Miracle-dz/UniFAR-FTUs huggingface dataset:
Holding a Handle for Balance during Continuous Postural Perturbations—Immediate and Transitionary Effects on Whole Body Posture

When balance is exposed to perturbations, hand contacts are often used to assist postural control. We investigated the immediate and the transitionary effects of supportive hand contacts during continuous anteroposterior perturbations of stance by automated waist-pulls. Ten young adults were perturbed for 5 min and required to maintain balance by holding to a stationary, shoulder-high handle and following its removal. Center of pressure (COP) displacement, hip, knee and ankle angles, leg and trunk muscle activity and handle contact forces were acquired. The analysis of results show that COP excursions are significantly smaller when the subjects utilize supportive hand contact and that the displacement of COP is strongly correlated to the perturbation force and significantly larger in the anterior than posterior direction. Regression analysis of hand forces revealed that subjects utilized the hand support significantly more during the posterior than anterior perturbations. Moreover, kinematical analysis showed that utilization of supportive hand contacts alter posture of the whole body and that postural readjustments after the release of the handle, occur at different time scales in the hip, knee and ankle joints. Overall, our findings show that supportive hand contacts are efficiently used for balance control during continuous postural perturbations and that utilization of a handle has significant immediate and transitionary effects on whole body posture.
Selection of cooperative parteners for virtual enterprise based on ant colony algorithm with the test points

Applying the ant colony algorithm to select cooperative partners for virtual enterprise doesn't need any artificial intervention. On the contrary, it can find the best scheme which satisfy the constraints intelligently through the interaction of indicators. In this paper, social reputation of companies is considered as a implicit index, which conforms to requirements of contemporary business. At the same time, this paper put forward an ant colony algorithm with test points to make each task requirement to be free to choose one or more companies to complete the task. In this way, the optimal proportion of distribution can be achieved, and the calculation process of the algorithm can be simplified as well.
Supernova Neutrino Opacity from Nucleon-Nucleon Bremsstrahlung and Related Processes

Elastic scattering on nucleons, νN → Nν, is the dominant supernova (SN) opacity source for μ and τ neutrinos. The dominant energy- and number-changing processes were thought to be νe- → e-ν and ν↔e+e− until Suzuki showed that the bremsstrahlung process νNN↔NN was actually more important. We find that for energy exchange, the related "inelastic scattering process" νNN↔NNν is even more effective by about a factor of 10. A simple estimate implies that the νμ and ντ spectra emitted during the Kelvin-Helmholtz cooling phase are much closer to that of e than had been thought previously. To facilitate a numerical study of the spectra formation we derive a scattering kernel that governs both bremsstrahlung and inelastic scattering and give an analytic approximation formula. We consider only neutron-neutron interactions; we use a one-pion exchange potential in Born approximation, nonrelativistic neutrons, and the long-wavelength limit, simplifications that appear justified for the surface layers of an SN core. We include the pion mass in the potential, and we allow for an arbitrary degree of neutron degeneracy. Our treatment does not include the neutron-proton process and does not include nucleon-nucleon correlations. Our perturbative approach applies only to the SN surface layers, i.e., to densities below about 1014 g cm-3.
Confined Crystals of the Smallest Phase-Change Material

The demand for high-density memory in tandem with limitations imposed by the minimum feature size of current storage devices has created a need for new materials that can store information in smaller volumes than currently possible. Successfully employed in commercial optical data storage products, phase-change materials, that can reversibly and rapidly change from an amorphous phase to a crystalline phase when subject to heating or cooling have been identified for the development of the next generation electronic memories. There are limitations to the miniaturization of these devices due to current synthesis and theoretical considerations that place a lower limit of 2 nm on the minimum bit size, below which the material does not transform in the structural phase. We show here that by using carbon nanotubes of less than 2 nm diameter as templates phase-change nanowires confined to their smallest conceivable scale are obtained. Contrary to previous experimental evidence and theoretical expectations, the nanowires are found to crystallize at this scale and display amorphous-to-crystalline phase changes, fulfilling an important prerequisite of a memory element. We show evidence for the smallest phase-change material, extending thus the size limit to explore phase-change memory devices at extreme scales.
Irregular to Regular Sampling, Denoising, and Deconvolution

We propose a restoration algorithm for band limited images that considers irregular (perturbed) sampling, denoising, and deconvolution. We explore the application of a family of regularizers that allow us to control the spectral behavior of the solution combined with the irregular to regular sampling algorithms proposed by Feichtinger, Grochenig, Rauth, and Strohmer. Moreover, the constraints given by the image acquisition model are incorporated as a set of local constraints. The analysis of such constraints leads to an early stopping rule meant to improve the speed of the algorithm. Finally, we present experiments focused on the restoration of satellite images, where the microvibrations are responsible of the type of distortions we are considering here. We will compare results of the proposed method with previous methods and show an extension to zoom.
Heuristics for Improving the Performance of Online SVM Training Algorithms

Recently, the sequential minimal optimization algorithm (SMO) was introduced [1, 2] as an effective method for training support vector machines (SVMs) on classification tasks defined on sparse data sets. SMO differs from most SVM algorithms in that it does not require a quadratic programming (QP) solver. One problem with SMO is that its rate of convergence slows down dramatically when data is non-sparse and when there are many support vectors in the solution. This work addresses this issue by showing how the kernel function outputs can be effectively cached. Caching in SMO is non-trivial because SMO tends to randomly access data points in a training set. The proposed modifications can improve convergence time by orders of magnitude.
Dynamic Routing and Virtual Machine Consolidation in Green Clouds

In the last few years, there has been a remarkable growth in the number of data centers, which represent one of the leading sources of increased business data traffic on the Internet. An effect of the growing scale and the wide use of data centers is the dramatic increase of power consumption, with significant consequences both in terms of environmental and operational costs. Hence, energy awareness has become one of the major design constraints for Cloud infrastructures. In order to face these challenges, a new generation of energy-efficient and ecosustainable network infrastructures is needed. In this work, a novel energy-aware resource orchestration framework for distributed Cloud infrastructures is introduced, in order to manage both network and IT resources in a typical optical backbone. A high-level overview of the system architecture is provided by focusing on the definition of the different layers of the whole infrastructure, and introducing the Path Computation Element, which is the key component of the proposed architecture. The aim is to explain how both network and IT resources can be managed while, at the same time, the overall power consumption is being minimized and QoS requirements are satisfied. Finally, a green migration plan that is obtained by applying Virtual Machine relocation algorithms is discussed, in order to dynamically react to the fluctuating resource requirements of the VMs
Brain regions associated with the acquisition of conditioned place preference for cocaine vs. social interaction

Positive social interaction could play an essential role in switching the preference of the substance dependent individual away from drug related activities. We have previously shown that conditioned place preference (CPP) for cocaine at the dose of 15 mg/kg and CPP for four 15-min episodes of social interaction were equally strong when rats were concurrently conditioned for place preference by pairing cocaine with one compartment and social interaction with the other. The aim of the present study was to investigate the differential activation of brain regions related to the reward circuitry after acquisition/expression of cocaine CPP or social interaction CPP. Our findings indicate that cocaine CPP and social interaction CPP activated almost the same brain regions. However, the granular insular cortex and the dorsal part of the agranular insular cortex were more activated after cocaine CPP, whereas the prelimbic cortex and the core subregion of the nucleus accumbens were more activated after social interaction CPP. These results suggest that the insular cortex appears to be potently activated after drug conditioning learning while activation of the prelimbic cortex—nucleus accumbens core projection seems to be preferentially involved in the conditioning to non-drug stimuli such as social interaction.
An investigation into the electromagnetic behavior of the vector controlled induction motor drives

This paper explores the fundamental magnetic response in vector controlled induction motors. Radial and tangential components of the electromagnetic force in the airgap of a vector controlled induction machine have been investigated. The study reveals the correlation between the average value and undulation of the force components to the stator currents in the synchronous reference frame. Furthermore, the flux and force density distributions for an induction machine with and without vector control, with rotor dynamic eccentricity, and with broken rotor bar (i.e. eccentric rotor) conditions have been compared. The studies have been performed using a transient finite element model of a 4-pole induction machine.
Perceived control and purchase intention in online shopping: The mediating role of self-efficacy

We investigated whether or not self-efficacy mediated the enhancing effect of perceived control on purchase intention in online shopping. We randomly assigned 263 participants to experimental conditions in which they encountered different customer services. We assessed their perceived control, self-efficacy, and purchase intention via a self-evaluation survey. Results indicated that participants with the availability of live customer service had a higher level of perceived control and stronger purchase intention. There were significantly positive correlations among perceived control, self-efficacy, and purchase intention. Structural equation modeling showed that self-efficacy was a significant partial mediator of the effect of perceived control on purchase intention, accounting for 17.4% of the total effect. This finding implies that the provision of customer service in online shopping that leads consumers to have a perception of greater control can enhance their self-efficacy, and induce stronger purchase intention.
Collaborative Face Orientation Detection in Wireless Image Sensor Networks

Most face recognition and tracking techniques employed in surveillance and human-computer interaction (HCI) systems rely on the assumption of a frontal view of the human face. In alternative approaches, knowledge of the orientation angle of the face in captured images can improve the performance of techniques based on non-frontal face views. In this paper, we propose a collaborative technique for face analysis in smart camera networks with a dual objective of detecting the camera view closest to a frontal view of the subject, and estimating the face orientation angles in all the camera views based on additional fusion of local angle estimates. Soft information indicating the probabilities of face and eye candidates in each image is exchanged between the cameras, and epipolar geometry mapping is employed to assess correspondence between candidates in different views. Once the camera with the closest view to the frontal face view is identified, further exchange of the face orientation angles estimated by all cameras allows for a collaborative refinement of the estimates according to their associated confidence levels. The proposed collaborative detection and estimation schemes employ low-complexity algorithms and do not require image transfer between the cameras. Hence, these schemes are applicable to networks of image sensors with in-node processing and narrowband wireless communication.
Programme-Based Assessment Mechanisms for Establishing a Culture of Excellence in Open and Distance Learning at the Zimbabwe Open University (ZOU)

This study sought to interrogate programme-based assessment mechanisms (PBAMs) for establishing a culture of excellence in open and distance learning (ODL) at the Zimbabwe Open University (ZOU). The study utilized a qualitative research methodology and adopted the case study research design. A population comprising Regional Programme Coordinators (RPCs) of the ZOU from two Regional Campuses was considered from which a sample of 20 (N=20) was selected. The purposive sampling technique was utilised in selecting the participants. The study used Questerviews as the primary research instruments. Data collected from the study was analysed based on the different thematic areas which were designed by the researchers as well as ranking specific service areas for programmes. The major findings of the study were that the ZOU academic programmes have official assessment documentation at Regional Campus level and are provided with maximum administrative support. The study further revealed that the programmes are assessed in a benchmarked way basing on the trends and standards of leading international universities. The study recommended that higher education open and distance learning (HEODL) institutions should generally have in place a standard and broad framework of programme-based assessment mechanism which covers key areas including programme design, implementation, review and assessment.
Development of a Paradigm for Examining Social Exclusion in Schizophrenia: Dissociating Expectancy Violations from Social Distress

Author(s): Clayson, Peter Eugene | Advisor(s): Miller, Gregory Allen; Yee, Cindy M | Abstract: Despite the well-established finding that psychosocial stressors influence symptom onset and clinical relapse in patients with schizophrenia, less is known about how these stressors influence such changes in schizophrenia and why only a subset of patients relapse. Stress elicited by social evaluative threat (SET) may provide a mechanism by which psychosocial stressors influence symptoms and relapse. The present study sought to develop a modified Cyberball paradigm to examine social exclusion, a type of SET, in patients in an effort to understand how sensitivity to SET impacts symptoms and relapse. Additionally, there is controversy regarding the functional significance of the activation of the dorsal anterior cingulate cortex (dACC) region of the brain during the Cyberball task, with some studies implicating dACC in detecting violations of expectancy and other studies implicating dACC in responding to social distress and negative affect. The present examination evaluated the functional significance of exclusion-related neural activity during the task. Electroencephalogram (EEG) data were recorded while 32 healthy participants completed a modified Cyberball paradigm. EEG data were fit to a source model with six regional sources, including dACC and anterior insula (AI). Participants self-reported similar levels of social distress to those reported in prior Cyberball studies, suggesting that the social exclusion manipulation was successful. Present findings provided evidence that early dACC activity is sensitive to violations of expectancy and that late dACC activity is sensitive to changes in negative affect. Bilateral AI activity was greater during the first block of the exclusion phase than during the inclusion phase and positively correlated with measures of social distress, supporting previous research implicating AI in responding to changes in social distress following exclusion. By identifying the functional significance of scalp- and source-space activity during a modified Cyberball task, these findings lay the groundwork for examining SET in patients with schizophrenia. This study capitalized on the temporal resolution of EEG in order to identify the functional significance of early and late dACC activity and provided evidence that the functional significance of dACC is not fully accounted for by either expectancy violations or social distress and negative affect alone.
Dietary Salt Intake, Sugar-Sweetened Beverage Consumption, and Obesity Risk

OBJECTIVE: To determine the association among dietary salt, fluid, and sugar-sweetened beverage (SSB) consumption and weight status in a nationally representative sample of Australian children aged 2 to 16 years. METHODS: Cross-sectional data from the 2007 Australian National Children’s Nutrition and Physical Activity Survey. Consumption of dietary salt, fluid, and SSB was determined via two 24-hour dietary recalls. BMI was calculated from recorded height and weight. Regression analysis was used to assess the association between salt, fluid, SSB consumption, and weight status. RESULTS: Of the 4283 participants, 62% reported consuming SSBs. Older children and those of lower socioeconomic status (SES) were more likely to consume SSBs (both Ps < .001). Dietary salt intake was positively associated with fluid consumption (r = 0.42, P < .001); each additional 1 g/d of salt was associated with a 46 g/d greater intake of fluid, adjusted for age, gender, BMI, and SES (P < .001). In those consuming SSBs (n = 2571), salt intake was positively associated with SSB consumption (r = 0.35, P < .001); each additional 1 g/d of salt was associated with a 17 g/d greater intake of SSB, adjusted for age, gender, SES, and energy (P < .001). Participants who consumed more than 1 serving (≥250 g) of SSB were 26% more likely to be overweight/obese (odds ratio: 1.26, 95% confidence interval: 1.03–1.53). CONCLUSIONS: Dietary salt intake predicted total fluid consumption and SSB consumption within consumers of SSBs. Furthermore, SSB consumption was associated with obesity risk. In addition to the known benefits of lowering blood pressure, salt reduction strategies may be useful in childhood obesity prevention efforts.
Motif Tool Manager: a web-based framework for motif discovery

MOTIVATION Motif Tool Manager is a web-based framework for comparing and combining different approaches to discover novel DNA motifs. It comes with a set of five well-known approaches to motif discovery. It provides an easy mechanism for adding new motif finding tools to the framework through a web-interface and a minimal setup of the tools on the server. Users can execute the tools through the web-based framework and compare results from such executions. The framework provides a basic mechanism for identifying the most similar motif candidates found by a majority of themotif finding tools. AVAILABILITY http://cetus.cs. memphis.edu/motif
Reverse engineering complex join queries

We study the following problem: Given a database D with schema G and an output table Out, compute a join query Q that generates OUT from D. A simpler variant allows Q to return a superset of Out. This problem has numerous applications, both by itself, and as a building block for other problems. Related prior work imposes conditions on the structure of Q which are not always consistent with the application, but simplify computation. We discuss several natural SQL queries that do not satisfy these conditions and cannot be discovered by prior work. In this paper, we propose an efficient algorithm that discovers queries with arbitrary join graphs. A crucial insight is that any graph can be characterized by the combination of a simple structure, called a star, and a series of merge steps over the star. The merge steps define a lattice over graphs derived from the same star. This allows us to explore the set of candidate solutions in a principled way and quickly prune out a large number of infeasible graphs. We also design several optimizations that significantly reduce the running time. Finally, we conduct an extensive experimental study over a benchmark database and show that our approach is scalable and accurately discovers complex join queries.
Wireless P 2 P : Problem or Opportunity ?

P2P is currently considered a problem by many wired and wireless providers, especially because of the large amount of traffic it generates. However, given new technology developments such as Wi-Fi Direct, we see an opportunity for P2P in mobile settings that, rather than treating mobiles as second-class citizens, seeks to take advantage of their capabilities over stationary devices. In this paper, we outline a new approach for fully decentralized mobile P2P that allows mobiles to run a variety of services and at the same time alleviates data overload in mobile networks. We consider mobiles integral and a richer class of nodes, and assume that they are capable of forming P2P networks without necessarily relying on the aid of stationary hosts or servers. We present a new architecture based on JXTA middleware, which is meant to not only optimize mobile resources, but also aims to take full advantage of the features that mobiles offer, such as mobility, ubiquity, location-awareness and sensors. Keywords-Wireless; Peer-To-Peer; Mobiles; Broadbands.
AHSM: ADAPTIVE PACKET FILTERING WITH NETWORK TRAFFIC STATISTICS

Packet filtering plays an important role in network devices such as firewalls, routers, security gateways and intrusion detection systems. Numerous schemes have been proposed to improve packet filtering techniques. Many previous works struggled to utilize the characteristics of filtering rule-sets as optimization heuristics. However, there are rarely efforts excavating network traffic characteristics. This paper focuses on analyzing the statistical characteristics of network traffic and imposing it to optimize packet filtering algorithms. Contribution of the paper includes two aspects: first, the skewness and time correlation in real-life traffic is presented to illustrate network traffic statistics; second, an adaptive packet filtering algorithm, AHSM, is proposed based on HSM algorithm for improving average packet filtering speed. AHSM takes traffic statistics as heuristics and constructs statistical search trees for single field searching. Experimental results show that the optimized algorithm reduces 20%~50% of the single field matching overhead compared with the HSM algorithm and improves the overall performance by 35%~45%, while retaining the same memory usage.