Miracle-dz/UniFAR-FTUs huggingface dataset:
What They Think About How They Are Evaluated: Perspectives of New York State Physical Educators on Teacher Evaluation Policy

While research on high stakes testing continues to expand, little is known regarding how the use of student test scores to evaluate teachers is affecting physical education (PE). Â A proportionate, stratified random sample of physical educators in New York State was drawn (n=489) to survey them about their district’s practices and their attitudes about the state’s new teacher evaluation policy. Results indicated that 38% of respondents were evaluated in part on the basis of results from written tests of students, while 27% indicated their district used student fitness tests for this purpose. Â Eighteen percent of respondents reported their district used state mandated English Language Arts (ELA) and mathematics test scores in calculating physical educator performance ranks. While few reported using performance-based measures, 94% of respondents indicated these as the preferred means of assessment in PE. Eighty-three percent of respondents predicted that the new teacher evaluation system would not improve PE.
Optimized Signaling of Binary Correlated Sources Over Gaussian Multiple Access Channels

This work focuses on the construction of optimized binary signaling schemes for two-sender uncoded transmission of correlated non-uniform sources over non-orthogonal Gaussian multiple access channels. Based on an error-rate analysis under joint maximum-a-posteriori decoding, optimized binary-pulsed-amplitude modulation constellations for two senders are derived to minimize the system's error rate. The joint probability distribution of the two-senders' source is observed to induce a special layout of optimized constellations which can effectively control the interference due to non-orthogonal transmission. Numerical results further confirm that significant gains are achievable by the proposed design.
The influence of elevated CO2 on the activities of antioxidative enzymes in two soybean genotypes

The effects of ele vated compared to current atmospheric CO2 concentration (720 and 365 µL L -1 , respec­ tively) on antioxidative enzymatic activities of two soybean (Glycine max (L.) Merr. ) genotypes (R and S) grown in open-top field chambers were investigated. Enzymatic activities of leaves collected 40, 47, 54 and 61 d after plant­ ing were measured. Elevated CO2 significantly decreased activities of superoxide dismutase (SOD, EC 1.15.1.1), peroxidase (POD, EC 1.11.1.7), catalase (CAT, EC 1.11.1.6), ascorbate peroxidase (APOD, EC 1.11.1.7), gluta­ thione peroxidase (GPOD, EC 1.11.1.9) and glutathione reductase (GR, EC 1.6.4.2) in both genotypes. The activi­ ties of dehydroascorbate reductase (DAR, EC 1.8.5.1) and monodehydroascorbate reductase (MDAR, EC 1.1.5.4.) increased in genotype S, but decreased in genotype R under elevated CO2. Elevated CO2 decreased rubisco activity and rubisco, chlorophyll, carotenoids and total soluble protein contents in both genotypes. Results indicate that con­ stitutive antioxidative enzymatic activities may decrease in a high-CO2 world. Significant CO2 × genotype interac­ tions, however, suggest that there may be key genotypic differences in response patterns, potentially conferring differential resistance to biotic and abiotic stress.
Distant Speech Recognition in a Smart Home: Comparison of Several Multisource ASRs in Realistic Conditions

While the smart home domain has become a major field of application of ICT to improve support and wellness of people in loss of autonomy, speech technology in smart home has, comparatively to other ICTs, received limited attention. This paper presents the SWEET-HOME project whose aim is to make it possible for frail persons to control their domestic environment through voice interfaces. Several state-of-the-art and novel ASR techniques were evaluated on realistic data acquired in a multiroom smart home. This distant speech French corpus was recorded with 21 speakers playing scenarios including activities of daily living in a smart home equipped with several microphones. Techniques acting at the decoding stage and using a priori knowledge such as DDA give better results (WER=8.8%, Domotic F-measure=96.8%) than the baseline (WER=18.3%, Domotic F-measure=89.2%) and other approaches.
User-SERP Interaction Prediction through Deep Multi-task Learning

User behavior signals such as clicks are strong indicators of a search engines performance. Many existing search algorithms focus on predicting users interactions, by optimizing a relevance cost function for the query and individual web documents. The result set (list) is then generated by ranking web documents with this score. However, the probability of user interaction with a web document on a Search Engine Result Page (SERP) depends not only on a web document in isolation, but also other documents/elements present on the SERP. Our approach better predicts user interactions on web documents by not only considering the relevance of individual documents for a query, but also their interdependencies by modeling the interactions of a User on a SERP with a Multi-task Bidirectional Recurrent Neural Network (RNN).
Halt Autoimmune Diabetes To Effector T Cell Function in Inflamed Islets Therapeutic Regulatory T Cells Subvert

Therapeutic regulatory T cells (Tregs) can reverse pre-established autoimmune pathology. In this study, using a mouse model of autoimmune diabetes, we aimed to determine the means by which therapeutic Tregs control islet inﬂammation. Islet Ag-speciﬁc Tregs inﬁltrated inﬂamed islets soon after infusion into prediabetic mice, which was quickly followed by a selective reduction of mRNA associated with effector T cells in the islets. This change was partially due to decreased CD8 + T cell accumulation in the tissue. CD8 + T cells that remained in the islets after Treg treatment were able to engage dendritic cells in a manner similar to that found in untreated mice, consistent with the retention of an activated phenotype by islet dendritic cells shortly after Treg treatment. Nonetheless, Treg treatment abrogated IFN- g production by intraislet CD8 + and CD4 + T cells at the protein level with minimal effect on IFN- g mRNA. Sustained expression of IFN- g protein by effector T cells was dependent on common g -chain cytokine activation of the mTOR pathway, which was suppressed in islet CD8 + T cells in vivo after Treg treatment. These multifaceted mechanisms underlie the efﬁcacy of therapeutic Treg subversion of effector T cell functions at the site of inﬂammation to restore normal tissue homeostasis. The Journal of Immunology , 2015, 194: 000–000.
Microbial Forensics and Plant Pathogens: Attribution of Agricultural Crime

New awareness of the vulnerability of a nation's agricultural infrastructure to the intentional introduction of pathogens or pests has led to the enhancement of programs for prevention and preparedness. A necessary component of a balanced biosecurity plan is the capability to determine whether an outbreak may have been deliberate, to trace that outbreak to its source, and to identify those responsible for it. Microbial forensics is an emerging discipline that blends elements of numerous disciplines including microbiology, forensic science, and agricultural sciences. The discipline of plant pathology offers much knowledge, as well as many technologies and resources developed for peaceful purposes, which can be adapted and applied to the development of the new subdisciplines of plant pathogen forensics. Targeted research and education programs also will be needed to meet this need. Keywords: microbial forensics; attribution; plant pathogen; match
Investigating Impacts of Self-Exciting Jumps in Returns and Volatility: A Bayesian Learning Approach

The paper proposes a new class of continuous-time asset pricing models where whenever there is a negative jump in asset returns, it is simultaneously passed on to diffusion variance and the jump intensity, generating co-jumps of prices and volatility and jump clustering. To properly deal with parameter uncertainty and hindsight bias, we employ a Bayesian learning approach, which generates all quantities necessary for sequential real-time model analysis. Empirical study using S&P 500 index returns shows that volatility jumps at the same time as negative jumps in asset returns mainly through jumps in diffusion volatility. We find weak evidence of jump clustering. Learning and parameter uncertainty are shown to have important implications for risk management, option pricing and volatility forecasting.
EFFECT OF NITROGEN FERTILIZATION AND UNDERSOWING ON YIELD AND QUALITY OF CYNOSURETUM CRISTATI-TYPE MEADOWS IN HILLY-MOUNTAINOUS GRASSLANDS IN SERBIA

The trial was carried out during two years (2003 and 2004) on Cynosuretum cristati-type meadow in the hillymountainous region of Serbia (altitude 1158 m). The investigation included five nitrogen fertilizer rates (0, 40, 80, 120 and 160 kg ha-1 yr-1) and undersowing with red clover and birdsfoot trefoil. Increase in nitrogen fertilization level resulted in corresponding increases in the quantity and quality of grass, while legumes and other herbages decreased. Maximum two-year average dry matter yield of 4.44 t ha-1 was achieved with the highest N rate (160 kg ha-1). The increase was 2.03 t ha-1 or 85.0% compared with the control. Increased N rates increasing the contents of protein, ash, fat, Cu, Co, and NO3, and reduced the contents of cellulose, K, P, Ca, Mg, S, Zn, and B. Dry matter yield in the undersowing treatment was low, only slightly over that of the control in both study years. Furthermore, undersowing failed to affect the chemical and mineral composition of dry matter.
Preparation of Novel Core-Shell Nanocomposite Particles by Controlled Polymer Bridging

Ceramics that are composed of nanosized granules show enhanced properties in various applications. A layer-bylayer deposition process is developed in this study to prepare core-shell nanocomposite particles, using controlled polymer adsorption. Submicrometer-sized alumina particles that have been chosen as the starting core particles are first dispersed by pH control and then modified by adsorption of anionic poly (acrylic acid) to facilitate the subsequent deposition of nanoparticles on them. A key step in the processing involves the removal of excess polymer in the supernatant after the adsorption by controlled washing, so that the added nanoparticles do not self-flocculate among themselves. A coating of nanosized particles is indicated by the charge reversal of the micrometer-sized composite particles. The isoelectric point of the composite particle is similar to that of nanosized particles under both low and high coverage conditions. Scanning electron microscopic observation or coated particles shows full monolayer coverage of the nanoparticles on core particles, which confirms the efficiency or the coating scheme that is discussed here. The present study reveals the reasibility of coating nanoparticles onto micrometer-sized core particles, using controlled polymerbridging. for the preparation of the multilayer nanocomposite powders.
Neural Correlates of Heart Rate Variability: Threat and Safety Perception

The connection between the heart and the brain was coined 150 years ago by Claude Bernard and has since then been an interesting topic of research. Scientists have for many years searched for biomarkers of stress and health to map the current status of the organism. Heart rate variability (HRV) has been presented as an emerging objective and promising marker to achieve just this. HRV refers to the beat-to-beat variations in heart rate (HR) and is thought to be a useful signal in understanding and providing valuable information of the autonomic nervous system (ANS). HRV has also been proposed as a marker of stress and health by sharing neural correlates and functions with several executive functions. This thesis identified several regions, including the ventromedial prefrontal cortex and the amygdala, in which significant associations across several studies were found between threat and safety perception, emotional regulation and HRV. This suggest that HRV may function as an index of the brain mechanism and structures that guide and govern adaptive functions and thus, provide researchers with valuable information regarding the stress and health of an organism. Two major theoretical frameworks, which articulate and explain the role of HRV as an indicator of individuals ability to adapt to environmental changes and cope under stress is presented. HRV can also be used in practice in several ways and a growing and promising field of application is HRV biofeedback.
A NOVEL APPROACH FOR INFORMATION RETRIEVAL TECHNIQUE FOR WEB USING NLP

Webpages are loaded with vast and different kinds of information about the entities in the real-world. Information retrieval from the Web is of a greater significance today to get the accurate queried data within the desired time frame which is increasingly becoming difficult with each passing day. Need to develop a system to solve entity extraction problems from the web as compared to the traditional system. It’s critical to have a clear understanding of natural language sentence processing in the web page along with the structure of the web page to get the correct information with speed. Here we have proposed approach for information retrieval technique for Web using NLP where techniques Hierarchical Conditional Random Fields (i.e. HCRF) and extended Semi-Markov Conditional Random Fields (i.e. SemiCRF) along with Visual Page Segmentation is used to get the accurate results. Also parallel processing is used to achieve the results in desired time frame. It further improves the decision making between HCRF and Semi-CRF by using bidirectional approach rather than top-down approach. It enables better understanding of the content and page structure.
Murray, J and Gough, S and Yohannes, A (2016)Using video-reflexive ethnography and simulation-based education to explore patient management and error recognition by pre-registration physiotherapists. Advances in Sim-

Background Upon graduation, physiotherapists are required to manage clinical caseloads involving deteriorating patients with complex conditions. In, particular, emergency on-call physiotherapists are required to provide respiratory/cardiorespiratory/cardiothoracic physiotherapy, out of normal working hours, without senior physiotherapist support. To optimise patient safety, physiotherapists are required to function within complex clinical environments, drawing on their knowledge and skills (technical and non-technical) to maintain situational awareness to function efficiently whilst optimally managing the patient and filtering unwanted stimuli from the environment. Prior to this study, the extent to which final year physiotherapy students were able to manage a deteriorating patient and recognise errors in their own simulated practice was unknown. Methods A focused video-reflexive ethnography study was undertaken to explore behaviours, error recognition abilities and personal experiences of 21 final year (pre-registration) physiotherapy students from one Higher Education Institution. Social constructivism and complexity theoretical perspectives informed the methodological design of the study. Video and thematic analysis of 12 simulation scenarios and video reflexive interviews were undertaken. Results Participants worked within the expected professional standards of physiotherapy practice expected of entry-level physiotherapists. Students reflected appropriate responses to their own and others’ actions in the midst of uncertainly of the situation
Re-Ranking Strategies for Ranking High Precision Information Web Search

A web search engine is a tool designed to search for information on the World Wide Web. The search results are usually presented in a list. The information may consist of web pages, images, information and other types of files. Some search engines also mine data available in databases. Unlike Web directories, which are maintained by human editors, search engines operate algorithmically or are a mixture of algorithmic and human input. The Search Engines often return a large volume of results with possibly a few relevant results. The notion of relevance is subjective and depends on the user and context. The Re-ranking of the results reflects the most relevant results for the user and has become very important in current scenario. In this paper, we propose a novel approach for re-ranking of the search results which would be more efficient and effective of a given user as well as the other users. Our approach is to learn the profiles of the users by making use of past browsing histories including queries posed and documents found relevant or irrelevant.
On the relative importance of the effects of selection and complementarity as drivers of diversity–productivity relationships in Mediterranean shrublands

Extensive research has been devoted to understanding the role of biodiversity as a driver of ecosystem functioning. However, no previous study has evaluated the relative contribution of complementarity and selection to productivity in shrublands. We have attempted to do this for a Mediterranean shrubland dominated by Quercus coccifera, Cistus albidus, Ulex parviflorus and Rosmarinus officinalis. We found a highly significant and linear positive relationship between productivity and species richness. No selection effect was apparent, but both the complementarity and net effects were highly significant. The magnitude of these effects increased from two to three species, but became non-significant in the four-species mixtures. Analysis of pairwise interactions revealed that legumes did not promote overyielding. Complementarity was mostly driven by Cistus, which always performed better when growing with other species than when growing with conspecifics. Our results are an addition to the still scarce literature dealing with diversity� productivity relationships in communities dominated by woody species, and show that methodologies commonly used to assess complementarity may not provide a precise estimation when a given species has negative effects on its conspecifics.
When Should a Service Robot Switch Tasks ? A Learning-Based Approach for Interrupting Task Execution

While mobile robots reliably perform each service task by accurately localizing and safely navigating avoiding obstacles, they do not respond in any other way to the people and their environment. One aspect that increases a robot’s responsiveness to its environment is the ability to interrupt the task execution and switch to another task based on observations. We present a novel approach that enables an autonomous robot to learn from observations, when to interrupt task execution and what task to switch to next. We test the effectiveness of our approach in a human-robot interaction scenario and show that our approach significantly decreases the amount of sensory input processing during the execution of tasks.
Combining Panel Data Sets with Attrition and Refreshment Samples

In many fields researchers wish to consider statistical models that allow for more complex relationships than can be inferred using only cross-sectional data. Panel or longitudinal data where the same units are observed repeatedly at different points in time can often provide the richer data needed for such models. Although such data allows researchers to identify more complex models than cross-sectional data, missing data problems can be more severe in panels. In particular, even units who respond in initial waves of the panel may drop out in subsequent waves, so that the subsample with complete data for all waves of the panel can be less representative of the population than the original sample. Sometimes, in the hope of mitigating the effects of attrition without losing the advantages of panel data over cross-sections, panel data sets are augmented by replacing units who have dropped out with new units randomly sampled from the original population. Following Ridder (1992), who used these replacement units to test some models for attrition, we call such additional samples refreshment samples. We explore the benefits of these samples for estimating models of attrition. We describe the manner in which the presence of refreshment samples allows the researcher to test various models for attrition in panel data, including models based on the assumption that missing data are missing at random (MAR, Rubin, 1976; Little and Rubin, 1987). The main result in the paper makes precise the extent to which refreshment samples are informative about the attrition process; a class of non-ignorable missing data models can be identified without making strong distributional or functional form assumptions if refreshment samples are available.
MAGIC Observations of the Unidentified γ-Ray Source TeV J2032+4130

We observed the first known very high energy (VHE) γ-ray-emitting unidentified source, TeV J2032+4130, for 94 hr with the MAGIC telescope. The source was detected with a significance of 5.6 σ. The flux, position, and angular extension are compatible with the previous ones measured by the HEGRA telescope system 5 years ago. The integral flux amounts to (4.5 ± 0.3stat ± 0.35sys) × 10−13 photons cm−2 s−1 above 1 TeV. The source energy spectrum, obtained with the lowest energy threshold to date, is compatible with a single power law with a hard photon index of Γ = –2.0 ± 0.3stat ± 0.2sys.
Systematic evaluation of the unsoundness of call graph construction algorithms for Java

Call graphs are at the core of many static analyses ranging from the detection of unused methods to advanced control-and data-flow analyses. Therefore, a comprehensive understanding of the precision and recall of the respective graphs is crucial to enable an assessment which call-graph construction algorithms are suited in which analysis scenario. For example, malware is often obfuscated and tries to hide its intent by using Reflection. Call graphs that do not represent reflective method calls are, therefore, of limited use when analyzing such apps. In general, the precision is well understood, but the recall is not, i.e., in which cases a call graph will not contain any call edges. In this paper, we discuss the design of a comprehensive test suite that enables us to compute a fingerprint of the unsoundness of the respective call-graph construction algorithms. This suite also enables us to make a comparative evaluation of static analysis frameworks. Comparing Soot and WALA shows that WALA currently has better support for new Java 8 features and also for Java Reflection. However, in some cases both fail to include expected edges.