The influence of space loading suits on interhemispheric asymmetry of the brain in infantile spastic cerebral palsy

The paper presents the study concerning influence of somatosensory stimulation (single wearing of either space loading costume "PENGUIN" or its modification--"ADELY" costume) on the individual profile of interhemispheral cerebral assymmetry (IPIHCA) in patients with spastic form of infantile cerebral paralysis (ICP). The computer stabilograph analyzed motor arms' asymmetry, sensory asymmetry of visual hemiareas, asymmetry of the position of centre of gravity. It is shown that peculiarities of the realization of the standing position either with visual control or without it both in healthy individuals and in patients depended on initial IPIHCA. Initial stability was higher in healthy individuals than in patients, besides in healthy persons it was higher in right-handers while in patients--in left-handers. There was possibility of changes of both IPIHCA and stability during keeping up vertical position even during single somatosensory stimulation. For elaboration of new criteria of the estimation of the efficiency of treatment in patients with CNS damages, including ICP, it is necessary to take into consideration different influence of somatosensory stimulation on IPIHC in right-handers and left-handers.     

Genetic and Environmental Influences on Pubertal Development: Longitudinal Data From Finnish Twins at Ages 11 and 14.

To study sources of individual differences in pubertal development, the authors fit a sex-limitation common factor model to data reported, at ages 11 and 14 years, by 1,891 twin pairs on items that comprise the Pubertal Development Scale (PDS; A. C. Petersen, L. Crockett, M. Richards, & A. Boxer, 1988). The model divides variation into a general pubertal factor and item-specific variation and, in addition, decomposes it into constituent sources. In both boys and girls, genetic influences made the largest contribution to variance common to PDS items. Genetic and nonshared environmental factors accounted for variation specific to PDS items in boys, whereas for girls, common environmental influences were added for growth spurt and menarcheal status. For both common and item-specific variation, genetic effects were partially sex specific. Subsidiary analyses found accelerated maturation in both boys and girls who at age 14 were reared in father-absent homes. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

A hybrid Branch-and-Bound and evolutionary approach for allocating strings of applications to heterogeneous distributed computing systems

Providing efficient workload management is an important issue for a large-scale heterogeneous distributed computing environment where a set of periodic applications is executed. The considered shipboard distributed system is expected to operate in an environment where the input workload is likely to change unpredictably, possibly invalidating a resource allocation that was based on the initial workload estimate. The tasks consist of multiple strings, each made up of an ordered sequence of applications. There is a quality of service (QoS) minimum throughput constraint that must be satisfied for each application in a string, and a maximum utilization constraint that must be satisfied on each of the hardware resources in the system. The challenge, therefore, is to efficiently and robustly manage both computation and communication resources in this unpredictable environment to achieve high performance while satisfying the imposed constraints. This work addresses the problem of finding a robust initial allocation of resources to strings of applications that is able to absorb some level of unknown input workload increase without rescheduling. The proposed hybrid two-stage method of finding a near-optimal allocation of resources incorporates two specially designed mapping techniques: (1) the Permutation Space Genitor-Based heuristic, and (2) the follow-up Branch-and-Bound heuristic based on an Integer Linear Programming (ILP) problem formulation. The performance of the proposed resource allocation method is evaluated under different simulation scenarios and compared to an iteratively computed upper bound.     

EMUSIM: an integrated emulation and simulation environment for modeling,evaluation, and validation of performance of Cloud computing applications

Cloud computing allows the deployment and delivery of application services for users worldwide. Software as a Service providers with limited upfront budget can take advantage of Cloud computing and lease the required capacity in a pay‐as‐you‐go basis, which also enables flexible and dynamic resource allocation according to service demand. One key challenge potential Cloud customers have before renting resources is to know how their services will behave in a set of resources and the costs involved when growing and shrinking their resource pool. Most of the studies in this area rely on simulation‐based experiments, which consider simplified modeling of applications and computing environment. In order to better predict service's behavior on Cloud platforms, we developed an integrated architecture that is based on both simulation and emulation. The proposed architecture, named EMUSIM, automatically extracts information from application behavior via emulation and then uses this information to generate the corresponding simulation model. We performed experiments using an image processing application as a case study and found that EMUSIM was able to accurately model such application via emulation and use the model to supply information about its potential performance in a Cloud provider. We also discuss our experience using EMUSIM for deploying applications in a real public Cloud provider. EMUSIM is based on an open source software stack and therefore it can be extended for analysis behavior of several other applications. Copyright © 2012 John Wiley & Sons, Ltd.     

Association between spinal loads and the psychophysical determination of maximum acceptable force during pushing tasks

The objective of this study was to investigate potential associations between an individual's psychophysical maximum acceptable force (MAF) during pushing tasks and biomechanical tissue loads within the lumbar spine. Ten subjects (eight males, two females) pushed a cart with an unknown weight at one push every two minute for a distance of 3.9 m. Two independent variables were investigated, cart control and handle orientation while evaluating their association with the MAF. Dependent variables of hand force and tissue loads for each MAF determination and preceding push trial were assessed using a validated, electromyography-assisted biomechanical model that calculated spinal load distribution throughout the lumbar spine. Results showed no association between spinal loads and the MAF. Only hand forces were associated with the MAF. Therefore, MAFs may be dependent upon tactile sensations from the hands, not the loads on the spine and thus may be unrelated to risk of low back injury.

Practitioner Summary: Pushing tasks have become common in manual materials handling (MMH) and these tasks impose different tissue loads compared to lifting tasks. Industry has commonly used the psychophysical tables for job assent and decision of MMH tasks. However, due to the biomechanical complexity of pushing tasks, psychophysics may be misinterpreting risk.     

Modelling blast loads on buildings in complex city geometries

This paper is concerned with an accurate prediction of the effects of adjacent structures on the blast loads on a building in urban terrain. Blast loadings on structures have typically been evaluated using empirical relationships. These relationships assume that there are no obstacles between the charge and the target. In real situations, the actual blast loads can either be reduced due to shadowing by other buildings or can be enhanced due to the presence of other buildings in the vicinity. Results of the numerical simulations presented in this study for multiple buildings in an urban environment have demonstrated the importance of accounting for adjacent structures when determining the blast loads on buildings. An approach to determining the enhancement factors is described.     

Systems Engineering Analysis of a TRMM PR-Like Rainfall Retrieval Algorithm

Systems engineering constitutes a group of processes and methods to design and implement a system for optimal performance given limited time, technology, or resources. As with any system, it is important to understand which subcomponents are most important and which are less important so that appropriate resource allocations may be made. An example of a complex system is the Tropical Rainfall Measuring Mission (TRMM). Its subsystems include the satellite vehicle, the precipitation radar (PR), the ground validation system, and the retrieval algorithms. Each of these subsystems contributes to the overall success of the mission. Sensitivity analysis (SA) is a method whereby the output response from a model can be linked back to the variability in the input parameters. This paper describes a method of performing SA on a TRMM PR-like (TL) rainfall retrieval algorithm (based on the TRMM 2A25 algorithm) to better describe how the uncertainty in the model output can be apportioned to the uncertainty in the input factors and gain greater understanding as to the relative importance of each factor. For example, assuming a model with several input factors, if one factor is found to be the dominating cause of model error, and the others contribute relatively little, then resources can be devoted to improving the accuracy of one factor, thereby improving the overall model accuracy. This paper is based on global SA using a variance decomposition technique. Analyses are done and results are presented for factor importance for cases over both ocean and land. Results for the simple TL algorithm considered in this paper show that at low rain rate, the a and b coefficients in the R=aZ_e ^b relationship contribute the greatest amount to the output variance. At higher rain rates, above about 8 mm/h, the error from Deltasigmadeg is the greatest contributor to error in algorithm output