Movement Patterns Of Groups Research Articles

The role of compensatory movements patterns in spontaneous recovery after stroke.

[Purpose] Post-stroke motor recovery consists of both true recovery and compensatory movements. Although compensatory movements are learned more quickly early after stroke, the role of compensatory movement patterns in functional recovery is controversial. We investigated the role of compensatory movement patterns in the long-term functional motor recovery after stroke. [Subjects and Methods] Male Wistar rats were subjected to photothrombotic infarction to induce motor and sensorimotor cortex lesions. The rats were given task-specific training. Behavior tests and analyses of compensatory movement patterns (head lift, limb withdrawal impairment, phantom grasps, and pellet chasing) during the single-pellet reaching test were performed 2, 7, 14, 21, 28, and 35 days post stroke. [Results] Successful retrieval during the single-pellet reaching test was significantly correlated with compensatory movement patterns in stroke groups. Motor cortex stroke showed significant correlation in limb withdrawal impairment and pellet chasing. But, sensorimotor cortex stroke was significant correlation in pellet chasing. [Conclusion] The data suggest that compensatory movements after stroke are correlated with spontaneous recovery. Since some compensatory movement patterns are detrimental to functional recovery, the correct timing of training and control of compensatory movement patterns might be important.

An Automated Approach for Job Scheduling and Work Flow Mining

Now a day’s work allotment in a software firm become more important and cumbersome. The main objective of this concept is to reduce the work of the software developers in a software company and work allocation. Here the work will be allotted for the each person automatically by splitting the modules into tasks. When developing a big project more confusion and more discussions will occur, and some clauses will arise between modules while splitting into tasks and who the person to develop the particular task And performance evolution will not be in accurate, which confuse with the actual work allotment by the HR. So that still companies are struggling to book multiple software projects at a same time. So that still companies are yielding less works from their employees. In order to reduce these problems, implementing work flow mining, some of them are Group movement pattern, Heterogeneous project details, Ranking model adaptation SVM (RA-SVM), Domain specific search, Distributed clustering etc.

Emergent group level navigation: an agent-based evaluation of movement patterns in a folivorous primate.

The foraging activity of many organisms reveal strategic movement patterns, showing efficient use of spatially distributed resources. The underlying mechanisms behind these movement patterns, such as the use of spatial memory, are topics of considerable debate. To augment existing evidence of spatial memory use in primates, we generated movement patterns from simulated primate agents with simple sensory and behavioral capabilities. We developed agents representing various hypotheses of memory use, and compared the movement patterns of simulated groups to those of an observed group of red colobus monkeys (Procolobus rufomitratus), testing for: the effects of memory type (Euclidian or landmark based), amount of memory retention, and the effects of social rules in making foraging choices at the scale of the group (independent or leader led). Our results indicate that red colobus movement patterns fit best with simulated groups that have landmark based memory and a follow the leader foraging strategy. Comparisons between simulated agents revealed that social rules had the greatest impact on a group’s step length, whereas the type of memory had the highest impact on a group’s path tortuosity and cohesion. Using simulation studies as experimental trials to test theories of spatial memory use allows the development of insight into the behavioral mechanisms behind animal movement, developing case-specific results, as well as general results informing how changes to perception and behavior influence movement patterns.

Validating the use of colouration patterns for individual recognition in the worm pipefish using a novel set of microsatellite markers

In studies of behaviour, ecology and evolution, identification of individual organisms can be an invaluable tool, capable of unravelling otherwise cryptic information regarding group structure, movement patterns, population size and mating strategies. The use of natural markings is arguably the least invasive method for identification. However, to be truly useful natural markings must be sufficiently variable to allow for unique identification, while being stable enough to permit long-term studies. Non-invasive marking techniques are especially important in fishes of the Family Syngnathidae (pipefishes, seahorses and seadragons), as many of these taxa are of conservation concern or used extensively in studies of sexual selection. Here, we assessed the reliability of natural markings as a character for individual identification in a wild population of Nerophis lumbriciformis by comparing results from natural markings to individual genetic assignments based on eight novel microsatellite loci. We also established a minimally invasive method based on epithelial cell swabbing to sample DNA. All pipefish used in the validation of natural markings, independently of sex or time between recaptures, were individually recognized through facial colouration patterns. Their identities were verified by the observation of the same multilocus genotype at every sampling event for each individual that was identified on the basis of natural markings. Successful recaptures of previously swabbed pipefish indicated that this process probably did not induce an elevated rate of mortality. Also, the recapture of newly pregnant males showed that swabbing did not affect reproductive behaviour.

Random walk analysis of ranging patterns of sympatric langurs in a complex resource landscape

The identification of random walk models to characterize the movement patterns of social groups of primates, and the behavioral processes that give rise to such movement patterns, remain open questions in movement ecology. Movement patterns characterized by a power-law tail with exponent between 1 and 3 (Lévy flight) occur when animals forage on scarce, randomly distributed resources. For primates and similar foragers with memory processes, movements resembling Lévy flights emerge when feeding trees (targets) are randomly distributed and the trunk size distribution of targets follows a power-law. We tested three competing random walk models to describe movement patterns of two langur species. We found a truncated power law to be the most suitable model. The power-law model was poorly supported by the data and hence we found no support for Lévy-flight-like behavior. Moreover, the spatial distribution of feeding trees and the probability distribution of feeding tree size differed from values suggested to result in Lévy-flight-like patterns. We identify intraspecific territoriality, foraging behavior, and the spatial and size distribution of food patches as plausible mechanisms that may have given rise to the observed movement patterns.

Searching in heterogeneous and limiting environments: foraging strategies of white-lipped peccaries (Tayassu pecari)

Searching for patchily distributed, highly localized, and seasonally variable resources in heterogeneous environments poses significant challenges for social species living in cohesive groups. Here, we studied the searching strategies of a highly social mammal, the white-lipped peccary (Tayassu pecari), in Calakmul Biosphere Reserve, Mexico. Calakmul Biosphere Reserve is a seasonal tropical forest where important resources, such as water and food, are patchy distributed and temporarily scarce. We attempted to determine what theoretical searching model best explained the movement patterns of groups of white-lipped peccaries, including short-tailed, long-tailed, and scale-free distributions. We found that the only distribution that was well supported by the data was a zero-inflated lognormal distribution; this implies a general pattern of normally short-range intensive searching with occasional long-distance directed movements taking the animals away from previously searched areas. We also found that groups concentrated foraging activities around sources of water during the dry season, behaving as central-place foragers while occasionally searching distant areas. We discuss the potential adaptive values of such behavioral strategies for social species living in highly heterogeneous environments.

Linking places to problems: geospatial theories of neighborhoods, alcohol and crime

This paper provides a critical review of two broad categories of social ecological theories of crime, social integration and place-based theories, and their relationships to spatial assessments of crime patterns. Social integration theories emphasize the role of neighborhood disorganization on crime, while place theories stress the social interactions within and between places as a source of crime. We provide an analysis of the extent to which these two types of theorizing describe processes and mechanisms that are truly ecologic (identify specific interactions between individuals and their environments) and truly spatial (identify specific movement and interaction patterns of individuals and groups) as they endeavor to explain crime outcomes. We suggest that social integration theories do not provide spatial signatures of sufficient specificity to justify the application of spatial statistical techniques as quantitative arbiters of the theory. On the other hand, place based theories go some way toward addressing these issues because the emphasis is placed on understanding the exact physical and social characteristics of place and the activities that occur around locations as sources of crime. Routine activities and crime potential theories attempt to explain clustering or "hot spots" of crime in ways that give clear spatial dimension by looking at micro-spatial interactions between offenders and targets of crime. These theories have strong ecological implications as well, since they contain specific statements about how people use the space around them and how these patterns of use are related to patterns of criminal activity. We conclude by identifying a set of requirements for successful empirical tests of geospatial theories, including the development of valid measures of key theoretical constructs and the formulation of critical empirical assessments of geospatial hypotheses derived from motivating theory.

Common functional principal components analysis: A new approach to analyzing human movement data

In many human movement studies angle-time series data on several groups of individuals are measured. Current methods to compare groups include comparisons of the mean value in each group or use multivariate techniques such as principal components analysis and perform tests on the principal component scores. Such methods have been useful, though discard a large amount of information. Functional data analysis (FDA) is an emerging statistical analysis technique in human movement research which treats the angle-time series data as a function rather than a series of discrete measurements. This approach retains all of the information in the data. Functional principal components analysis (FPCA) is an extension of multivariate principal components analysis which examines the variability of a sample of curves and has been used to examine differences in movement patterns of several groups of individuals. Currently the functional principal components (FPCs) for each group are either determined separately (yielding components that are group-specific), or by combining the data for all groups and determining the FPCs of the combined data (yielding components that summarize the entire data set). The group-specific FPCs contain both within and between group variation and issues arise when comparing FPCs across groups when the order of the FPCs alter in each group. The FPCs of the combined data may not adequately describe all groups of individuals and comparisons between groups typically use t-tests of the mean FPC scores in each group. When these differences are statistically non-significant it can be difficult to determine how a particular intervention is affecting movement patterns or how injured subjects differ from controls. In this paper we aim to perform FPCA in a manner allowing sensible comparisons between groups of curves. A statistical technique called common functional principal components analysis (CFPCA) is implemented. CFPCA identifies the common sources of variation evident across groups but allows the order of each component to change for a particular group. This allows for the direct comparison of components across groups. We use our method to analyze a biomechanical data set examining the mechanisms of chronic Achilles tendon injury and the functional effects of orthoses.

Mining Group Movement Patterns for Tracking Moving Objects Efficiently

Existing object tracking applications focus on finding the moving patterns of a single object or all objects. In contrast, we propose a distributed mining algorithm that identifies a group of objects with similar movement patterns. This information is important in some biological research domains, such as the study of animals' social behavior and wildlife migration. The proposed algorithm comprises a local mining phase and a cluster ensembling phase. In the local mining phase, the algorithm finds movement patterns based on local trajectories. Then, based on the derived patterns, we propose a new similarity measure to compute the similarity of moving objects and identify the local group relationships. To address the energy conservation issue in resource-constrained environments, the algorithm only transmits the local grouping results to the sink node for further ensembling. In the cluster ensembling phase, our algorithm combines the local grouping results to derive the group relationships from a global view. We further leverage the mining results to track moving objects efficiently. The results of experiments show that the proposed mining algorithm achieves good grouping quality, and the mining technique helps reduce the energy consumption by reducing the amount of data to be transmitted.

Exploring Application-Level Semantics for Data Compression

Natural phenomena show that many creatures form large social groups and move in regular patterns. However, previous works focus on finding the movement patterns of each single object or all objects. In this paper, we first propose an efficient distributed mining algorithm to jointly identify a group of moving objects and discover their movement patterns in wireless sensor networks. Afterward, we propose a compression algorithm, called 2P2D, which exploits the obtained group movement patterns to reduce the amount of delivered data. The compression algorithm includes a sequence merge and an entropy reduction phases. In the sequence merge phase, we propose a Merge algorithm to merge and compress the location data of a group of moving objects. In the entropy reduction phase, we formulate a Hit Item Replacement (HIR) problem and propose a Replace algorithm that obtains the optimal solution. Moreover, we devise three replacement rules and derive the maximum compression ratio. The experimental results show that the proposed compression algorithm leverages the group movement patterns to reduce the amount of delivered data effectively and efficiently.

Effects of Human Traffic on the Movement Patterns of Hawaiian Spinner Dolphins (<I>Stenella longirostris</I>) in Kealakekua Bay, Hawaii

Kealakekua Bay is an important resting site for Hawaiian spinner dolphins (Stenella longirostris) and is popular with both local residents and tourists. Human activities occurring here include swimming, snorkeling, kayaking, and motor-boating. The objectives of this study were to document movement patterns of dolphin groups in Kealakekua Bay, to determine if different types and levels of human activity within the bay result in quantifiable changes in dolphin group movement patterns, and to provide baseline data for future studies. Theodolite tracking was used to assess responses of dolphin groups to human traffic. Variables examined included group mean leg speed (leg speed: the distance between two consecutive theodolite fixes of a dolphin group divided by time; mean leg speed: the average of all leg speeds comprising a track) and group reorientation rate. Swimmers and/or vessels were present within 100 m of all dolphin groups tracked during all surveys. Regression analyses were used to examine potential relationships between dolphin group related variables (e.g., reorientation rate, mean leg speed) and variables related to human activities (e.g., swimming, kayaking, motor-boating). Increasing levels of human activity had a limited but measurable effect on the movement patterns of Hawaiian spinner dolphin groups at this site.

Spatial modeling of the geographic distribution of wildlife populations: a case study in the lower Mississippi River region

A geographic information system (GIS)-based spatial modeling approach was developed to study environmental and land use impacts on the geographic distribution of wintering northern pintails ( Anas acuta) in the Lower Mississippi River region. Pintails were fitted with backpack radio transmitter packages at Catahoula Lake, LA, in October 1992–1994 and located weekly through the following March. Pintail survey data were converted into a digital database in ARC/INFO GIS format and integrated with environmental GIS data through a customized modeling interface. The study verified the relationship between pintail distributions and major environmental factors and developed a conceptual relation model. Visualization-based spatial simulations were used to display the movement patterns of specific population groups under spatial and temporal constraints. The spatial modeling helped understand the seasonal movement patterns of pintails in relation to their habitat usage in Arkansas and southwestern Louisiana for wintering and interchange situations among population groups wintering in Texas and southeastern Louisiana.