Miracle-dz/UniFAR-FTUs huggingface dataset:
Short-Chain Fatty Acids as Bacterial Enterocytes and Therapeutic Target in Diabetes Mellitus Type 2

Diabetes mellitus is a disease with multiple gastrointestinal symptoms (diarrhea or constipation, abdominal pain, bloating) whose pathogenesis is multifactorial. The most important of these factors is the enteric nervous system, also known as the “second brain”; a part of the peripheral nervous system capable of functioning independently of the central nervous system. Modulation of the enteric nervous system can be done by short-chain fatty acids, which are bacterial metabolites of the intestinal microbiota. In addition, these acids provide multiple benefits in diabetes, particularly by stimulating glucagon-like peptide 1 and insulin secretion. However, it is not clear what type of nutraceuticals (probiotics, prebiotics, and alimentary supplements) can be used to increase the amount of short-chain fatty acids and achieve the beneficial effects in diabetes. Thus, even if several studies demonstrate that the gut microbiota modulates the activity of the ENS, and thus, may have a positive effect in diabetes, further studies are needed to underline this effect. This review outlines the most recent data regarding the involvement of SCFAs as a disease modifying agent in diabetes mellitus type 2. For an in-depth understanding of the modulation of gut dysbiosis with SCFAs in diabetes, we provide an overview of the interplay between gut microbiota and ENS.
The Effect of The Principal's Managerial Activities and Work Culture on the Work Climate and Job Satisfaction

This study aims to determine and analyze the effect of the principal's managerial activities and work culture on job satisfaction through the work climate. This research is a correlational research with a quantitative approach formulated into a path analysis model. The study population was 220 with 101 studies. The data collection was carried out using instruments consisting of the principal's managerial activities (33 items), work culture (34 items), work climate (24 items), job satisfaction (18 items) which had been tested for validity and reliability. Data analysis of this study used Path Analysis. The results of the study showed that there was an effect of the principal's managerial activities on job satisfaction, work culture on job satisfaction, work climate on job satisfaction, principal's managerial activities on the work climate, work culture on the work climate, principal's managerial activities on job satisfaction through the work climate, and work culture on job satisfaction through the work climate.
COVID-19 stressors and effects related to depression with American university students

ABSTRACT The present study reported data from the COVID-19 Well-Being Study to illustrate the impact of COVID-19-related stressors and effects on depression among 719 students at three public colleges within an urban University System in the Northeastern region of the US. Modified Poisson regression analyses showed that students who knew someone who died from COVID-19, students who reported severe to moderate disruption due to COVID-19 in physical health, emotional well-being, or ability to afford food, and students who reported having two or more COVID-19 stressors or two or more COVID-19 effects had a higher prevalence of reported depression.
Should Inflammatory Bowel Disease Clinicians Provide Their Patients with e-Health Resources? Patients' and Professionals' Perspectives

Introduction: The internet is emerging as a source of information for patients with inflammatory bowel disease (IBD). However, it is not always reliable and may cause anxiety. We aim to assess patients' information habits and patients' and professionals' perceptions of a national website integrated as an educational resource for the IBD unit. Methods: Patients aged 18–65 years, comfortable with the internet, and attending follow-ups at participating IBD units (March–June 2019) and their professionals were invited to evaluate a recommended website through an online survey. Results: Three hundred eighty-nine patients and 95 professionals completed the survey. The internet (n = 109; 27.4%) was the second preferred source of information after the health care team (n = 229; 57.5%). Eighty percent of patients searched the internet for information on their disease and 28.6% did so at least once a week (n = 114), especially newly diagnosed ones (<2 years). Patients valued a website recommended by their professional (n = 379; 95.2%) and endorsed by the National Working Group (n = 377; 94.7%). They would attend online educational initiatives on the website (n = 279; 70.1%) and complete periodical surveys to improve its usefulness (n = 338; 84.9%). According to IBD professionals, this type of website is the best patient source of supplementary information (n = 76; 80%) and they “prescribe” it to most patients (67.0 ± 25.2%), especially the newly diagnosed patients (52.7 ± 26.5%). It effectively integrates routine face-to-face education (n = 95; 100%). Conclusions: Patients of IBD units, especially newly diagnosed ones, appreciate a trusted e-Health resource to back up professional information. The favorable opinion of patients and professionals will allow its use in training interventions.
A Three-Stage Stochastic Framework for Smart Electric Vehicle Charging

As one of the most significant part of carbon neutralisation, the rapid growth of electric vehicle (EV) market in past few years has greatly expedited the transport electrification, which, however, has brought in new challenges to power system including isolated distribution network for commercial and industrial set up. Stochastic and complex EV behaviours would violate network permissible operation region and increase costs for system operators. To address these problems, a chance-constrained smart EV charging strategy in a DC microgrid (DCMG) supporting large office complex is proposed to minimize system cost from distribution network and fleet battery degradation cost from EVs providing ancillary service to the DCMG. When dealing with uncertainties from EVs, a Markov Chain Monte Carlo (MCMC) model is built to couple different parameters in load profiles and characterize the time series of likelihood of charging and discharging. A state-of-charge (SOC) space random walk method is then proposed to solve the resultant massive recursive probabilistic charging requirements. Based on that, a three-stage optimization framework is established to illustrate the work flow in system level. Numerical results verifying the effectiveness of the proposed method are also presented.
Expanding maps on sets which are almost invariant. Decay and chaos

Let A c RI be a bounded open set with finitely many connected components Aj and let T: A -+ RI be a smooth map with A c T(A). Assume that for each Aj, A c T'(Aj) for all m sufficiently large. We assume that T is "expansive", but we do not assume that T(A) = A. Hence for x E A, T'(x) may escape A as i increases. Let pb be a smooth measure on A (with infA dpo/dx > 0) and let x E A be chosen at random (using y0). Since T is "expansive" we may expect T'(x) to oscillate chaotically on A for a certain time and eventually escape A. For each measurable set E c A define &,(E) to be the conditional probability that T (x) E E given that x, T(x),. , Tm(x) are in A. We show that p& converges to a smooth measure IL which is independent of the choice of pb. One dimensional examples are stressed.
Genomic prediction of tocochromanols in exotic‐derived maize

Tocochromanols (vitamin E) are an essential part of the human diet. Plant products, including maize (Zea mays L.) grain, are the major dietary source of tocochromanols; therefore, breeding maize with higher vitamin content (biofortification) could improve human nutrition. Incorporating exotic germplasm in maize breeding for trait improvement including biofortification is a promising approach and an important research topic. However, information about genomic prediction of exotic‐derived lines using available training data from adapted germplasm is limited. In this study, genomic prediction was systematically investigated for nine tocochromanol traits within both an adapted (Ames Diversity Panel [AP]) and an exotic‐derived (Backcrossed Germplasm Enhancement of Maize [BGEM]) maize population. Although prediction accuracies up to 0.79 were achieved using genomic best linear unbiased prediction (gBLUP) when predicting within each population, genomic prediction of BGEM based on an AP training set resulted in low prediction accuracies. Optimal training population (OTP) design methods fast and unique representative subset selection (FURS), maximization of connectedness and diversity (MaxCD), and partitioning around medoids (PAM) were adapted for inbreds and, along with the methods mean coefficient of determination (CDmean) and mean prediction error variance (PEVmean), often improved prediction accuracies compared with random training sets of the same size. When applied to the combined population, OTP designs enabled successful prediction of the rest of the exotic‐derived population. Our findings highlight the importance of leveraging genotype data in training set design to efficiently incorporate new exotic germplasm into a plant breeding program.
Goodness of fit tests in models for life history data based on cumulative hazard rates

To check the validity of an assumed parametric model for survival data, one may compare Â(t), the nonparametric Nelson-Aalen plot of the cumulative hazard rate, with A(t, θˇ), the estimated parametric cumulative hazard rate, θˇ being for example the maximum likelihood estimator. Convergence in distribution of √n(Â(t)-A(t,θˇ)) and more general processes is studied, employing the general framework of counting processes, which allows for quite general models for life history data and for quite general censoring schemes. The results are applied to the construction of χ 2 -type statistics for goodness of fit. Cramer-von Mises and Kolmogorov-Smirnov type tests are presented in the case where the unknown parameter is one-dimensional
Investigation of the structure of ferroelectric domain boundaries by transmission electron microscopy

A transmission electron microscopy investigation has been conducted on the structure of 90° and 180° domain boundaries in polycrystalline BaTiO3. When such boundaries were imaged with a continuous set of lattice planes, fringes were observed, indicating a stacking‐fault‐type displacement of the crystal lattices on either side of the boundaries. For a 90° domain boundary, this displacement most likely consists of both a dilatation and shear of {110} planes parallel to the boundary plane. The displacement for a 180° boundary lies approximately parallel to [101] and is of a greater magnitude. Structural models of both types of boundaries are derived from the observed displacements. The models suggest a distortion of the crystal structure in the boundary region. This distortion allows the polarization vector to simultaneously rotate and decrease in magnitude to zero at the center of the boundary, resulting in the required 90° or 180° rotation of the vector. The presence of the displacement associated with the 180° boundary suggests a substantial boundary thickness, in contradiction to previous models.
Looking Towards 2030: Strengthening the Environmental Health in Childhood–Adolescent Cancer Survivor Programs

Childhood and adolescent cancer survivors (CACS) are a high-risk population for non-communicable diseases and secondary carcinogenesis. The Environmental and Community Health Program for Longitudinal Follow-up of CACS in the region of Murcia, Spain, is an ongoing pioneering program that constitutes a model for social innovation. This study aims to present the program tools and protocol as a whole, as well as a profile of the incidence, survival, and spatiotemporal distribution of childhood cancer in the region of Murcia, Spain, using 822 sample cases of cancer diagnosed in children under 15 years of age (1998–2020). While the crude incidence rate across that entire period was 149.6 per 1 million, there was an increase over that time in the incidence. The areas with a higher standardized incidence ratio have shifted from the northwest (1998-2003) to the southeast (2016–2020) region. Overall, the ten-year survival rate for all tumor types was 80.1% over the entire period, increasing the five-year survival rate from 76.1 (1998–2003) to 85.5 (2014–2018). CACS living in areas with very poor outdoor air quality had lower survival rates. Furthermore, integrating environmental health into clinical practice could improve knowledge of the etiology and prognosis, as well as the outcomes of CACS. Finally, monitoring individual carbon footprints and creating healthier lifestyles, alongside healthier environments for CACS, could promote wellbeing, environmental awareness, and empowerment in order to attain Sustainable Development Goals for non-communicable diseases in this population.
The performance of covariance selection methods that consider decomposable models only.

We consider the behavior of Bayesian procedures that perform model selection for decomposable Gaussian graphical models when the true model is in fact non-decomposable. We examine the asymptotic behavior of the posterior when models are misspecified in this way, and find that the posterior will converge to graphical structures that are minimal triangulations of the true structure. The marginal log likelihood ratio comparing different minimal triangulations is stochastically bounded, and appears to remain data dependent regardless of the sample size. The covariance matrices corresponding to the different minimal triangulations are essentially equivalent, so model averaging is of minimal benefit. Using simulated data sets and a particular high performing Bayesian method for fitting decomposable models, feature inclusion stochastic search, we illustrate that these predictions are borne out in practice. Finally, a comparison is made to penalized likelihood methods for graphical models, which make no decomposability restriction. Despite its inability to fit the true model, feature inclusion stochastic search produces models that are competitive or superior to the penalized likelihood methods, especially at higher dimensions.
Construction of a Fab Library Merging Chains from Semisynthetic and Immune Origin, Suitable for Developing New Tools for Gluten Immunodetection in Food

The observed increase in the prevalence of gluten-related disorders has prompted the development of novel immunological systems for gluten detection in foodstuff. The innovation on these methods relies on the generation of new antibodies, which might alternatively be obtained by molecular evolution methods such as phage display. This work presents a novel approach for the generation of a Fab library by merging semi-synthetic heavy chains built-up from a pre-existent recombinant antibody fragment (dAb8E) with an immune light chain set derived from celiac donors. From the initial phage population (107 candidates) and after three rounds of selection and amplification, four different clones were isolated for further characterization. The phage Fab8E-4 presented the best features to be applied in an indirect ELISA for the detection of gluten in foods, resulting in improved specificity and sensitivity.
The CH Stars. III. Heavy Element Abundances

The s-process abundances in seven CH giants have been derived. Large enhancement of s-process elements relative to solar values are found, [s/Fe]=+1.0 to +2.0. In addition, the heavy s-process peak elements (Ba through Sm) are relatively more enhanced than the light s-process peak elements (Sr,Y,Zr), the average ratio of heavy-to-light s-process elements in the CH stars is +0.9 dex. In addition, the abundance patterns are best fit by models in which seed nuclei are exposed to a single neutron irradiation instead of an exponentially decaying distribution of neutron exposures
An Analysis of Health Perceptions and Performance in Elementary Students in Korea during the ongoing COVID-19 Pandemic

During the coronavirus disease 2019 (COVID-19) pandemic, social distancing guidelines changed lifestyles, including increased sedentary time, physical inactivity, and disrupted sleep patterns among children. The purpose of the present study is to analyze the health awareness (mental health, disease, physical activity, sleep, eating habit, and hygiene health management) of elementary school students during the COVID-19 pandemic, and use the importance-performance analysis (IPA) technique to identify gender differences in health perceptions. We collected data on 1006 students, which was analyzed using frequency analysis, reliability testing, independent sample t-tests, and importance-performance analysis (IPA). A median importance value of 0.163 and a median performance value of 4.048 were selected as cross points to distribute the IPA matrix into four quadrants. The highest performance was given for wearing a mask and sanitary practice; the IPA matrix indicated that the sense of belonging, happiness, trust, and movement activity were located in quadrant I. Children’s regular physical activity and level of physical activity were low, especially that of girls. Children’s sleep management was poor. Their physical activity and sleep-related factors must be improved under the facilitation of the national government, public education institutions, and families.
Evaluation Approach for Efficient Countermeasure Techniques Against Denial-of-Service Attack on MPSoC-Based IoT Using Multi-Criteria Decision-Making

Context: Denial-of-Service Attack countermeasure techniques (DoS A-CTs) evaluation is a Multi-criteria decision-making (MCDM) problem based on different MPSoCs of IoT platform design, performance, and design overhead. Therefore, the Fermatean by fuzzy decision opinion score method (F-FDOSM) for prioritizing the powerful countermeasure technique against Denial-of-Service (DoS) attack is the best approach because it employs the most efficient MCDM ranking technique. Nonetheless, the FDOSM method needs to weight the criteria before being submitted for the ranking process. In order to address this theoretical challenge, the Criteria-importance through inter-criteria correlation (CRITIC) technique can be applied as an effective MCDM weighting technique to offer an explicit weight for a set of criteria with no inconsistency based on the standard deviation, which uses correlation analysis to determine the relevance of each criterion. Objectives: This research proposes a Fermatean-FDOSM framework for evaluating DoS A-CTs in the context of MPSoCs-based IoT and CRITIC techniques to weight the criteria. Methods: The methodology is presented in three phases. Firstly, a proposed countermeasure techniques dataset was collected that included eighteen defense approaches (e.g., Sniffer, SeRA, and RLAN) based on thirteen criteria (e.g., size, power, latency, and effectiveness…etc.). Then, the Decision matrix (DM) was built based on an intersection of the countermeasure techniques as an alternative and MPSoC design and performance criteria. Then, the multi-criteria decision-making methods were integrated. The CRITIC method for criteria weighting was followed by the development of the Fermatean-FDOSM method for ranking. Results: (1) CRITIC weighting shows that MPSoC NoC Routing Algorithm (XY and YX) is the highest weight criterion, whereas latency (clock/cycle) is the less weight criterion. (2) The Fermatean-FDOSM-based group ranking shows that the Collision Point Router Detection (CPRD) countermeasure technique is the first-ranked alternative compared to the Secure Model Checkers (SMCs) approach. (3) The DoS A-CTs priority ranks were subjected to a systematic ranking that was confirmed by solid correlation results throughout thirteen criterion weight values. A comparison with recent studies confirmed the feasibility of the proposed framework. Conclusion: The results of this research are expected to provide a specific understanding and guide for those who want to engage in MPSoCs-based IoT and NoC communication security research with decision theory.
Coaching Leadership and Employees’ Deviant Innovation Behavior: Mediation and Chain Mediation of Interactional Justice and Organizational Identification

Purpose Previous studies are based on social exchange theory to explore the influence of leadership style on employees’ deviant innovation behavior. However, deviant innovation is risky, not supported by the organization, and is expected to benefit the long-term development of the organization. The key to the problem lies in how to guide employees to think and solve problems from the perspective of the organization, instead of just relying on material or spiritual exchange and return. Therefore, the purpose of this study was to analyze the relationship between coaching leadership, interactional justice, organizational identification and employees’ deviant innovation from the perspective of changing cognition. Methods This work surveyed employees in 26 Chinese enterprises in more than 10 regions. Questionnaires were distributed to 450 employees, the first round of survey mainly investigated demographic information of employees and coaching leadership style of supervisors, and the second round of survey mainly investigated employees’ organizational identification, interactional justice, and deviant innovation behavior. By tracking and matching, 340 valid questionnaires were finally obtained. Spss 22.0 was used to describe all the study variables; Mplus 7.0 is used to carry out a confirmatory factor analysis and a multi-path regression model. Results According to self-categorization theory, the results demonstrated that coaching leadership can directly or indirectly promote employees’ deviant innovation behavior through the dual-path intermediary and chain intermediary of interactional fairness and organizational identification. Conclusion Under the open situation created by coaching leadership, coaching leaders will interact and communicate sincerely with employees, and employees’ cognition will change. The original “I” of employees will be transformed into “big self” with organizational membership, which will guide employees to show behaviors beneficial to the organization. Therefore, interactional justice and organizational identification can play a key role of the influence of coaching leadership on employees’ deviant innovation behavior.
Theory of a Finite Difference Method on Irregular Networks

A new theory is presented for the approximation of second order elliptic Dirichlet boundary value problems by a well-known finite difference scheme on irregular networks which cannot be handled by the finite element theory. Adequate regularity conditions are imposed on the network, a finite difference scheme is set up, and the convergence of its solution towards the solution of the continuous boundary value problems is established, as well as a bound for the discretization error. A numerical example illustrates the theory.
Supporting teachers’ effective classroom and behavior management: what do teachers tell us?

Abstract Elementary teachers (N = 160) from two districts responded to survey questions about inservice professional development and administrator feedback and support for implementing research-based, effective classroom and behavior management (C/BM) strategies. Results indicated slightly more than half (55%) of teachers reported their participation in formal, inservice professional development activities improved their ability to implement research-based C/BM strategies. A higher percentage (77%) of teachers reported they receive adequate feedback from their current school supervisor (e.g., principal, curriculum/instructional coach) on their use of C/BM. Teachers’ reported specific ways for school and district administrators to better prepare and support them for challenges related to C/BM. Implications are provided for improving inservice professional development and administrator feedback to promote teachers’ use of effective classroom and behavior management practices.