Miracle-dz/UniFAR-FTUs huggingface dataset:
Influence of Homogeneity of Student Characteristics in a Group-Based Social Competence Intervention

Although some literature reviews cited mixed results for group-based social competence interventions in schools, existing descriptions of intervention efficacy often lack attention on important factors that may moderate differential response. Some studies suggest that individual characteristics such as diagnosis (i.e., specific deficit clusters) or behavioral profiles may be important social outcome moderators. Given the interactive nature of group-based interventions, understanding how individual characteristics combine to influence outcomes for the group as a whole is an important next step. By using a multisite cluster randomized control trial (n = 274), the current study explores the impact that varying student characteristics have on outcomes of the Social Competence Intervention for Adolescents (SCI-A; Stichter, Herzog, Owens, & Malugen, 2016; Stichter et al., 2010) compared to outcomes of business-as-usual (BAU) practices. Researchers hypothesized that (a) SCI-A would be more effective than BAU in improving ratings of students’ social functioning when students within groups were more similar to each other on relevant diagnostic and behavioral indicators, and (b) that within SCI-A only, more versus less homogenous groups would demonstrate greater social outcome gains. Results offer some support for these hypotheses: SCI-A was more effective in improving social communication and motivation when groups were diagnostically similar (ds > 0.55). Considering changes in social awareness and communication, SCI-A was more effective when groups were heterogeneous on socially competent behavior (ds > 1.32) and less effective when groups were heterogeneous on antisocial behavior (ds > 1.00). The authors discuss the implications and importance of research exploring factors such as group composition that may moderate intervention response in applied settings.
J. Gen. Appl. Microbiol

Advance Publication J. Gen. Appl. Microbiol. doi 10.2323/jgam.2021. 05.001 ©2021 Applied Microbiology, Molecular and Cellular Biosciences Research Foundation Full Paper 1 Comparative evaluation of fibrous artificial carbons and 2 bamboo charcoal in terms of recovery of current from 3 sewage wastewater 4 (Received March 11, 2021; Accepted May 12, 2021; J-STAGE Advance publication date: August 31, 2021) 5 1,† 1,†1 Wataru Nagahashi and Naoko Yoshida 6 7
Comparative Efficacy of Autologous Stromal Vascular Fraction and Autologous Adipose-Derived Mesenchymal Stem Cells Combined With Hyaluronic Acid for the Treatment of Sheep Osteoarthritis

The current study explored whether intra-articular (IA) injection of autologous adipose mesenchymal stem cells (ASCs) combined with hyaluronic acid (HA) achieved better therapeutic efficacy than autologous stromal vascular fraction (SVF) combined with HA to prevent osteoarthritis (OA) progression and determined how long autologous ASCs combined with HA must remain in the joint to observe efficacy. OA models were established by performing anterior cruciate ligament transection (ACLT) and medial meniscectomy (MM). Autologous SVF (1×107 mononuclear cells), autologous low-dose ASCs (1×107), and autologous high-dose ASCs (5×107) combined with HA, and HA alone, or saline alone were injected into the OA model animals at 12 and 15 weeks after surgery, respectively. Compared with SVF+HA treatment, low-dose ASC+HA treatment yielded better magnetic resonance imaging (MRI) scores and macroscopic results, while the cartilage thickness of the tibial plateau did not differ between low, high ASC+HA and SVF+HA treatments detected by micro-computed tomography (µCT). Immunohistochemistry revealed that high-dose ASC+HA treatment rescued hypertrophic chondrocytes expressing collagen X in the deep area of articular cartilage. Western blotting analysis indicated the high- and low-dose ASC+HA groups expressed more collagen X than did the SVF+HA group. Enzyme-linked immunosorbent assay showed treatment with both ASC+HA and SVF+HA resulted in differing anti-inflammatory and trophic effects. Moreover, superparamagnetic iron oxide particle (SPIO)-labeled autologous ASC signals were detected by MRI at 2 and 18 weeks post-injection and were found in the lateral meniscus at 2 weeks and in the marrow cavity of the femoral condyle at 18 weeks post-injection. Thus, IA injection of autologous ASC+HA may demonstrate better efficacy than autologous SVF+HA in blocking OA progression and promoting cartilage regeneration, and autologous ASCs (5×107 cells) combined with HA potentially survive for at least 18 weeks after IA injection.
Insights on representational similarity in neural networks with canonical correlation

Comparing different neural network representations and determining how representations evolve over time remain challenging open questions in our understanding of the function of neural networks. Comparing representations in neural networks is fundamentally difficult as the structure of representations varies greatly, even across groups of networks trained on identical tasks, and over the course of training. Here, we develop projection weighted CCA (Canonical Correlation Analysis) as a tool for understanding neural networks, building off of SVCCA, a recently proposed method (Raghu et al., 2017). We first improve the core method, showing how to differentiate between signal and noise, and then apply this technique to compare across a group of CNNs, demonstrating that networks which generalize converge to more similar representations than networks which memorize, that wider networks converge to more similar solutions than narrow networks, and that trained networks with identical topology but different learning rates converge to distinct clusters with diverse representations. We also investigate the representational dynamics of RNNs, across both training and sequential timesteps, finding that RNNs converge in a bottom-up pattern over the course of training and that the hidden state is highly variable over the course of a sequence, even when accounting for linear transforms. Together, these results provide new insights into the function of CNNs and RNNs, and demonstrate the utility of using CCA to understand representations.
Reduction in Serum Triglyceride Levels in Diabetic Patients May Result in Decreased Insulin Dependence and Disease Regression.

BACKGROUND Type 2 diabetes mellitus is a multifactorial disease in which genetic susceptibility and environmental factors induce pancreatic β-cell dysfunction and insulin resistance. Additional factors such as hyperglycemia and hyperlipidemia have roles in β-cell dysfunction and disease progression. The phenomenon of lipid-induced pancreatic β-dysfunction, designated as lipotoxicity, has been observed in several in vitro and in vivo experiments; however, there is still no solid evidence for the occurrence of this event in humans. The toxic effect of high lipid levels on β-cell function consists of impaired insulin gene expression, apoptosis, and reduced glucose-stimulated insulin secretion. OBJECTIVES To demonstrate the importance of treating hypertriglyceridemia in reducing glucose intolerance and the need for insulin therapy in hospitalized diabetic patients. METHODS We evaluated five clinical case reports and conducted a detailed literature review via the PubMed search engine. RESULTS Reduction in elevated blood triglyceride and glucose levels in hospitalized diabetic patients resulted in a rapid decline in glucose levels and in the need for insulin therapy. CONCLUSIONS A decrease in high triglyceride levels in "lipotoxic" diabetic patients may improve insulin intolerance and glucose homeostasis and reduce the need for insulin therapy.
Endothelial cells are critical regulators of iron transport in a model of the human blood–brain barrier

Iron delivery to the brain is essential for multiple neurological processes such as myelination, neurotransmitter synthesis, and energy production. Loss of brain iron homeostasis is a significant factor in multiple neurological disorders. Understanding the mechanism by which the transport of iron across the blood–brain barrier (BBB) is regulated is crucial to address the impact of iron deficiency on brain development and excessive accumulation of iron in neurodegenerative diseases. Using induced pluripotent stem cell (iPSC)-derived brain endothelial cells (huECs) as a human BBB model, we demonstrate the ability of transferrin, hepcidin, and DMT1 to impact iron transport and release. Our model reveals a new function for H-ferritin to transport iron across the BBB by binding to the T-cell immunoglobulin and mucin receptor 1. We show that huECs secrete both transferrin and H-ferritin, which can serve as iron sources for the brain. Based on our data, brain iron status can exert control of iron transport across the endothelial cells that constitute the BBB. These data address a number of pertinent questions such as how brain iron uptake is regulated at the regional level, the source of iron delivery to the brain, and the clinical strategies for attempting to treat brain iron deficiency.
Learning a Patch Quality Comparator for Single Image Dehazing

In bad weather conditions such as fog and haze, the particles present in the atmosphere scatter incident light in different directions. As a result, the image taken under these conditions suffers from reduced visibility and lack of contrast, and as a result, it appears colorless. An image dehazing method tries to recover a haze-free portrayal of the given hazy image. In this paper, we propose a method that dehazes a given image by comparing various output patches with the original hazy version and then choosing the best one. The comparison is performed by our proposed dehazed patch quality comparator based on the convolutional neural network. To select the best dehazed patch, we employ binary search. Quantitative and qualitative evaluations show that our method achieves good results in most of the cases, and are, on an average, comparable with the state-of-the-art methods.
CVI-SLAM—Collaborative Visual-Inertial SLAM

With robotic perception constituting the biggest impediment before robots are ready for employment in real missions, the promise of more efficient and robust robotic perception in multiagent, collaborative missions can have a great impact on many robotic applications. Employing an ubiquitous and well-established visual-inertial setup onboard each agent, in this letter, we propose CVI-SLAM, a novel visual-inertial framework for centralized collaborative simultaneous localization and mapping (SLAM). Sharing all information with a central server, each agent outsources computationally expensive tasks, such as global map optimization to relieve onboard resources and passes on measurements to other participating agents, while running visual-inertial odometry onboard to ensure autonomy throughout the mission. Thoroughly analyzing CVI-SLAM, we attest to its accuracy and the improvements arising from the collaboration, and evaluate its scalability in the number of participating agents and applicability in terms of network requirements.
Behaviour change techniques associated with adherence to prescribed exercise in patients with persistent musculoskeletal pain: Systematic review

Purpose Exercise (planned, structured, repetitive movement) improves pain and function in people with persistent musculoskeletal pain (PMSK), but adherence is often poor. This systematic review evaluates the evidence from randomized controlled trials (RCTs) on the effectiveness of interventions to improve exercise adherence in people with PMSK and describes the content, context, and theoretical underpinning of behaviour change interventions designed to increase adherence. Methods Nine electronic databases were searched from inception dates to August 2017. Studies were included if they were RCTs that included adults with PMSK ≥3 months; ≥one measure of exercise adherence, exercise prescribed to both groups, and employed ≥one behaviour change technique (BCT) in the treatment group. Independent data extraction, theory coding, BCT taxonomy coding, and quality assessment using Cochrane Risk of Bias (RoB) tool was conducted by two reviewers. Results Eight RCTs (five low, three high RoB) met inclusion criteria. Five trials reported between‐group differences in exercise adherence, favouring the treatment group. Three trials reported theoretical underpinning. There was moderate evidence that five BCTs, social support, goal setting, instruction of behaviour, demonstration of behaviour, and practice/rehearsal, improved exercise adherence. Interventions employing ≤seven BCTs, unique to those included in the control group, were most effective at enhancing exercise adherence. Conclusions Limited moderate‐quality evidence supports using a small number of BCTs to enhance exercise adherence in people with PMSK. Further research should explore the associations and synergies between BCTs and explicitly report how theory was utilized. This may inform recommendations for health care professionals working with this population. Statement of contribution What is already known on this subject? Exercise (i.e., planned, structured, repetitive movements) improves pain and function in people with persistent musculoskeletal pain (PMSK). Many people with PMSK do not adhere to exercises prescribed by a health care professional. Little research has explored how to enhance adherence to prescribed exercise in people with PMSK. What does this study add? Moderate‐quality evidence from eight trials suggests behaviour change interventions enhance exercise adherence. Social support, goal setting, demonstration, instruction, and rehearsal were employed in effective interventions. Interventions with ≤7 behaviour change techniques were more effective at improving adherence than those employing >7.
Size and modality effects in Braille learning: Implications for the blind child from pre‐reading sighted children

BACKGROUND Beginning readers are typically introduced to enlarged print, and the size of this print decreases as readers become more fluent. In comparison, beginning blind readers are expected to learn standard-sized Braille from the outset because past research suggests letter knowledge cannot be transferred across different sizes of Braille. AIMS The study aims to investigate whether learning Braille using an oversized pegboard leads to faster, transferable, letter learning and whether performance is mediated by either tactile or visual learning. SAMPLE Sixty-eight children participated in the study. All children were sighted pre-readers with no previous knowledge of Braille. The children came from two nursery schools with an average age of 47.8 months. METHODS Children were taught specific Braille letters using either an enlarged pegboard or standard Braille. Two other groups of children were taught using visually presented Braille characters in either an enlarged or standard size and a further control group mirrored the experience of blind children in receiving non-specific tactile training prior to being introduced to Braille. In all tactile conditions it was ensured that the children did not visually experience any Braille for the duration of the study. RESULTS Results demonstrated that initially training children with large Braille tactually led to the best subsequent learning of standard Braille. Despite the fact that both initial visual and large tactual learning were significantly faster than learning standard Braille, when transferring letter knowledge to standard tactile Braille, previous tactile experience with the large pegboard offered the most efficient route. CONCLUSIONS Braille letter knowledge can be transferred across size and modality particularly effectively with large tactile Braille. This has significant implications for the education of blind children.
The Road to Success: Assessing the Fate of Linguistic Innovations in Online Communities

We investigate the birth and diffusion of lexical innovations in a large dataset of online social communities. We build on sociolinguistic theories and focus on the relation between the spread of a novel term and the social role of the individuals who use it, uncovering characteristics of innovators and adopters. Finally, we perform a prediction task that allows us to anticipate whether an innovation will successfully spread within a community.
Major depression impairs incentive processing: evidence from the heart and the face

Abstract Background The present study tested the hypothesis of a differential pattern of reward and punishment responsiveness in depression measuring effort mobilization during anticipation and facial expressions during consumption. Methods Twenty patients with major depressive disorder (MDD) and 20 control participants worked on a memory task under neutral, reward, and punishment instructions. Effort mobilization was operationalized as cardiovascular reactivity, while facial expressions were measured by facial electromyographic reactivity. Self-report measures for each phase complemented this multi-method approach. Results During anticipation, MDD patients showed weaker cardiac pre-ejection period (PEP) reactivity to reward and blunted self-reported wanting, but weaker PEP reactivity to punishment and unchanged self-reported avoidance motivation. During consumption, MDD patients showed reduced zygomaticus major muscle reactivity to reward and blunted self-reported liking, but unchanged corrugator supercilii muscle reactivity to punishment and unchanged self-reported disliking. Conclusions These findings demonstrate reduced effort mobilization during reward and punishment anticipation in depression. Moreover, they show reduced facial expressions during reward consumption and unchanged facial expressions during punishment consumption in depression.
An association study of FOXO3 variant and longevity

Abstract Human longevity is a polygenic and multifactorial trait. Pathways related to lifespan are complex and involve molecular, cellular, and environmental processes. In this analytical observational study, we evaluated the relationship between environment factors, oxidative stress status, DNA integrity level, and the association of FOXO3 (rs2802292), SOD2 (rs4880), APOE (rs429358 and rs7412), and SIRT1 (rs2273773) polymorphisms with longevity in oldest-old individuals from southeastern Brazil. We found an association between the FOXO3 GG genotype and gender. While lifestyle, anthropometric, and biochemical characteristics showed significant results, DNA damage and oxidative stress were not related to lifespan. We found that long-lived individuals with FOXO3 GT genotype had low levels of triglycerides. This study is the first to demonstrate that FOXO3 could be a candidate gene for longevity in the Brazilian population. These results are important in terms of provisions of health care for age-related diseases and lifespan, and provide insight for further research on epigenetic, gene regulation, and expression in oldest-old individuals.
Financial Risk and Returns Prediction with Modular Networked Learning

An artificial agent for financial risk and returns' prediction is built with a modular cognitive system comprised of interconnected recurrent neural networks, such that the agent learns to predict the financial returns, and learns to predict the squared deviation around these predicted returns. These two expectations are used to build a volatility-sensitive interval prediction for financial returns, which is evaluated on three major financial indices and shown to be able to predict financial returns with higher than 80% success rate in interval prediction in both training and testing, raising into question the Efficient Market Hypothesis. The agent is introduced as an example of a class of artificial intelligent systems that are equipped with a Modular Networked Learning cognitive system, defined as an integrated networked system of machine learning modules, where each module constitutes a functional unit that is trained for a given specific task that solves a subproblem of a complex main problem expressed as a network of linked subproblems. In the case of neural networks, these systems function as a form of an "artificial brain", where each module is like a specialized brain region comprised of a neural network with a specific architecture.
Combined Speed and Current Terminal Sliding Mode Control With Nonlinear Disturbance Observer for PMSM Drive

A terminal sliding mode control (SMC) method based on nonlinear disturbance observer is investigated to realize the speed and the current tracking control for the permanent magnet synchronous motor (PMSM) drive system in this paper. The proposed method adopts the speed-current single-loop control structure instead of the traditional cascade control in the vector control of the PMSM. First, considering the nonlinear and the coupling characteristic, a single-loop terminal sliding mode controller is designed for PMSM drive system through feedback linearization technology. This method can make the motor speed and current reach the reference value in finite time, which can realize the fast transient response. Although the SMC is less sensitive to parameter uncertainties and external disturbance, it may produce a large switching gain, which may cause the undesired chattering. Meanwhile, the SMC cannot keep the property of invariance in the presence of unmatched uncertainties. Then, a nonlinear disturbance observer is proposed to the estimate the lump disturbance, which is used in the feed-forward compensation control. Thus, a composite control scheme is developed for the PMSM drive system. The results show that the motor control system based on the proposed method has good speed and current tracking performance and strong robustness.
Development and Validation of a Mental Wellbeing Scale in Singapore

With a total number of 3400 participants, a sequence of four studies in two waves of data collection, the present study identified the conceptualization and construction of a mental wellbeing scale in a modern Asian multi-ethnic community-Singapore. Study 1 consisted a series of interviews (N = 351), surveys (N = 161) and focus group discussions (N = 59) to examine the popular conceptualization and manifestation of the construct of mental wellbeing in Singapore. The multi-ethnic inputs were then categorized into popular categories to construct a prototype of the Singapore Mental Wellbeing (SMWEB) Scale. With a nationally representative sample of 741 participants, Study 2 found the internal reliability (α = .962, 30 items) and a strong construct validity of the SMWEB. EFA and CFA confirmed a five dimensional structure of the SMWEB: Asian Self-esteem, Social Intelligence, Emotional Intelligence, Resilience and Cognitive Efficacy. Each dimension is internally coherent and culturally meaningful. With an additional nationally representative sample of 2091 participants, Study 3 constructed a short form of the SMWEB, the SMWEB-S with high internal reliability (α = .932, 16 items) and strong construct validity. Using Sample 2 and the SMWEB-S, Study 4 further validated the SMWEB as a measure of mental wellbeing by testing two theoretical models: the multi-dimensional model of mental wellbeing and the two factor model of mental wellbeing versus mental disorders. Excellent fit indices were found with both models. Further, the SMWEB-S showed significant construct validity by significantly predicting the culturally sanctioned goal pursuits: personal income and education attainment.