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A General HIV Incidence Inference Scheme Based on Likelihood of Individual Level Data and a Population Renewal Equation  [PDF]
Guy Severin Mahiane, Rachid Ouifki, Hilmarie Brand, Wim Delva, Alex Welte
PLOS ONE , 2012, DOI: 10.1371/journal.pone.0044377
Abstract: We derive a new method to estimate the age specific incidence of an infection with a differential mortality, using individual level infection status data from successive surveys. The method consists of a) an SI-type model to express the incidence rate in terms of the prevalence and its derivatives as well as the difference in mortality rate, and b) a maximum likelihood approach to estimate the prevalence and its derivatives. Estimates can in principle be obtained for any chosen age and time, and no particular assumptions are made about the epidemiological or demographic context. This is in contrast with earlier methods for estimating incidence from prevalence data, which work with aggregated data, and the aggregated effect of demographic and epidemiological rates over the time interval between prevalence surveys. Numerical simulation of HIV epidemics, under the presumption of known excess mortality due to infection, shows improved control of bias and variance, compared to previous methods. Our analysis motivates for a) effort to be applied to obtain accurate estimates of excess mortality rates as a function of age and time among HIV infected individuals and b) use of individual level rather than aggregated data in order to estimate HIV incidence rates at times between two prevalence surveys.
Better Safe than Sorry - Socio-Spatial Group Structure Emerges from Individual Variation in Fleeing, Avoidance or Velocity in an Agent-Based Model  [PDF]
Ellen Evers, Han de Vries, Berry M. Spruijt, Elisabeth H. M. Sterck
PLOS ONE , 2011, DOI: 10.1371/journal.pone.0026189
Abstract: In group-living animals, such as primates, the average spatial group structure often reflects the dominance hierarchy, with central dominants and peripheral subordinates. This central-peripheral group structure can arise by self-organization as a result of subordinates fleeing from dominants after losing a fight. However, in real primates, subordinates often avoid interactions with potentially aggressive group members, thereby preventing aggression and subsequent fleeing. Using agent-based modeling, we investigated which spatial and encounter structures emerge when subordinates also avoid known potential aggressors at a distance as compared with the model which only included fleeing after losing a fight (fleeing model). A central-peripheral group structure emerged in most conditions. When avoidance was employed at small or intermediate distances, centrality of dominants emerged similar to the fleeing model, but in a more pronounced way. This result was also found when fleeing after a fight was made independent of dominance rank, i.e. occurred randomly. Employing avoidance at larger distances yielded more spread out groups. This provides a possible explanation of larger group spread in more aggressive species. With avoidance at very large distances, spatially and socially distinct subgroups emerged. We also investigated how encounters were distributed amongst group members. In the fleeing model all individuals encountered all group members equally often, whereas in the avoidance model encounters occurred mostly among similar-ranking individuals. Finally, we also identified a very general and simple mechanism causing a central-peripheral group structure: when individuals merely differed in velocity, faster individuals automatically ended up at the periphery. In summary, a central-peripheral group pattern can easily emerge from individual variation in different movement properties in general, such as fleeing, avoidance or velocity. Moreover, avoidance behavior also affects the encounter structure and can lead to subgroup formation.
Parameter Inference for an Individual Based Model of Chytridiomycosis in Frogs  [PDF]
Leah R. Johnson,Cheryl J. Briggs
Quantitative Biology , 2010,
Abstract: Individual Based Models (IBMs) and Agent Based Models (ABMs) have become widely used tools to understand complex biological systems. However, general methods of parameter inference for IBMs are not available. In this paper we show that it is possible to address this problem with a traditional likelihood-based approach, using an example of an IBM developed to describe the spread of Chytridiomycosis in a population of frogs as a case study. We show that if the IBM satisfies certain criteria we can find the likelihood (or posterior) analytically, and use standard computational techniques, such as Markov Chain Monte Carlo (MCMC), for parameter inference.
Multimodal Movement Prediction - Towards an Individual Assistance of Patients  [PDF]
Elsa Andrea Kirchner, Marc Tabie, Anett Seeland
PLOS ONE , 2014, DOI: 10.1371/journal.pone.0085060
Abstract: Assistive devices, like exoskeletons or orthoses, often make use of physiological data that allow the detection or prediction of movement onset. Movement onset can be detected at the executing site, the skeletal muscles, as by means of electromyography. Movement intention can be detected by the analysis of brain activity, recorded by, e.g., electroencephalography, or in the behavior of the subject by, e.g., eye movement analysis. These different approaches can be used depending on the kind of neuromuscular disorder, state of therapy or assistive device. In this work we conducted experiments with healthy subjects while performing self-initiated and self-paced arm movements. While other studies showed that multimodal signal analysis can improve the performance of predictions, we show that a sensible combination of electroencephalographic and electromyographic data can potentially improve the adaptability of assistive technical devices with respect to the individual demands of, e.g., early and late stages in rehabilitation therapy. In earlier stages for patients with weak muscle or motor related brain activity it is important to achieve high positive detection rates to support self-initiated movements. To detect most movement intentions from electroencephalographic or electromyographic data motivates a patient and can enhance her/his progress in rehabilitation. In a later stage for patients with stronger muscle or brain activity, reliable movement prediction is more important to encourage patients to behave more accurately and to invest more effort in the task. Further, the false detection rate needs to be reduced. We propose that both types of physiological data can be used in an and combination, where both signals must be detected to drive a movement. By this approach the behavior of the patient during later therapy can be controlled better and false positive detections, which can be very annoying for patients who are further advanced in rehabilitation, can be avoided.
Macroparticle Movement Velocity in Dusty Structures of Various Compositions  [PDF]
A. D. Khakhaev,A. A. Piskunov,S. F. Podryadchikov
Physics , 2012,
Abstract: The results of experimental investigations of the movement velocity of a macroparticle in the dusty structures of various physicalchemical compositions formed in a stratified column of a dc glow discharge, are presented. The macroparticle substances are alumina (r = 10 - 35 microns), polydisperse Zn (r = 1 - 20 microns) and Zn0 (r = 20 - 35 microns). Plasma-forming gases are inert gases (Ne, Ar). The inverse relation between the velocity and the gas pressure (in the range 40-400 Pa) is found and, for the same material of macroparticles in different gas plasmas, is confirmed by theory and does not contradict observations. But, to explain a difference of quantitative data for macroparticles made from different materials in Ar plasma, the additional research is required.
Sparse movement data can reveal social influences on individual travel decisions  [PDF]
Tyler R. Bonnell,S. Peter Henzi,Louise Barrett
Statistics , 2015,
Abstract: The monitoring of animal movement patterns provides insights into animals decision-making behaviour. It is generally assumed that high-resolution data are needed to extract meaningful behavioural patterns, which potentially limits the application of this approach. Obtaining high-resolution movement data continues to be an economic and technical challenge, particularly for animals that live in social groups. Here, we test whether accurate movement behaviour can be extracted from data that possesses increasingly lower temporal resolution. To do so, we use a modified version of force matching, in which simulated forces acting on a focal animal are compared to observed movement data. We show that useful information can be extracted from sparse data. We apply this approach to a sparse movement dataset collected on the adult members of a troop of baboons in the DeHoop Nature Reserve, South Africa. We use these data to test the hypothesis that individuals are sensitive to isolation from the group as a whole or, alternatively, whether they are sensitive to the location of specific individuals within the group. Using data from a focal animal, our data provide support for both hypothesis, with stronger support for the latter. Although the focal animal was found to be sensitive to the group, this occurred only on a small number of occasions when the group as a whole was highly clustered as a single entity away from the focal animal. We suggest that specific social interactions may thus drive overall group cohesion. Given that sparse movement data is informative about individual movement behaviour, we suggest that both high (~seconds) and relatively low (~minutes) resolution datasets are valuable for the study of how individuals react to and manipulate their local social and ecological environments.
About new quasilinear model of heat conduction with finite velocity of heat front movement  [PDF]
A. N. Skripka
Physics , 2003,
Abstract: A new quasilinear mathematical model of heat conduction with finite velocity of heat front movement is offered.
The Impact of the Earth’s Movement through the Space on Measuring the Velocity of Light  [PDF]
Milo? ?ojanovi?
Journal of Applied Mathematics and Physics (JAMP) , 2016, DOI: 10.4236/jamp.2016.46121
Abstract: Goal of this experiment is basically measuring the velocity of light. As usual we will measure two-way velocity of light (from A to B and back). In contrast to the similar experiments we will not assume that speeds of light from A to B and from B to A are equal. To achieve this we will take into account Earth’s movement through the space, rotation around its axis and apply “least squares method for cosine function”, which will be explained in Section 9. Assuming that direction East-West is already known, one clock, a source of light and a mirror, is all equipment we need for this experiment.
THE INFLUENCE OF VELOCITY OVERSHOOT MOVEMENT ARTIFACT ON ISOKINETIC KNEE EXTENSION TESTS  [cached]
Fabiano Peruzzo Schwartz,Martim Bottaro,Rodrigo Souza Celes,Lee E. Brown
Journal of Sports Science and Medicine , 2010,
Abstract: Exercise on an isokinetic device involves three distinct movement phases: acceleration, constant velocity, and deceleration. Inherent in these phases are unique occurrences that may confound test data and, thereby, test interpretation. Standard methods of data reduction like windowing and other techniques consist of removing the acceleration and deceleration phases in order to assure analysis under constant velocity conditions. However, none of these techniques adequately quantify the velocity overshoot (VO) movement artifact which is a result of the devices resistance imposed to the limb. This study tested the influence of VO on isokinetic data interpretation. A computational algorithm was developed to accurately identify each movement phase and to delineate the VO segment. Therefore, the VO was then treated as a fourth and independent phase. A total of sixteen healthy men (26.8 ± 4.7 yrs, 1.76 ± 0.05 m, and 79.2 ± 9.4 kg) performed two sets of ten maximal concentric extension repetitions of their dominant knee (at 60o·s-1 and 180o·s-1), on separate days and in a counterbalanced order, on a Biodex System 3 Pro dynamometer. All the phases of the isokinetic exercise were measured in terms of their biomechanical descriptors and according to the developed algorithm, the windowing method, and a data reduction technique that eliminates the first and last 10o of the total range of motion. Results showed significant differences (p < 0.05) between the constant velocity phases found by each method: the largest segment was obtained with the windowing method; the second one, with the algorithm; and the smallest, with data reduction technique. The point of peak torque was not affected by none of the techniques, but significant differences (p < 0.05) were found between the data including and not including the VO phase, concerning total work, time interval, and average length of load range: VO represents more than 10% of the amount calculated in constant velocity phase. As a consequence, the correct removal of VO was suggested as a required procedure to adequately interpret isokinetic tests. Therefore, the use of the proposed algorithm is advisable in order to perform analysis according to the isokinetic definition
Level velocity statistics of hyperbolic chaos  [PDF]
R. Sankaranarayanan
Physics , 2003, DOI: 10.1016/j.physleta.2004.03.031
Abstract: A generalized version of standard map is quantized as a model of quantum chaos. It is shown that, in hyperbolic chaotic regime, second moment of quantum level velocity is $\sim 1/\hbar$ as predicted by the random matrix theory.
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