoria L.; Hartmann, John W.; Cupples, Michael
2003-01-01
Outer-planet mission analysis was performed using three next generation solar-electric ion thruster models. Optimal trajectories are presented that maximize the delivered mass to the designated outer planet. Trajectories to Saturn and Neptune with a single Venus gravity assist are investigated. For each thruster model, the delivered mass versus flight time curve was generated to obtain thruster model performance. The effects of power to the thrusters and resonance ratio of Venutian orbital periods to spacecraft period were also studied. Multiple locally optimal trajectories to Saturn and Neptune have been discovered in different regions of the parameter search space. The characteristics of each trajectory are noted.
Two-Year Trajectory of Fall Risk in People With Parkinson Disease: A Latent Class Analysis.
Paul, Serene S; Thackeray, Anne; Duncan, Ryan P; Cavanaugh, James T; Ellis, Theresa D; Earhart, Gammon M; Ford, Matthew P; Foreman, K Bo; Dibble, Leland E
2016-03-01
To examine fall risk trajectories occurring naturally in a sample of individuals with early to middle stage Parkinson disease (PD). Latent class analysis, specifically growth mixture modeling (GMM), of longitudinal fall risk trajectories. Assessments were conducted at 1 of 4 universities. Community-dwelling participants with PD of a longitudinal cohort study who attended at least 2 of 5 assessments over a 2-year follow-up period (N=230). Not applicable. Fall risk trajectory (low, medium, or high risk) and stability of fall risk trajectory (stable or fluctuating). Fall risk was determined at 6 monthly intervals using a simple clinical tool based on fall history, freezing of gait, and gait speed. The GMM optimally grouped participants into 3 fall risk trajectories that closely mirrored baseline fall risk status (P=.001). The high fall risk trajectory was most common (42.6%) and included participants with longer and more severe disease and with higher postural instability and gait disability (PIGD) scores than the low and medium fall risk trajectories (P<.001). Fluctuating fall risk (posterior probability <0.8 of belonging to any trajectory) was found in only 22.6% of the sample, most commonly among individuals who were transitioning to PIGD predominance. Regardless of their baseline characteristics, most participants had clear and stable fall risk trajectories over 2 years. Further investigation is required to determine whether interventions to improve gait and balance may improve fall risk trajectories in people with PD. Copyright © 2016 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.
BIGNASim: a NoSQL database structure and analysis portal for nucleic acids simulation data.
Hospital, Adam; Andrio, Pau; Cugnasco, Cesare; Codo, Laia; Becerra, Yolanda; Dans, Pablo D; Battistini, Federica; Torres, Jordi; Goñi, Ramón; Orozco, Modesto; Gelpí, Josep Ll
2016-01-04
Molecular dynamics simulation (MD) is, just behind genomics, the bioinformatics tool that generates the largest amounts of data, and that is using the largest amount of CPU time in supercomputing centres. MD trajectories are obtained after months of calculations, analysed in situ, and in practice forgotten. Several projects to generate stable trajectory databases have been developed for proteins, but no equivalence exists in the nucleic acids world. We present here a novel database system to store MD trajectories and analyses of nucleic acids. The initial data set available consists mainly of the benchmark of the new molecular dynamics force-field, parmBSC1. It contains 156 simulations, with over 120 μs of total simulation time. A deposition protocol is available to accept the submission of new trajectory data. The database is based on the combination of two NoSQL engines, Cassandra for storing trajectories and MongoDB to store analysis results and simulation metadata. The analyses available include backbone geometries, helical analysis, NMR observables and a variety of mechanical analyses. Individual trajectories and combined meta-trajectories can be downloaded from the portal. The system is accessible through http://mmb.irbbarcelona.org/BIGNASim/. Supplementary Material is also available on-line at http://mmb.irbbarcelona.org/BIGNASim/SuppMaterial/. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.
Phase separation and large deviations of lattice active matter
NASA Astrophysics Data System (ADS)
Whitelam, Stephen; Klymko, Katherine; Mandal, Dibyendu
2018-04-01
Off-lattice active Brownian particles form clusters and undergo phase separation even in the absence of attractions or velocity-alignment mechanisms. Arguments that explain this phenomenon appeal only to the ability of particles to move persistently in a direction that fluctuates, but existing lattice models of hard particles that account for this behavior do not exhibit phase separation. Here we present a lattice model of active matter that exhibits motility-induced phase separation in the absence of velocity alignment. Using direct and rare-event sampling of dynamical trajectories, we show that clustering and phase separation are accompanied by pronounced fluctuations of static and dynamic order parameters. This model provides a complement to off-lattice models for the study of motility-induced phase separation.
Simulated trajectories error analysis program, version 2. Volume 2: Programmer's manual
NASA Technical Reports Server (NTRS)
Vogt, E. D.; Adams, G. L.; Working, M. M.; Ferguson, J. B.; Bynum, M. R.
1971-01-01
A series of three computer programs for the mathematical analysis of navigation and guidance of lunar and interplanetary trajectories was developed. All three programs require the integration of n-body trajectories for both interplanetary and lunar missions. The virutal mass technique is used in all three programs. The user's manual contains the information necessary to operate the programs. The input and output quantities of the programs are described. Sample cases are given and discussed.
Silvatti, Amanda P; Cerveri, Pietro; Telles, Thiago; Dias, Fábio A S; Baroni, Guido; Barros, Ricardo M L
2013-01-01
In this study we aim at investigating the applicability of underwater 3D motion capture based on submerged video cameras in terms of 3D accuracy analysis and trajectory reconstruction. Static points with classical direct linear transform (DLT) solution, a moving wand with bundle adjustment and a moving 2D plate with Zhang's method were considered for camera calibration. As an example of the final application, we reconstructed the hand motion trajectories in different swimming styles and qualitatively compared this with Maglischo's model. Four highly trained male swimmers performed butterfly, breaststroke and freestyle tasks. The middle fingertip trajectories of both hands in the underwater phase were considered. The accuracy (mean absolute error) of the two calibration approaches (wand: 0.96 mm - 2D plate: 0.73 mm) was comparable to out of water results and highly superior to the classical DLT results (9.74 mm). Among all the swimmers, the hands' trajectories of the expert swimmer in the style were almost symmetric and in good agreement with Maglischo's model. The kinematic results highlight symmetry or asymmetry between the two hand sides, intra- and inter-subject variability in terms of the motion patterns and agreement or disagreement with the model. The two outcomes, calibration results and trajectory reconstruction, both move towards the quantitative 3D underwater motion analysis.
Visual traffic jam analysis based on trajectory data.
Wang, Zuchao; Lu, Min; Yuan, Xiaoru; Zhang, Junping; van de Wetering, Huub
2013-12-01
In this work, we present an interactive system for visual analysis of urban traffic congestion based on GPS trajectories. For these trajectories we develop strategies to extract and derive traffic jam information. After cleaning the trajectories, they are matched to a road network. Subsequently, traffic speed on each road segment is computed and traffic jam events are automatically detected. Spatially and temporally related events are concatenated in, so-called, traffic jam propagation graphs. These graphs form a high-level description of a traffic jam and its propagation in time and space. Our system provides multiple views for visually exploring and analyzing the traffic condition of a large city as a whole, on the level of propagation graphs, and on road segment level. Case studies with 24 days of taxi GPS trajectories collected in Beijing demonstrate the effectiveness of our system.
Data Intensive Analysis of Biomolecular Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Straatsma, TP; Soares, Thereza A.
2007-12-01
The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less
Data Intensive Analysis of Biomolecular Simulations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Straatsma, TP
2008-03-01
The advances in biomolecular modeling and simulation made possible by the availability of increasingly powerful high performance computing resources is extending molecular simulations to biological more relevant system size and time scales. At the same time, advances in simulation methodologies are allowing more complex processes to be described more accurately. These developments make a systems approach to computational structural biology feasible, but this will require a focused emphasis on the comparative analysis of the increasing number of molecular simulations that are being carried out for biomolecular systems with more realistic models, multi-component environments, and for longer simulation times. Just asmore » in the case of the analysis of the large data sources created by the new high-throughput experimental technologies, biomolecular computer simulations contribute to the progress in biology through comparative analysis. The continuing increase in available protein structures allows the comparative analysis of the role of structure and conformational flexibility in protein function, and is the foundation of the discipline of structural bioinformatics. This creates the opportunity to derive general findings from the comparative analysis of molecular dynamics simulations of a wide range of proteins, protein-protein complexes and other complex biological systems. Because of the importance of protein conformational dynamics for protein function, it is essential that the analysis of molecular trajectories is carried out using a novel, more integrative and systematic approach. We are developing a much needed rigorous computer science based framework for the efficient analysis of the increasingly large data sets resulting from molecular simulations. Such a suite of capabilities will also provide the required tools for access and analysis of a distributed library of generated trajectories. Our research is focusing on the following areas: (1) the development of an efficient analysis framework for very large scale trajectories on massively parallel architectures, (2) the development of novel methodologies that allow automated detection of events in these very large data sets, and (3) the efficient comparative analysis of multiple trajectories. The goal of the presented work is the development of new algorithms that will allow biomolecular simulation studies to become an integral tool to address the challenges of post-genomic biological research. The strategy to deliver the required data intensive computing applications that can effectively deal with the volume of simulation data that will become available is based on taking advantage of the capabilities offered by the use of large globally addressable memory architectures. The first requirement is the design of a flexible underlying data structure for single large trajectories that will form an adaptable framework for a wide range of analysis capabilities. The typical approach to trajectory analysis is to sequentially process trajectories time frame by time frame. This is the implementation found in molecular simulation codes such as NWChem, and has been designed in this way to be able to run on workstation computers and other architectures with an aggregate amount of memory that would not allow entire trajectories to be held in core. The consequence of this approach is an I/O dominated solution that scales very poorly on parallel machines. We are currently using an approach of developing tools specifically intended for use on large scale machines with sufficient main memory that entire trajectories can be held in core. This greatly reduces the cost of I/O as trajectories are read only once during the analysis. In our current Data Intensive Analysis (DIANA) implementation, each processor determines and skips to the entry within the trajectory that typically will be available in multiple files and independently from all other processors read the appropriate frames.« less
NASA Astrophysics Data System (ADS)
Harabuchi, Yu; Ono, Yuriko; Maeda, Satoshi; Taketsugu, Tetsuya
2015-11-01
The existence of a valley-ridge transition (VRT) point along the intrinsic reaction coordinate does not always indicate the existence of two minima in the product side, but VRT is a sign of bifurcating nature of dynamical trajectories running on the potential energy surface. It is demonstrated by molecular dynamics simulations.
Caggiano, Rosa; Calamita, Giuseppe; Sabia, Serena; Trippetta, Serena
2017-03-01
The investigation of the potential natural and anthropogenic contribution to atmospheric aerosol particles by using lichen-bag technique was performed in the Agri Valley (Basilicata region, southern Italy). This is an area of international concern since it houses one of the largest European on-shore reservoirs and the biggest oil/gas pre-treatment plant (i.e., Centro Olio Val d'Agri (COVA)) within an anthropized context. In particular, the concentrations of 17 trace elements (Al, Ca, Cd, Cr, Cu, Fe, K, Li, Mg, Mn, Na, Ni, P, Pb, S, Ti, and Zn) were measured in lichen bags exposed in 59 selected monitoring points over periods of 6 months (from October 2011 to April 2012) and 12 months (from October 2011 to October 2012). The general origin of the main air masses affecting the sampling site during the study period was assessed by the back trajectories clustering calculated using the HYbrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model. The results allowed the identification and characterization of the crustal material, smoke, sea salt, sulfate, and anthropogenic trace element contributions to the atmospheric aerosol particles in the study area. Finally, the application of the trend surface analysis (TSA) allowed the study of the spatial distribution of the considered contributions highlighting the existence of a continuous broad variation of these contributions in the area of interest.
Tomlinson, Samuel B.; Bermudez, Camilo; Conley, Chiara; Brown, Merritt W.; Porter, Brenda E.; Marsh, Eric D.
2016-01-01
Synchronized cortical activity is implicated in both normative cognitive functioning and many neurologic disorders. For epilepsy patients with intractable seizures, irregular synchronization within the epileptogenic zone (EZ) is believed to provide the network substrate through which seizures initiate and propagate. Mapping the EZ prior to epilepsy surgery is critical for detecting seizure networks in order to achieve postsurgical seizure control. However, automated techniques for characterizing epileptic networks have yet to gain traction in the clinical setting. Recent advances in signal processing and spike detection have made it possible to examine the spatiotemporal propagation of interictal spike discharges across the epileptic cortex. In this study, we present a novel methodology for detecting, extracting, and visualizing spike propagation and demonstrate its potential utility as a biomarker for the EZ. Eighteen presurgical intracranial EEG recordings were obtained from pediatric patients ultimately experiencing favorable (i.e., seizure-free, n = 9) or unfavorable (i.e., seizure-persistent, n = 9) surgical outcomes. Novel algorithms were applied to extract multichannel spike discharges and visualize their spatiotemporal propagation. Quantitative analysis of spike propagation was performed using trajectory clustering and spatial autocorrelation techniques. Comparison of interictal propagation patterns revealed an increase in trajectory organization (i.e., spatial autocorrelation) among Sz-Free patients compared with Sz-Persist patients. The pathophysiological basis and clinical implications of these findings are considered. PMID:28066315
A Survey of Ballistic Transfers to the Lunar Surface
NASA Technical Reports Server (NTRS)
Anderson, Rodney L.; Parker, Jeffrey S.
2011-01-01
In this study techniques are developed which allow an analysis of a range of different types of transfer trajectories from the Earth to the lunar surface. Trajectories ranging from those obtained using the invariant manifolds of unstable orbits to those derived from collision orbits are analyzed. These techniques allow the computation of trajectories encompassing low-energy trajectories as well as more direct transfers. The range of possible trajectory options is summarized, and a broad range of trajectories that exist as a result of the Sun's influence are computed and analyzed. The results are then classified by type, and trades between different measures of cost are discussed.
Spyrakis, Francesca; Benedetti, Paolo; Decherchi, Sergio; Rocchia, Walter; Cavalli, Andrea; Alcaro, Stefano; Ortuso, Francesco; Baroni, Massimo; Cruciani, Gabriele
2015-10-26
The importance of taking into account protein flexibility in drug design and virtual ligand screening (VS) has been widely debated in the literature, and molecular dynamics (MD) has been recognized as one of the most powerful tools for investigating intrinsic protein dynamics. Nevertheless, deciphering the amount of information hidden in MD simulations and recognizing a significant minimal set of states to be used in virtual screening experiments can be quite complicated. Here we present an integrated MD-FLAP (molecular dynamics-fingerprints for ligand and proteins) approach, comprising a pipeline of molecular dynamics, clustering and linear discriminant analysis, for enhancing accuracy and efficacy in VS campaigns. We first extracted a limited number of representative structures from tens of nanoseconds of MD trajectories by means of the k-medoids clustering algorithm as implemented in the BiKi Life Science Suite ( http://www.bikitech.com [accessed July 21, 2015]). Then, instead of applying arbitrary selection criteria, that is, RMSD, pharmacophore properties, or enrichment performances, we allowed the linear discriminant analysis algorithm implemented in FLAP ( http://www.moldiscovery.com [accessed July 21, 2015]) to automatically choose the best performing conformational states among medoids and X-ray structures. Retrospective virtual screenings confirmed that ensemble receptor protocols outperform single rigid receptor approaches, proved that computationally generated conformations comprise the same quantity/quality of information included in X-ray structures, and pointed to the MD-FLAP approach as a valuable tool for improving VS performances.
Patterns of Recovery from Pain after Cesarean Delivery.
Booth, Jessica L; Sharpe, Emily E; Houle, Timothy T; Harris, Lynnette; Curry, Regina S; Aschenbrenner, Carol A; Eisenach, James C
2018-06-13
We know very little about the change in pain in the first 2 months after surgery. To address this gap, we studied 530 women scheduled for elective cesarean delivery who completed daily pain diaries for two months after surgery via text messaging. Over 82% of subjects missed fewer than 10 diary entries and were included in the analysis. Completers were more likely to be Caucasian, non-smokers, and with fewer previous pregnancies than non-completers. Daily worst pain intensity ratings for the previous 24 hours were fit to a log(time) function and allowed to change to a different function up to 3 times according to a Bayesian criterion. All women had at least one change point, occurring 22 ± 9 days postoperatively, and 81% of women had only one change, most commonly to a linear function at 0 pain. Approximately 9% of women were predicted to have pain 2 months after surgery, similar to previous observations. Cluster analysis revealed 6 trajectories of recovery from pain. Predictors of cluster membership included severity of acute pain, perceived stress, surgical factors, and smoking status. These data demonstrate feasibility but considerable challenges to this approach to data acquisition. The form of the initial process of recovery from pain is common to all women, with divergence of patterns at 2-4 weeks after cesarean delivery. The change point model accurately predicts recovery from pain, its parameters can be used to assess predictors of speed of recovery, and it may be useful for future observational, forecasting, and interventional trials.
Morphometric and kinematic sperm subpopulations in split ejaculates of normozoospermic men
Santolaria, Pilar; Soler, Carles; Recreo, Pilar; Carretero, Teresa; Bono, Araceli; Berné, José M; Yániz, Jesús L
2016-01-01
This study was designed to analyze the sperm kinematic and morphometric subpopulations in the different fractions of the ejaculate in normozoospermic men. Ejaculates from eight normozoospermic men were collected by masturbation in three fractions after 3–5 days of sexual abstinence. Analyses of sperm motility by computer-assisted sperm analysis (CASA-Mot), and of sperm morphometry by computer-assisted sperm morphometry analysis (CASA-Morph) using fluorescence were performed. Clustering and discriminant procedures were performed to identify sperm subpopulations in the kinematic and morphometric data obtained. Clustering procedures resulted in the classification of spermatozoa into three kinematic subpopulations (slow with low ALH [35.6% of all motile spermatozoa], with circular trajectories [32.0%], and rapid with high ALH [32.4%]), and three morphometric subpopulations (large-round [33.9% of all spermatozoa], elongated [32.0%], and small [34.10%]). The distribution of kinematic sperm subpopulations was different among ejaculate fractions (P < 0.001), with higher percentages of spermatozoa exhibiting slow movements with low ALH in the second and third portions, and with a more homogeneous distribution of kinematic sperm subpopulations in the first portion. The distribution of morphometric sperm subpopulations was also different among ejaculate fractions (P < 0.001), with more elongated spermatozoa in the first, and of small spermatozoa in the third, portion. It is concluded that important variations in the distribution of kinematic and morphometric sperm subpopulations exist between ejaculate fractions, with possible functional implications. PMID:27624985
Shallow seismicity patterns in the northwestern section of the Mexico Subduction Zone
NASA Astrophysics Data System (ADS)
Abbott, Elizabeth R.; Brudzinski, Michael R.
2015-11-01
This study characterizes subduction related seismicity with local deployments along the northwestern section of the Mexico Subduction Zone where 4 portions of the plate interface have ruptured in 1973, 1985, 1995, and 2003. It has been proposed that the subducted boundary between the Cocos and Rivera plates occurs beneath this region, as indicated by inland volcanic activity, a gap in tectonic tremor, and the Manzanillo Trough and Colima Graben, which are depressions thought to be associated with the splitting of the two plates after subduction. Data from 50 broadband stations that comprised the MARS seismic array, deployed from January 2006 to June 2007, were processed with the software program Antelope and its generalized source location algorithm, genloc, to detect and locate earthquakes within the network. Slab surface depth contours from the resulting catalog indicate a change in subduction trajectory between the Rivera and Cocos plates. The earthquake locations are spatially anti-correlated with tectonic tremor, supporting the idea that they represent different types of fault slip. Hypocentral patterns also reveal areas of more intense seismic activity (clusters) that appear to be associated with the 2003 and 1973 megathrust rupture regions. Seismicity concentrated inland of the 2003 rupture is consistent with slip on a shallowly dipping trajectory for the Rivera plate interface as opposed to crustal faulting in the overriding North American plate. A prominent cluster of seismicity within the suspected 1973 rupture zone appears to be a commonly active portion of the megathrust as it has been active during three previous deployments. We support these interpretations by determining focal mechanisms and detailed relocations of the largest events within the 1973 and inland 2003 clusters, which indicate primarily thrust mechanisms near the plate interface.
Nevanperä, Nina; Seitsamo, Jorma; Ala-Mursula, Leena; Remes, Jouko; Hopsu, Leila; Auvinen, Juha; Tammelin, Tuija; Järvelin, Marjo-Riitta; Laitinen, Jaana
2016-04-01
Most of the few studies that exist on the longitudinal associations between health behaviors and work ability target to single health behaviors. To investigate how lifetime clusters of unhealthy behaviors associate with perceived work ability in early midlife. The study population consisted of 46-year-old men and women (n = 3107) born in Northern Finland in 1966. Their current perceived work ability compared to lifetime best, and their unhealthy behaviors (physical inactivity, smoking, and alcohol consumption) were assessed by questionnaires. We determined clusters of unhealthy behaviors at the ages of 14, 31, and 46 and created lifetime development trajectories of health behaviors. We also assessed stress-related eating and drinking at the ages of 31 and 46. Cross-tabulations and multivariate logistic regression models were used to investigate the associations between clusters of health behaviors, stress-related eating and drinking, and work ability at 46 years. The analyses were controlled for basic education and physical strenuousness of work, psychosocial job characteristics, perceived work ability, and BMI (kg/m(2)) at 31 years. Four health behavior trajectories emerged: always healthy, moderate (reference group), deteriorated. and always unhealthy. Among men, always unhealthy behaviors [OR (95 % confidence interval) 2.81 (1.35, 5.86)], and among women, deteriorated health behaviors [1.67 (1.07, 2.58)] associated with poor perceived work ability at 46 years. In addition, stress-related eating and drinking associated independently with poor perceived work ability at 46 years [men 2.58 (1.62, 4.12) and women 2.48 (1.70, 3.61)]. Long-lasting and stress-related unhealthy behaviors increase the risk of poor work ability in midlife.
NASA Astrophysics Data System (ADS)
Khusainov, R.; Klimchik, A.; Magid, E.
2017-01-01
The paper presents comparison analysis of two approaches in defining leg trajectories for biped locomotion. The first one operates only with kinematic limitations of leg joints and finds the maximum possible locomotion speed for given limits. The second approach defines leg trajectories from the dynamic stability point of view and utilizes ZMP criteria. We show that two methods give different trajectories and demonstrate that trajectories based on pure dynamic optimization cannot be realized due to joint limits. Kinematic optimization provides unstable solution which can be balanced by upper body movement.
Johnson, L; van Jaarsveld, C H M; Llewellyn, C H; Cole, T J; Wardle, J
2014-01-01
Objective: Infant growth trajectories, in terms of size, tempo and velocity, may programme lifelong obesity risk. Timing of breastfeeding cessation and weaning are both implicated in rapid infant growth; we examined the association of both simultaneously with a range of growth parameters. Design: Longitudinal population-based twin birth cohort. Subjects: The Gemini cohort provided data on 4680 UK infants with a median of 10 (interquartile range=8–15) weight measurements between birth and a median of 6.5 months. Age at breastfeeding cessation and weaning were reported by parents at mean age 8.2 months (s.d.=2.2, range=4–20). Growth trajectories were modelled using SuperImposition by Translation And Rotation (SITAR) to generate three descriptors of individual growth relative to the average trajectory: size (grams), tempo (weeks, indicating the timing of the peak growth rate) and velocity (% difference from average, reflecting mean growth rate). Complex-samples general linear models adjusting for family clustering and confounders examined associations between infant feeding and SITAR parameters. Results: Longer breastfeeding (>4 months vs never) was independently associated with lower growth velocity by 6.8% (s.e.=1.3%) and delayed growth tempo by 1.0 (s.e.=0.2 weeks), but not with smaller size. Later weaning (⩾6 months vs <4 months) was independently associated with lower growth velocity by 4.9% (s.e.=1.1%) and smaller size by 102 g (s.e.=25 g). Conclusions: Infants breastfed for longer grew slower for longer after birth (later peak growth rate) but were no different in size, while infants weaned later grew slower overall and were smaller but the timing of peak growth did not differ. Slower trajectories with a delayed peak in growth may have beneficial implications for programming later obesity risk. Replication in cohorts with longer follow-up, alternative confounding structures or randomised controlled trials are required to confirm the long-term effects and directionality, and to rule out residual confounding. PMID:24722545
Rapid Design of Gravity Assist Trajectories
NASA Technical Reports Server (NTRS)
Carrico, J.; Hooper, H. L.; Roszman, L.; Gramling, C.
1991-01-01
Several International Solar Terrestrial Physics (ISTP) missions require the design of complex gravity assisted trajectories in order to investigate the interaction of the solar wind with the Earth's magnetic field. These trajectories present a formidable trajectory design and optimization problem. The philosophy and methodology that enable an analyst to design and analyse such trajectories are discussed. The so called 'floating end point' targeting, which allows the inherently nonlinear multiple body problem to be solved with simple linear techniques, is described. The combination of floating end point targeting with analytic approximations with a Newton method targeter to achieve trajectory design goals quickly, even for the very sensitive double lunar swingby trajectories used by the ISTP missions, is demonstrated. A multiconic orbit integration scheme allows fast and accurate orbit propagation. A prototype software tool, Swingby, built for trajectory design and launch window analysis, is described.
Trajectory Browser: An Online Tool for Interplanetary Trajectory Analysis and Visualization
NASA Technical Reports Server (NTRS)
Foster, Cyrus James
2013-01-01
The trajectory browser is a web-based tool developed at the NASA Ames Research Center for finding preliminary trajectories to planetary bodies and for providing relevant launch date, time-of-flight and (Delta)V requirements. The site hosts a database of transfer trajectories from Earth to planets and small-bodies for various types of missions such as rendezvous, sample return or flybys. A search engine allows the user to find trajectories meeting desired constraints on the launch window, mission duration and (Delta)V capability, while a trajectory viewer tool allows the visualization of the heliocentric trajectory and the detailed mission itinerary. The anticipated user base of this tool consists primarily of scientists and engineers designing interplanetary missions in the context of pre-phase A studies, particularly for performing accessibility surveys to large populations of small-bodies.
Scout trajectory error propagation computer program
NASA Technical Reports Server (NTRS)
Myler, T. R.
1982-01-01
Since 1969, flight experience has been used as the basis for predicting Scout orbital accuracy. The data used for calculating the accuracy consists of errors in the trajectory parameters (altitude, velocity, etc.) at stage burnout as observed on Scout flights. Approximately 50 sets of errors are used in Monte Carlo analysis to generate error statistics in the trajectory parameters. A covariance matrix is formed which may be propagated in time. The mechanization of this process resulted in computer program Scout Trajectory Error Propagation (STEP) and is described herein. Computer program STEP may be used in conjunction with the Statistical Orbital Analysis Routine to generate accuracy in the orbit parameters (apogee, perigee, inclination, etc.) based upon flight experience.
Investigation of water droplet trajectories within the NASA icing research tunnel
NASA Technical Reports Server (NTRS)
Reehorst, Andrew; Ibrahim, Mounir
1995-01-01
Water droplet trajectories within the NASA Lewis Research Center's Icing Research Tunnel (IRT) were studied through computer analysis. Of interest was the influence of the wind tunnel contraction and wind tunnel model blockage on the water droplet trajectories. The computer analysis was carried out with a program package consisting of a three-dimensional potential panel code and a three-dimensional droplet trajectory code. The wind tunnel contraction was found to influence the droplet size distribution and liquid water content distribution across the test section from that at the inlet. The wind tunnel walls were found to have negligible influence upon the impingement of water droplets upon a wing model.
Clonal development and organization of the adult Drosophila central brain.
Yu, Hung-Hsiang; Awasaki, Takeshi; Schroeder, Mark David; Long, Fuhui; Yang, Jacob S; He, Yisheng; Ding, Peng; Kao, Jui-Chun; Wu, Gloria Yueh-Yi; Peng, Hanchuan; Myers, Gene; Lee, Tzumin
2013-04-22
The insect brain can be divided into neuropils that are formed by neurites of both local and remote origin. The complexity of the interconnections obscures how these neuropils are established and interconnected through development. The Drosophila central brain develops from a fixed number of neuroblasts (NBs) that deposit neurons in regional clusters. By determining individual NB clones and pursuing their projections into specific neuropils, we unravel the regional development of the brain neural network. Exhaustive clonal analysis revealed 95 stereotyped neuronal lineages with characteristic cell-body locations and neurite trajectories. Most clones show complex projection patterns, but despite the complexity, neighboring clones often coinnervate the same local neuropil or neuropils and further target a restricted set of distant neuropils. These observations argue for regional clonal development of both neuropils and neuropil connectivity throughout the Drosophila central brain. Copyright © 2013 Elsevier Ltd. All rights reserved.
Characteristics of size-segregated carbonaceous aerosols in the Beijing-Tianjin-Hebei region.
Guo, Yuhong
2016-07-01
Mass concentrations of organic carbon (OC) and elemental carbon (EC) in size-resolved aerosols were investigated at four sites (three cities and one country) in the Beijing-Tianjin-Hebei region from September 2009 to August 2011. The size distributions of OC and EC presented large evolutions among rural and urban sites, and among four seasons, with highest peaks of OC and EC in fine mode in urban areas during winter. Geometric mean diameters (GMDs) of OC and EC in fine particles at urban sites during winter were lower than those at rural site mainly due to effects of fine particle coagulation and organic compound repartitioning. Fossil fuel emissions were a dominant source of OC and EC in urban areas, while biomass burning was a major source of OC and EC at rural site. Trajectory clustering and CWT analysis showed that regional transport was an important contributor to OC and EC in Beijing.
Evolutionary Computation for the Identification of Emergent Behavior in Autonomous Systems
NASA Technical Reports Server (NTRS)
Terrile, Richard J.; Guillaume, Alexandre
2009-01-01
Over the past several years the Center for Evolutionary Computation and Automated Design at the Jet Propulsion Laboratory has developed a technique based on Evolutionary Computational Methods (ECM) that allows for the automated optimization of complex computationally modeled systems. An important application of this technique is for the identification of emergent behaviors in autonomous systems. Mobility platforms such as rovers or airborne vehicles are now being designed with autonomous mission controllers that can find trajectories over a solution space that is larger than can reasonably be tested. It is critical to identify control behaviors that are not predicted and can have surprising results (both good and bad). These emergent behaviors need to be identified, characterized and either incorporated into or isolated from the acceptable range of control characteristics. We use cluster analysis of automatically retrieved solutions to identify isolated populations of solutions with divergent behaviors.
Assessing the effects of transboundary ozone pollution between Ontario, Canada and New York, USA.
Brankov, Elvira; Henry, Robert F; Civerolo, Kevin L; Hao, Winston; Rao, S T; Misra, P K; Bloxam, Robert; Reid, Neville
2003-01-01
We investigated the effects of transboundary pollution between Ontario and New York using both observations and modeling results. Analysis of the spatial scales associated with ozone pollution revealed the regional and international character of this pollutant. A back-trajectory-clustering methodology was used to evaluate the potential for transboundary pollution trading and to identify potential pollution source regions for two sites: CN tower in Toronto and the World Trade Center in New York City. Transboundary pollution transport was evident at both locations. The major pollution source areas for the period examined were the Ohio River Valley and Midwest. Finally, we examined the transboundary impact of emission reductions through photochemical models. We found that emissions from both New York and Ontario were transported across the border and that reductions in predicted O3 levels can be substantial when emissions on both sides of the border are reduced.
NASA Astrophysics Data System (ADS)
Merler, Stefano
2016-09-01
Characterizing the early growth profile of an epidemic outbreak is key for predicting the likely trajectory of the number of cases and for designing adequate control measures. Epidemic profiles characterized by exponential growth have been widely observed in the past and a grounding theoretical framework for the analysis of infectious disease dynamics was provided by the pioneering work of Kermack and McKendrick [1]. In particular, exponential growth stems from the assumption that pathogens spread in homogeneous mixing populations; that is, individuals of the population mix uniformly and randomly with each other. However, this assumption was readily recognized as highly questionable [2], and sub-exponential profiles of epidemic growth have been observed in a number of epidemic outbreaks, including HIV/AIDS, foot-and-mouth disease, measles and, more recently, Ebola [3,4].
Single quantum dot tracking reveals the impact of nanoparticle surface on intracellular state.
Zahid, Mohammad U; Ma, Liang; Lim, Sung Jun; Smith, Andrew M
2018-05-08
Inefficient delivery of macromolecules and nanoparticles to intracellular targets is a major bottleneck in drug delivery, genetic engineering, and molecular imaging. Here we apply live-cell single-quantum-dot imaging and tracking to analyze and classify nanoparticle states after intracellular delivery. By merging trajectory diffusion parameters with brightness measurements, multidimensional analysis reveals distinct and heterogeneous populations that are indistinguishable using single parameters alone. We derive new quantitative metrics of particle loading, cluster distribution, and vesicular release in single cells, and evaluate intracellular nanoparticles with diverse surfaces following osmotic delivery. Surface properties have a major impact on cell uptake, but little impact on the absolute cytoplasmic numbers. A key outcome is that stable zwitterionic surfaces yield uniform cytosolic behavior, ideal for imaging agents. We anticipate that this combination of quantum dots and single-particle tracking can be widely applied to design and optimize next-generation imaging probes, nanoparticle therapeutics, and biologics.
Mission objectives and trajectories
NASA Technical Reports Server (NTRS)
1973-01-01
The present state of the knowledge of asteroids was assessed to identify mission and target priorities for planning asteroidal flights in the 1980's and beyond. Mission objectives, mission analysis, trajectory studies, and cost analysis are discussed. A bibliography of reports and technical memoranda is included.
Quantum trajectory analysis of multimode subsystem-bath dynamics.
Wyatt, Robert E; Na, Kyungsun
2002-01-01
The dynamics of a swarm of quantum trajectories is investigated for systems involving the interaction of an active mode (the subsystem) with an M-mode harmonic reservoir (the bath). Equations of motion for the position, velocity, and action function for elements of the probability fluid are integrated in the Lagrangian (moving with the fluid) picture of quantum hydrodynamics. These fluid elements are coupled through the Bohm quantum potential and as a result evolve as a correlated ensemble. Wave function synthesis along the trajectories permits an exact description of the quantum dynamics for the evolving probability fluid. The approach is fully quantum mechanical and does not involve classical or semiclassical approximations. Computational results are presented for three systems involving the interaction on an active mode with M=1, 10, and 15 bath modes. These results include configuration space trajectory evolution, flux analysis of the evolving ensemble, wave function synthesis along trajectories, and energy partitioning along specific trajectories. These results demonstrate the feasibility of using a small number of quantum trajectories to obtain accurate quantum results on some types of open quantum systems that are not amenable to standard quantum approaches involving basis set expansions or Eulerian space-fixed grids.
Sensitivity Analysis and Mitigation with Applications to Ballistic and Low-thrust Trajectory Design
NASA Astrophysics Data System (ADS)
Alizadeh, Iman
The ever increasing desire to expand space mission capabilities within the limited budgets of space industries requires new approaches to the old problem of spacecraft trajectory design. For example, recent initiatives for space exploration involve developing new tools to design low-cost, fail-safe trajectories to visit several potential destinations beyond our celestial neighborhood such as Jupiter's moons, asteroids, etc. Designing and navigating spacecraft trajectories to reach these destinations safely are complex and challenging. In particular, fundamental questions of orbital stability imposed by planetary protection requirements are not easily taken into account by standard optimal control schemes. The event of temporary engine loss or an unexpected missed thrust can indeed quickly lead to impact with planetary bodies or other unrecoverable trajectories. While electric propulsion technology provides superior efficiency compared to chemical engines, the very low-control authority and engine performance degradation can impose higher risk to the mission in strongly perturbed orbital environments. The risk is due to the complex gravitational field and its associated chaotic dynamics which causes large navigation dispersions in a short time if left un-controlled. Moreover, in these situations it can be outside the low-thrust propulsion system capability to correct the spacecraft trajectory in a reasonable time frame. These concerns can lead to complete or partial mission failure or even an infeasible mission concept at the early design stage. The goal of this research is to assess and increase orbital stability of ballistic and low-thrust transfer trajectories in multi-body systems. In particular, novel techniques are presented to characterize sensitivity and improve recovery characteristics of ballistic and low-thrust trajectories in unstable orbital environments. The techniques developed are based on perturbation analysis around ballistic trajectories to determine analytically the maximum divergence directions and also optimal control theory with nonstandard cost functions along with inverse dynamics applied to low-thrust trajectories. Several mission scenarios are shown to demonstrate the applicability of the techniques in the Earth-Moon and the Jupiter-Europa system. In addition, the results provide fundamental insight into design, stability analysis and guidance, navigation and control of low-thrust trajectories to meet challenging mission requirements in support of NASA's vision for space exploration.
Kronenberger, William G; Pisoni, David B; Harris, Michael S; Hoen, Helena M; Xu, Huiping; Miyamoto, Richard T
2013-06-01
Verbal short-term memory (STM) and working memory (WM) skills predict speech and language outcomes in children with cochlear implants (CIs) even after conventional demographic, device, and medical factors are taken into account. However, prior research has focused on single end point outcomes as opposed to the longitudinal process of development of verbal STM/WM and speech-language skills. In this study, the authors investigated relations between profiles of verbal STM/WM development and speech-language development over time. Profiles of verbal STM/WM development were identified through the use of group-based trajectory analysis of repeated digit span measures over at least a 2-year time period in a sample of 66 children (ages 6-16 years) with CIs. Subjects also completed repeated assessments of speech and language skills during the same time period. Clusters representing different patterns of development of verbal STM (digit span forward scores) were related to the growth rate of vocabulary and language comprehension skills over time. Clusters representing different patterns of development of verbal WM (digit span backward scores) were related to the growth rate of vocabulary and spoken word recognition skills over time. Different patterns of development of verbal STM/WM capacity predict the dynamic process of development of speech and language skills in this clinical population.
Dynamic Agent Classification and Tracking Using an Ad Hoc Mobile Acoustic Sensor Network
NASA Astrophysics Data System (ADS)
Friedlander, David; Griffin, Christopher; Jacobson, Noah; Phoha, Shashi; Brooks, Richard R.
2003-12-01
Autonomous networks of sensor platforms can be designed to interact in dynamic and noisy environments to determine the occurrence of specified transient events that define the dynamic process of interest. For example, a sensor network may be used for battlefield surveillance with the purpose of detecting, identifying, and tracking enemy activity. When the number of nodes is large, human oversight and control of low-level operations is not feasible. Coordination and self-organization of multiple autonomous nodes is necessary to maintain connectivity and sensor coverage and to combine information for better understanding the dynamics of the environment. Resource conservation requires adaptive clustering in the vicinity of the event. This paper presents methods for dynamic distributed signal processing using an ad hoc mobile network of microsensors to detect, identify, and track targets in noisy environments. They seamlessly integrate data from fixed and mobile platforms and dynamically organize platforms into clusters to process local data along the trajectory of the targets. Local analysis of sensor data is used to determine a set of target attribute values and classify the target. Sensor data from a field test in the Marine base at Twentynine Palms, Calif, was analyzed using the techniques described in this paper. The results were compared to "ground truth" data obtained from GPS receivers on the vehicles.
Trajectory Correction and Locomotion Analysis of a Hexapod Walking Robot with Semi-Round Rigid Feet
Zhu, Yaguang; Jin, Bo; Wu, Yongsheng; Guo, Tong; Zhao, Xiangmo
2016-01-01
Aimed at solving the misplaced body trajectory problem caused by the rolling of semi-round rigid feet when a robot is walking, a legged kinematic trajectory correction methodology based on the Least Squares Support Vector Machine (LS-SVM) is proposed. The concept of ideal foothold is put forward for the three-dimensional kinematic model modification of a robot leg, and the deviation value between the ideal foothold and real foothold is analyzed. The forward/inverse kinematic solutions between the ideal foothold and joint angular vectors are formulated and the problem of direct/inverse kinematic nonlinear mapping is solved by using the LS-SVM. Compared with the previous approximation method, this correction methodology has better accuracy and faster calculation speed with regards to inverse kinematics solutions. Experiments on a leg platform and a hexapod walking robot are conducted with multi-sensors for the analysis of foot tip trajectory, base joint vibration, contact force impact, direction deviation, and power consumption, respectively. The comparative analysis shows that the trajectory correction methodology can effectively correct the joint trajectory, thus eliminating the contact force influence of semi-round rigid feet, significantly improving the locomotion of the walking robot and reducing the total power consumption of the system. PMID:27589766
Kendzor, Darla E; Caughy, Margaret O; Owen, Margaret Tresch
2012-08-05
Childhood socioeconomic disadvantage has been linked with obesity in cross-sectional research, although less is known about how changes in socioeconomic status influence the development of obesity. Researchers have hypothesized that upward socioeconomic mobility may attenuate the health effects of earlier socioeconomic disadvantage; while downward socioeconomic mobility might have a negative influence on health despite relative socioeconomic advantages at earlier stages. The purpose of the current study was to characterize trajectories of family income during childhood, and to evaluate the influence of these trajectories on adiposity at age 15. Data were collected as part of the Study of Early Child Care and Youth Development (SECCYD) between 1991 and 2007 at 10 sites across the United States. A latent class growth analysis (LCGA) was conducted to identify trajectories of family income from birth to 15 years of age. Analyses of covariance (ANCOVAs) were conducted to determine whether measures of adiposity differed by trajectory, while controlling for relevant covariates. The LCGA supported a 5-class trajectory model, which included two stable, one downward, and two upward trajectories. ANCOVAs indicated that BMI percentile, waist circumference, and skinfold thicknesses at age 15 differed significantly by trajectory, such that those who experienced downward mobility or stable low income had greater adiposity relative to the more advantaged trajectories. Conversely, upwardly mobile children and those with consistently adequate incomes had similar and more positive outcomes relative to the most disadvantaged trajectories. Findings suggest that promoting upward socioeconomic mobility among disadvantaged families may have a positive impact on obesity-related outcomes in adolescence.
Yokoyama, Eiji; Uchimura, Masako
2007-11-01
Ninety-five enterohemorrhagic Escherichia coli serovar O157 strains, including 30 strains isolated from 13 intrafamily outbreaks and 14 strains isolated from 3 mass outbreaks, were studied by pulsed-field gel electrophoresis (PFGE) and variable number of tandem repeats (VNTR) typing, and the resulting data were subjected to cluster analysis. Cluster analysis of the VNTR typing data revealed that 57 (60.0%) of 95 strains, including all epidemiologically linked strains, formed clusters with at least 95% similarity. Cluster analysis of the PFGE patterns revealed that 67 (70.5%) of 95 strains, including all but 1 of the epidemiologically linked strains, formed clusters with 90% similarity. The number of epidemiologically unlinked strains forming clusters was significantly less by VNTR cluster analysis than by PFGE cluster analysis. The congruence value between PFGE and VNTR cluster analysis was low and did not show an obvious correlation. With two-step cluster analysis, the number of clustered epidemiologically unlinked strains by PFGE cluster analysis that were divided by subsequent VNTR cluster analysis was significantly higher than the number by VNTR cluster analysis that were divided by subsequent PFGE cluster analysis. These results indicate that VNTR cluster analysis is more efficient than PFGE cluster analysis as an epidemiological tool to trace the transmission of enterohemorrhagic E. coli O157.
Bring It to the Pitch: Combining Video and Movement Data to Enhance Team Sport Analysis.
Stein, Manuel; Janetzko, Halldor; Lamprecht, Andreas; Breitkreutz, Thorsten; Zimmermann, Philipp; Goldlucke, Bastian; Schreck, Tobias; Andrienko, Gennady; Grossniklaus, Michael; Keim, Daniel A
2018-01-01
Analysts in professional team sport regularly perform analysis to gain strategic and tactical insights into player and team behavior. Goals of team sport analysis regularly include identification of weaknesses of opposing teams, or assessing performance and improvement potential of a coached team. Current analysis workflows are typically based on the analysis of team videos. Also, analysts can rely on techniques from Information Visualization, to depict e.g., player or ball trajectories. However, video analysis is typically a time-consuming process, where the analyst needs to memorize and annotate scenes. In contrast, visualization typically relies on an abstract data model, often using abstract visual mappings, and is not directly linked to the observed movement context anymore. We propose a visual analytics system that tightly integrates team sport video recordings with abstract visualization of underlying trajectory data. We apply appropriate computer vision techniques to extract trajectory data from video input. Furthermore, we apply advanced trajectory and movement analysis techniques to derive relevant team sport analytic measures for region, event and player analysis in the case of soccer analysis. Our system seamlessly integrates video and visualization modalities, enabling analysts to draw on the advantages of both analysis forms. Several expert studies conducted with team sport analysts indicate the effectiveness of our integrated approach.
NASA Astrophysics Data System (ADS)
Bendle, James; Kawamura, Kimitaka; Yamazaki, Koji; Niwai, Takeji
2007-12-01
We investigated the latitudinal changes in atmospheric transport of organic matter to the western Pacific and Southern Ocean (27.58°N-64.70°S). Molecular distributions of lipid compound classes (homologous series of C 15 to C 35n-alkanes, C 8 to C 34n-alkanoic acids, C 12 to C 30n-alkanols) and compound-specific stable isotopes (δ 13C of C 29 and C 31n-alkanes) were measured in marine aerosol filter samples collected during a cruise by the R/V Hakuho Maru. The geographical source areas for each sample were estimated from air-mass back-trajectory computations. Concentrations of TC and lipid compound classes were several orders of magnitude lower than observations from urban sites in Asia. A stronger signature of terrestrial higher plant inputs was apparent in three samples collected under conditions of strong terrestrial winds. Unresolved complex mixtures (UCM) showed increasing values in the North Pacific, highlighting the influence of the plume of polluted air exported from East Asia. n-Alkane average chain length (ACL) distribution had two clusters, with samples showing a relation to latitude between 28°N and 47°S (highest ACL values in the tropics), whilst a subset of southern samples had anomalously high ACL values. Compound-specific carbon isotopic analysis of the C 29 (-25.6‰ to -34.5‰) and C 31n-alkanes (-28.3‰ to -37‰) revealed heavier δ 13C values in the northern latitudes with a transition to lighter values in the Southern Ocean. By comparing the isotopic measurements with back-trajectory analysis it was generally possible to discriminate between different source areas. The terrestrial vegetation source for a subset of the southernmost Southern Ocean is enigmatic; the back-trajectories indicate eastern Antarctica as the only intercepted terrestrial source area. These samples may represent a southern hemisphere background of well mixed and very long range transported higher plant organic material.
Evaluating management risks using landscape trajectory analysis: a case study of California fisher
Craig M. Thompson; William J. Zielinski; Kathryn L. Purcell
2011-01-01
Ecosystem management requires an understanding of how landscapes vary in space and time, how this variation can be affected by management decisions or stochastic events, and the potential consequences for species. Landscape trajectory analysis, coupled with a basic knowledge of species habitat selection, offers a straightforward approach to ecological risk analysis and...
Tidal origin of NGC 1427A in the Fornax cluster
NASA Astrophysics Data System (ADS)
Lee-Waddell, K.; Serra, P.; Koribalski, B.; Venhola, A.; Iodice, E.; Catinella, B.; Cortese, L.; Peletier, R.; Popping, A.; Keenan, O.; Capaccioli, M.
2018-02-01
We present new HI observations from the Australia Telescope Compact Array and deep optical imaging from OmegaCam on the VLT Survey Telescope of NGC 1427A, an arrow-shaped dwarf irregular galaxy located in the Fornax cluster. The data reveal a star-less HI tail that contains ˜10 per cent of the atomic gas of NGC 1427A as well as extended stellar emission that shed new light on the recent history of this galaxy. Rather than being the result of ram pressure induced star formation, as previously suggested in the literature, the disturbed optical appearance of NGC 1427A has tidal origins. The galaxy itself likely consists of two individual objects in an advanced stage of merging. The HI tail may be made of gas expelled to large radii during the same tidal interaction. It is possible that some of this gas is subject to ram pressure, which would be considered a secondary effect and implies a north-west trajectory of NGC 1427A within the Fornax cluster.
Keegan, Conor; Conroy, Ronán; Doyle, Frank
2016-02-01
Depression is associated with increased mortality in patients with acute coronary syndrome (ACS). However, little is known about the theoretical causes of depression trajectories post-ACS, and whether these trajectories predict subsequent morbidity/mortality. We tested a longitudinal model of depressive vulnerabilities, trajectories and mortality. A prospective observational study of 374 ACS patients was conducted. Participants completed questionnaires on theoretical vulnerabilities (interpersonal life events, reinforcing events, cognitive distortions, and Type D personality) during hospitalisation and depression at baseline and 3, 6 and 12 months post-hospitalisation. Latent class analysis determined trajectories of depression. Path analysis was used to test relationships among vulnerabilities, depression trajectories and outcomes (combination of 1-year morbidity and 7-year mortality). Vulnerabilities independently predicted persistent and subthreshold depression trajectory categories, with effect sizes significantly highest for persistent depression. Both subthreshold and persistent depression trajectories were significant predictors of morbidity/mortality (e.g. persistent depression OR=2.4, 95% CI=1.8-3.1, relative to never depressed). Causality cannot be inferred from these associations. We had no measures of history of depression or treatments, which may affect associations. Theoretical vulnerabilities predicted depression trajectories, which in turn predicted increased morbidity/mortality, demonstrating for the first time a potential longitudinal chain of events post-ACS. This longitudinal model has important practical implications as clinicians can use vulnerability measures to identify those at most risk of poor outcomes. Copyright © 2015. Published by Elsevier B.V.
NASA Technical Reports Server (NTRS)
Sauer, Carl G., Jr.
1989-01-01
A patched conic trajectory optimization program MIDAS is described that was developed to investigate a wide variety of complex ballistic heliocentric transfer trajectories. MIDAS includes the capability of optimizing trajectory event times such as departure date, arrival date, and intermediate planetary flyby dates and is able to both add and delete deep space maneuvers when dictated by the optimization process. Both powered and unpowered flyby or gravity assist trajectories of intermediate bodies can be handled and capability is included to optimize trajectories having a rendezvous with an intermediate body such as for a sample return mission. Capability is included in the optimization process to constrain launch energy and launch vehicle parking orbit parameters.
Sridharan, Sanjeev; Jones, Bobby; Caudill, Barry; Nakaima, April
2016-10-01
This paper describes a framework that can help refine program theory through data explorations and stakeholder dialogue. The framework incorporates the following steps: a recognition that program implementation might need to be multi-phased for a number of interventions, the need to take stock of program theory, the application of pattern recognition methods to help identify heterogeneous program mechanisms, and stakeholder dialogue to refine the program. As part of the data exploration, a method known as developmental trajectories is implemented to learn about heterogeneous trajectories of outcomes in longitudinal evaluations. This method identifies trajectory clusters and also can estimate different treatment impacts for the various groups. The framework is highlighted with data collected in an evaluation of an alcohol risk-reduction program delivered in a college fraternity setting. The framework discussed in the paper is informed by a realist focus on "what works for whom under what contexts." The utility of the framework in contributing to a dialogue on heterogeneous mechanism and subsequent implementation is described. The connection of the ideas in paper to a 'learning through principled discovery' approach is also described. Copyright © 2016. Published by Elsevier Ltd.
Developmental Trajectories of Anxiety Symptoms Among Boys Across Early and Middle Childhood
Feng, Xin; Shaw, Daniel S.; Silk, Jennifer S.
2009-01-01
This study examined the developmental trajectory of anxiety symptoms among 290 boys and evaluated the association of trajectory groups with child and family risk factors and children’s internalizing disorders. Anxiety symptoms were measured using maternal reports from the Child Behavior Checklist (T. M. Achenbach, 1991, 1992) for boys between the ages of 2 and 10. A group-based trajectory analysis revealed 4 distinct trajectories in the development of anxiety symptoms: low, low increasing, high declining, and high-increasing trajectories. Child shy temperament tended to differentiate between initial high and low groups, whereas maternal negative control and maternal depression were associated with increasing trajectories and elevated anxiety symptoms in middle childhood. Follow-up analyses to diagnoses of preadolescent depression and/or anxiety disorders revealed different patterns on the basis of trajectory group membership. The results are discussed in terms of the mechanisms of risk factors and implications for early identification and prevention. PMID:18266484
Ares I-X Best Estimated Trajectory Analysis and Results
NASA Technical Reports Server (NTRS)
Karlgaard, Christopher D.; Beck, Roger E.; Starr, Brett R.; Derry, Stephen D.; Brandon, Jay; Olds, Aaron D.
2011-01-01
The Ares I-X trajectory reconstruction produced best estimated trajectories of the flight test vehicle ascent through stage separation, and of the first and upper stage entries after separation. The trajectory reconstruction process combines on-board, ground-based, and atmospheric measurements to produce the trajectory estimates. The Ares I-X vehicle had a number of on-board and ground based sensors that were available, including inertial measurement units, radar, air-data, and weather balloons. However, due to problems with calibrations and/or data, not all of the sensor data were used. The trajectory estimate was generated using an Iterative Extended Kalman Filter algorithm, which is an industry standard processing algorithm for filtering and estimation applications. This paper describes the methodology and results of the trajectory reconstruction process, including flight data preprocessing and input uncertainties, trajectory estimation algorithms, output transformations, and comparisons with preflight predictions.
NASA Technical Reports Server (NTRS)
Patrick, Sean; Oliver, Emerson
2018-01-01
One of the SLS Navigation System's key performance requirements is a constraint on the payload system's delta-v allocation to correct for insertion errors due to vehicle state uncertainty at payload separation. The SLS navigation team has developed a Delta-Delta-V analysis approach to assess the effect on trajectory correction maneuver (TCM) design needed to correct for navigation errors. This approach differs from traditional covariance analysis based methods and makes no assumptions with regard to the propagation of the state dynamics. This allows for consideration of non-linearity in the propagation of state uncertainties. The Delta-Delta-V analysis approach re-optimizes perturbed SLS mission trajectories by varying key mission states in accordance with an assumed state error. The state error is developed from detailed vehicle 6-DOF Monte Carlo analysis or generated using covariance analysis. These perturbed trajectories are compared to a nominal trajectory to determine necessary TCM design. To implement this analysis approach, a tool set was developed which combines the functionality of a 3-DOF trajectory optimization tool, Copernicus, and a detailed 6-DOF vehicle simulation tool, Marshall Aerospace Vehicle Representation in C (MAVERIC). In addition to delta-v allocation constraints on SLS navigation performance, SLS mission requirement dictate successful upper stage disposal. Due to engine and propellant constraints, the SLS Exploration Upper Stage (EUS) must dispose into heliocentric space by means of a lunar fly-by maneuver. As with payload delta-v allocation, upper stage disposal maneuvers must place the EUS on a trajectory that maximizes the probability of achieving a heliocentric orbit post Lunar fly-by considering all sources of vehicle state uncertainty prior to the maneuver. To ensure disposal, the SLS navigation team has developed an analysis approach to derive optimal disposal guidance targets. This approach maximizes the state error covariance prior to the maneuver to develop and re-optimize a nominal disposal maneuver (DM) target that, if achieved, would maximize the potential for successful upper stage disposal. For EUS disposal analysis, a set of two tools was developed. The first considers only the nominal pre-disposal maneuver state, vehicle constraints, and an a priori estimate of the state error covariance. In the analysis, the optimal nominal disposal target is determined. This is performed by re-formulating the trajectory optimization to consider constraints on the eigenvectors of the error ellipse applied to the nominal trajectory. A bisection search methodology is implemented in the tool to refine these dispersions resulting in the maximum dispersion feasible for successful disposal via lunar fly-by. Success is defined based on the probability that the vehicle will not impact the lunar surface and will achieve a characteristic energy (C3) relative to the Earth such that it is no longer in the Earth-Moon system. The second tool propagates post-disposal maneuver states to determine the success of disposal for provided trajectory achieved states. This is performed using the optimized nominal target within the 6-DOF vehicle simulation. This paper will discuss the application of the Delta-Delta-V analysis approach for performance evaluation as well as trajectory re-optimization so as to demonstrate the system's capability in meeting performance constraints. Additionally, further discussion of the implementation of assessing disposal analysis will be provided.
CRISPR Diversity and Microevolution in Clostridium difficile
Andersen, Joakim M.; Shoup, Madelyn; Robinson, Cathy; Britton, Robert; Olsen, Katharina E.P.; Barrangou, Rodolphe
2016-01-01
Abstract Virulent strains of Clostridium difficile have become a global health problem associated with morbidity and mortality. Traditional typing methods do not provide ideal resolution to track outbreak strains, ascertain genetic diversity between isolates, or monitor the phylogeny of this species on a global basis. Here, we investigate the occurrence and diversity of clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated genes (cas) in C. difficile to assess the potential of CRISPR-based phylogeny and high-resolution genotyping. A single Type-IB CRISPR-Cas system was identified in 217 analyzed genomes with cas gene clusters present at conserved chromosomal locations, suggesting vertical evolution of the system, assessing a total of 1,865 CRISPR arrays. The CRISPR arrays, markedly enriched (8.5 arrays/genome) compared with other species, occur both at conserved and variable locations across strains, and thus provide a basis for typing based on locus occurrence and spacer polymorphism. Clustering of strains by array composition correlated with sequence type (ST) analysis. Spacer content and polymorphism within conserved CRISPR arrays revealed phylogenetic relationship across clades and within ST. Spacer polymorphisms of conserved arrays were instrumental for differentiating closely related strains, e.g., ST1/RT027/B1 strains and pathogenicity locus encoding ST3/RT001 strains. CRISPR spacers showed sequence similarity to phage sequences, which is consistent with the native role of CRISPR-Cas as adaptive immune systems in bacteria. Overall, CRISPR-Cas sequences constitute a valuable basis for genotyping of C. difficile isolates, provide insights into the micro-evolutionary events that occur between closely related strains, and reflect the evolutionary trajectory of these genomes. PMID:27576538
NASA Astrophysics Data System (ADS)
Lian, Liping; Song, Weiguo; Richard, Yuen Kwok Kit; Ma, Jian; Telesca, Luciano
2017-03-01
Pedestrian stampede happened more and more often during these years, such as Love Parade disaster in Germany 2010, trampling in Shanghai bund 2014 and crowd stampede in pilgrimages. Love Parade disaster 2010 stands out for well recorded videos, which are HD quality and available for researchers. There were totally seven surveillance cameras capturing the whole festival progress and the video we study is just before the disaster happened. Pedestrian motion was special and a small disturbance would lead the group to an avalanche in this kind of critical situation. Here we focus on the individual movement pattern. The trajectories of each pedestrian involved were extracted by a mean-shift algorithm. We analyzed the space-time patterns of the pedestrians involved in the Love Parade stampede by using the detrended fluctuation analysis and the coefficient of variation. Our results reveal that the pedestrians' movement in crowd-quakes is persistent in space, globally time-clusterized but locally regular or quasi-periodic behavior. Pedestrian movement was treated as stop and go state by point process-based representation. When the threshold increases, this means that the "go" state is longer and pedestrians keep on walking in several consecutive time frames; this is difficult in crowded situations and lead to special time-clustering behavior of the sequence of "go" events. The study reveals pedestrian motion characteristics in critical situations, which will enhance the understanding of pedestrian behaviors and supply early warning features for not only Love Parade Disaster, but also other similar large events.
The kinematics of the Scorpius-Centaurus OB association from Gaia DR1
NASA Astrophysics Data System (ADS)
Wright, Nicholas J.; Mamajek, Eric E.
2018-05-01
We present a kinematic study of the Scorpius-Centaurus (Sco-Cen) OB association (Sco OB2) using Gaia DR1 parallaxes and proper motions. Our goal is to test the classical theory that OB associations are the expanded remnants of dense and compact star clusters disrupted by processes such as residual gas expulsion. Gaia astrometry is available for 258 out of 433 members of the association, with revised Hipparcos astrometry used for the remainder. We use these data to confirm that the three subgroups of Sco-Cen are gravitationally unbound and have non-isotropic velocity dispersions, suggesting that they have not had time to dynamically relax. We also explore the internal kinematics of the subgroups to search for evidence of expansion. We test Blaauw's classical linear model of expansion, search for velocity trends along the Galactic axes, compare the expanding and non-expanding convergence points, perform traceback analysis assuming both linear trajectories and using an epicycle approximation, and assess the evidence for expansion in proper motions corrected for virtual expansion/contraction. None of these methods provide coherent evidence for expansion of the subgroups, with no evidence to suggest that the subgroups had a more compact configuration in the past. We find evidence for kinematic substructure within the subgroups that supports the view that they were not formed by the disruption of individual star clusters. We conclude that Sco-Cen was likely to have been born highly substructured, with multiple small-scale star formation events contributing to the overall OB association, and not as single, monolithic burst of clustered star formation.
Bruno, Agostino; Beato, Claudia; Costantino, Gabriele
2011-04-01
G-protein coupled receptors may exist as functional homodimers, heterodimers and even as higher aggregates. In this work, we investigate the 5-HT(2A) receptor, which is a known target for antipsychotic drugs. Recently, 5-HT(2A) has been shown to form functional homodimers and heterodimers with the mGluR2 receptor. The objective of this study is to build up 3D models of the 5-HT(2A)/mGluR2 heterodimer and of the 5-HT(2A)-5-HT(2A) homodimer, and to evaluate the impact of the dimerization interface on the shape of the 5-HT(2A) binding pocket by using molecular dynamics simulations and docking studies. The heterodimer, homodimer and monomeric 5-HT(2A) receptors were simulated by molecular dynamics for 40 ns each. The trajectories were clustered and representative structures of six clusters for each system were generated. Inspection of the these representative structures clearly indicate an effect of the dimerization interface on the topology of the binding pocket. Docking studies allowed to generate receiver operating characteristic curves for a set of 5-HT(2A) ligands, indicating that different complexes prefer different classes of 5-HT(2A) ligands. This study clearly indicates that the presence of a dimerization interface must explicitly be considered when studying G-protein coupled receptors known to exist as dimers. Molecular dynamics simulation and cluster analysis are appropriate tools to study the phenomenon.
Multiple Trajectories of Successful Aging of Older and Younger Cohorts
ERIC Educational Resources Information Center
Hsu, Hui-Chuan; Jones, Bobby L.
2012-01-01
Purpose: The purpose of this study was to apply group-based trajectory analysis to identify multiple successful aging trajectories by multiple indicators and to examine the factors related to successful aging among the elderly population in Taiwan. Design and Methods: Nation-representative longitudinal data collected from 1993 to 2007 and…
Computer program documentation user information for the MPAD trajectory tape print program (TRJPR1)
NASA Technical Reports Server (NTRS)
Gibbs, P. M.
1981-01-01
The Trajectory Tape Print Program (TRJPR1) was developed to print applicable information from a Space Trajectory tape created by the Mission Planning and Analysis Division (MPAD) in the MPAD Common Format for the on-orbit phase of the Mission. Instructions for TRJPR1's use are given.
Soccer Ball Lift Coefficients via Trajectory Analysis
ERIC Educational Resources Information Center
Goff, John Eric; Carre, Matt J.
2010-01-01
We performed experiments in which a soccer ball was launched from a machine while two high-speed cameras recorded portions of the trajectory. Using the trajectory data and published drag coefficients, we extracted lift coefficients for a soccer ball. We determined lift coefficients for a wide range of spin parameters, including several spin…
ERIC Educational Resources Information Center
Jahromi, Laudan B.; Umaña-Taylor, Adriana J.; Updegraff, Kimberly A.; Zeiders, Katharine H.
2016-01-01
Children of adolescent mothers are at risk for developmental delays. Less is known about the heterogeneity in these children's developmental trajectories, and factors associated with different patterns of development. This longitudinal study used latent class growth analysis (LCGA) to identify distinct trajectories in children of Mexican-origin…
Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram
2017-01-01
Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed similarities to Concord grape and indicates the strong effect of genetic background on metabolic partitioning in primary and secondary metabolism.
Wang, Lei; Sun, Xiaoliang; Weiszmann, Jakob; Weckwerth, Wolfram
2017-01-01
Grapevine is a fruit crop with worldwide economic importance. The grape berry undergoes complex biochemical changes from fruit set until ripening. This ripening process and production processes define the wine quality. Thus, a thorough understanding of berry ripening is crucial for the prediction of wine quality. For a systemic analysis of grape berry development we applied mass spectrometry based platforms to analyse the metabolome and proteome of Early Campbell at 12 stages covering major developmental phases. Primary metabolites involved in central carbon metabolism, such as sugars, organic acids and amino acids together with various bioactive secondary metabolites like flavonols, flavan-3-ols and anthocyanins were annotated and quantified. At the same time, the proteomic analysis revealed the protein dynamics of the developing grape berries. Multivariate statistical analysis of the integrated metabolomic and proteomic dataset revealed the growth trajectory and corresponding metabolites and proteins contributing most to the specific developmental process. K-means clustering analysis revealed 12 highly specific clusters of co-regulated metabolites and proteins. Granger causality network analysis allowed for the identification of time-shift correlations between metabolite-metabolite, protein- protein and protein-metabolite pairs which is especially interesting for the understanding of developmental processes. The integration of metabolite and protein dynamics with their corresponding biochemical pathways revealed an energy-linked metabolism before veraison with high abundances of amino acids and accumulation of organic acids, followed by protein and secondary metabolite synthesis. Anthocyanins were strongly accumulated after veraison whereas other flavonoids were in higher abundance at early developmental stages and decreased during the grape berry developmental processes. A comparison of the anthocyanin profile of Early Campbell to other cultivars revealed similarities to Concord grape and indicates the strong effect of genetic background on metabolic partitioning in primary and secondary metabolism. PMID:28713396
How a visual surveillance system hypothesizes how you behave.
Micheloni, C; Piciarelli, C; Foresti, G L
2006-08-01
In the last few years, the installation of a large number of cameras has led to a need for increased capabilities in video surveillance systems. It has, indeed, been more and more necessary for human operators to be helped in the understanding of ongoing activities in real environments. Nowadays, the technology and the research in the machine vision and artificial intelligence fields allow one to expect a new generation of completely autonomous systems able to reckon the behaviors of entities such as pedestrians, vehicles, and so forth. Hence, whereas the sensing aspect of these systems has been the issue considered the most so far, research is now focused mainly on more newsworthy problems concerning understanding. In this article, we present a novel method for hypothesizing the evolution of behavior. For such purposes, the system is required to extract useful information by means of low-level techniques for detecting and maintaining track of moving objects. The further estimation of performed trajectories, together with objects classification, enables one to compute the probability distribution of the normal activities (e.g., trajectories). Such a distribution is defined by means of a novel clustering technique. The resulting clusters are used to estimate the evolution of objects' behaviors and to speculate about any intention to act dangerously. The provided solution for hypothesizing behaviors occurring in real environments was tested in the context of an outdoor parking lot
Tsur, Noga; Defrin, Ruth; Lahav, Yael; Solomon, Zahava
2018-03-01
Orientation to bodily signals is defined as the way somatic sensations are attended, perceived and interpreted. Research suggests that trauma exposure, particularly the pathological reaction to trauma (i.e., PTSD), is associated with catastrophic and frightful orientation to bodily signals. However, little is known regarding the long-term ramifications of trauma exposure and PTSD for orientation to bodily signals. Less is known regarding which PTSD symptom cluster manifests in the 'somatic route' through which orientation to bodily signals is altered. The current study examined the long-term implications of trauma and PTSD trajectories on orientation to bodily signals. Fifty-nine ex-prisoners of war (ex-POWs) and 44 controls were assessed for PTSD along three time-points (18, 30 and 35 years post-war). Orientation to bodily signals (pain catastrophizing and anxiety sensitivity-physical concerns) was assessed at T3. Participants with a chronic PTSD trajectory had higher pain catastrophizing compared to participants with no PTSD. PTSD symptom severity at T2 and T3 mediated the association between captivity and orientation. Among PTSD symptom clusters, hyperarousal at two time-points and intrusion at three time-point mediated the association between captivity and orientation. These findings allude to the cardinal role of long-term PTSD in the subjective experience of the body following trauma. Copyright © 2018 Elsevier B.V. All rights reserved.
Space Trajectories Error Analysis (STEAP) Programs. Volume 1: Analytic manual, update
NASA Technical Reports Server (NTRS)
1971-01-01
Manual revisions are presented for the modified and expanded STEAP series. The STEAP 2 is composed of three independent but related programs: NOMAL for the generation of n-body nominal trajectories performing a number of deterministic guidance events; ERRAN for the linear error analysis and generalized covariance analysis along specific targeted trajectories; and SIMUL for testing the mathematical models used in the navigation and guidance process. The analytic manual provides general problem description, formulation, and solution and the detailed analysis of subroutines. The programmers' manual gives descriptions of the overall structure of the programs as well as the computational flow and analysis of the individual subroutines. The user's manual provides information on the input and output quantities of the programs. These are updates to N69-36472 and N69-36473.
Ares-I-X Vehicle Preliminary Range Safety Malfunction Turn Analysis
NASA Technical Reports Server (NTRS)
Beaty, James R.; Starr, Brett R.; Gowan, John W., Jr.
2008-01-01
Ares-I-X is the designation given to the flight test version of the Ares-I rocket (also known as the Crew Launch Vehicle - CLV) being developed by NASA. As part of the preliminary flight plan approval process for the test vehicle, a range safety malfunction turn analysis was performed to support the launch area risk assessment and vehicle destruct criteria development processes. Several vehicle failure scenarios were identified which could cause the vehicle trajectory to deviate from its normal flight path, and the effects of these failures were evaluated with an Ares-I-X 6 degrees-of-freedom (6-DOF) digital simulation, using the Program to Optimize Simulated Trajectories Version 2 (POST2) simulation framework. The Ares-I-X simulation analysis provides output files containing vehicle state information, which are used by other risk assessment and vehicle debris trajectory simulation tools to determine the risk to personnel and facilities in the vicinity of the launch area at Kennedy Space Center (KSC), and to develop the vehicle destruct criteria used by the flight test range safety officer. The simulation analysis approach used for this study is described, including descriptions of the failure modes which were considered and the underlying assumptions and ground rules of the study, and preliminary results are presented, determined by analysis of the trajectory deviation of the failure cases, compared with the expected vehicle trajectory.
[Spatiotemporal trends and the impact factors of acid rain in Anhui Province].
Shi, Chun-E; Qiu, Ming-Yan; Zhang, Ai-Min; Zhang, Hao; Zhang, Su; Wang, Zi-Fa
2010-06-01
The observational data of acid rain at seven stations in Anhui province operated by China Meteorological Administration (CMA), as well as the coal consumptions in Anhui and some surrounding provinces along with satellite measured tropospheric NO2 columns, were used to analyze the spatiotemporal trends of acid rain in Anhui and the potential reasons of the increasing occurrence frequency of acid rain. In addition, the technique of back-trajectory-cluster analysis was used to examine the impacts of transport patterns on the precipitation acidity in Anhui. The occurrence frequency shows the lowest in summer and the highest in autumn, with 3-year average pH < 5.6 during 2006-2008 at all stations, hereinto, pH values are between 5.0 and 4.5 in Hefei, Anqing, Maanshan and Bengbu. In spatial, acid rain were the most severe in southern to middle Anhui and mitigated to north. The distributions of pH were concentrative at Fuyang, Tongling and Huangshan, with more than 75% occurred between 6.00-7.50 (Fuyang), 5.00-6.00 (Tongling) and 5.00-6.50 (Huangshan); quite dispersive at other stations, with the maximum at 4.00-4.50 (Hefei and Anqing), 5.00-5.50 (Maanshan) and 5.50-6.00 (Bengbu). The occurrence frequencies of acid rain increased evidently at all stations comparing with those in the end of 1990s. The results of back-trajectories-cluster analysis show that the acid rain is closely related with the regional-range transport of acid rain precursors at each station. The air-masses from southeast and northeast, especially those passing through Jiangsu and Zhejiang, associated with the highest frequencies of acid rain with pH < 5.0, indicating that the industrial emissions in the economy developed areas of Yangtze Delta play key roles in acid rain in Anhui province. In addition, statistics shows that the occurrence frequency of acid rain in Hefei was highly correlated with the trends of the provincial coal consumptions in Anhui, Jiangsu and Zhejiang, also tropospheric NO2 column content over Anhui province and surrounding areas with all correlation coefficients > 0.7, suggesting the close relationship between the quick increasing acid rain in Hefei and the regional pollutant emissions.
A Distributed Trajectory-Oriented Approach to Managing Traffic Complexity
NASA Technical Reports Server (NTRS)
Idris, Husni; Wing, David J.; Vivona, Robert; Garcia-Chico, Jose-Luis
2007-01-01
In order to handle the expected increase in air traffic volume, the next generation air transportation system is moving towards a distributed control architecture, in which ground-based service providers such as controllers and traffic managers and air-based users such as pilots share responsibility for aircraft trajectory generation and management. While its architecture becomes more distributed, the goal of the Air Traffic Management (ATM) system remains to achieve objectives such as maintaining safety and efficiency. It is, therefore, critical to design appropriate control elements to ensure that aircraft and groundbased actions result in achieving these objectives without unduly restricting user-preferred trajectories. This paper presents a trajectory-oriented approach containing two such elements. One is a trajectory flexibility preservation function, by which aircraft plan their trajectories to preserve flexibility to accommodate unforeseen events. And the other is a trajectory constraint minimization function by which ground-based agents, in collaboration with air-based agents, impose just-enough restrictions on trajectories to achieve ATM objectives, such as separation assurance and flow management. The underlying hypothesis is that preserving trajectory flexibility of each individual aircraft naturally achieves the aggregate objective of avoiding excessive traffic complexity, and that trajectory flexibility is increased by minimizing constraints without jeopardizing the intended ATM objectives. The paper presents conceptually how the two functions operate in a distributed control architecture that includes self separation. The paper illustrates the concept through hypothetical scenarios involving conflict resolution and flow management. It presents a functional analysis of the interaction and information flow between the functions. It also presents an analytical framework for defining metrics and developing methods to preserve trajectory flexibility and minimize its constraints. In this framework flexibility is defined in terms of robustness and adaptability to disturbances and the impact of constraints is illustrated through analysis of a trajectory solution space with limited degrees of freedom and in simple constraint situations involving meeting multiple times of arrival and resolving a conflict.
Slator, Paddy J.; Cairo, Christopher W.; Burroughs, Nigel J.
2015-01-01
We develop a Bayesian analysis framework to detect heterogeneity in the diffusive behaviour of single particle trajectories on cells, implementing model selection to classify trajectories as either consistent with Brownian motion or with a two-state (diffusion coefficient) switching model. The incorporation of localisation accuracy is essential, as otherwise false detection of switching within a trajectory was observed and diffusion coefficient estimates were inflated. Since our analysis is on a single trajectory basis, we are able to examine heterogeneity between trajectories in a quantitative manner. Applying our method to the lymphocyte function-associated antigen 1 (LFA-1) receptor tagged with latex beads (4 s trajectories at 1000 frames s−1), both intra- and inter-trajectory heterogeneity were detected; 12–26% of trajectories display clear switching between diffusive states dependent on condition, whilst the inter-trajectory variability is highly structured with the diffusion coefficients being related by D 1 = 0.68D 0 − 1.5 × 104 nm2 s−1, suggestive that on these time scales we are detecting switching due to a single process. Further, the inter-trajectory variability of the diffusion coefficient estimates (1.6 × 102 − 2.6 × 105 nm2 s−1) is very much larger than the measurement uncertainty within trajectories, suggesting that LFA-1 aggregation and cytoskeletal interactions are significantly affecting mobility, whilst the timescales of these processes are distinctly different giving rise to inter- and intra-trajectory variability. There is also an ‘immobile’ state (defined as D < 3.0 × 103 nm2 s−1) that is rarely involved in switching, immobility occurring with the highest frequency (47%) under T cell activation (phorbol-12-myristate-13-acetate (PMA) treatment) with enhanced cytoskeletal attachment (calpain inhibition). Such ‘immobile’ states frequently display slow linear drift, potentially reflecting binding to a dynamic actin cortex. Our methods allow significantly more information to be extracted from individual trajectories (ultimately limited by time resolution and time-series length), and allow statistical comparisons between trajectories thereby quantifying inter-trajectory heterogeneity. Such methods will be highly informative for the construction and fitting of molecule mobility models within membranes incorporating aggregation, binding to the cytoskeleton, or traversing membrane microdomains. PMID:26473352
Leonard, Stephanie A; Rasmussen, Kathleen M; King, Janet C; Abrams, Barbara
2017-11-01
Background: Prepregnancy body mass index [BMI (in kg/m 2 )], gestational weight gain, and postpartum weight retention may have distinct effects on the development of child obesity, but their combined effect is currently unknown. Objective: We described longitudinal trajectories of maternal weight from before pregnancy through the postpartum period and assessed the relations between maternal weight trajectories and offspring obesity in childhood. Design: We analyzed data from 4436 pairs of mothers and their children in the National Longitudinal Survey of Youth 1979 (1981-2014). We used latent-class growth modeling in addition to national recommendations for prepregnancy BMI, gestational weight gain, and postpartum weight retention to create maternal weight trajectory groups. We used modified Poisson regression models to assess the associations between maternal weight trajectory group and offspring obesity at 3 age periods (2-5, 6-11, and 12-19 y). Results: Our analysis using maternal weight trajectories based on either latent-class results or recommendations showed that the risk of child obesity was lowest in the lowest maternal weight trajectory group. The differences in obesity risk were largest after 5 y of age and persisted into adolescence. In the latent-class analysis, the highest-order maternal weight trajectory group consisted almost entirely of women who were obese before pregnancy and was associated with a >2-fold increase in the risk of offspring obesity at ages 6-11 y (adjusted RR: 2.39; 95% CI: 1.97, 2.89) and 12-19 y (adjusted RR: 2.74; 95% CI: 2.13, 3.52). In the analysis with maternal weight trajectory groups based on recommendations, the risk of child obesity was consistently highest for women who were overweight or obese at the beginning of pregnancy. Conclusion: These findings suggest that high maternal weight across the childbearing period increases the risk of obesity in offspring during childhood, but high prepregnancy BMI has a stronger influence than either gestational weight gain or postpartum weight retention. © 2017 American Society for Nutrition.
Mars entry-to-landing trajectory optimization and closed loop guidance
NASA Technical Reports Server (NTRS)
Ilgen, Marc R.; Manning, Raymund A.; Cruz, Manuel I.
1991-01-01
The guidance strategy of the Mars Rover Sample Return mission is presented in detail. Aeromaneuver versus aerobrake trades are examined, and an aerobrake analysis is presented which takes into account targeting, guidance, flight control, trajectory profile, delivery accuracy. An aeromaneuver analysis is given which includes the entry corridor, maneuver footprint, guidance, preentry phase, constant drag phase, equilibrium guide phase, variable drag phase, influence of trajectory profile on the entry flight loads, parachute deployment conditions and strategies, and landing accuracy. The Mars terminal descent phase is analyzed.
Røsstad, Tove; Salvesen, Øyvind; Steinsbekk, Aslak; Grimsmo, Anders; Sletvold, Olav; Garåsen, Helge
2017-04-17
Improved discharge arrangements and targeted post-discharge follow-up can reduce the risk of adverse events after hospital discharge for elderly patients. Although more care is to shift from specialist to primary care, there are few studies on post-discharge interventions run by primary care. A generic care pathway, Patient Trajectory for Home-dwelling elders (PaTH) including discharge arrangements and follow-up by primary care, was developed and introduced in Central Norway Region in 2009, applying checklists at defined stages in the patient trajectory. In a previous paper, we found that PaTH had potential of improving follow-up in primary care. The aim of this study was to establish the effect of PaTH-compared to usual care-for elderly in need of home care services after discharge from hospital. We did an unblinded, cluster randomised controlled trial with 12 home care clusters. Outcomes were measured at the patient level during a 12-month follow-up period for the individual patient and analysed applying linear and logistic mixed models. Primary outcomes were readmissions within 30 days and functional level assessed by Nottingham extended ADL scale. Secondary outcomes were number and length of inpatient hospital care and nursing home care, days at home, consultations with the general practitioners (GPs), mortality and health related quality of life (SF-36). One-hundred and sixty-three patients were included in the PaTH group (six clusters), and 141 patients received care as usual (six clusters). We found no statistically significant differences between the groups for primary and secondary outcomes except for more consultations with the GPs in PaTH group (p = 0.04). Adherence to the intervention was insufficient as only 36% of the patients in the intervention group were assessed by at least three of the four main checklists in PaTH, but this improved over time. Lack of adherence to PaTH rendered the study inconclusive regarding the elderly's functional level, number of readmissions after hospital discharge, and health care utilisation except for more consultations with the GPs. A targeted exploration of prerequisites for implementation is recommended in the pre-trial phase of complex intervention studies. Clinical Trials.gov NCT01107119 , retrospectively registered 2010.04.18.
Mercuri, Eugenio; Signorovitch, James Edward; Swallow, Elyse; Song, Jinlin; Ward, Susan J
2016-09-01
High variability in patients' changes in 6 minute walk distance (6MWD) over time has complicated clinical trials of treatment efficacy in Duchenne muscular dystrophy (DMD). We assessed whether boys with DMD could be grouped into classes that shared similar ambulatory function trajectories as measured by 6MWD. Ambulatory boys aged 5 years or older with genetically confirmed DMD who were enrolled in a natural history study at 11 care centers throughout Italy were included. For each boy, standardized assessments of 6MWD were available at annual intervals spanning 3 years. Trajectories of 6MWD vs. age and trajectories of 6MWD vs. time from enrollment were examined using latent class analysis. A total of 96 boys were included. At enrollment, the mean age was 8.3 years (mean 6MWD: 374 meters). After accounting for age, baseline 6MWD, and steroid use, four latent trajectory classes were identified as explaining 3-year 6MWD outcomes significantly better than a single average trajectory. Patient trajectories of 6MWD change from enrollment were categorized as having fast decline (n = 25), moderate decline (n = 19), stable function (n = 37), and improving function (n = 15) during the 3-year follow-up. After accounting for trajectory classes, the standard deviation of variation in 6MWD was reduced by approximately 40%. The natural history of ambulatory function in DMD may be composed of distinct trajectory classes. The extent to which trajectories are associated with novel and established prognostic factors warrants further study. Reducing unexplained variation in patient outcomes could help to further improve DMD clinical trial design and analysis. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.
Importance of many-body dispersion and temperature effects on gas-phase gold cluster (meta)stability
NASA Astrophysics Data System (ADS)
Goldsmith, Bryan R.; Gruene, Philipp; Lyon, Jonathan T.; Rayner, David M.; Fielicke, André; Scheffler, Matthias; Ghiringhelli, Luca M.
Gold clusters in the gas phase exhibit many structural isomers that are shown to intercovert frequently, even at room temperature. We performed ab initio replica-exchange molecular dynamics (REMD) calculations on gold clusters (of sizes 5-14 atoms) to identify metastable states and their relative populations at finite temperature, as well as to examine the importance of temperature and van der Waals (vdW) on their isomer energetic ordering. Free energies of the gold cluster isomers are optimally estimated using the Multistate Bennett Acceptance Ratio. The distribution of bond coordination numbers and radius of gyration are used to address the challenge of discriminating isomers along their dynamical trajectories. Dispersion effects are important for stabilizing three-dimensional structures relative to planar structures and brings isomer energetic predictions to closer quantitative agreement compared with RPA@PBE calculations. We find that higher temperatures typically stabilize metastable three-dimensional structures relative to planar/quasiplanar structures. Computed IR spectra of low free energy Au9, Au10, and Au12 isomers are in agreement with experimental spectra obtained by far-IR multiple photon dissociation in a molecular beam at 100 K.
Novel Flood Detection and Analysis Method Using Recurrence Property
NASA Astrophysics Data System (ADS)
Wendi, Dadiyorto; Merz, Bruno; Marwan, Norbert
2016-04-01
Temporal changes in flood hazard are known to be difficult to detect and attribute due to multiple drivers that include processes that are non-stationary and highly variable. These drivers, such as human-induced climate change, natural climate variability, implementation of flood defence, river training, or land use change, could impact variably on space-time scales and influence or mask each other. Flood time series may show complex behavior that vary at a range of time scales and may cluster in time. This study focuses on the application of recurrence based data analysis techniques (recurrence plot) for understanding and quantifying spatio-temporal changes in flood hazard in Germany. The recurrence plot is known as an effective tool to visualize the dynamics of phase space trajectories i.e. constructed from a time series by using an embedding dimension and a time delay, and it is known to be effective in analyzing non-stationary and non-linear time series. The emphasis will be on the identification of characteristic recurrence properties that could associate typical dynamic behavior to certain flood situations.
Bravo, J A; Montanero, J; Calero, R; Roy, T J
2011-11-01
The aims of this study were to identify different motile sperm subpopulations in fresh ejaculates from six Ile de France rams, by using a computer-assisted sperm motility analysis (CASA) system, and to evaluate the effects of individual ram and season on population distribution. Overall sperm motility and individual kinematic parameters of motile spermatozoa were evaluated for 125,312 spermatozoa, defined by curvilinear velocity (VCL), linear velocity (VSL), average path velocity (VAP), linearity coefficient (LIN), straightness coefficient (STR), wobble coefficient (WOB), mean amplitude of lateral head displacement (ALH) and frequency of head displacement (BCF). A multivariate cluster analysis was carried out to classify these spermatozoa into a reduced number of subpopulations according to their movement patterns. The statistical analysis clustered the whole motile sperm population into five separate groups: subpopulation 1, constituted by rapid, progressive and non sinuous spermatozoa (VCL=126.41 μm/s, STR=92.87% and LIN=86.47%); subpopulation 2, characterized by progressive spermatozoa with moderate velocity (VCL=74.74 μm/s and STR=84.03%); subpopulation 3, represented by rapid, progressive and sinuous spermatozoa (VCL=130.45 μm/s, STR=76.02% and LIN=47.68%); subpopulation 4 represents rapid nonprogressive spermatozoa (VCL=128.69 μm/s and STR=44.09%); subpopulation 5 includes poorly motile, nonprogressive spermatozoa with a very irregular trajectory (VCL=36.81 μm/s and STR=47.04%). Our results show the existence of five subpopulations of motile spermatozoa in ram ejaculates. The frequency distribution of spermatozoa within subpopulations was quite similar for the six rams, and the five subpopulations turned out to be very stable along seasons. Copyright © 2011 Elsevier B.V. All rights reserved.
Construction of Shale Gas Well
NASA Astrophysics Data System (ADS)
Sapińska-Śliwa, Aneta; Wiśniowski, Rafał; Skrzypaszek, Krzysztof
2018-03-01
The paper describes shale gas borehole axes trajectories (vertical, horizontal, multilateral). The methodology of trajectory design in a two-and three-dimensional space has been developed. The selection of the profile type of the trajectory axes of the directional borehole depends on the technical and technological possibilities of its implementation and the results of a comprehensive economic analysis of the availability and development of the field. The work assumes the possibility of a multivariate design of trajectories depending on the accepted (available or imposed) input data.
Sabbath, Erika L; Mejía-Guevara, Iván; Noelke, Clemens; Berkman, Lisa F
2015-12-01
Work stress and family composition have been separately linked with later-life mortality among working women, but it is not known how combinations of these exposures impact mortality, particularly when exposure is assessed cumulatively over the life course. We tested whether, among US women, lifelong work stress and lifelong family circumstances would jointly predict mortality risk. We studied formerly working mothers in the US Health and Retirement Study (HRS) born 1924-1957 (n = 7352). We used sequence analysis to determine five prototypical trajectories of marriage and parenthood in our sample. Using detailed information on occupation and industry of each woman's longest-held job, we assigned each respondent a score for job control and job demands. We calculated age-standardized mortality rates by combined job demands, job control, and family status, then modeled hazard ratios for death based on family constellation, job control tertiles, and their combination. Married women who had children later in life had the lowest mortality risks (93/1000). The highest-risk family clusters were characterized by spells of single motherhood (132/1000). Generally, we observed linear relationships between job control and mortality hazard within each family trajectory. But while mortality risk was high for all long-term single mothers, we did not observe a job control-mortality gradient in this group. The highest-mortality subgroup was previously married women who became single mothers later in life and had low job control (HR 1.91, 95% CI 1.38,2.63). Studies of associations between psychosocial work characteristics and health might consider heterogeneity of effects by family circumstances. Worksite interventions simultaneously considering both work and family characteristics may be most effective in reducing health risks. Copyright © 2015 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Fawole, Olusegun G.; Cai, Xiaoming; Levine, James G.; Pinker, Rachel T.; MacKenzie, A. R.
2016-12-01
The West African region, with its peculiar climate and atmospheric dynamics, is a prominent source of aerosols. Reliable and long-term in situ measurements of aerosol properties are not readily available across the region. In this study, Version 2 Level 1.5 Aerosol Robotic Network (AERONET) data were used to study the absorption and size distribution properties of aerosols from dominant sources identified by trajectory analysis. The trajectory analysis was used to define four sources of aerosols over a 10 year period. Sorting the AERONET aerosol retrievals by these putative sources, the hypothesis that there exists an optically distinct gas flaring signal was tested. Dominance of each source cluster varies with season: desert-dust (DD) and biomass burning (BB) aerosols are dominant in months prior to the West African Monsoon (WAM); urban (UB) and gas flaring (GF) aerosol are dominant during the WAM months. BB aerosol, with single scattering albedo (SSA) at 675 nm value of 0.86 ± 0.03 and GF aerosol with SSA (675 nm) value of 0.9 ± 0.07, is the most absorbing of the aerosol categories. The range of Absorption Angstr&öm Exponent (AAE) for DD, BB, UB and GF classes are 1.99 ± 0.35, 1.45 ± 0.26, 1.21 ± 0.38 and 0.98 ± 0.25, respectively, indicating different aerosol composition for each source. The AAE (440-870 nm) and Angstr&öm Exponent (AE) (440-870 nm) relationships further show the spread and overlap of the variation of these optical and microphysical properties, presumably due in part to similarity in the sources of aerosols and in part, due to mixing of air parcels from different sources en route to the measurement site.
Sabbath, Erika L.; Mejía-Guevara, Iván; Noelke, Clemens; Berkman, Lisa F.
2015-01-01
Background Work stress and family composition have been separately linked to later-life mortality among working women, but it is not known how combinations of these exposures impact mortality, particularly when exposure is assessed cumulatively over the life course. We tested whether, among US women, lifelong work stress and lifelong family circumstances would jointly predict mortality risk. Procedures We studied formerly working mothers in the US Health and Retirement Study (HRS) born 1924-1957 (n=7,352). We used sequence analysis to determine five prototypical trajectories of marriage and parenthood in our sample. Using detailed information on occupation and industry of each woman’s longest-held job, we assigned each respondent a score for job control and job demands. We calculated age-standardized mortality rates by combined job demands, job control, and family status, then modeled hazard ratios for death based on family constellation, job control tertiles, and their combination. Results Married women who had children later in life had the lowest mortality risks (93/1,000). The highest-risk family clusters were characterized by spells of single motherhood (132/1,000). Generally, we observed linear relationships between job control and mortality hazard within each family trajectory. But while mortality risk was high for all long-term single mothers, we did not observe a job control-mortality gradient in this group. The highest-mortality subgroup was previously married women who became single mothers later in life and had low job control (HR 1.91, 95% CI 1.38,2.63). Practical implications Studies of associations between psychosocial work characteristics and health might consider heterogeneity of effects by family circumstances. Worksite interventions simultaneously considering both work and family characteristics may be most effective in reducing health risks. PMID:26513120
Complex Road Intersection Modelling Based on Low-Frequency GPS Track Data
NASA Astrophysics Data System (ADS)
Huang, J.; Deng, M.; Zhang, Y.; Liu, H.
2017-09-01
It is widely accepted that digital map becomes an indispensable guide for human daily traveling. Traditional road network maps are produced in the time-consuming and labour-intensive ways, such as digitizing printed maps and extraction from remote sensing images. At present, a large number of GPS trajectory data collected by floating vehicles makes it a reality to extract high-detailed and up-to-date road network information. Road intersections are often accident-prone areas and very critical to route planning and the connectivity of road networks is mainly determined by the topological geometry of road intersections. A few studies paid attention on detecting complex road intersections and mining the attached traffic information (e.g., connectivity, topology and turning restriction) from massive GPS traces. To the authors' knowledge, recent studies mainly used high frequency (1 s sampling rate) trajectory data to detect the crossroads regions or extract rough intersection models. It is still difficult to make use of low frequency (20-100 s) and easily available trajectory data to modelling complex road intersections geometrically and semantically. The paper thus attempts to construct precise models for complex road intersection by using low frequency GPS traces. We propose to firstly extract the complex road intersections by a LCSS-based (Longest Common Subsequence) trajectory clustering method, then delineate the geometry shapes of complex road intersections by a K-segment principle curve algorithm, and finally infer the traffic constraint rules inside the complex intersections.
ERIC Educational Resources Information Center
Pedersen, Sara
2005-01-01
This study applied individual growth trajectory analyses and person-oriented analysis to identify common profiles of out-of-school activity engagement trajectories among racially and ethnically diverse inner city teens (N = 1,430). On average, teens exhibited declining trajectories of participation in school-based and team sports activities and…
ERIC Educational Resources Information Center
Wiesner, Margit; Silbereisen, Rainer K.
2003-01-01
This longitudinal study examined individual, family, and peer covariates of distinctive trajectories of juvenile delinquency, using data from a community sample of 318 German adolescents (mean age at the first wave was 11.45 years). Latent growth mixture modelling analysis revealed four trajectory groups: high-level offenders, medium-level…
ERIC Educational Resources Information Center
Marti, C. Nathan; Stice, Eric; Springer, David W.
2010-01-01
We used data from a school-based study of 496 adolescent girls to identify qualitatively distinct substance use and substance abuse developmental trajectory groups and tested whether the problematic groups differed from the non-problematic groups on baseline and outcome validation variables. Results identified four substance use groups (late…
Educational Progress of Looked-After Children in England: A Study Using Group Trajectory Analysis.
Sutcliffe, Alastair G; Gardiner, Julian; Melhuish, Edward
2017-09-01
Looked-after children in local authority care are among the most disadvantaged, and measures of their well-being, including educational outcomes, are poorer than other children's. The study sample consisted of all children in England born in academic years 1993 to 1994 through 1997 to 1998 who were in local authority care at any point during the academic years 2005 to 2006 through 2012 to 2013 and for whom results of national tests in literacy and numeracy were available at ages 7, 11, and 16 ( N = 47 500). Group trajectory analysis of children's educational progress identified 5 trajectory groups: low achievement, late improvement, late decline, predominant, and high achievement. Being looked after earlier was associated with a higher probability of following a high achievement trajectory and a lower probability of following a late decline trajectory. For children first looked after between ages 7 and 16, having a longer total time looked after by age 16 was associated with a higher probability of following a high achievement trajectory. For children with poor outcomes at ages 7 and 11, being looked after by age 16 was associated with an increased chance of educational improvement by age 16. This study provides evidence that early entry into care can reduce the risk of poor educational outcomes. It also establishes group trajectory analysis as an effective method for analyzing the educational progress of looked-after children, with the particular strength that it allows factors associated with a late decline or improvement in educational progress to be identified. Copyright © 2017 by the American Academy of Pediatrics.
Hockenberry, Marilyn J; Hooke, Mary C; Rodgers, Cheryl; Taylor, Olga; Koerner, Kari M; Mitby, Pauline; Moore, Ida; Scheurer, Michael E; Pan, Wei
2017-07-01
Cancer treatment symptoms play a major role in determining the health of children with cancer. Symptom toxicity often results in complications, treatment delays, and therapy dose reductions that can compromise leukemia therapy and jeopardize chances for long-term survival. Critical to understanding symptom experiences during treatment is the need for exploration of "why" inter-individual symptom differences occur; this will determine who may be most susceptible to treatment toxicities. This study examined specific symptom trajectories during the first 18 months of childhood leukemia treatment. Symptom measures included fatigue, sleep disturbances, pain, nausea, and depression. Symptom trajectories of 236 children with leukemia three to 18 years old were explored prospectively over four periods: initiation of post-induction therapy, four and eight post-induction therapy, and the last time point was at the beginning of maintenance/continuation therapy. Latent class growth analysis was used to classify patients into distinctive groups with similar symptom trajectories based on patients' response patterns on the symptom measures over time. Three latent classes of symptom trajectories were identified and classified into mild, moderate, and severe symptom trajectories. The only demographic characteristic with a significant relationship to membership in the latent class symptom trajectories was race/ethnicity. All other demographic characteristics including leukemia risk levels showed no significant relationships. This study is unique in that groups of patients with similar symptoms were identified rather than groups of symptoms. Further research using latent class growth analysis is needed. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.
Comparison of two trajectory based models for locating particle sources for two rural New York sites
NASA Astrophysics Data System (ADS)
Zhou, Liming; Hopke, Philip K.; Liu, Wei
Two back trajectory-based statistical models, simplified quantitative transport bias analysis and residence-time weighted concentrations (RTWC) have been compared for their capabilities of identifying likely locations of source emissions contributing to observed particle concentrations at Potsdam and Stockton, New York. Quantitative transport bias analysis (QTBA) attempts to take into account the distribution of concentrations around the directions of the back trajectories. In full QTBA approach, deposition processes (wet and dry) are also considered. Simplified QTBA omits the consideration of deposition. It is best used with multiple site data. Similarly the RTWC approach uses concentrations measured at different sites along with the back trajectories to distribute the concentration contributions across the spatial domain of the trajectories. In this study, these models are used in combination with the source contribution values obtained by the previous positive matrix factorization analysis of particle composition data from Potsdam and Stockton. The six common sources for the two sites, sulfate, soil, zinc smelter, nitrate, wood smoke and copper smelter were analyzed. The results of the two methods are consistent and locate large and clearly defined sources well. RTWC approach can find more minor sources but may also give unrealistic estimations of the source locations.
Trajectory selection for the Mariner Jupiter/Saturn 1977 Project
NASA Technical Reports Server (NTRS)
Dyer, J. S.; Miles, R. F., Jr.
1974-01-01
This paper describes the use of decision analysis to facilitate a group decision-making problem in the selection of trajectories for the two spacecraft of the Mariner Jupiter/Saturn 1977 Project. This NASA project includes the participation of some eighty scientists divided by specialization among eleven science teams. A set of thirty-two candidate trajectory pairs was developed by the Project in collaboration with the science teams. Each science team then ordinally ranked and assigned cardinal utility function values to the trajectory pairs. These data and statistics derived from collective choice rules were used by the scientists in selecting the preferred trajectory pair.
Flight test trajectory control analysis
NASA Technical Reports Server (NTRS)
Walker, R.; Gupta, N.
1983-01-01
Recent extensions to optimal control theory applied to meaningful linear models with sufficiently flexible software tools provide powerful techniques for designing flight test trajectory controllers (FTTCs). This report describes the principal steps for systematic development of flight trajectory controllers, which can be summarized as planning, modeling, designing, and validating a trajectory controller. The techniques have been kept as general as possible and should apply to a wide range of problems where quantities must be computed and displayed to a pilot to improve pilot effectiveness and to reduce workload and fatigue. To illustrate the approach, a detailed trajectory guidance law is developed and demonstrated for the F-15 aircraft flying the zoom-and-pushover maneuver.
Particle trajectory computation on a 3-dimensional engine inlet. Final Report Ph.D. Thesis
NASA Technical Reports Server (NTRS)
Kim, J. J.
1986-01-01
A 3-dimensional particle trajectory computer code was developed to compute the distribution of water droplet impingement efficiency on a 3-dimensional engine inlet. The computed results provide the essential droplet impingement data required for the engine inlet anti-icing system design and analysis. The droplet trajectories are obtained by solving the trajectory equation using the fourth order Runge-Kutta and Adams predictor-corrector schemes. A compressible 3-D full potential flow code is employed to obtain a cylindrical grid definition of the flowfield on and about the engine inlet. The inlet surface is defined mathematically through a system of bi-cubic parametric patches in order to compute the droplet impingement points accurately. Analysis results of the 3-D trajectory code obtained for an axisymmetric droplet impingement problem are in good agreement with NACA experimental data. Experimental data are not yet available for the engine inlet impingement problem analyzed. Applicability of the method to solid particle impingement problems, such as engine sand ingestion, is also demonstrated.
Hyper-X Stage Separation Trajectory Validation Studies
NASA Technical Reports Server (NTRS)
Tartabini, Paul V.; Bose, David M.; McMinn, John D.; Martin, John G.; Strovers, Brian K.
2003-01-01
An independent twelve degree-of-freedom simulation of the X-43A separation trajectory was created with the Program to Optimize Simulated trajectories (POST II). This simulation modeled the multi-body dynamics of the X-43A and its booster and included the effect of two pyrotechnically actuated pistons used to push the vehicles apart as well as aerodynamic interaction forces and moments between the two vehicles. The simulation was developed to validate trajectory studies conducted with a 14 degree-of-freedom simulation created early in the program using the Automatic Dynamic Analysis of Mechanics Systems (ADAMS) simulation software. The POST simulation was less detailed than the official ADAMS-based simulation used by the Project, but was simpler, more concise and ran faster, while providing similar results. The increase in speed provided by the POST simulation provided the Project with an alternate analysis tool. This tool was ideal for performing separation control logic trade studies that required the running of numerous Monte Carlo trajectories.
Hamel, Sandra; Yoccoz, Nigel G; Gaillard, Jean-Michel
2017-05-01
Mixed models are now well-established methods in ecology and evolution because they allow accounting for and quantifying within- and between-individual variation. However, the required normal distribution of the random effects can often be violated by the presence of clusters among subjects, which leads to multi-modal distributions. In such cases, using what is known as mixture regression models might offer a more appropriate approach. These models are widely used in psychology, sociology, and medicine to describe the diversity of trajectories occurring within a population over time (e.g. psychological development, growth). In ecology and evolution, however, these models are seldom used even though understanding changes in individual trajectories is an active area of research in life-history studies. Our aim is to demonstrate the value of using mixture models to describe variation in individual life-history tactics within a population, and hence to promote the use of these models by ecologists and evolutionary ecologists. We first ran a set of simulations to determine whether and when a mixture model allows teasing apart latent clustering, and to contrast the precision and accuracy of estimates obtained from mixture models versus mixed models under a wide range of ecological contexts. We then used empirical data from long-term studies of large mammals to illustrate the potential of using mixture models for assessing within-population variation in life-history tactics. Mixture models performed well in most cases, except for variables following a Bernoulli distribution and when sample size was small. The four selection criteria we evaluated [Akaike information criterion (AIC), Bayesian information criterion (BIC), and two bootstrap methods] performed similarly well, selecting the right number of clusters in most ecological situations. We then showed that the normality of random effects implicitly assumed by evolutionary ecologists when using mixed models was often violated in life-history data. Mixed models were quite robust to this violation in the sense that fixed effects were unbiased at the population level. However, fixed effects at the cluster level and random effects were better estimated using mixture models. Our empirical analyses demonstrated that using mixture models facilitates the identification of the diversity of growth and reproductive tactics occurring within a population. Therefore, using this modelling framework allows testing for the presence of clusters and, when clusters occur, provides reliable estimates of fixed and random effects for each cluster of the population. In the presence or expectation of clusters, using mixture models offers a suitable extension of mixed models, particularly when evolutionary ecologists aim at identifying how ecological and evolutionary processes change within a population. Mixture regression models therefore provide a valuable addition to the statistical toolbox of evolutionary ecologists. As these models are complex and have their own limitations, we provide recommendations to guide future users. © 2016 Cambridge Philosophical Society.
NASA Astrophysics Data System (ADS)
Striepe, Scott Allen
The objectives of this research were to develop a reconstruction capability using the Program to Optimize Simulated Trajectories II (POST2), apply this capability to reconstruct the Huygens Titan probe entry, descent, and landing (EDL) trajectory, evaluate the newly developed POST2 reconstruction module, analyze the reconstructed trajectory, and assess the pre-flight simulation models used for Huygens EDL simulation. An extended Kalman filter (EKF) module was developed and integrated into POST2 to enable trajectory reconstruction (especially when using POST2-based mission specific simulations). Several validation cases, ranging from a single, constant parameter estimate to multivariable estimation cases similar to an actual mission flight, were executed to test the POST2 reconstruction module. Trajectory reconstruction of the Huygens entry probe at Titan was accomplished using accelerometer measurements taken during flight to adjust an estimated state (e.g., position, velocity, parachute drag, wind velocity, etc.) in a POST2-based simulation developed to support EDL analyses and design prior to entry. Although the main emphasis of the trajectory reconstruction was to evaluate models used in the NASA pre-entry trajectory simulation, the resulting reconstructed trajectory was also assessed to provide an independent evaluation of the ESA result. Major findings from this analysis include: Altitude profiles from this analysis agree well with other NASA and ESA results but not with Radar data, whereas a scale factor of about 0.93 would bring the radar measurements into compliance with these results; entry capsule aerodynamics predictions (axial component only) were well within 3-sigma bounds established pre-flight for most of the entry when compared to reconstructed values; Main parachute drag of 9% to 19% above ESA model was determined from the reconstructed trajectory; based on the tilt sensor and accelerometer data, the conclusion from this assessment was that the probe was tilted about 10 degrees during the Drogue parachute phase.
Nonparametric Trajectory Analysis (NTA), a receptor-oriented model, was used to assess the impact of local sources of air pollution at monitoring sites located adjacent to highway I-15 in Las Vegas, NV. Measurements of black carbon, carbon monoxide, nitrogen oxides, and sulfur di...
Squires, R Burke; Pickett, Brett E; Das, Sajal; Scheuermann, Richard H
2014-12-01
In 2009 a novel pandemic H1N1 influenza virus (H1N1pdm09) emerged as the first official influenza pandemic of the 21st century. Early genomic sequence analysis pointed to the swine origin of the virus. Here we report a novel computational approach to determine the evolutionary trajectory of viral sequences that uses data-driven estimations of nucleotide substitution rates to track the gradual accumulation of observed sequence alterations over time. Phylogenetic analysis and multiple sequence alignments show that sequences belonging to the resulting evolutionary trajectory of the H1N1pdm09 lineage exhibit a gradual accumulation of sequence variations and tight temporal correlations in the topological structure of the phylogenetic trees. These results suggest that our evolutionary trajectory analysis (ETA) can more effectively pinpoint the evolutionary history of viruses, including the host and geographical location traversed by each segment, when compared against either BLAST or traditional phylogenetic analysis alone. Copyright © 2014 Elsevier B.V. All rights reserved.
Taboo search by successive confinement: Surveying a potential energy surface
NASA Astrophysics Data System (ADS)
Chekmarev, Sergei F.
2001-09-01
A taboo search for minima on a potential energy surface (PES) is performed by means of confinement molecular dynamics: the molecular dynamics trajectory of the system is successively confined to various basins on the PES that have not been sampled yet. The approach is illustrated for a 13-atom Lennard-Jones cluster. It is shown that the taboo search radically accelerates the process of surveying the PES, with the probability of finding a new minimum defined by a propagating Fermi-like distribution.
The pointing errors of geosynchronous satellites
NASA Technical Reports Server (NTRS)
Sikdar, D. N.; Das, A.
1971-01-01
A study of the correlation between cloud motion and wind field was initiated. Cloud heights and displacements were being obtained from a ceilometer and movie pictures, while winds were measured from pilot balloon observations on a near-simultaneous basis. Cloud motion vectors were obtained from time-lapse cloud pictures, using the WINDCO program, for 27, 28 July, 1969, in the Atlantic. The relationship between observed features of cloud clusters and the ambient wind field derived from cloud trajectories on a wide range of space and time scales is discussed.
Motion estimation of subcellular structures from fluorescence microscopy images.
Vallmitjana, A; Civera-Tregon, A; Hoenicka, J; Palau, F; Benitez, R
2017-07-01
We present an automatic image processing framework to study moving intracellular structures from live cell fluorescence microscopy. The system includes the identification of static and dynamic structures from time-lapse images using data clustering as well as the identification of the trajectory of moving objects with a probabilistic tracking algorithm. The method has been successfully applied to study mitochondrial movement in neurons. The approach provides excellent performance under different experimental conditions and is robust to common sources of noise including experimental, molecular and biological fluctuations.
Computer Aided Ballistic Orbit Classification Around Small Bodies
NASA Astrophysics Data System (ADS)
Villac, Benjamin F.; Anderson, Rodney L.; Pini, Alex J.
2016-09-01
Orbital dynamics around small bodies are as varied as the shapes and dynamical states of these bodies. While various classes of orbits have been analyzed in detail, the global overview of relevant ballistic orbits at particular bodies is not easily computed or organized. Yet, correctly categorizing these orbits will ease their future use in the overall trajectory design process. This paper overviews methods that have been used to organize orbits, focusing on periodic orbits in particular, and introduces new methods based on clustering approaches.
A quality assessment of 3D video analysis for full scale rockfall experiments
NASA Astrophysics Data System (ADS)
Volkwein, A.; Glover, J.; Bourrier, F.; Gerber, W.
2012-04-01
Main goal of full scale rockfall experiments is to retrieve a 3D trajectory of a boulder along the slope. Such trajectories then can be used to calibrate rockfall simulation models. This contribution presents the application of video analysis techniques capturing rock fall velocity of some free fall full scale rockfall experiments along a rock face with an inclination of about 50 degrees. Different scaling methodologies have been evaluated. They mainly differ in the way the scaling factors between the movie frames and the reality and are determined. For this purpose some scale bars and targets with known dimensions have been distributed in advance along the slope. The single scaling approaches are briefly described as follows: (i) Image raster is scaled to the distant fixed scale bar then recalibrated to the plane of the passing rock boulder by taking the measured position of the nearest impact as the distance to the camera. The distance between the camera, scale bar, and passing boulder are surveyed. (ii) The image raster was scaled using the four nearest targets (identified using frontal video) from the trajectory to be analyzed. The average of the scaling factors was finally taken as scaling factor. (iii) The image raster was scaled using the four nearest targets from the trajectory to be analyzed. The scaling factor for one trajectory was calculated by balancing the mean scaling factors associated with the two nearest and the two farthest targets in relation to their mean distance to the analyzed trajectory. (iv) Same as previous method but with varying scaling factors during along the trajectory. It has shown that a direct measure of the scaling target and nearest impact zone is the most accurate. If constant plane is assumed it doesn't account for the lateral deviations of the rock boulder from the fall line consequently adding error into the analysis. Thus a combination of scaling methods (i) and (iv) are considered to give the best results. For best results regarding the lateral rough positioning along the slope, the frontal video must also be scaled. The error in scaling the video images can be evaluated by comparing the data by additional combination of the vertical trajectory component over time with the theoretical polynomial trend according to gravity. The different tracking techniques used to plot the position of the boulder's center of gravity all generated positional data with minimal error acceptable for trajectory analysis. However, when calculating instantaneous velocities an amplification of this error becomes un acceptable. A regression analysis of the data is helpful to optimize trajectory and velocity, respectively.
NASA Astrophysics Data System (ADS)
Mahalik, S. S.; Kundu, M.
2016-12-01
Linear resonance (LR) absorption of an intense 800 nm laser light in a nano-cluster requires a long laser pulse >100 fs when Mie-plasma frequency ( ω M ) of electrons in the expanding cluster matches the laser frequency (ω). For a short duration of the pulse, the condition for LR is not satisfied. In this case, it was shown by a model and particle-in-cell (PIC) simulations [Phys. Rev. Lett. 96, 123401 (2006)] that electrons absorb laser energy by anharmonic resonance (AHR) when the position-dependent frequency Ω [ r ( t ) ] of an electron in the self-consistent anharmonic potential of the cluster satisfies Ω [ r ( t ) ] = ω . However, AHR remains to be a debate and still obscure in multi-particle plasma simulations. Here, we identify AHR mechanism in a laser driven cluster using molecular dynamics (MD) simulations. By analyzing the trajectory of each MD electron and extracting its Ω [ r ( t ) ] in the self-generated anharmonic plasma potential, it is found that electron is outer ionized only when AHR is met. An anharmonic oscillator model, introduced here, brings out most of the features of MD electrons while passing the AHR. Thus, we not only bridge the gap between PIC simulations, analytical models, and MD calculations for the first time but also unequivocally prove that AHR process is a universal dominant collisionless mechanism of absorption in the short pulse regime or in the early time of longer pulses in clusters.
ERIC Educational Resources Information Center
Kamp Dush, Claire M.; Taylor, Miles G.
2012-01-01
Using typologies outlined by Gottman and Fitzpatrick as well as institutional and companionate models of marriage, the authors conducted a latent class analysis of marital conflict trajectories using 20 years of data from the Marital Instability Over the Life Course study. Respondents were in one of three groups: high, medium (around the mean), or…
In situ data analytics and indexing of protein trajectories.
Johnston, Travis; Zhang, Boyu; Liwo, Adam; Crivelli, Silvia; Taufer, Michela
2017-06-15
The transition toward exascale computing will be accompanied by a performance dichotomy. Computational peak performance will rapidly increase; I/O performance will either grow slowly or be completely stagnant. Essentially, the rate at which data are generated will grow much faster than the rate at which data can be read from and written to the disk. MD simulations will soon face the I/O problem of efficiently writing to and reading from disk on the next generation of supercomputers. This article targets MD simulations at the exascale and proposes a novel technique for in situ data analysis and indexing of MD trajectories. Our technique maps individual trajectories' substructures (i.e., α-helices, β-strands) to metadata frame by frame. The metadata captures the conformational properties of the substructures. The ensemble of metadata can be used for automatic, strategic analysis within a trajectory or across trajectories, without manually identify those portions of trajectories in which critical changes take place. We demonstrate our technique's effectiveness by applying it to 26.3k helices and 31.2k strands from 9917 PDB proteins and by providing three empirical case studies. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Doyle, Frank; McGee, Hannah; Delaney, Mary; Motterlini, Nicola; Conroy, Ronán
2011-01-01
Depression is prevalent in patients hospitalized with acute coronary syndrome (ACS). We determined whether theoretical vulnerabilities for depression (interpersonal life events, reinforcing events, cognitive distortions, Type D personality) predicted depression, or depression trajectories, post-hospitalization. We followed 375 ACS patients who completed depression scales during hospital admission and at least once during three follow-up intervals over 1 year (949 observations). Questionnaires assessing vulnerabilities were completed at baseline. Logistic regression for panel/longitudinal data predicted depression status during follow-up. Latent class analysis determined depression trajectories. Multinomial logistic regression modeled the relationship between vulnerabilities and trajectories. Vulnerabilities predicted depression status over time in univariate and multivariate analysis, even when controlling for baseline depression. Proportions in each depression trajectory category were as follows: persistent (15%), subthreshold (37%), never depressed (48%). Vulnerabilities independently predicted each of these trajectories, with effect sizes significantly highest for the persistent depression group. Self-reported vulnerabilities - stressful life events, reduced reinforcing events, cognitive distortions, personality - measured during hospitalization can identify those at risk for depression post-ACS and especially those with persistent depressive episodes. Interventions should focus on these vulnerabilities. Copyright © 2011 Elsevier Inc. All rights reserved.
Das, Raibatak; Cairo, Christopher W.; Coombs, Daniel
2009-01-01
The extraction of hidden information from complex trajectories is a continuing problem in single-particle and single-molecule experiments. Particle trajectories are the result of multiple phenomena, and new methods for revealing changes in molecular processes are needed. We have developed a practical technique that is capable of identifying multiple states of diffusion within experimental trajectories. We model single particle tracks for a membrane-associated protein interacting with a homogeneously distributed binding partner and show that, with certain simplifying assumptions, particle trajectories can be regarded as the outcome of a two-state hidden Markov model. Using simulated trajectories, we demonstrate that this model can be used to identify the key biophysical parameters for such a system, namely the diffusion coefficients of the underlying states, and the rates of transition between them. We use a stochastic optimization scheme to compute maximum likelihood estimates of these parameters. We have applied this analysis to single-particle trajectories of the integrin receptor lymphocyte function-associated antigen-1 (LFA-1) on live T cells. Our analysis reveals that the diffusion of LFA-1 is indeed approximately two-state, and is characterized by large changes in cytoskeletal interactions upon cellular activation. PMID:19893741
Marsiglia, Flavio F.; Kulis, Stephen; Kellison, Joshua G.
2010-01-01
Objectives. Under an ecodevelopmental framework, we examined lifetime segmented assimilation trajectories (diverging assimilation pathways influenced by prior life conditions) and related them to quality-of-life indicators in a diverse sample of 258 men in the Pheonix, AZ, metropolitan area. Methods. We used a growth mixture model analysis of lifetime changes in socioeconomic status, and used acculturation to identify distinct lifetime segmented assimilation trajectory groups, which we compared on life satisfaction, exercise, and dietary behaviors. We hypothesized that lifetime assimilation change toward mainstream American culture (upward assimilation) would be associated with favorable health outcomes, and downward assimilation change with unfavorable health outcomes. Results. A growth mixture model latent class analysis identified 4 distinct assimilation trajectory groups. In partial support of the study hypotheses, the extreme upward assimilation trajectory group (the most successful of the assimilation pathways) exhibited the highest life satisfaction and the lowest frequency of unhealthy food consumption. Conclusions. Upward segmented assimilation is associated in adulthood with certain positive health outcomes. This may be the first study to model upward and downward lifetime segmented assimilation trajectories, and to associate these with life satisfaction, exercise, and dietary behaviors. PMID:20167890
The power of a single trajectory
NASA Astrophysics Data System (ADS)
Schnellbächer, Nikolas D.; Schwarz, Ulrich S.
2018-03-01
Random walks are often evaluated in terms of their mean squared displacements, either for a large number of trajectories or for one very long trajectory. An alternative evaluation is based on the power spectral density, but here it is less clear which information can be extracted from a single trajectory. For continuous-time Brownian motion, Krapf et al now have mathematically proven that the one property that can be reliably extracted from a single trajectory is the frequency dependence of the ensemble-averaged power spectral density (Krapf et al 2018 New J. Phys. 20 023029). Their mathematical analysis also identifies the appropriate frequency window for this procedure and shows that the diffusion coefficient can be extracted by averaging over a small number of trajectories. The authors have verified their analytical results both by computer simulations and experiments.
Stone, Juliet; Evandrou, Maria; Falkingham, Jane; Vlachantoni, Athina
2015-09-01
Previous research has highlighted the importance of accumulated life-course labour market status and the balancing of multiple roles for understanding inequalities in health in later life. This may be particularly important for women, who are increasingly required to balance work and family life in liberal welfare contexts, such as in Britain. This study analyses retrospective life history data for 2160 women aged 64+ years (born 1909-1943) from the English Longitudinal Study of Ageing, collected in 2006-2007 as part of an ongoing panel study. Optimal matching and cluster analyses are used to produce a taxonomy of women's life-course economic activity trajectories based on their experiences between ages 16 and 64 years. This classification is then used in logistic regression analysis to investigate associations with self-rated health in later life. A set of five trajectories emerge as the dominant patterns of women's economic activity over the life course for those cohorts of English women born prior to 1943: (1) full-time workers; (2) family carers; (3) full-time returners; (4) part-time returners; (5) atypical/inactive. Regression analyses show that women who experience defined periods of full-time work both before and after focusing on family life appear to have the most favourable later life health outcomes. The findings are discussed with reference to the accumulation of social and economic resources over the life course and the balancing of multiple roles in work and family domains. In conclusion, the development of policies that facilitate women, if they wish, to successfully combine paid employment with family life could have a positive impact on their health in later life. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
An integrated approach using high time-resolved tools to study the origin of aerosols.
Di Gilio, A; de Gennaro, G; Dambruoso, P; Ventrella, G
2015-10-15
Long-range transport of natural and/or anthropogenic particles can contribute significantly to PM10 and PM2.5 concentrations and some European cities often fail to comply with PM daily limit values due to the additional impact of particles from remote sources. For this reason, reliable methodologies to identify long-range transport (LRT) events would be useful to better understand air pollution phenomena and support proper decision-making. This study explores the potential of an integrated and high time-resolved monitoring approach for the identification and characterization of local, regional and long-range transport events of high PM. In particular, the goal of this work was also the identification of time-limited event. For this purpose, a high time-resolved monitoring campaign was carried out at an urban background site in Bari (southern Italy) for about 20 days (1st-20th October 2011). The integration of collected data as the hourly measurements of inorganic ions in PM2.5 and their gas precursors and of the natural radioactivity, in addition to the analyses of aerosol maps and hourly back trajectories (BT), provided useful information for the identification and chemical characterization of local sources and trans-boundary intrusions. Non-sea salt (nss) sulfate levels were found to increase when air masses came from northeastern Europe and higher dispersive conditions of the atmosphere were detected. Instead, higher nitrate and lower nss-sulfate concentrations were registered in correspondence with air mass stagnation and attributed to local traffic source. In some cases, combinations of local and trans-boundary sources were observed. Finally, statistical investigations such as the principal component analysis (PCA) applied on hourly ion concentrations and the cluster analyses, the Potential Source Contribution Function (PSCF) and the Concentration Weighted Trajectory (CWT) models computed on hourly back-trajectories enabled to complete a cognitive framework and confirm the influence of aerosol transported from heavily polluted areas on the receptor site. Copyright © 2015 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Yunxiao, CAO; Zhiqiang, WANG; Jinjun, WANG; Guofeng, LI
2018-05-01
Electrostatic separation has been extensively used in mineral processing, and has the potential to separate gangue minerals from raw talcum ore. As for electrostatic separation, the particle charging status is one of important influence factors. To describe the talcum particle charging status in a parallel plate electrostatic separator accurately, this paper proposes a modern images processing method. Based on the actual trajectories obtained from sequence images of particle movement and the analysis of physical forces applied on a charged particle, a numerical model is built, which could calculate the charge-to-mass ratios represented as the charging status of particle and simulate the particle trajectories. The simulated trajectories agree well with the experimental results obtained by images processing. In addition, chemical composition analysis is employed to reveal the relationship between ferrum gangue mineral content and charge-to-mass ratios. Research results show that the proposed method is effective for describing the particle charging status in electrostatic separation.
Growth Trajectories of Health Behaviors from Adolescence through Young Adulthood.
Wiium, Nora; Breivik, Kyrre; Wold, Bente
2015-10-28
Based on nine waves of data collected during a period of 17 years (1990-2007), the present study explored different developmental trajectories of the following unhealthy behaviors: regular smoking, lack of regular exercise, lack of daily fruit intake, and drunkenness. A baseline sample of 1195 13-year-old pupils was from 22 randomly selected schools in the Hordaland County in western Norway. Latent class growth analysis revealed three developmental trajectories. The first trajectory was a conventional trajectory, comprising 36.3% of participants, who showed changes in smoking, physical exercise, fruit intake, and drunkenness consistent with the prevailing age specific norms of these behaviors in the Norwegian society at the time. The second trajectory was a passive trajectory, comprising 25.5% of participants, who reported low levels of both healthy and unhealthy behaviors during the 17-year period. The third trajectory was an unhealthy trajectory, comprising 38.2% of participants, who had high levels of unhealthy behaviors over time. Several covariates were examined, but only sex and mother's and father's educational levels were found to be significantly associated with the identified trajectories. While these findings need to be replicated in future studies, the identification of the different trajectories suggests the need to tailor intervention according to specific needs.