Miracle-dz/UniFAR-FTUs huggingface dataset:
SBAG: A Hybrid Deep Learning Model for Large Scale Traffic Speed Prediction

Intelligent Transportation System (ITS) is the fundamental requirement to an intelligent transport system. The proposed hybrid model Stacked Bidirectional LSTM and Attention-based GRU (SBAG) is used for predicting the large scale traffic speed. To capture bidirectional temporal dependencies and spatial features, BDLSTM and attention-based GRU are exploited. It is the first time in traffic speed prediction that bidirectional LSTM and attention-based GRU are exploited as a building block of network architecture to measure the backward dependencies of a network. We have also examined the behaviour of the attention layer in our proposed model. We compared the proposed model with state-of-the-art models e.g. Fully Convolutional Network, Gated Recurrent Unit, Long -short term Memory, Bidirectional Long-short term Memory and achieved superior performance in large scale traffic speed prediction.
Running head: VICTIMIZATION–AGGRESSION LINK IN CHILDHOOD 1 Understanding the Victimization–Aggression Link in Childhood: The Roles of Sympathy and Resting Respiratory Sinus Arrhythmia

With a sample of 4and 8-year-olds (N = 131), we tested the extent to which more frequent experiences of victimization were associated with heightened aggression towards others, and how sympathetic concern and resting respiratory sinus arrhythmia (RSA) factored into this relationship. Caregivers reported their children’s aggression and sympathy. Children reported their victimization and their resting RSA was calculated from electrocardiogram data in response to a nondescript video. Findings revealed that children who reported more frequent victimization were rated as less sympathetic and, in turn, more aggressive. However, resting RSA moderated this path, such that children with high levels were rated as more versus less sympathetic when they reported less versus more victimization, respectively. Results suggest that considering children’s sympathetic tendencies and physiology is important to gain a nuanced understanding of their victimization-related aggression.
X-ray tracking of structural changes during a subnanosecond solid-solid phase transition in cobalt nanoparticles

This work presents measurements of laser-induced solid-solid phase transitions in Co nanoparticles, using time-resolved wide-angle x-ray scattering with < 100-ps time resolution. A comparison of the experimental results with scattering simulations indicates a phase transition from the as-synthesized (cid:2) phase into a mixed phase of 2 / 3 hcp and 1 / 3 fcc character during the ﬁrst 100 ps. The measured scattering signal observed at the shortest investigated time delay of 20 ps has less scattering intensity at the dominant fcc / hcp Bragg peak positions compared to the difference signal acquired at 100 ps. This suggests the formation of a partially disordered solid intermediate phase on the sub-100-ps timescale.
Climate Change and Cattle Production: Impact and Adaptation

Climate change has far-reaching consequences on several sectors of agriculture. Cattle production within animal agriculture is one of the most susceptible sectors for the devastating effects of climate change. Climate change associated heat stress negatively impacts cattle production both directly and indirectly. Heat stress reduces the feed intake which ultimately reduces the body weight, average daily gain and body condition scoring in cattle. Further, heat stress associated reduced feed intake also affects the milk production, meat production and reproduction in cattle. The high producing cattle are more vulnerable to heat stress than the low producing animals. Livestock exhibits a wide range of adaptive mechanisms to cope with environmental challenges. The classical adaptive mechanisms include morphological, behavioral, physiological, neuroendocrine, blood biochemical and cellular responses that act in coordination to promote the welfare and favour their survival in a specific environment. The detailed studies on these adaptive mechanisms have identified respiration rate, rectal temperature, Hb, PCV, cortisol, thyroid hormones to be reliable phenotypic markers and HSP70 as a confirmatory genotypic biomarker to assess the impact of heat stress in dairy cattle.
Mechanism of Estrogen Receptor α Regulation: Ligand Independent Activation by Phosphorylation

Estrogen operates through estrogen receptors (ER) α and β, which belong to the superfamily of steroid nuclear receptor transcription factors and operate by recruiting cofactors, which form complexes that bind to target genes. Post translational modifications play a role in directing ER activation. We demonstrate that a phospho-mimetic S305E induces ERα activity in the absence of ligand, and enhances activity with estradiol above wild-type. This activation also results cofactor binding and an increase in cell proliferation. We identified a novel protein interaction between ERα and the focal adhesion associated protein zyxin. Zyxin acts as a coactivator by increasing ERα activation. We also demonstrate that mutating the acetylation site of ERα K303 results in downregulation of phosphorylated p38, suggesting a link ERα between and p38 MAPK pathway. Together these data suggest that regulation of the receptor is linked to several kinase mediated signaling pathways and has role in breast cancer progression.
Visceral Adipose Tissue Radiodensity Is Linked to Prognosis in Hepatocellular Carcinoma Patients Treated with Selective Internal Radiation Therapy

Hepatocellular carcinoma (HCC) constitutes the fourth leading cause of cancer-related mortality. Various factors, such as tumor size, tumor multiplicity, and liver function, have been linked to the prognosis of HCC. The aim of this study was to explore the prognostic significance of muscle, subcutaneous and visceral adipose tissue (VAT) mass, and radiodensity, in a cohort of 101 HCC patients treated with selective internal radiation therapy (SIRT). Muscle and adipose tissue cross sectional area (cm2/m2) and radiodensity, reported as the Hounsfield Unit (HU), were determined using pre-SIRT computed tomography images. Cox proportional hazard models and exact logistic regression were conducted to assess associations between body composition and adverse outcomes. Majority of the patients were male (88%) with a mean VAT radiodensity of −85 ± 9 HU. VAT radiodensity was independently associated with mortality (HR 1.05; 95% CI: 1.01–1.08; p = 0.01), after adjusting for cirrhosis etiology, Barcelona Clinic Liver Cancer stage, previous HCC treatment, and portal hypertension markers. Patients with a high VAT radiodensity of ≥–85 HU had a two times higher risk of mortality (HR 2.01, 95% CI 1.14–3.54, p = 0.02), compared to their counterpart. Clinical features of portal hypertension were more prevalent in patients with high VAT radiodensity. High VAT radiodensity was associated with severe adverse events after adjusting for confounding factors. High VAT radiodensity is independently associated with both increased mortality and severe adverse events in patients treated with SIRT. VAT radiodensity measurement might serve as an objective approach to identify patients who will experience the most benefit from SIRT.
Modification of polyphenols and cuticular surface lipids of Kale (B. oleracea convar. sabellica) with non-thermal oxygen plasma gaseous species

The production and consumption of minimally processed food have grown rapidly over the past decades. Concomitant with popularity an increased number of microbial infections have been documented. Though efficiently inactivating microorganisms, conventional thermal food preservation significantly change the concentration, bioavailability and bioactivity of phytochemicals in food. In this context, non-thermal plasma (NTP) seems to be a promising alternative. Although much work has already been done in investigating the effects of non-thermal plasma on microorganisms, little is known about the influence of plasma treatment on food and food compounds. To this end, we investigated the effects of a non-thermal oxygen plasma on the stability and functionality of phenolic compounds in kale (Brassica oleracea convar. sabellica). Reactions were followed by high performance liquid chromatography/diode-array detection (HPLC-DAD). Samples were characterized using scanning electron microscopy and attenuated total reflectance-Fourier transform infrared spectroscopy (ATRFTIR). Our results show that plasma treatment significantly influenced the flavonoid content in leaf tissue. This is in agreement to results showing that during roasting and cooking processes oxidative species lead to the formation of characteristic low-molecular weight degradation products. The degradation was not caused from photodesorption or thermodesorption processes at the adsorbate surface but clearly stemmed from the combined interaction of the various plasma reactive species in the plasma effluent. Epicuticular waxes on the abaxial side were visibly degraded. The outcomes of this work represent a first step towards a molecular approach of plasma-food interactions and aim to open up novel insight into the reaction of flavonoids with reactive oxygen species at the solid-gas interface. This is especially important in view of future applications.
Do electoral politics and partisan articulations matter for regional economic development ? Evidence from Turkey ' s provinces

In countries with highly polarised political environments, the literature suggests that partisan articulations may influence regional economic performance via the privileged provision of government goods to constituencies with the right political affiliation, at the expenses of opponents. The article tests such prediction through a model of regional growth over 2004-2011 on the 81 provinces of Turkey, a country which has traditionally lacked inclusive political institutions. Results confirm the existence of a reduced-form relationship between votes for the national Government party and faster regional growth. Such relationship is, at least in part, explained by the heterogeneous allocation of public infrastructural investment and investment incentives by the Government to constituencies. Yet, once endogeneity between electoral results and growth is addressed, economic performance is almost entirely explained by standard drivers, primarily human capital endowment. Results overall suggest that the impact of votes on economic performance outcomes is extremely limited. They also provide a picture of the Turkish economy where partisan factionalism does not topple standard socio-economic factors. Under such light, the confrontational and autocratic stance adopted by Turkey’s Prime Minister in recent years may mark a lost opportunity to capitalise any positive societal achievements during his first years in office.
Categorizing Attributes in Identifying Learning Style using Rough Set Theory

In a learning process, learning style becomes one crucial factor that should be considered. However, it is still challenging to determine the learning style of the student, especially in an online learning activity. Data-driven methods such as artificial intelligence and machine learning are the latest and popular approaches for predicting the learning style. However, these methods involve complex data and attributes. It makes it quite heavy in the computational process. On the other hand, the literate based driven approach has a limitation in inconsistency between results with the learning behavior. Combination, both approaches, gives a better accuracy level. However, it still leaves some issues such as ambiguity and a wide of range of attributes value. These issues can be reduced by finding the right approach and categorization of attributes. Rough set proposed the simple way that can compromise with the ambiguity, vague, and uncertainty. Rough set generated the rules that can be used for prediction or classification decision attributes. Yet, due to the method based on categorical data, it must be careful in determining the category of attributes. Hence, this research investigated several categorizing attributes in the identification learning style. The results showed that the approach gives a better prediction of the learning style. Different categories give different results in terms of accuracy level, number of eliminated data, number of eliminated attributes, and number of generated rules criteria. For decision making, it can be considered by balancing of these criteria.
Finding Robust Nash equilibria

When agents or decision maker have uncertainties of underlying parameters, they may want to take “robust” decisions that are optimal against the worst possible values of those parameters, leading to some max-min optimization problems. With several agents in competition, in game theory, uncertainties are even more important and robust games or game with non-unique prior have gained a lot of interest recently, notably in auctions. The existence of robust equilibria in those games is guaranteed using standard fixed point theorems as in classical finite games, so we focus on the problem of finding and characterizing them. Under some linear assumption on the structure of the uncertainties, we provide a polynomial reduction of the robust Nash problem to a standard Nash problem (on some auxiliary different game). This is possible by proving the existence of a lifting transforming robust linear programs into standard linear programs. In the general case, the above direct reduction is not always possible. However, we prove how to adapt the Lemke-Howson algorithm to find robust Nash equilibria in non-degenerate games.
Optimal Data Placement for Heterogeneous Cache, Memory, and Storage Systems

New memory technologies are blurring the previously distinctive performance characteristics of adjacent layers in the memory hierarchy. No longer are such layers orders of magnitude different in request latency or capacity. Beyond the traditional single-layer view of caching, we now must re-cast the problem as a data placement challenge: which data should be cached in faster memory if it could instead be served directly from slower memory? We present CHOPT, an offline algorithm for data placement across multiple tiers of memory with asymmetric read and write costs. We show that CHOPT is optimal and can therefore serve as the upper bound of performance gain for any data placement algorithm. We also demonstrate an approximation of CHOPT which makes its execution time for long traces practical using spatial sampling of requests incurring a small 0.2% average error on representative workloads at a sampling ratio of 1%. Our evaluation of CHOPT on more than 30 production traces and benchmarks shows that optimal data placement decisions could improve average request latency by 8.2%-44.8% when compared with the long-established gold standard: Belady and Mattson's offline, evict-farthest-in-the-future optimal algorithms. Our results identify substantial improvement opportunities for future online memory management research.
Two-Stream Attention Network for Pain Recognition from Video Sequences

Several approaches have been proposed for the analysis of pain-related facial expressions. These approaches range from common classification architectures based on a set of carefully designed handcrafted features, to deep neural networks characterised by an autonomous extraction of relevant facial descriptors and simultaneous optimisation of a classification architecture. In the current work, an end-to-end approach based on attention networks for the analysis and recognition of pain-related facial expressions is proposed. The method combines both spatial and temporal aspects of facial expressions through a weighted aggregation of attention-based neural networks’ outputs, based on sequences of Motion History Images (MHIs) and Optical Flow Images (OFIs). Each input stream is fed into a specific attention network consisting of a Convolutional Neural Network (CNN) coupled to a Bidirectional Long Short-Term Memory (BiLSTM) Recurrent Neural Network (RNN). An attention mechanism generates a single weighted representation of each input stream (MHI sequence and OFI sequence), which is subsequently used to perform specific classification tasks. Simultaneously, a weighted aggregation of the classification scores specific to each input stream is performed to generate a final classification output. The assessment conducted on both the BioVid Heat Pain Database (Part A) and SenseEmotion Database points at the relevance of the proposed approach, as its classification performance is on par with state-of-the-art classification approaches proposed in the literature.
Going Back to School Takes Time: Evidence from a Negative Trade Shock

We estimate the impact of a negative trade shock on labour market outcomes and educational choices of workers. We exploit the Canadian lumber exports crisis beginning in 2007 in a quasi-experimental design. We find that the employment probability of forestry industry workers decreased by 4.1 percentage points following the crisis relative to other workers in comparable industries. While one would expect younger forestry workers to return to school in such cir-cumstances, we find that in the first two years following the crisis, unemployed workers did not go back to school. But going back to school takes time, and after 3 to 4 years, we find that education enrollment increases by 2.5 percentage points (p=0.083). This confirms the idea that adjustments towards an increase in education enrollment are gradual, as it is easier to drop out than to enroll. In time of crisis, facilitating a return to education might be a valuable policy intervention.
Assessment of Basic and Advanced Knowledge in Biostatistics and Clinical Research among Health care Professionals at King Fahad Medical City, Riyadh, KSA: A cross-Sectional Survey

Background: Adequate biostatistics knowledge among healthcare professionals is imperative for understanding medical literature and practicing evidence-based medicine. This study assessed the basic and advanced knowledge in biostatistics and clinical research among healthcare workers at the King Fahad Medical City (KFMC), Riyadh, Saudi Arabia. Methods: In this cross-sectional survey, data was collected from healthcare providers using a self-administered questionnaire, having questions related to demographics, biostatistics and clinical research. Data analysis was performed using statistical package SPSS 22. Results: Of 194 participants (63 [32.5%] consultants, 52 [26.8%] residents, and 79 [40.7%] allied healthcare providers), 45.4% had positive attitude towards learning biostatistics. Only 35.1% correctly answered biostatistics and clinical research instrument-related questions. Half participants had low score, 33% had good score, and 18-19% had excellent score of basic and advanced knowledge of biostatistics and clinical research. The highest degree and number of years of experience in biostatistics after medical school graduation were significantly (χ2 (2)=16.589, p<0.001) associated with basic and advanced biostatistics knowledge scores. Conclusion: Timely and painstaking training courses in biostatistics and clinical research are needed to improve the research standards in Saudi Arabia. Interested candidates should collaborated with statisticians to improve quality of their work and enhance their statistical skills.
Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data

The success of the large neural language models on many NLP tasks is exciting. However, we find that these successes sometimes lead to hype in which these models are being described as “understanding” language or capturing “meaning”. In this position paper, we argue that a system trained only on form has a priori no way to learn meaning. In keeping with the ACL 2020 theme of “Taking Stock of Where We’ve Been and Where We’re Going”, we argue that a clear understanding of the distinction between form and meaning will help guide the field towards better science around natural language understanding.
COPD_A_220346 2745..2752

School of Public Health & Preventive Medicine, Monash University, Melbourne, Australia; Shaare Zedek Medical Center and The Hebrew University Hadassah Medical School, Jerusalem, Israel; National Healthcare Group Polyclinics, Singapore; Centre For Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, Parkville, Australia; Southern Academic Primary Care Research Unit, Department of General Practice, Monash University, Notting Hill, Australia; Discipline of Physiotherapy, La Trobe University and Alfred Health, Melbourne, Australia; Faculty of Health Sciences & Medicine, Bond University, Gold Coast, Australia; School of Medicine and Public Health, University of Newcastle, Callaghan, Australia; The Nossal Institute For Global Health, University of Melbourne, Melbourne, Australia; Eastern Melbourne PHN (EMPHN), Box Hill, Australia; Lung Foundation Australia (LFA), Milton, Australia; Department of Infrastructure Engineering, The University of Melbourne, Melbourne, Australia Purpose: Many older adults with a history of smoking and asthma develop clinical features of both asthma and COPD, an entity sometimes called asthma-COPD overlap (ACO). Patients with ACO may be at higher risk of poor health outcomes than those with asthma or COPD alone. However, understanding of ACO is limited in the primary care setting and more information is needed to better inform patient management. We aimed to compare the characteristics of patients with ACO or COPD in Australian general practices. Patients and methods: Data were from the RADICALS (Review of Airway Dysfunction and Interdisciplinary Community-based care of Adult Long-term Smokers) trial, an intervention study of an interdisciplinary community-based model of care. Baseline demographic and clinical characteristics, preand post-bronchodilator spirometry, dyspnoea and St. George’s Respiratory Questionnaire scores were compared between 60 ACO patients and 212 with COPD alone. Results: Pre-bronchodilator Forced Expiratory Volume in 1 second (mean±SD 58.4±14.3 vs 67.5±20.1% predicted) and Forced Vital Capacity (mean 82.1±16.9 v 91.9±17.2% predicted) were significantly lower in the ACO group (p<0.001), but no difference was found in postbronchodilator spirometry. Demographic and clinical characteristics, dyspnoea, quality of life, comorbidities and treatment prescribed did not differ significantly between groups. Conclusion: This is the first study describing the clinical characteristics of ACO patients in Australian general practices. Our finding of lower pre-bronchodilator lung function in the ACO group compared to those with COPD reinforces the importance of spirometry in primary care to inform management. Trial registration: Australian New Zealand Clinical Trials Registry ACTRN12614001155684.
Green supply chain management (GSCM) practices and their impact on performance: An insight from the Jordanian construction sector

This paper aims to investigate the relationship between green supply chain management (GSCM) practices and performance (environmental, economic and organisational) within the construction sector in Jordan. Based on the literature review, the survey designed included46 key items. Data was collected from 133 managers in the construction sector. Multiple regression analysis wasundertakento test the study hypotheses. The analysis showedmixed results, green construction and investment recovery wassupported in three hypotheses; internal environmental management was supported only with organisationalperformance. The practical implicationsof the findings include creating more effort to attaining benefits from the world trade organisation(WTO) initiatives to establish long-term relationships with foreign customers to learn and enhance green practices in Jordan’s construction sector. This work is one of few studies thatinvestigatesGSCM practices in the construction sector ofa developing country.