Miracle-dz/UniFAR-FTUs huggingface dataset:
A Single Session of Low-Intensity Exercise Is Sufficient to Enhance Insulin Sensitivity Into the Next Day in Obese Adults

OBJECTIVE The purpose of this study was to determine the effect of a relatively modest session of exercise on insulin sensitivity and fatty acid uptake the next day in obese adults. RESEARCH DESIGN AND METHODS Eleven sedentary obese adults (male/female: 3/8; BMI 37 ± 1 kg/m2; peak oxygen uptake [VO2peak] 20 ± 1 mL/kg/min) completed three experimental trials. On two of these occasions, subjects exercised to expend 350 kcal in the afternoon. These two exercise trials were identical except for the exercise intensity (50% VO2peak [EX50] and 65% VO2peak [EX65]) and the duration of exercise necessary to expend 350 kcal (EX50 = ∼70 min; EX65 = ∼55 min). Subjects also completed a control trial (CON), without exercise. The next morning, we measured insulin sensitivity (hyperinsulinemic-euglycemic clamp) and whole-body fatty acid uptake (palmitate rate of disappearance from plasma [Rd]). RESULTS Exercise increased insulin sensitivity the next day, but whereas the 35% improvement after EX50 compared with CON was statistically significant (P = 0.01), the 20% improvement after EX65 was not (P = 0.17). Despite nearly identical values between CON and EX65 (P = 0.88), systemic fatty acid uptake was lower after EX50 compared with EX65 (P = 0.02), but not quite significant compared with CON (P = 0.07). Importantly, the change in fatty acid uptake after exercise compared with CON was negatively correlated with the change in insulin sensitivity for all trials (r = −0.60, P = 0.003). CONCLUSIONS A relatively modest single session of exercise in obese adults improved insulin sensitivity the next day, and a reduction in systemic fatty acid uptake in the several hours after exercise may be important for this effect.
Assessment for learning? Thinking outside the (black) box

This article draws on a survey of 83 teachers, to explore the concepts of ‘assessment for learning’, ‘assessment’ and ‘learning’. ‘Assessment for learning’ is categorized as meaning: monitoring pupils' performance against targets or objectives; using assessment to inform next steps in teaching and learning; teachers giving feedback for improvement; (teachers) learning about children's learning; children taking some control of their own learning and assessment; and turning assessment into a learning event. Conceptions of assessment include assessment‐as‐measurement and assessment‐as‐inquiry. These conceptions are related to two conceptions of learning: learning‐as‐attaining‐objectives and learning‐as‐the‐construction‐of‐knowledge. The conceptions of assessment‐as‐measurement and learning‐as‐attaining‐objectives are dominant in English educational policy today. The article suggests that these conceptions need to be challenged and expanded, since conceptions held by those who have power in education determine what sort of assessment and learning happen in the classroom, and therefore the quality of the student's learning processes and products.
Dental Students' Knowledge of Oral Health for Persons with Special Needs: A Pilot Study

Objectives. The purpose of this pilot study was to assess the knowledge and awareness of dental students with respect to oral health care of the person with special health care needs (SHCN) and evaluate effectiveness of an education program on improving their knowledge. Method. An evaluation consisting of a questionnaire was answered before and immediately after a 30-minute educational presentation in the form of a DVD that includes a PowerPoint and a video of oral health care for individuals with SHCN. The questionnaire was based on the materials and information presented in the DVD and included 26 questions (true/false/I do not know). Results. The mean (±SD) score on the pretest was 10.85 (±5.20), which increased to 16.85 (±5.47) on the posttest. This difference was statistically significant (P < 0.001). Forty percent of the students surveyed reported that they were very satisfied with the educational part of the presentation, while 50% were somewhat satisfied. Thirty percent of students expressed that the educational intervention used is very effective. Conclusions. Viewing the educational intervention was effective in informing the sophomore students and providing them with instructive basic information on person with SHCN. Dental colleges should increase students' knowledge, training, and exposure to individuals with SHCN.
Effects of Artificial Supercooling Followed by Slow Freezing on the Microstructure and Qualities of Pork Loin

This study investigated the effects of artificial supercooling followed by still air freezing (SSF) on the qualities of pork loin. The qualities of pork frozen by SSF were compared with the fresh control (CT, stored at 4℃ for 24 h), slow freezing (SAF, still air freezing) and rapid freezing (EIF, ethanol immersion freezing) treatments. Compared with no supercooling phenomena of SAF and EIF, the extent of supercooling obtained by SSF treatment was 1.4℃. Despite that SSF was conducted with the same method with SAF, application of artificial supercooling accelerated the phase transition (traverse from -0.6℃ to -5℃) from 3.07 h (SAF) to 2.23 h (SSF). The observation of a microstructure indicated that the SSF prevented tissue damage caused by ice crystallization and maintained the structural integrity. The estimated quality parameters reflected that SSF exhibited superior meat quality compared with slow freezing (SAF). SSF showed better water-holding capacity (lower thawing loss, cooking loss and expressible moisture) and tenderness than SAF, and these quality parameters of SSF were not significantly different with ultra-fast freezing treatment (EIF). Consequently, the results demonstrated that the generation of supercooling followed by conventional freezing potentially had the advantage of minimizing the quality deterioration caused by the slow freezing of meat.
Protection of IFNAR (−/−) Mice against Bluetongue Virus Serotype 8, by Heterologous (DNA/rMVA) and Homologous (rMVA/rMVA) Vaccination, Expressing Outer-Capsid Protein VP2

The protective efficacy of recombinant vaccines expressing serotype 8 bluetongue virus (BTV-8) capsid proteins was tested in a mouse model. The recombinant vaccines comprised plasmid DNA or Modified Vaccinia Ankara viruses encoding BTV VP2, VP5 or VP7 proteins. These constructs were administered alone or in combination using either a homologous prime boost vaccination regime (rMVA/rMVA) or a heterologous vaccination regime (DNA/rMVA). The DNA/rMVA or rMVA/rMVA prime-boost were administered at a three week interval and all of the animals that received VP2 generated neutralising antibodies. The vaccinated and non-vaccinated-control mice were subsequently challenged with a lethal dose of BTV-8. Mice vaccinated with VP7 alone were not protected. However, mice vaccinated with DNA/rMVA or rMVA/rMVA expressing VP2, VP5 and VP7 or VP2 alone were all protected.
Joint word2vec Networks for Bilingual Semantic Representations

We extend the word2vec framework to capture meaning across languages. The input consists of a source text and a word-aligned parallel text in a second language. The joint word2vec tool then represents words in both languages within a common “semantic” vector space. The result can be used to enrich lexicons of under-resourced languages, to identify ambiguities, and to perform clustering and classiﬁcation. Experiments were conducted on a parallel English-Arabic corpus, as well as on English and Hebrew Biblical texts.
Simulating the emission and outflows from accretion discs

The radio source Sagittarius A* (Sgr A*) is believed to be a hot, inhomogeneous, magnetized plasma flowing near the event horizon of the 3.6 × 106 M⊙ black hole at the galactic centre. At a distance of 8 kpc (≃ 2.5 × 1022 cm) the black hole would be among the largest black holes as judged by angular size. Recent observations are consistent with the idea that the millimetre and sub-millimetre photons are dominated by optically thin, thermal synchrotron emission. Anticipating future Very Long Baseline Interferometry (VLBI) observations of Sgr A* at these wavelengths, we present here the first dynamically self-consistent models of millimetre and sub-millimetre emission from Sgr A* based on general relativistic numerical simulations of the accretion flow. Angle-dependent spectra are calculated assuming a thermal distribution of electrons at the baryonic temperature dictated by the simulation and the accretion rate, which acts as a free parameter in our model. The effects of varying model parameters (black hole spin and inclination of the spin to the line of sight) and source variability on the spectrum are shown. We find that the accretion rate value needed to match our calculated millimetre flux to the observed flux is consistent with constraints on the accretion rate inferred from detections of the rotation measure. We also describe the relativistic jet that is launched along the black hole spin axis by the accretion disc and evolves to scales of ∼103GMc−2, where M is the mass of the black hole.
Poverty marriage timing and transitions to adulthood in Nepal: a longitudinal analysis using the Nepal Living Standards Survey.

This study examines the influence of household poverty experienced during early childhood on early marriage and outcomes in schooling and workforce participation for girls during adolescence in Nepal. Much of the evidence concerning these relationships is drawn from cross-sectional data that cannot be used to and has not been able to address causality. In this study we use longitudinal data from the Nepal Living Standards Survey (NLSS) a two-wave panel in which the waves were conducted eight years apart to address these questions. For a sample of girls aged five to nine in the NLSS1 who were contacted again in the NLSS2 when they were aged 13 to 17 (N = 400) multinomial logistic regression estimates indicate that household poverty during childhood is associated with a higher likelihood that girls will marry early or join the workforce as adolescents rather than remain in school. Analyzing the data by household-wealth quintiles reveals surprisingly nonlinear results indicating that these associations are largest for the second-poorest quintile rather than for the poorest one. This study also highlights the role of the household rather than of the individual in decisionmaking for these adolescent girls.
Trust and Reputation Algorithms for Hierarchically Structured Peer-to-Peer Systems

This research focuses on the redesign of trust and reputation algorithms in the context of hierarchically structured Peer-to-Peer (P2P) networks with Chord, a scalable P2P lookup service for Internet applications. Chord, which is an open source project, is an overlay network based on a distributed hash table(DHT), and all peers in Chord are arranged around a circle. In this work, we propose four adapted trust and reputation algorithms for hierarchically structured P2P networks: EigenTrust, PowerTrust, Absolute Trust and NodeRanking. EigenTrust is one of the most well-known trust and reputation algorithms, as well as the most simple. To calculate the reputation, EigenTrust needs to normalize trust and rely on pre-trusted peers. Like EigenTrust, PowerTrust relies on feedback and the use of a distributed ranking mechanism. It chooses a limited number of power nodes with a high reputation. By combining a random walk strategy and the power nodes, it improves accuracy of global reputation. AbsoluteTrust does not require normalization of trust, pretrusted peers or any centralized authority. Weighted average combined with feedback from peers is employed to determine trust. NodeRanking relies on both individual reputation and social relationship to compute the trust value. NodeRanking evaluates reputation using local information. A node’s reputation value can be readily determined by the number of references from other nodes in the network. These adapted algorithms are capable of handling a huge number of nodes disseminated in different rings, which improves complexity and reduces the number of malicious nodes in a hierarchical context.Furthermore, we describe the components of the hierarchical model architecture and present and discuss the results from the experiments. These experiments are employed to verify and compare reduction of downloads from malicious peers, load distribution and residual curl in flat structured networks and in hierarchically structured networks.
A History of the Improvement of Internet Protocols Over Satellites Using ACTS

This paper outlines the main results of a number of ACTS experiments on the efficacy of using standard Internet protocols over long-delay satellite channels. These experiments have been jointly conducted by NASA’s Glenn Research Center and Ohio University over the last six years. The focus of our investigations has been the impact of long-delay networks with non-zero bit-error rates on the performance of the suite of Internet protocols. In particular, we have focused on the most widely used transport protocol, the Transmission Control Protocol (TCP), as well as several application layer protocols. This paper presents our main results, as well as references to more verbose discussions of our experiments.
Understanding and Promoting Stress Management Practices Among College Students Through an Integrated Health Behavior Model

ABSTRACT Background: College students are susceptible to undermanaged stress and its detrimental effects, and though they could use evidence-based stress reduction techniques (SRTs) to remedy this, many do not. Unfortunately, little is known about what might encourage greater use. Purpose: This study examined to what extent a framework integrating cognitive, social, behavioral, and experiential factors related to influential health behavior models could account for increased intention to use SRTs (intention) and willingness to recommend SRTs (promoter willingness). Methods: College students (n = 233) completed a survey assessing health beliefs, past and intended future use of SRTs, willingness to recommend SRTs, and potential changes in intention or promoter willingness following brief Health Education messages. Results: Health Belief Model components, theory of planned behavior descriptive norms, and prior SRT use predicted significant variability in intention and promoter willingness (experienced effectiveness of particular SRTs also predicted intention), and Health Education messages increased both outcomes. Discussion: Informational and experiential exposure to different SRTs may promote greater SRT use and dissemination. Translation to Health Education Practice: Institutions can assess student stress management needs and increase student SRT use and dissemination through existing modalities that provide students information, peer discussion opportunities, and reinforcing effects of SRT practice.
Constrained multi-objective aerodynamic shape optimization via swarm intelligence

In this paper, we present a Multi-objective Particle Swarm Optimizer (MOPSO) based on a decomposition approach, which is proposed to solve Constrained Multi-Objective Aerodynamic Shape Optimization Problems (CMO-ASOPs). The constraint-handling technique adopted in this approach is based on the well-known epsilon-constraint method. Since the ε-constraint method was initially proposed to deal with constrained single-objective optimization Problems, we adapted it so that it could be incorporated into a MOPSO. Our main focus is to solve CMO-ASOPs in an efficient and effective manner. The proposed constrained MOPSO guides the search by updating the position of each particle using a set of solutions considered as the global best according to both the decomposition approach and the epsilon-constraint method. Our preliminary results indicate that our proposed approach is able to outperform a state-of-the-art MOEA in several CMO-ASOPs.
Does my dizzy patient have a stroke? A systematic review of bedside diagnosis in acute vestibular syndrome

Dizziness is the third most common major medical symptom reported in general medical clinics[1][1] and accounts for about 3%–5% of visits across care settings. [2][2] In the United States, this translates to 10 million ambulatory visits per year because of dizziness,[3][3] with roughly 25% of these
Long-term treatment efficacy in primary inflammatory breast cancer by hormonal receptor- and HER2-defined subtypes.

BACKGROUND Subtypes defined by hormonal receptor (HR) and HER2 status have not been well studied in inflammatory breast cancer (IBC). We characterized clinical parameters and long-term outcomes, and compared pathological complete response (pCR) rates by HR/HER2 subtype in a large IBC patient population. We also compared disease-free survival (DFS) and overall survival (OS) between IBC patients who received targeted therapies (anti-hormonal, anti-HER2) and those who did not. PATIENTS AND METHODS We retrospectively reviewed the records of patients diagnosed with IBC and treated at MD Anderson Cancer Center from January 1989 to January 2011. Of those, 527 patients had received neoadjuvant chemotherapy and had available information on estrogen receptor (ER), progesterone receptor (PR), and HER2 status. HR status was considered positive if either ER or PR status was positive. Using the Kaplan-Meier method, we estimated median DFS and OS durations from the time of definitive surgery. Using the Cox proportional hazards regression model, we determined the effect of prognostic factors on DFS and OS. Results were compared by subtype. RESULTS The overall pCR rate in stage III IBC was 15.2%, with the HR-positive/HER2-negative subtype showing the lowest rate (7.5%) and the HR-negative/HER2-positive subtype, the highest (30.6%). The HR-negative, HER2-negative subtype (triple-negative breast cancer, TNBC) had the worst survival rate. HR-positive disease, irrespective of HER2 status, had poor prognosis that did not differ from that of the HR-negative/HER2-positive subtype with regard to OS or DFS. Achieving pCR, no evidence of vascular invasion, non-TNBC, adjuvant hormonal therapy, and radiotherapy were associated with longer DFS and OS. CONCLUSIONS Hormone receptor and HER2 molecular subtypes had limited predictive and prognostic power in our IBC population. All molecular subtypes of IBC had a poor prognosis. HR-positive status did not necessarily confer a good prognosis. For all IBC subtypes, novel, specific treatment strategies are needed in the neoadjuvant and adjuvant settings.
Multi-layer progressive secret image sharing

This paper proposes a special type secret image sharing method. Based on the theories of secret image sharing and frequency domain transform, a multi-threshold secret image sharing is achieved. The method contains more properties compared with conventional secret image sharing which just has only one threshold. The properties of the proposed method include fault tolerance, small size of shares, secure, multi-threshold and progressive transmission. The method not only has the advantages of conventional secret image sharing, but also is more flexible. Users can set several thresholds in the method. When the number of shares is less than the smallest threshold, no secret will be revealed. While the numbers of shares collected are more than smallest threshold, a low quality secret image will be revealed. The quality of recovered secret image will be better after collecting more shares. When the amount of shares is over the maximum threshold, the recovered secret image is the same as the original secret image.
Nice weather for bettongs: using weather events, not climate means, in species distribution models

Current applications of species distribution models (SDM) are typically static, in that they are based on correlations between where a species has been observed (ignoring the date of the observation) and environmental features, such as long-term climate means, that are assumed to be constant for each site. Because of this SDMs do not account for temporal variation in the distribution of suitable habitat across the range of a species. Here, we demonstrate the temporal variability in the potential geographic distributions of an endangered marsupial, the northern bettong Bettongia tropica as a case study. Models of the species distribution using temporally matched observations of the species with weather data (including extreme weather events) at the time of species observations, were better able to define habitat suitability, identify range edges and uncover competitive interactions than models based on static long-term climate means. Droughts and variable temperature are implicated in low densities and local extinctions of northern bettong populations close to range edges. Further, we show how variable weather can influence the results of competition with the common rufous bettong Aepyprymnus rufescens. Because traditional SDMs do not account for temporal variability of suitable habitat, static SDMs may underestimate the impacts of climate change particularly as the incidence of extreme weather events is likely to rise.
Biogas Production from Algae Biomass Harvested at Wastewater Treatment Ponds

Waste-grown microalgae are a potentially important biomass for biofuel production. However, most of the 7,000 wastewater treatment ponds systems in the US do not use algae harvesting. Those that do, typically return the biomass to the ponds, where it decomposes on the pond floor, releasing methane to the atmosphere and degrading water quality. Instead, the algae biomass could be processed in anaerobic digesters. Algae typically yield less methane than wastewater sludge (~0.3 vs. 0.40 L CH4/g volatile solids introduced). Ammonia toxicity and recalcitrant cell walls are commonly cited causes of the lower yields. Ammonia toxicity might be counteracted by co-digesting algae with high-carbon organic wastes. This paper describes the state of the current literature on algae digestion and presents new data on co-digestion with organic wastes. The focus of the project is to identify the essential information required for full-scale implementation of algae co-digestion at wastewater treatment plants, including the optimal conditions to maximize the methane yield, the volumetric methane productivity, and net energy production.
Online neuro-identification of nonlinear systems using Extreme Learning Machine

In this paper, an identification scheme via extreme learning machine neural network is proposed. The proposed identification scheme ensures the convergence of the residual state error to zero and boundedness of all associated approximation errors, even in the presence of approximation error and disturbances. Lyapunov-like analysis using Barbalat's Lemma and a dynamic single-hidden layer neural network (DSHLNN) model with hidden nodes randomly generated to establish the aforementioned properties are employed. Hence, faster convergence and better computational efficiency than DSHLNNs is assured. Simulations to validate the theoretical results and show the effectiveness of the proposed method are provided.