Miracle-dz/UniFAR-FTUs huggingface dataset:
In Situ Methods, Infrastructures, and Applications on High Performance Computing Platforms

The considerable interest in the high performance computing (HPC) community regarding analyzing and visualization data without first writing to disk, i. e. , in situ processing, is due to several factors. First is an I/O cost savings, where data is analyzed/visualized while being generated, without first storing to a filesystem. Second is the potential for increased accuracy, where fine temporal sampling of transient analysis might expose some complex behavior missed in coarse temporal sampling. Third is the ability to use all available resources, CPU's and accelerators, in the computation of analysis products. This STAR paper brings together researchers, developers and practitioners using in situ methods in extreme‐scale HPC with the goal to present existing methods, infrastructures, and a range of computational science and engineering applications using in situ analysis and visualization.
Surface Roughness Optimization of Polyamide-6/Nanoclay Nanocomposites Using Artificial Neural Network: Genetic Algorithm Approach

During the past decade, polymer nanocomposites attracted considerable investment in research and development worldwide. One of the key factors that affect the quality of polymer nanocomposite products in machining is surface roughness. To obtain high quality products and reduce machining costs it is very important to determine the optimal machining conditions so as to achieve enhanced machining performance. The objective of this paper is to develop a predictive model using a combined design of experiments and artificial intelligence approach for optimization of surface roughness in milling of polyamide-6 (PA-6) nanocomposites. A surface roughness predictive model was developed in terms of milling parameters (spindle speed and feed rate) and nanoclay (NC) content using artificial neural network (ANN). As the present study deals with relatively small number of data obtained from full factorial design, application of genetic algorithm (GA) for ANN training is thought to be an appropriate approach for the purpose of developing accurate and robust ANN model. In the optimization phase, a GA is considered in conjunction with the explicit nonlinear function derived from the ANN to determine the optimal milling parameters for minimization of surface roughness for each PA-6 nanocomposite.
Kernel-based object tracking using adaptive feature selection

One of the major parts of the multimedia research is object localisation and object tracking. In this paper we try to create a surveillance system that uses object tracking and background subtraction. The final system can keep track of a person walking trough a room and detect if something is left behind. For the tracker, adaptive feature selection is used which means that the tracker selects the best image feature it can find to track the object all by itself. For this purpose we implemented several image features. The background subtractor works using an adaptive background and motion detection system.
Discrete Time Rescaling Theorem: Determining Goodness of Fit for Discrete Time Statistical Models of Neural Spiking

One approach for understanding the encoding of information by spike trains is to fit statistical models and then test their goodness of fit. The time-rescaling theorem provides a goodness-of-fit test consistent with the point process nature of spike trains. The interspike intervals (ISIs) are rescaled (as a function of the model's spike probability) to be independent and exponentially distributed if the model is accurate. A Kolmogorov-Smirnov (KS) test between the rescaled ISIs and the exponential distribution is then used to check goodness of fit. This rescaling relies on assumptions of continuously defined time and instantaneous events. However, spikes have finite width, and statistical models of spike trains almost always discretize time into bins. Here we demonstrate that finite temporal resolution of discrete time models prevents their rescaled ISIs from being exponentially distributed. Poor goodness of fit may be erroneously indicated even if the model is exactly correct. We present two adaptations of the time-rescaling theorem to discrete time models. In the first we propose that instead of assuming the rescaled times to be exponential, the reference distribution be estimated through direct simulation by the fitted model. In the second, we prove a discrete time version of the time-rescaling theorem that analytically corrects for the effects of finite resolution. This allows us to define a rescaled time that is exponentially distributed, even at arbitrary temporal discretizations. We demonstrate the efficacy of both techniques by fitting generalized linear models to both simulated spike trains and spike trains recorded experimentally in monkey V1 cortex. Both techniques give nearly identical results, reducing the false-positive rate of the KS test and greatly increasing the reliability of model evaluation based on the time-rescaling theorem.
Screening vdsm outliers using nominal and subthreshold supply voltage I/sub DDQ/

Very Deep Sub-Micron (VDSM) defects are resolved as Statistical Post-Processing™ (SPP) outliers of a new IDDQ screen. The screen applies an IDDQ pattern once to the Device Under Test (DUT) and takes two quiescent current measurements. The quiescent current measurements are taken at nominal and at subthreshold supply voltages. The scr een is demonstrated with 0. 18µm and 0. 13µm volume data. The screen's effectiveness is compared to stuck -at and other IDDQ screens.
Modification in self-rated health in patients discharged by a geriatric rehabilitation ward

Self-rated health is a valuable outcome in geriatric rehabilitation besides objective results. The present work aims at measuring and analyzing overall health as it is perceived at admission into and at discharge from a geriatric rehabilitation ward. Overall health was self-appraised through a visual-analogue scale (VAS), spanning from 0 (worst) to 10 (best). We studied 1997 patients (70% females), aged 79 (standard deviation, s.d. 8.7) years; most were frail, either functionally, clinically and cognitively. 80% of patients were discharged to home after a length of stay lasting 47.5 (s.d. 22.7) days. At admission, 3/5 patients appraised favorably their overall health (VAS ≥ 6/10): at discharge, the proportion rose to 3/4, with a mean (s.d.) gain = 2 (2) points. The improvement in self-perceived health score positively correlates with the grade expressing clients’ overall satisfaction for the stay (p 0.001), and with discharge versus admission differences in: Barthel Index (BI) total score (p items GDS), pain (VAS 0 to 10). A Linear regression model predicting the changes in self-perceived health included changes in BI, MMSE, GDS, pain, dropping Tinetti test. Changes in self-rated health were positively correlated to functional gain adjusted for pre-morbid level, and to relative functional gain. By analysis of variance, health self-appraisal changed more favorably in patients discharged to home than for other social outcomes (all p
IMG/VR: a database of cultured and uncultured DNA Viruses and retroviruses

Viruses represent the most abundant life forms on the planet. Recent experimental and computational improvements have led to a dramatic increase in the number of viral genome sequences identified primarily from metagenomic samples. As a result of the expanding catalog of metagenomic viral sequences, there exists a need for a comprehensive computational platform integrating all these sequences with associated metadata and analytical tools. Here we present IMG/VR (https://img.jgi.doe.gov/vr/), the largest publicly available database of 3908 isolate reference DNA viruses with 264 413 computationally identified viral contigs from >6000 ecologically diverse metagenomic samples. Approximately half of the viral contigs are grouped into genetically distinct quasi-species clusters. Microbial hosts are predicted for 20 000 viral sequences, revealing nine microbial phyla previously unreported to be infected by viruses. Viral sequences can be queried using a variety of associated metadata, including habitat type and geographic location of the samples, or taxonomic classification according to hallmark viral genes. IMG/VR has a user-friendly interface that allows users to interrogate all integrated data and interact by comparing with external sequences, thus serving as an essential resource in the viral genomics community.
MoX-MAC: A low power and efficient access delay for mobile wireless sensor networks

Mobility management in Wireless Sensor Networks (WSNs) is a complex problem that must be taken into account in all layers of the protocol stack. But this mobility becomes very challenging at the MAC level in order to do not degrade the energy efficiency between sensor nodes that are in communication. However, among medium access protocols, sampling protocols reflect better the dynamics of such scenarios. Nevertheless, the main problem, of such protocols, remains the management of collisions and idle listening between nodes. Previous approaches like B-MAC and X-MAC, based on sampling protocols present some shortcomings. Therefore, we address the mobility issue of WSNs that use as medium access sampling protocols. It is worth noticing that sampling protocols remain the most adaptive protocols for dynamic scenarios. In this paper, we propose a mobile access solution based on the X-MAC protocol which remains a reference protocol. This proposal, called MoX-MAC, incorporates different mechanisms in order to mitigate the energy consumption of mobile sensor nodes. Through an extensive experimental validation, we show that MoX-MAC enables to reduce the energy consumption of sensor nodes, as well the medium access delay of node with respect to the channel, and the average packets loss.
MalikCredit - A New Credit Unit for P2P Computing

The peer-to-peer (P2P) paradigm operates in an uncontrolled voluntary environment and, as the shared resources contributed by the general public have no legal obligation with respect to resource provisioning, an incentive based approach is needed to motivate and encourage participants to continue with the project and attract new volunteers. The Berkeley Open Infrastructure for Network Computing (BOINC), one of the most widely used middleware platforms in P2P systems, has devised an Accounting System to provide incentives to the project participants in order to attract more participants and retain existing ones. The primary incentive provided by the BOINC Accounting System is the award of 'credits', which themselves have no monetary value. However, one of the problems with the credit system is the use of significantly inconsistent performance results obtained from the Dhrystone and Whetstone benchmarks for calculating credits. This study analyses the existing BOINC Credits calculation system and proposes a new credit unit - MalikCredits - based on a more consistent synthetic lightweight benchmark - MalikStone, which is specifically designed for the dynamic challenges of the P2P paradigm. The results of this newly proposed credit calculation system have highlighted its superiority over the BOINC Credit calculation system in terms of consistency.
Nanostructures for peroxidases

Peroxidases are enzymes catalyzing redox reactions that cleave peroxides. Their active redox centers have heme, cysteine thiols, selenium, manganese, and other chemical moieties. Peroxidases and their mimetic systems have several technological and biomedical applications such as environment protection, energy production, bioremediation, sensors and immunoassays design, and drug delivery devices. The combination of peroxidases or systems with peroxidase-like activity with nanostructures such as nanoparticles, nanotubes, thin films, liposomes, micelles, nanoflowers, nanorods and others is often an efficient strategy to improve catalytic activity, targeting, and reusability.
Querying Databases from Description Logics

Two diierent aspects of data management are addressed by description logics (DL) and databases (DB): the semantic organization of data and powerful reasoning services (by DL) and their eecient management and access (by DB). It is recently emerging that experiences from both DL and DB should prootably cross-fertilize each other, and a great interest is rising about this topic. In the present paper our technique, that allows uniform access { by means of a DL-based query language { to information distributed over knowledge bases and databases, is brieey reviewed. Our extended paradigm integrates the separately existing retrieving functions of description logics management systems (DLMS) and of database management systems (DBMS) in order to allow, via a query language grounded on a DL-based schema knowledge , uniformly formulating and answering queries, so that uniform retrieval from mixed knowledge/data bases is possible. In particular, some new developments extending those presented in Bresciani, 1994] are introduced. By means of them the mapping between DL concepts and DB views is not more limited to primitive concepts , but also to some non-primitively de-ned ones.
Wireless Magnetoelastic Resonance Sensors: A Critical Review

This paper presents a comprehensive review of magnetoelastic environmental sensor technology; topics include operating physics, sensor design, and illustrative applications. Magnetoelastic sensors are made of amorphous metallic glass ribbons or wires, with a characteristic resonant frequency inversely proportional to length. The remotely detected resonant frequency of a magnetoelastic sensor shifts in response to different physical parameters including stress, pressure, temperature, flow velocity, liquid viscosity, magnetic field, and mass loading. Coating the magnetoelastic sensor with a mass changing, chemically responsive layer enables realization of chemical sensors. Magnetoelastic sensors can be remotely interrogated by magnetic, acoustic, or optical means. The sensors can be characterized in the time domain, where the resonant frequency is determined through analysis of the sensor transient response, or in the frequency domain where the resonant frequency is determined from the frequency-amplitude spectrum of the sensor.
Understanding students’ experiences in a PE, health and well-being context: a self-determination theory perspective

ABSTRACT Framed by Self-Determination Theory, this investigation explored student experience as they engaged in their physical education (PE), health and well-being (HWB) curriculum in Scotland for the first time. We aimed to uncover the features of various learning environments that appeared to impact upon student motivation in PE over the period one academic year. We carried out focus group interviews with students from one state secondary school (secondary 1 and 2; ages 12–14) and its feeder primary schools (primary 7; age 11 years) immediately after a selection of PE lessons throughout the year. Furthermore, to provide some additional context for our analysis, the students in each year completed a questionnaire (pre–post) to identify and understand their motivation for PE over time. The results from the interviews indicated that students had a number of positive and negative PE experiences. However, the results from the questionnaire demonstrate that the students’ experiences during the first year of this ‘new’ curriculum had little impact on their motivation for PE. The findings highlight the importance of mixed methods research to provide context-specific account of student experience. This detail may be critical for the development of informed and effective pedagogy that supports student learning, health and well-being.
AMPA Receptor Channels with Long-Lasting Desensitization in Bipolar Interneurons Contribute to Synaptic Depression in a Novel Feedback Circuit in Layer 2/3 of Rat Neocortex

A novel, local inhibitory circuit in layer 2/3 of rat somatosensory cortex is described that connects pyramidal cells reciprocally with GABAergic vasoactive intestinal polypeptide-immunoreactive bipolar interneurons. In paired whole-cell recordings, the glutamatergic unitary responses (EPSPs or EPSCs) in bipolar cells evoked by repetitive (10 Hz) stimulation of a pyramidal cell show strong frequency-dependent depression. Unitary IPSPs evoked in pyramidal cells by repetitive stimulation of bipolar cells, on average, maintained their amplitude. This suggests that the excitatory synapses on bipolar cells act as a low-pass filter in the reciprocal pyramid-to-bipolar circuit. The EPSCs in bipolar cells are mediated predominantly by AMPA receptor (AMPAR) channels. AMPARs desensitize rapidly and recover slowly from desensitization evoked by a brief pulse of glutamate. In slices, reduction of AMPAR desensitization by cyclothiazide (50–100 μm) or conditioning steady-state desensitization induced by application of extracellular AMPA (50 nm) or glutamate (50 μm) strongly reduced synaptic depression. It is concluded that in the local circuits between pyramidal and bipolar cells the desensitization of AMPARs in bipolar cells contributes to low-pass feedback inhibition of layer 2/3 pyramidal neurons by bipolar cells.
Improving Adult Learners’ Experience with Continuing Professional Education: A Transformational Path to Andragogy

The topic of this organizational improvement plan is to improve the learning satisfaction of adult learners in professional programs who return to universities to attend formal academic courses or programmes in class while pursuing their employment. Its purpose is to promote and support the teaching faculty involved in such courses and programmes in adopting andragogical methods to support those adult learners and improve their learning experience. The research is informed organizational leadership, organizational change, and by andragogic theories. This study will impact adult learners, teaching faculty, administrators, and organizational culture as it relates to Continuing Professional Education (CPE), with particular focus on helping instructors teach adults better using more andragogical methods. It is expected that in doing so, they will improve their learning experience, academic achievement, recruiting and retention of the growing number of professional adult learners seeking formal education at universities. The design of this study is based on quality assurance and quality improvement. It is a research-informed quality improvement plan based on the trans-theoretical model (Prochaska & Velicer, 1997), the intelligent leadership model (Sydänmaanlakka, 2003), and transformational leadership (Burns, 1978; Bass, 1985). This study promotes an organizational culture of learning that meets the targeted needs of learners, to improve their learning experience, while bringing greater awareness of the needs of adult learning.
ThomCat : A Bayesian Blackboard model of Hierarchical Temporal Perception XXXXXXXXXXXXX

We present a Bayesian blackboard system for temporal perception, applied to a minidomain task in musical scene analysis. It is similar to the classic CopyCat architecture (Hofstadter 1995) but is derived from rigourous modern Bayesian network theory (Bishop 2006), with heuristics added for speed. It borrows ideas of priming, pruning and attention and fuses them with modern inference algorithms, and provides a general theory of hierarchical constructive perception, illustrated and implemented in a minidomain.
Duration modeling results for an on-line handwriting recognizer

This paper describes a series of experiments that have been conducted to investigate the effect of duration modeling in a hidden Markov model (HMM) based online handwriting recognition system. The issues discussed include parametric vs. non-parametric distributions to model duration, different methods for training transition probabilities and the effect of weighting on duration terms.
Increased susceptibility to ischemia‐induced brain damage in transgenic mice overexpressing a dominant negative form of SHP2

Cell culture studies have established SH2 domain‐containing protein tyrosine phosphatase‐2 (SHP2) as an important factor in growth factor and cytokine‐activated signaling pathways. However, the significance of SHP2 in the mammalian central nervous system (CNS) is not known since early embryonic lethality occurs in shp2 null mice. To bypass this embryonic lethality, transgenic animals containing a catalytically inactive mutant of SHP2 (SHP2‐CS) under the control of a nestin intron II/thymidine kinase minimal promoter were generated. In the developing CNS of these animals, although high‐level transgene expression was detected in the neuroepithelium, there was no obvious abnormality in progenitor cell proliferation or migration. In the adult brain, high‐level transgene expression was detected in the subventricular zone, rostral migratory stream, dentate gyrus of hippocampus, and cerebellum. Because SHP2 function is likely important in cell survival pathways, we used a focal cerebral ischemia model to examined whether SHP2 is important during CNS injury. Ischemia‐induced damage and neuronal death was found to be significantly greater in nestin‐SHP2‐CS mice than in wildtype littermates. These findings indicate that SHP2 is a required factor in signaling pathway(s) important for neuronal survival. —Aoki, Y. , Huang, Z. , Thomas, S. S. , Bhide, P. G. , Huang, I. , Moskowitz, M. A. , Reeves, S. A. Increased susceptibility to ischemiainduced brain damage in transgenic mice overexpressing a dominant negative form of SHP2. FASEB J. 14, 1965–1973 (2000)
A web trust-inducing model for e-commerce and empirical research

Trust is critical to the success of e-commerce. Despite the richness of e-trust literature, it is lack of empirical research on this area. So in this paper, we made a review on the e-commerce trust studies, both the literature and empirical studies. Basing on relevant trust literatures we presented a web trust-inducing model and proposed four hypotheses. This model consists of four dimensions, namely graphic design, structure design, content design and social-cue design. In order to test the original model and hypotheses, an online survey was conducted. The results of this study provide support for a majority of the original design features. Finally we identified 12 trust-inducing features, and by applying them, the e-commerce merchant might anticipate fostering optimal levels of trust in their customers. The revised model we present is a reasonable starting point for developing a friendly interface for inducing trust in e-commerce.
Efficient Rule-Based Inferencing for OWL EL

We review recent results on inferencing for SROEL(×), a description logic that subsumes the main features of the W3C recommendation OWL EL. Rule-based deduction systems are developed for various reasoning tasks and logical sublanguages. Certain feature combinations lead to increased space upper bounds for materialisation, suggesting that efficient implementations are easier to obtain for suitable fragments of OWL EL.
Towards building a Dynamic Bayesian Network for monitoring oral cancer progression using time-course gene expression data

In this work we present a methodology for modeling and monitoring the evolvement of oral cancer in remittent patients during the post-treatment follow-up period. Our primary aim is to calculate the probability that a patient will develop a relapse but also to identify the approximate time-frame that this relapse is prone to appear. To this end, we start off by analyzing a broad set of time-course gene expression data in order to identify a set of genes that are mostly differentially expressed between patients with and without relapse and are therefore discriminatory and indicative of a disease reoccurrence evolvement. Next, we employ the maintained genes coupled with a patient-specific risk indicator in order to build upon them a Dynamic Bayesian Network (DBN) able to stratify patients based on their probability for a disease reoccurrence, but also pinpoint an approximate time-frame that the relapse might appear.