Miracle-dz/UniFAR-FTUs huggingface dataset:
Hierarchical Attention Based Recurrent Neural Network Framework for Mobile MOBA Game Recommender Systems

The mobile multiplayer online battle arena (MOBA) game is a genre of real-time strategy video games on mobile devices, such as King of Glory. The main business model is to drive players to purchase items like heroes or skins. Recommending items based on player interest is the core task of recommender systems. In the MOBA game, player interest changes over the game experience, which is implied in player behavior based on historical game matches. Match sequences, that consist of every match in the timeline, indicate how players interact with the game and the change process of player interest. Recurrent neural networks (RNNs) are employed by many recommendation scenes to model sequence data to profile user preference for better recommendation accuracy. However, their RNNs based frameworks ignore the interpretability of recommendation results, which is an important requirement for mobile MOBA games. To solve this challenge, we propose an interpretable RNN framework based on hierarchical attention in this work, which is inspired by the attention mechanism applied in machine translation. The main component long short-term memory (LSTM), that is the RNN variant, models player interest from historical match sequences, and the hierarchical attention is used to measure the effect factors of matches and behavior events happened in a match. To verify effectiveness, we train several models on real mobile MOBA game King of Glory datasets. Compared to non-sequence models, our model achieves 2% higher accuracy; with hierarchical attention, the proposed model can interpret the recommendation results effectively compared to naive RNN based models.
Expanding the Sample: The Relationship between the Black Hole Mass of BCGs and the Total Mass of Galaxy Clusters

Supermassive black holes (BHs) residing in brightest cluster galaxies (BCGs) are overly massive when considering the local relationships between the BH mass and stellar bulge mass or velocity dispersion. Because of the location of these BHs within the cluster, large-scale cluster processes may aid the growth of BHs in BCGs. In this work, we study a sample of 71 galaxy clusters to explore the relationship between the BH mass, stellar bulge mass of the BCG, and the total gravitating mass of the host clusters. Because of difficulties in obtaining dynamically measured BH masses in distant galaxies, we use the Fundamental Plane relationship of BHs to infer their masses. We utilize X-ray observations taken by Chandra to measure the temperature of the intracluster medium, which is a proxy for the total mass of the cluster. We analyze the MBH–kT and MBH–Mbulge relationships and establish the best-fitting power laws: = −0.35+2.08 and = −1.09+1.92 . Both relations are comparable with that established earlier for a sample of brightest group/cluster galaxies with dynamically measured BH masses. Although both the MBH–kT and the MBH–Mbulge relationships exhibit large intrinsic scatter, on the basis of Monte Carlo simulations, we conclude that dominant fraction of the scatter originates from the Fundamental Plane relationship. We split the sample into cool core and noncool core resembling clusters but do not find statistically significant differences in the MBH–kT relation. We speculate that the overly massive BHs in BCGs may be due to frequent mergers and cool gas inflows onto the cluster center.
Stiffened Shear Diaphragm Design Requirements for Bracing of Beams

The lateral-torsional buckling capacity of steel girders can be improved with the addition of intermediate bracing. One form of bracing commonly used in the building industry is profiled sheeting that acts as a shear diaphragm to restrain the warping deformation of the top flange. Although metal deck forms are also commonly used in the bridge industry, the forms are not currently permitted to be relied upon for bracing due to flexibility in the connection method. Shear diaphragms attached to the top flange of adjacent girders can be relied on for bracing provided they have adequate stiffness and strength, both of which are sensitive to the connection details. Shear diaphragms may be engaged to act as lateral bracing by connecting the diaphragm along either two or four sides. A common connection detail consists of connecting the diaphragm along two edges that are parallel to the longitudinal axis of the girder and studies have been carried out to develop strength requirements for suitable bracing. Provisions have not been adequately developed in stiffened diaphragms when the stiffening members are perpendicular to the longitudinal axis of the girder. This paper documents a computational study to develop strength requirements for stiffened diaphragms used for stability bracing. 1 Graduate Research Assistant, University of Texas at Austin, <colter.roskos@utexas.edu> 2 Graduate Research Assistant, University of Texas at Austin, <paul.biju-duval@utexas.edu> 3 Professor, University of Texas at Austin, < thelwig@mail.utexas.edu >
Is the Iron Treatment Important for Lowering Erythrocyte Zinc in Non-Dialyzed Patients with Chronic Kidney Disease?

Introduction: Zinc (Zn) protoporphyrin (ZPP) presents in red blood cells (RBC) in small amounts, but increases in iron deficiency or lead poisoning. Formation of heme - a component of hemoglobin - finished with insertion of an iron into the molecule of protoporphyrin. In iron deficiency, or inhibition of iron insertion (lead poisoning), zinc replaces iron to form ZPP, which cannot bind to oxygen. Plasma zinc is lower in patients with chronic kidney diseases (CKD), but it’s not yet clear whether it’s a real deficit or is due to redistribution. Aim: The aim of this study was to evaluate the effects of iron supplementation on zinc redistribution in the body tissues of non-dialyzed chronic kidney disease (CKD) patients. Material and Methods: Zn and Fe status of 38 non-dialyzed patients with iron-deficit anemia (17 males; 21 females);mean GFR - 43.3 mL/min(32.5 to 57.3 mL/min), was evaluated before and after 5 i.v. injections of 100 mg iron each. The following parameters were tested: RBC and plasma Zn, ZPP, ferritin (F), transferrin saturation (TFS), and total iron (Fe). Results: F and TFS increased from 86.5+/-61.2 ng/mL to 132.4+/-64.3 ng/mL and from 21.5+/-9.4% to 26.8+/-8.3% (P<0.05), respectively, after iron supplementation. Absolute iron deficiency (ferritin <100 g/L and TFS < 20%) was present in 44% of the patients and decreased to 25% after iron treatment. After supplementation, patients with low plasma zinc decreased from 49.5% to 30.8% (p N.S.). At start of the study 29 of the patients had high erythrocyte zinc. After iron treatment, erythrocyte zinc decreased significantly in 24 patients (p< 0.001), and only a weak lowering was observed in ZPP (p N.S.). Conclusions: The study suggests that iron deficiency may participate in the inadequate distribution of zinc in patients with CKD and iron supplementation may decrease the abnormal elevated erythrocyte zinc levels.
Curve Text Detection with Local Segmentation Network and Curve Connection

Curve text or arbitrary shape text is very common in real-world scenarios. In this paper, we propose a novel framework with the local segmentation network (LSN) followed by the curve connection to detect text in horizontal, oriented and curved forms. The LSN is composed of two elements, i.e., proposal generation to get the horizontal rectangle proposals with high overlap with text and text segmentation to find the arbitrary shape text region within proposals. The curve connection is then designed to connect the local mask to the detection results. We conduct experiments using the proposed framework on two real-world curve text detection datasets and demonstrate the effectiveness over previous approaches.
The risk of endometriosis after exposure to endocrine-disrupting chemicals: a meta-analysis of 30 epidemiology studies

Abstract Endocrine-disrupting chemicals (EDCs) are suspected to be associated with endometriosis (EMs). This study aimed to synthesize published data and evaluate the relationship between four classic EDCs exposure and the risk of EMs. A systematic literature search for original peer reviewed papers was performed in the databases PubMed, EMBASE, and Web of Science based on inclusion criteria up to January 2018. Subsequently, a total of 20 papers conducting 30 studies fulfilled the eligibility criteria and were included in this meta-analysis (four studies for bisphenol A (BPA), 12 studies for polychlorinated biphenyls (PCBs), eight studies for organochlorine pesticides (OCPs), and six studies for phthalate esters (PAEs)). The overall odds ratio (OR) across all exposures and EMs was 1.41 (95% confidence interval (CI): 1.23–1.60). When assessing four specific chemicals, respectively, consistent increases in the risk of EMs were found in PCBs group (OR = 1.58; 95% CI: 1.18–2.12), OCPs group (OR = 1.40; 95% CI: 1.02–1.92) and PAEs group (OR = 1.27; 95% CI: 1.00–1.60), while BPA showed no significant association with EMs. Besides, in the di-(2-ethylhexyl)-phthalate (DEHP) group – the most commonly used PAEs, significant risk was also found (OR = 1.42; 95% CI: 1.19–1.70). The current meta-analysis strengthens the evidence that specific EDCs or their metabolites may promote the occurrence of EMs.
Differences in dietary recall and subjective physical functioning status in stroke survivors with self-reported cognitive impairment

ABSTRACT Background: Little is known about the dietary intake of these nutrients in stroke survivors, who often experience greater difficulties with physical functioning due to cognitive impairment. Objectives: To explore whether dietary intake and physical function differ between those with and without self-report cognitive impairment. Methods: The present study analyzes data from the 2011–2012 and 2013–2014 National Health and Nutrition Examination Survey. Individuals were included if they self-reported a stroke and had data regarding cognitive impairment (self-reported “periods of confusion or memory problems”) and dietary intake from 24-hr recalls (N = 360). A subset had handgrip strength (N = 330) and questionnaire data regarding the presence of 19 different functional limitations (N = 187). Results: Of the 360 stroke survivor participants (66 ± 1 years, 53% female, mean±SEM), 48% reported cognitive impairment. Dietary intake of polyunsaturated fatty acids was 19% lower (p = 0.01), with a trend for 13% lower vitamin B6 intake (p = 0.07) in those with cognitive impairment compared to those who did not. Those with cognitive impairment had lower handgrip strength and reported twice as many functional limitations (p’s<0.01). Conclusion: A lower intake of polyunsaturated fat and vitamin B6 may be associated with cognitive function, ultimately affecting physical functioning, post-stroke. It is possible that differing stroke severity and difficulty recalling dietary habits could have affected the present findings. Therefore, further research is needed to determine if interventions designed to modify polyunsaturated fat and vitamin B6 intakes are able to influence cognitive and physical function in stroke survivors with varying degrees of functional and cognitive deficits.
Oral Health and Cognitive Function in Older Adults: A Systematic Review

Background: It has often been argued that there is a relationship between oral health and cognitive decline in late adulthood, but a recent systematic review concluded that it was unclear “how or whether” any relationship exists. However, most of the studies that contributed to this review operationalised cognitive function using a brief cognitive screen and/or dementia status. Objective: An updated systematic review was conducted that focused on how oral health relates to specific cognitive abilities in older adults (specifically, the neurocognitive domains specified in the DSM-5: learning and memory, perceptual motor function, language, executive function, complex attention, and social cognition). Methods: A systematic review was undertaken and completed in August 2018. From a total of 1,304 potentially relevant articles, 23 were identified that assessed oral health and at least one of the specific cognitive domains in an older adult cohort. Results: The most consistent relationships were identified with learning and memory, complex attention, and executive function. For each of these cognitive domains, most studies identified significant unadjusted associations with oral health; where adjustments for covariates were made, at least one of the associations with oral health remained significant in half or more of the studies. Results were less clear for the domains of language and perceptual motor function. No study assessed the relationship between social cognition and oral health. Conclusions: This systematic review provides evidence of an association between learning and memory, complex attention, and executive function with oral health in old age. Gaining a detailed picture of how specific types of cognitive decline relate to oral health has potential implications for earlier identification of older adults who experience oral health problems, and may also inform the development of more effective interventions focused on enhancing oral health outcomes in this group.
Effects of Amisulpride Adjunctive Therapy on Working Memory and Brain Metabolism in the Frontal Cortex of Patients with Schizophrenia: A Preliminary Positron Emission Tomography/Computerized Tomography Investigation

Objective Dopamine plays a significant role in working memory by acting as a key neuromodulator between brain networks. Additionally, treatment of patients with schizophrenia using amisulpride, a pure dopamine class 2/3 receptor antagonist, improves their clinical symptoms with fewer side effects. We hypothesized that patients with schizophrenia treated with amisulpride and aripiprazole show increased working memory and glucose metabolism compared with those treated with cognitive behavioral therapy (CBT) and aripiprazole instead. Methods Sixteen patients with schizophrenia (eight in the amisulpride group [aripiprazole+amisulpride] and eight in the CBT group [aripiprazole+CBT]) and 15 age- and sex-matched healthy control subjects were recruited for a 12-week-long prospective trial. An [18F]-fluorodeoxyglucose-positron emission tomography/computerized tomography scanner was used to acquire the images. Results After 12 weeks of treatment, the amisulpride group showed greater improvement in the Letter-Number Span scores than the CBT group. Additionally, although brain metabolism in the left middle frontal gyrus, left occipital lingual gyrus, and right inferior parietal lobe was increased in all patients with schizophrenia, the amisulpride group exhibited a greater increase in metabolism in both the right superior frontal gyrus and right frontal precentral gyrus than the CBT group. Conclusion This study suggests that a small dose of amisulpride improves the general psychopathology, working memory performance, and brain glucose metabolism of patients with schizophrenia treated with aripiprazole.
Breeding for organic dairy farming: what types of cows are needed?

Abstract Organic farming is believed by many to be an environmentally friendly production system that promotes the use of local forage while strongly limiting the input of chemicals, including allopathic treatments. As organic dairy farming has grown, farmers have realised that many available conventional breeds of cow are not well adapted to the new situations and that more ‘robust’ cows, able to function well in the constraining organic environment, are needed to yield acceptable longevity and productivity. In this review paper, the current breed diversity in organic dairy farming is analysed with the aim of identifying the types of cow that would best fulfil organic breeding goals. Unlike the conventional sector, organic dairy farming is very heterogeneous and no single type of cow can adapt well to all scenarios. There are advantages and disadvantages to the use of existing breeds (rustic Holstein-Friesian, other rustic breeds and crosses), and strong genotype × environment interactions demand different strategies for very diverse situations. Organic dairy farms producing milk for systems that recompense milk volume would benefit from using higher milk yielding cows, and rustic Holstein-Friesian cows may be the best option in such cases. Although most Holstein-Friesian cows are currently selected for use in conventional systems, this situation could be reversed by the implementation of an organic merit index that includes organic breeding goals. Farms producing milk either for systems that recompense milk solids or for transformation into dairy products would benefit from using breeds other than Holstein-Friesian or their crosses. Organic farmers who focus on rural tourism, farm schools or other businesses in which marketing strategies must be taken into account could benefit from using local breeds (when possible) or other rustic breeds that are highly valued by consumers.
Comparative Study of the Continuous and Batch Thermal Processing of MgB2 Wires

The last stage of the manufacturing process requires complex reactive diffusion formation process of MgB2 in the presence of SiC nanoparticles. Continuous thermal processing was adopted to produce long length MgB2 in situ wires with a homogeneous mixture of micron-sized Mg, nanosized B, as well as SiC dopant powders. This process has enabled the formation of MgB2 superconducting compound in a relatively short time. Traditional superconductor batch processing requires the wire batch to be heat treated in dedicated large furnaces. Additionally, such a batch process requires controllable slow heating-up, dwelling, and cooling down procedures to ensure uniformity of the superconducting properties along the wire length. Such a prolonged reactive diffusion process does require lower dwelling temperature and can potentially prevent full utilization of the doping materials, resulting in less effective pinning centers formation. On the other hand, continuous wire thermal processing enables rapid formation of the doped MgB2 with full utilization of the dopant. Also, in the continuous process, the moving thermal front brings complex dynamics to Mg–B, C–B, Mg–Si interaction during MgB2 formation processes. The manuscript presents a comparative study of the reactive diffusion kinetics, the microstructural formation of the doped MgB2 compound, and their Jc(B, T) characteristics.
Non-Interactive Group Key Pre-Distribution Scheme (GKPS) for End-to-End Routing in Wireless Sensor Networks

A novel design of secure end-to-end routing protocol in wireless sensor networks was recently proposed by Harn <italic>et al.</italic> Their design is based on a group key pre-distribution scheme (GKPS) using a multivariate polynomial. A group key also called a <italic>path key</italic>, is used to protect data transmitted in the entire routing path. Specifically, instead of using a link-to-link secure communication that uses multiple pairwise shared keys, it is an end-to-end secure communication that uses a single path key to protect data over the entire path. The problem with all polynomial-based key distribution schemes is that the security of these schemes, which are called <italic>deterministic k-secure</italic>, depends on the degree of the chosen polynomial. In other words, if the degree of the chosen polynomial is <inline-formula> <tex-math notation="LaTeX">$k$ </tex-math></inline-formula>, then capturing the <inline-formula> <tex-math notation="LaTeX">$k+1$ </tex-math></inline-formula> sensors (or more) can compromise the system’s security. Although increasing the degree of the polynomial can improve the security, it increases the storage and computational requirements of the sensors. In this paper, we propose the first probabilistic polynomial-based GKPS, which is based on a multivariate polynomial. The security of our scheme is <italic>probabilistic k-secure</italic>, which means it is probabilistic to compromise the security of our GKPS after capturing the <inline-formula> <tex-math notation="LaTeX">$k+1$ </tex-math></inline-formula> sensors. We show that the probability of a sensor capture attack can be significantly reduced.
Gender Effects in Perceptions of Robots and Humans with Varying Emotional Intelligence

Robots are machines and as such do not have gender. However, many of the gender-related perceptions and expectations formed in human-human interactions may be inadvertently and unreasonably transferred to interactions with social robots. In this paper, we investigate how gender effects in people's perception of robots and humans depend on their emotional intelligence (EI), a crucial component of successful human social interactions. Our results show that participants perceive different levels of EI in robots just as they do in humans. Also, their EI perceptions are affected by gender-related expectations both when judging humans and when judging robots with minimal gender markers, such as voice or even just a name. We discuss the implications for human-robot interactions (HRI) and propose further explorations of EI for future HRI studies.
Intelligent Prediction of Human Lower Extremity Joint Moment: An Artificial Neural Network Approach

Human joint moment plays an important role in quantitative rehabilitation assessment and exoskeleton robot control. However, the existing moment prediction methods require kinematic and kinetic data of human body as input, and the measurement of them needs special equipment, which makes them unable to be used in an unconstrained environment. According to the situation, this paper develops a novel method where a small number of input variables selected by Elastic Net are used as the input of artificial neural network (ANN) to predict joint moments, which makes the prediction in daily life possible. The method is tested on the experimental data collected from eight healthy subjects that are running on a treadmill at a speed of 2, 3, 4, and 5 m/s, respectively. Taking the right lower limb’s 10 electromyography (EMG) and 5 joints angle data as candidate variable sets, Elastic Net is used to obtain the variable coefficients of the right lower limb’s four joint moments. The inputs of the ANN determined by the variable coefficients are used to train and predict the joint moments. Prediction accuracy is evaluated by using the normalized root-mean-square error (NRMSE %) and cross correlation coefficient ( $\rho$ ) between the predicted joint moment and multi-body dynamics moment. Results of our study suggest that the method can accurately predict joint moment (NRMSE < 7.89%, $\rho >0.9633$ ) with only 5–6 EMG signals. In conclusion, this method can effectively reduce the input variables while keeping a certain precision, which makes the joint moment prediction simple and out of equipment limitation. This method may facilitate the researches on real-time gait analysis and exoskeleton robot control in motor rehabilitation.