Knee joint kinematics of the pendulum test in children with and without Down syndrome

Background: The Wartenberg pendulum test is a common clinical test that is used to measure stiffness about the knee in persons with and without disabilities such as cerebral palsy and Down syndrome (DS). Adults and adolescents with DS show fewer number of swing cycles and a lower relaxation index than healthy controls. However, it is not clear if children with DS show a similar trend compared to typically developing (TD) children. Research question: Was the knee joint kinematics different between children with and without DS during the pendulum test? Methods: Thirteen children with DS and 13 TD children participated in this study. There were two load conditions: no load (NL) and with ankle load (AL) equal to 2 % of the subject’s body weight. Five trials of a pendulum test were collected for each condition. Results: The DS group showed a smaller first flexion excursion, a lower relaxation index, lower mean and peak velocities and accelerations during the first and second flexion and extension, and greater variability of acceleration during the first flexion than the TD group across both load conditions. This suggests that the DS group may have greater stiffness of the knee than the TD group to compensate for joint instability. Significance: The pendulum test appears to be a valid test to evaluate the passive stiffness of the knee in children with DS. The lower relaxation index in children with DS suggests that larger bursts of quadriceps may be activated during a pendulum test, particularly in the first flexion excursion, to assure the knee joint stability

Dynamique de systèmes optomécaniques hybrides et multimodes

Recent experimental developments have brought into focus optomechanical systems containing multiple optical and mechanical modes interacting with each other. Examples include a setup with a movable membrane between two end-mirrors and “optomechanical crystal” devices that support localized optical and mechanical modes in a photonic crystal type structure. We discuss how mechanical driving of such structures results in coherent photon transfer between optical modes, and how the physics of Landau–Zener–Stueckelberg oscillations arises in this context. Another area where multiple modes are involved are hybrid systems. There, we review the recent proposal of a single atom whose mechanical motion is coupled to a membrane via the light field. This is a special case of the general principle of cavity-mediated mechanical coupling. Such a setup would allow the well-developed tools of atomic physics to be employed to access the quantum state of the ‘macroscopic’ mechanical mode of the membrane

Self-healing capability of concrete with crystalline admixtures in different environments

The aim of this study is analyzing the self-healing effect of a crystalline admixture in four types of environmental exposure comparing with a reference concrete. Healing was studied by means of permeability tests on cracked specimens and physical closing of the crack was observed by optic microscope and quantified through crack geometrical parameters. The studied crack openings were under 300 pm and the time set for healing was 42 days. The results show a different healing behavior depending on the exposure and the presence of the crystalline admixture, demonstrating that the presence of water is necessary for the healing reactions. (C) 2015 Elsevier Ltd. All rights reserved.Roig Flores, M.; Moscato, S.; Serna Ros, P.; Ferrara, L. (2015). Self-healing capability of concrete with crystalline admixtures in different environments. Construction and Building Materials. 86:1-11. doi:10.1016/j.conbuildmat.2015.03.091S1118

mSpray: A mobile phone technology to improve malaria control efforts and monitor human exposure to malaria control pesticides in Limpopo, South Africa

Recent estimates indicate that malaria has led to over half a million deaths worldwide, mostly to African children. Indoor residual spraying (IRS) of insecticides is one of the primary vector control interventions. However, current reporting systems do not obtain precise location of IRS events in relation to malaria cases, which poses challenges for effective and efficient malaria control. This information is also critical to avoid unnecessary human exposure to IRS insecticides. We developed and piloted a mobile-based application (mSpray) to collect comprehensive information on IRS spray events. We assessed the utility, acceptability and feasibility of using mSpray to gather improved homestead- and chemical-level IRS coverage data. We installed mSpray on 10 cell phones with data bundles, and pilot tested it with 13 users in Limpopo, South Africa. Users completed basic information (number of rooms/shelters sprayed; chemical used, etc.) on spray events. Upon submission, this information as well as geographic positioning system coordinates and time/date stamp were uploaded to a Google Drive Spreadsheet to be viewed in real time. We administered questionnaires, conducted focus groups, and interviewed key informants to evaluate the utility of the app. The low-cost, cell phone-based “mSpray” app was learned quickly by users, well accepted and preferred to the current paper-based method. We recorded 2865 entries (99.1% had a GPS accuracy of 20 m or less) and identified areas of improvement including increased battery life. We also identified a number of logistic and user problems (e.g., cost of cell phones and cellular bundles, battery life, obtaining accurate GPS measures, user errors, etc.) that would need to be overcome before full deployment. Use of cell phone technology could increase the efficiency of IRS malaria control efforts by mapping spray events in relation to malaria cases, resulting in more judicious use of chemicals that are potentially harmful to humans and the environment.This publication was supported by grant numbers: R01 ES020360 and R01 ES020360-S1 from the National Institute of Environmental Health Sciences (NIEHS). We would also like to thank Zinto Corporation, South Africa for donating Smartphones

Concurrent tolerance allocation and scheduling for complex assemblies

Traditionally, tolerance allocation and scheduling have been dealt with separately in the literature. The aim of tolerance allocation is to minimize the tolerance cost. When scheduling the sequence of product operations, the goal is to minimize the makespan, mean flow time, machine idle time, and machine idle time cost. Calculations of manufacturing costs derived separately using tolerance allocation and scheduling separately will not be accurate. Hence, in this work, component tolerance was allocated by minimizing both the manufacturing cost (sum of the tolerance and quality loss cost) and the machine idle time cost, considering the product sequence. A genetic algorithm (GA) was developed for allocating the tolerance of the components and determining the best product sequence of the scheduling. To illustrate the effectiveness of the proposed method, the results are compared with those obtained with existing wheel mounting assembly discussed in the literature

Identification of serum biomarkers of hepatocarcinoma through liquid chromatography/mass spectrometry-based metabonomic method

Late diagnosis of hepatocarcinoma (HCC) is one of the most primary factors for the poor survival of patients. Thereby, identification of sensitive and specific biomarkers for HCC early diagnosis is of great importance in biological medicine to date. In the present study, serum metabolites of the HCC patients and healthy controls were investigated using the improved liquid chromatography–mass spectrometry (LC/MS). A wavelet-based method was utilized to find and align peaks of LC–MS. The characteristic peaks were selected by performing a two-sample t test statistics (p value <0.05). Clustering analysis based on principal component analysis showed a clear separation between HCC patients and healthy individuals. The serum metabolite, namely 1-methyladenosine, was identified as the characteristic metabolite for HCC. Moreover, receiver–operator curves were calculated with 1-methyladenosine and/or alpha fetal protein (AFP). The higher area under curve value was achieved in 1-methyladenosine group than AFP group (0.802 vs. 0.592), and the diagnostic model combining 1-methyladenosine with AFP exhibited significant improved sensitivity, which could identify those patients who missed the diagnosis of HCC by determining serum AFP alone. Overall, these results suggested that LC/MS-based metabonomic study is a potent and promising strategy for identifying novel biomarkers of HCC

Multi-objective optimization for optimum tolerance synthesis with process and machine selection using a genetic algorithm

This paper presents a new approach to the tolerance synthesis of the component parts of assemblies by simultaneously optimizing three manufacturing parameters: manufacturing cost, including tolerance cost and quality loss cost; machining time; and machine overhead/idle time cost. A methodology has been developed using the Genetic Algorithm (GA) technique to solve this multi-objective optimization problem. The effectiveness of the proposed methodology has been demonstrated by solving a wheel mounting assembly problem consisting of five components, two subassemblies, two critical dimensions, two functional tolerances, and eight operations. Significant cost saving can be achieved by employing this methodology

Multi-scale Inference of Interaction Rules in Animal Groups Using Bayesian Model Selection

Inference of interaction rules of animals moving in groups usually relies on an analysis of large scale system behaviour. Models are tuned through repeated simulation until they match the observed behaviour. More recent work has used the fine scale motions of animals to validate and fit the rules of interaction of animals in groups. Here, we use a Bayesian methodology to compare a variety of models to the collective motion of glass prawns (Paratya australiensis). We show that these exhibit a stereotypical ‘phase transition’, whereby an increase in density leads to the onset of collective motion in one direction. We fit models to this data, which range from: a mean-field model where all prawns interact globally; to a spatial Markovian model where prawns are self-propelled particles influenced only by the current positions and directions of their neighbours; up to non-Markovian models where prawns have ‘memory’ of previous interactions, integrating their experiences over time when deciding to change behaviour. We show that the mean-field model fits the large scale behaviour of the system, but does not capture fine scale rules of interaction, which are primarily mediated by physical contact. Conversely, the Markovian self-propelled particle model captures the fine scale rules of interaction but fails to reproduce global dynamics. The most sophisticated model, the non-Markovian model, provides a good match to the data at both the fine scale and in terms of reproducing global dynamics. We conclude that prawns' movements are influenced by not just the current direction of nearby conspecifics, but also those encountered in the recent past. Given the simplicity of prawns as a study system our research suggests that self-propelled particle models of collective motion should, if they are to be realistic at multiple biological scales, include memory of previous interactions and other non-Markovian effects