Miracle-dz/UniFAR-FTUs huggingface dataset:
Dysfunctional Brain Reward System in Child Obesity.

Eating habits leading to obesity may reflect nonhomeostatic behavior based on excessive immediate-reward seeking. However, it is currently unknown to what extent excess weight is associated with functional alterations in the brain's reward system in children. We tested the integrity of reward circuits using resting-state functional connectivity magnetic resonance imaging in a population of 230 children aged 8-12 years. The major components of the reward system were identified within the ventral striatum network defined on the basis of the nucleus accumbens connectivity pattern. The functional structure of the cerebral cortex was characterized using a combination of local functional connectivity measures. Higher body mass index was associated with weaker connectivity between the cortical and subcortical elements of the reward system, and enhanced the integration of the sensorimotor cortex to superior parietal areas relevant to body image formation. Obese children, unlike WHO-defined overweight condition, showed functional structure alterations in the orbitofrontal cortex and amygdala region similar to those previously observed in primary obsessive-compulsive disorder and Prader-Willi syndrome associated with obsessive eating behavior. Results further support the view that childhood obesity is not simply a deviant habit with restricted physical health consequences but is associated with reward system dysfunction characterizing behavioral control disorders.
Automated caries detection with smartphone color photography using machine learning

Untreated caries is significant problem that affected billion people over the world. Therefore, the appropriate method and accuracy of caries detection in clinical decision-making in dental practices as well as in oral epidemiology or caries research, are required urgently. The aim of this study was to introduce a computational algorithm that can automate recognize carious lesions on tooth occlusal surfaces in smartphone images according to International Caries Detection and Assessment System (ICDAS). From a group of extracted teeth, 620 unrestored molars/premolars were photographed using smartphone. The obtained images were evaluated for caries diagnosis with the ICDAS II codes, and were labeled into three classes: “No Surface Change” (NSC); “Visually Non-Cavitated” (VNC); “Cavitated” (C). Then, a two steps detection scheme using Support Vector Machine (SVM) has been proposed: “C versus (VNC + NSC)” classification, and “VNC versus NSC” classification. The accuracy, sensitivity, and specificity of best model were 92.37%, 88.1%, and 96.6% for “C versus (VNC + NSC),” whereas they were 83.33%, 82.2%, and 66.7% for “VNC versus NSC. ” Although the proposed SVM system required further improvement and verification, with the data only imaged from the smartphone, it performed an auspicious potential for clinical diagnostics with reasonable accuracy and minimal cost.
Genome-wide analysis of lncRNA stability in human

Transcript stability is associated with many biological processes, and the factors affecting mRNA stability have been extensively studied. However, little is known about the features related to human long noncoding RNA (lncRNA) stability. By inhibiting transcription and collecting samples in 10 time points, genome-wide RNA-seq studies was performed in human lung adenocarcinoma cells (A549) and RNA half-life datasets were constructed. The following observations were obtained. First, the half-life distributions of both lncRNAs and messanger RNAs (mRNAs) with one exon (lnc-human1 and m-human1) were significantly different from those of both lncRNAs and mRNAs with more than one exon (lnc-human2 and m-human2). Furthermore, some factors such as full-length transcript secondary structures played a contrary role in lnc-human1 and m-human2. Second, through the half-life comparisons of nucleus- and cytoplasm-specific and common lncRNAs and mRNAs, lncRNAs (mRNAs) in the nucleus were found to be less stable than those in the cytoplasm, which was derived from transcripts themselves rather than cellular location. Third, kmers-based protein−RNA or RNA−RNA interactions promoted lncRNA stability from lnc-human1 and decreased mRNA stability from m-human2 with high probability. Finally, through applying deep learning−based regression, a non-linear relationship was found to exist between the half-lives of lncRNAs (mRNAs) and related factors. The present study established lncRNA and mRNA half-life regulation networks in the A549 cell line and shed new light on the degradation behaviors of both lncRNAs and mRNAs.
A brain-actuated robotic arm system using non-invasive hybrid brain–computer interface and shared control strategy

Objective. The electroencephalography (EEG)-based brain–computer interfaces (BCIs) have been used in the control of robotic arms. The performance of non-invasive BCIs may not be satisfactory due to the poor quality of EEG signals, so the shared control strategies were tried as an alternative solution. However, most of the existing shared control methods set the arbitration rules manually, which highly depended on the specific tasks and developer’s experience. In this study, we proposed a novel shared control model that automatically optimized the control commands in a dynamical way based on the context in real-time control. Besides, we employed the hybrid BCI to better allocate commands with multiple functions. The system allowed non-invasive BCI users to manipulate a robotic arm moving in a three-dimensional (3D) space and complete a pick-place task of multiple objects. Approach. Taking the scene information obtained by computer vision as a knowledge base, a machine agent was designed to infer the user’s intention and generate automatic commands. Based on the inference confidence and user’s characteristic, the proposed shared control model fused the machine autonomy and human intention dynamically for robotic arm motion optimization during the online control. In addition, we introduced a hybrid BCI scheme that applied steady-state visual evoked potentials and motor imagery to the divided primary and secondary BCI interfaces to better allocate the BCI resources (e.g. decoding computing power, screen occupation) and realize the multi-dimensional control of the robotic arm. Main results. Eleven subjects participated in the online experiments of picking and placing five objects that scattered at different positions in a 3D workspace. The results showed that most of the subjects could control the robotic arm to complete accurate and robust picking task with an average success rate of approximately 85% under the shared control strategy, while the average success rate of placing task controlled by pure BCI was 50% approximately. Significance. In this paper, we proposed a novel shared controller for motion automatic optimization, together with a hybrid BCI control scheme that allocated paradigms according to the importance of commands to realize multi-dimensional and effective control of a robotic arm. Our study indicated that the shared control strategy with hybrid BCI could greatly improve the performance of the brain-actuated robotic arm system.
Rules of nature’s Formula Run: Muscle mechanics during late stance is the key to explaining maximum running speed

The maximum running speed of legged animals is one evident factor for evolutionary selection—for predators and prey. Therefore, it has been studied across the entire size range of animals, from the smallest mites to the largest elephants, and even beyond to extinct dinosaurs. A recent analysis of the relation between animal mass (size) and maximum running speed showed that there seems to be an optimal range of body masses in which the highest terrestrial running speeds occur. However, the conclusion drawn from that analysis—namely, that maximum speed is limited by the fatigue of white muscle fibres in the acceleration of the body mass to some theoretically possible maximum speed—was based on coarse reasoning on metabolic grounds, which neglected important biomechanical factors and basic muscle-metabolic parameters. Here, we propose a generic biomechanical model to investigate the allometry of the maximum speed of legged running. The model incorporates biomechanically important concepts: the ground reaction force being counteracted by air drag, the leg with its gearing of both a muscle into a leg length change and the muscle into the ground reaction force, as well as the maximum muscle contraction velocity, which includes muscle-tendon dynamics, and the muscle inertia—with all of them scaling with body mass. Put together, these concepts’ characteristics and their interactions provide a mechanistic explanation for the allometry of maximum legged running speed. This accompanies the offering of an explanation for the empirically found, overall maximum in speed: In animals bigger than a cheetah or pronghorn, the time that any leg-extending muscle needs to settle, starting from being isometric at about midstance, at the concentric contraction speed required for running at highest speeds becomes too long to be attainable within the time period of a leg moving from midstance to lift-off. Based on our biomechanical model we, thus, suggest considering the overall speed maximum to indicate muscle inertia being functionally significant in animal locomotion. Furthermore, the model renders possible insights into biological design principles such as differences in the leg concept between cats and spiders, and the relevance of multi-leg (mammals: four, insects: six, spiders: eight) body designs and emerging gaits. Moreover, we expose a completely new consideration regarding the muscles’ metabolic energy consumption, both during acceleration to maximum speed and in steady-state locomotion.
Vascularized Microfluidics and Their Untapped Potential for Discovery in Diseases of the Microvasculature

Microengineering advances have enabled the development of perfusable, endothelialized models of the microvasculature that recapitulate the unique biological and biophysical conditions of the microcirculation in vivo. Indeed, at that size scale (<100 μm)—where blood no longer behaves as a simple continuum fluid; blood cells approximate the size of the vessels themselves; and complex interactions among blood cells, plasma molecules, and the endothelium constantly ensue—vascularized microfluidics are ideal tools to investigate these microvascular phenomena. Moreover, perfusable, endothelialized microfluidics offer unique opportunities for investigating microvascular diseases by enabling systematic dissection of both the blood and vascular components of the pathophysiology at hand. We review (a) the state of the art in microvascular devices and (b) the myriad of microvascular diseases and pressing challenges. The engineering community has unique opportunities to innovate with new microvascular devices and to partner with biomedical researchers to usher in a new era of understanding and discovery of microvascular diseases.
IL-27/IL-27R Mediates Protective Immunity against Chlamydial Infection by Suppressing Excessive Th17 Responses and Reducing Neutrophil Inflammation

Key Points IL-27/IL-27R promotes host defense against Chlamydia muridarum respiratory infection. IL-27/IL-27R suppresses the Th17 cell response in Chlamydia muridarum respiratory infection. IL-27/IL-27R suppresses neutrophil infiltration in Chlamydia muridarum respiratory infection. Visual Abstract IL-27, a heterodimeric cytokine of the IL-12 family, has diverse influences on the development of multiple inflammatory diseases. In this study, we identified the protective role of IL-27/IL-27R in host defense against Chlamydia muridarum respiratory infection and further investigated the immunological mechanism. Our results showed that IL-27 was involved in C. muridarum infection and that IL-27R knockout mice (WSX-1–/– mice) suffered more severe disease, with greater body weight loss, higher chlamydial loads, and more severe inflammatory reactions in the lungs than C57BL/6 wild-type mice. There were excessive IL-17–producing CD4+ T cells and many more neutrophils, neutrophil-related proteins, cytokines, and chemokines in the lungs of WSX-1–/– mice than in wild-type mice following C. muridarum infection. In addition, IL-17/IL-17A–blocking Ab treatment improved disease after C. muridarum infection in WSX-1–/– mice. Overall, we conclude that IL-27/IL-27R mediates protective immunity during chlamydial respiratory infection in mice by suppressing excessive Th17 responses and reducing neutrophil inflammation.
To Share or Hide? A Social Network Approach to Understanding Knowledge Sharing and Hiding in Organizational Work Teams

Although knowledge sharing is almost ubiquitously promoted in today’s organizations, knowledge hiding is still prevalent. Extending transactive memory systems (TMS) theory and the dialectical tension model, this study employs a social network approach to empirically examine how knowledge sharing is related to knowledge hiding, and how work and social relationships are related to knowledge sharing and hiding in organizational work teams. Whole-network survey data were collected from 200 employees in 31 organizational work teams across the U.S. and China. Exponential random graph modeling (ERGM) analyses of these network data show that knowledge sharing is not significantly related to knowledge hiding. Moreover, while work relationships such as work-related communication and task interdependence are positively related to knowledge sharing, social relationships such as interpersonal justice, social communication, and trust are negatively related to knowledge hiding. These findings validate the dialectical tension model by revealing a co-existent relationship between knowledge sharing and hiding, and endorse the critical role of work-related and social communication in TMS development.
“Because I said so!”: Mothers’ conventional conflict justifications related to resolution and child behavior problems and temperamental reactivity

A common strategy parents use to justify their point of view during parent–child conflict is conventional reasoning, which focuses on child obedience to authority. In this brief report, we examined mothers’ use of conventional justification during mother–child conflict discussions in relation to the resolution reached and children’s behavior problems and temperamental reactivity concurrently and longitudinally. Participants included 190 mothers and their 5- to 7-year-old children. Dyads engaged in a conflict discussion task in the laboratory, which was coded for mothers’ use of conventional justification and the type of resolution reached. Mothers reported on child behavior problems and temperamental reactivity then and 1 year later. Results showed mothers used more conventional reasoning during conflict discussions that resulted in a win/loss resolution compared to a compromise. Mothers’ conventional reasoning was concurrently associated with more child externalizing behaviors and temperamental reactivity at Year 1. Mothers’ conventional reasoning did not relate to changes in child behaviors over time. Findings are discussed in terms of mothers’ conceptions of parental authority and possible directions of effects.
EXPLORATION THE IMPACT OF THE CONVERSION PROCESS OF BRI TO BRI SYARIAH ON THE EFFECT OF COMPENSATION ON JOB SATISFACTION AND WORK MOTIVATION AND ITS IMPACT ON EMPLOYEE PERFORMANCE OF BRIREGIONAL OFFICE OF BANDA ACEH

This study intends to examine the Exploration of the Impact of the BRI to BRI Syariah (BRIS) Conversion Process on the Effect of Compensation on Job Satisfaction and Work Motivation and Its Impact on Employee Performance of BRI Regional Office of Banda Aceh. The population determined in this research was all BRI employees at the Aceh Regional Office totaling 530 employees. To facilitate the process of taking a relevant sample, the Simple Random Sampling technique was used. The sample was taken from 11 branches, one regional office, and one audit office throughout Aceh, 11 people were taken from each office so that the number of the sample used was 13 offices x 11 employees = 143 people. Data were analyzed using Structural Equation Modeling (SEM) with the help of Amos software. The results of the research found that, directly, the three factors, namely compensation, job satisfaction, and work motivation have a significant impact on employee performance. The impact of compensation on job satisfaction and motivation is also known to be significant, and satisfaction has a significant impact on work motivation. Furthermore, job satisfaction and work motivation have become a significant mediator on the effect of compensation on employee performance. Meanwhile, the BRIS (Organizational Change) conversion moderates significantly the relationship between compensation and job satisfaction, work motivation, and employee performance. This research provides an implementation that organizational change can work well when employee compensation is better or following the previous one so that job satisfaction and work motivation can be maintained or increased and in the end organizational changes can improve employee performance. The novelty of this research lies in the model that was built by testing the moderating effect of the relationships formed to provide a more complete justification for the impact of conversion in the world of Islamic banking. Future researchers should be able to develop this tested research model by adding variables such as employee turnover and organizational support. Keyword: Compensation, Job Satisfaction, Work Motivation, Employee Performance, Conversion.
Investigating the effect of conservatism on abnormal returns at the portfolio level

The purpose of this study is to investigate the effect of conservatism on stock abnormal returns at the portfolio level. Earnings that often consist of accruals do not persist in future periods, knowing that investors not paying attention to less persistence of accruals, which causes a negative relationship between accruals and future abnormal returns. On the other hand, conservatism is the asymmetrical verification requirements for gains and losses. Greater degree of verification required for gains versus losses. Hence expected increase in conservatism led to increase earnings persistence and reduce abnormal returns. To examine the issue, hedge portfolios formed by assigning stocks into quartiles by using a dual sorting based on their magnitude of annual deflated accruals then degrees of conservatism quartiles within each accrual quartile. For 208 companies (4*4 portfolios per year) during the years 2011-2018 the abnormal returns of the portfolios were calculated and compared using spss.26 software. The results showed that the return of a hedge portfolio that is long in low accrual quartile and short in high accrual quartile firms that also have a lower overall degree of conservatism is greater than the returns of a similar hedge portfolio that invests in higher overall degree of conservatism
Adoption of Clay Charcoal Briquetting to Curb Deforestation and the Impacts of Covid-19 Pandemic in Rural Areas, Kenya

Wood fuel is the principal source of energy in Kenya and contributes to more than 17% of the global deforestation. Saving on the amount of charcoal used at home will not only help save on cost that can be used to offset the economic burden caused by the impacts of COVID-19 pandemic but also control deforestation. This will foster the realization of more than10% tree cover in Kenya by 2022 as per the presidential directive of 2019, Kenya Vision 2030 and the Constitution of Kenya 2010. This study aimed at promoting this goal by encouraging adoption of charcoal briquettes made from clay soil as a binder, charcoal dust and charcoal pellets as raw materials and ignited by pure charcoal (PC) to produce energy to form Clay Charcoal Blend Briquettes (CCBB). The study compared the amount of energy consumed by a household of five people using CCBB and PC. The results were: adoption of CCBB reduced the amount of charcoal used by 1.025kg per day, 21.325kg per week, 92.25kg per month and 1,122.375kg per year. This would save hundreds of trees from destruction. Additionally, using CCBB saved a household Ksh.45 (0.41USD) a day, Ksh. 945 (8.59 USD) a week, Ksh. 4,050 (36.82 USD) a month and Ksh. 49,275 (447.95 USD) a year as compared to using PC. The study therefore encouraged for adoption of CCBB concept.
Effects of Tennis Match-induced Fatigue on Serve Performance in College Tennis Team Players

The aim of this study was to determine whether fatigue induced by a match-like protocol could impose a negative impact on tennis service accuracy and speed. Participants (N=8) served balls in both rested and after match-like protocol conditions. The result indicated that the match-like protocol did not influence both the service accuracy (.785, p<.05) and speed (-.487, p<.05). It was concluded that the match inducted fatigue may not influence the speed and accuracy of the tennis serve, at least on the male college team players. Further study should be conducted by including more participants with varying tennis playing levels or experiences. Female tennis players should be included in future studies to explore if fatigue affects gender differently.
PREDICTIVE MODELLING AND ANALYTICS FOR DIABETES USING A MACHINE LEARNING APPROACH

Adverse effects can be seen in the entire body due to the major disorders known as Diabetes. The risk of dangers like diabetic nephropathy, cardiac stroke and other disorders can increase severally because of the undiagnosed diabetes. Around the globe the people are suffering from this disease. For a healthy life early detection of this disease is very curtail. As the causes of the diabetes is increasing rapidly this disease might turn up as a reason for worldwide concern. Increasing the chances for a more accurate predictions and form experiences automatic learning by computational method may be provided by Machine Learning (ML). With the help of R data manipulation tool for trends development and with risk factor patterns detection in Pima Indian diabetes technique of machine learning is been used in the current researches. With the use of R data manipulation tool analysis and development five different predictive models is done for the categorization of patients into diabetic and non- diabetic. supervised machine learning algorithms namely multifactor dimensionality reduction (MDR), k-nearest neighbor (k-NN), artificial neural network (ANN) radial basis function (RBF) kernel support vector machine and linear kernel support vector machine (SVM-linear) are used for this purpose.
Controllable arrangement of integrated obstacles in silicon microchannels etched in 25 wt.% TMAX

In this paper, fabrication of silicon microchannels with integrated obstacles by using 25 wt % tetramethylammonium hydroxide (TMAH) aqueous solution at the temperature of 80 o C is presented and analysed. We studied basic island patterns, which present union of two symmetrical parallelograms with the sides along predetermined crystallographic directions (2 . Acute angles of the parallelograms were smaller than 45 o . We have derived analytical relations for determining dimensions of the integrated obstacles. The developed etching technique provides reduction of the distance between the obstacles. Before the experiments, we performed simulations of pattern etching based on the level set method and presented evolution of the etched basic patterns for the predetermined crystallographic directions . Combination of basic patterns with sides along the and crystallographic directions is used to fabricate a matrix of two row of silicon obstacles in a microchannel. We obtained a good agreement between the experimental results and simulations. Our results enable simple and cost-effective fabrication of various complex microfluidic silicon platforms with integrated obstacles.