Miracle-dz/UniFAR-FTUs huggingface dataset:
Sex-Specific Cut-Offs of Single Point Insulin Sensitivity Estimator (SPISE) in Predicting Metabolic Syndrome in the Arab Adolescents

The Single Point Insulin Sensitivity Estimator (SPISE) is a novel surrogate marker for insulin sensitivity and was found comparable to the gold standard clamp test as well as for predicting the Metabolic Syndrome (MetS) in several populations. The present study aimed to assess for the first time, the validity of SPISE in predicting MetS among Arab adolescents. In this cross-sectional study, 951 Saudi adolescents aged 10–17 years were randomly recruited from different schools across Riyadh, Saudi Arabia. Anthropometrics were measured and fasting blood samples were collected for the assessment of glucose, lipid profile, adipokines, C-reactive protein and 25 hydroxyvitamin (OH) D. MetS was defined using the National Cholesterol Education Program’s (NCEP) criteria with age-specific thresholds for adolescents. The SPISE as well as insulin resistance (HOMA-IR) indices were calculated. The over-all prevalence of MetS was 8.6% (82 out of 951). SPISE index was significantly lower in MetS than non-MetS participants in both sexes (5.5 ± 2.5 vs. 9.4 ± 3.2, p < 0.001 in boys and 4.4 ± 1.4 vs. 8.6 ± 3.2, p < 0.001 in girls). The SPISE index showed a significant inverse correlation with resistin, leptin, and C-reactive protein, and a significant positive correlation with adiponectin and 25(OH) D. Areas under the curve (AUC) revealed fair and good accuracy for predicting MetS 84.1% and 90.3% in boys and girls, respectively. The sex-specific cut-off proposed was SPISE index ≤6.1 (sensitivity 72.2% and specificity 83.9%) for boys and ≤6.46 (sensitivity 96.3% and specificity 73.4%), for girls. This study suggests that the SPISE index is a simple and promising diagnostic marker of insulin sensitivity and MetS in Arab adolescents.
Exercise Boundary Near Maturity for an American Option on Several Assets

We consider an American put option on a linear function of d dividend-paying assets. The value function of this option is given as the solution of a free boundary problem. When d = 1, the behavior of the free boundary near the maturity of the option is well known. In this article, we extend to the case d > 1 the study of the free boundary near maturity. A parameterization of the stopping region at time t is given. That enables us to define and give a convergence rate for this region when t goes to the maturity.
A Biodegradable Bioactive Glass-Based Hydration Sensor for Biomedical Applications

Monitoring changes in edema-associated intracranial pressure that complicates trauma or surgery would lead to improved outcomes. Implantable pressure sensors have been explored, but these sensors require post-surgical removal, leading to the risk of injury to brain tissue. The use of biodegradable implantable sensors would help to eliminate this risk. Here, we demonstrate a bioactive glass (BaG)-based hydration sensor. Fluorine (CaF2) containing BaG (BaG-F) was produced by adding 5, 10 or 20 wt. % of CaF2 to a BaG matrix using a melting manufacturing technique. The structure, morphology and electrical properties of the resulting constructs were evaluated to understand the physical and electrical behaviors of this BaG-based sensor. Synthesis process for the production of the BaG-F-based sensor was validated by assessing the structural and electrical properties. The structure was observed to be amorphous and dense, the porosity decreased and grain size increased with increasing CaF2 content in the BaG matrix. We demonstrated that this BaG-F chemical composition is highly sensitive to hydration, and that the electrical sensitivity (resistive–capacitive) is induced by hydration and reversed by dehydration. These properties make BaG-F suitable for use as a humidity sensor to monitor brain edema and, consequently, provide an alert for increased intracranial pressure.
Special solutions of the Toda chain and combinatorial numbers

We classify all solutions of the restricted Toda chain from the ansatz that all moments are expressed in terms of polynomials of some variable. We show that each such solution corresponds to the Sheffer class orthogonal polynomials. It is shown that corresponding Hankel determinants are related to some well-known combinatorial numbers.
Microbiome and Metabolome Variation as Indicator of Social Stress in Female Prairie Voles

Social isolation is detrimental to the health of social mammals inducing neurochemical and hormonal changes related to depression and anxiety, as well as impairments of cardiovascular and immune functioning. Likewise, perceptions of loneliness are increasingly recognized as detrimental to human psychological well-being, cognitive functioning, and physical health. Few studies, however, have examined the impact of social isolation on the intestinal microbiome and metabolome. To better understand the impact of social isolation on these systems, intestinal microbiota, and the systemic impact via the gut–brain axis, we employed prairie voles. Physiological stress on female prairie voles (n = 22) either with a same-sex sibling (n = 11) or in isolation (n = 11) for four weeks demonstrated behavioral indicators of increased anxiety and depression in isolated voles (p ≤ 0.01). Bacterial DNA from fecal and colon samples, collected at five time points (T0–4), were sequenced for all nine hypervariable regions of the 16S rRNA gene. Microbiome analyses revealed several differences in gut communities of paired and isolated voles with greater differences at T4. Notably, several taxa associated with host health including Anaerostipes and Lactobacillaceae were more prevalent in paired voles, whereas several taxa associated with known pathogens (e.g., Staphylococcaceae and Enterococcus) or disease were elevated in isolated animals. Similarly, metabolome analyses suggested isolated voles, when compared to paired animals, exhibited differences in metabolites associated with diabetes and colitis. These findings further contribute to our understanding of the harmful effects of social isolation, which cause perturbations in the gut microbiome and serum metabolites.
Generalized covariations, local time and Stratonovich Itô's formula for fractional Brownian motion with Hurst index H>=1/4

Given a locally bounded real function g, we examine the existence of a 4-covariation $[g(B^H), B^H, B^H, B^H]$, where $B^H$ is a fractional Brownian motion with a Hurst index $H \ge \tfrac{1}{4}$. We provide two essential applications. First, we relate the 4-covariation to one expression involving the derivative of local time, in the case $H = \tfrac{1}{4}$, generalizing an identity of Bouleau--Yor type, well known for the classical Brownian motion. A second application is an Ito formula of Stratonovich type for $f(B^H)$. The main difficulty comes from the fact $B^H$ has only a finite 4-variation.
Evaluation of Tree-Based Machine
Learning and Deep Learning Techniques
in Temperature-Based Potential
Evapotranspiration Prediction

In this study, Extreme Gradient Boosting (XGBoost), Gradient Boosting Machine (GBM), Random Forest (RF), Bagged Trees (BT), and Custom Deep Learning methods were used to estimate the potential evapotranspiration (PET) values at Diyarbakir airport station in the Tigris basin. In establishing the models, the average temperature, maximum temperature, minimum temperature, maximum wind speed, relative humidity, average wind speed, and total precipitation values in the monthly time period were chosen as inputs, and PET values were used as output. The data set is divided into 70% training and 30% testing. 10-fold cross-validation to avoid overfitting problems. Training and test data were randomly selected. The prediction performances of the models were evaluated according to the statistical criteria of determination coefficient (R 2 ), root mean square error (RMSE), mean absolute error (MAE), and rank analysis. The best PET estimates were obtained using the inputs of mean, min, maximum temperature, relative humidity, total precipitation, average, and maximum wind speed. It was also concluded that XGBoost was the highest performance. When the R 2 values were examined, it was seen that the Deep Learning model had higher performance. But for RMSE and MAE, XGBoost did better. As a result of the rank analysis, it was seen that XGBoost got a higher score.
The Interaction Between Age and Risk Factors for Diabetes and Prediabetes: A Community-Based Cross-Sectional Study

Objective This study aimed to investigate the interaction between age groups and risk factors for diabetes and prediabetes in Shanghai communities and to identify the effect of age on other risk factors for diabetes and prediabetes. Methods This study recruited 3540 participants with undiagnosed diabetes or prediabetes in 14 communities in Shanghai from February to August 2019. All participants underwent a comprehensive examination, including filling out a detailed questionnaire, physical examination, 75 g oral glucose tolerance test, and blood sample collection. In addition, logistic regression was used to analyze the interaction between age and risk factors for prediabetes and diabetes. Results The statistical analysis included 2776 people. In this study, the prevalence of diabetes and prediabetes were 15.1% and 52.3%, respectively. The prevalence of diabetes and prediabetes is higher in the elderly than in the middle-aged group. Among the risk factors for diabetes, overweight was associated with higher age (P-interaction 0.028). In addition, among the risk factors for prediabetes, a high level of education was associated with higher age (P-interaction 0.039) and elevated serum cholesterol level was associated with lower age (P-interaction 0.019). Conclusion This study confirmed an interaction between age and other influencing factors, which may be important in explaining differences in risk factors for diabetes and prediabetes in the middle-aged and elderly populations. Community health facilities can provide health guidance to people of different age groups to prevent and control prediabetes and diabetes.
Designing an App to Promote Physical Exercise in Sedentary People Using a Day-to-Day Algorithm to Ensure a Healthy Self-Programmed Exercise Training

Heart rate variability (HRV) has allowed the implementation of a methodology for daily decision making called day-to-day training, which allows data to be recorded by anyone with a smartphone. The purpose of the present work was to evaluate the validity and reliability of HRV measurements with a new mobile app (Selftraining UMH) in two resting conditions. Twenty healthy people (10 male and 10 female) were measured at rest in supine and seated positions with an electrocardiogram and an application for smartphones at the same time (Selftraining UMH) using recordings obtained through an already validated chest-worn heart rate monitor (Polar H10). The Selftraining UMH app showed no significant differences compared to an electrocardiogram, neither in supine nor in sitting position (p > 0.05) and they presented almost perfect correlation levels (r ≥ 0.99). Furthermore, no significant differences were found between ultra-short (1-min) and short (5-min) length measurements. The intraclass correlation coefficient showed excellent reliability (>0.90) and the standard error of measurement remained below 5%. The Selftraining UMH smartphone app connected via Bluetooth to the Polar H10 chest strap can be used to register daily HRV recordings in healthy sedentary people.
Relaxation Instability in Tokamaks

A three-dimensional, nonlinear, numerical simulation is described in which saw-tooth oscillations occur as a result of a hydromagnetic relaxation instability. The time evolution of the magnetic topology demonstrates the essential validity of the model suggested by Kadomtsev to explain the saw-tooth oscillations observed in tokamak experiments.
Calibration and Validation of Flow Parameters of Irregular Gravel Particles Based on the Multi-Response Concept

The discrete element method (DEM) often uses the angle of repose to study the microscopic parameters of particles. This paper proposes a multi-objective optimization method combining realistic modeling of particles and image analysis to calibrate gravel parameters, after obtaining the actual static angle of repose (αAoR_S) and dynamic angle of repose (βAoR_D) of the particles by physical tests. The design variables were obtained by Latin hypercube sampling (LHS), and the radial basis function (RBF) surrogate model was used to establish the relationship between the objective function and the design variables. The optimized design of the non-dominated sorting genetic algorithm II (NSGA-II) with the actual angle of repose measurements was used to optimize the design to obtain the best combination of parameters. Finally, the parameter set was validated by a hollow cylinder test, and the relative error between the validation test and the optimized simulation results was only 3.26%. The validation result indicates that the method can be reliably applied to the calibration process of the flow parameters of irregular gravel particles. The development of solid–liquid two-phase flow and the wear behavior of centrifugal pumps were investigated using the parameter set. The results show that the increase in cumulative tangential contact forces inside the volute of centrifugal pumps makes it the component most likely to develop wear behavior. The results also illustrate the significant meaning of the accurate application of the discrete element method for improving the efficient production of industrial scenarios.
Relation of Maternal Pre-Pregnancy Factors and Childhood Asthma: A Cross-Sectional Survey in Pre-School Children Aged 2–5 Years Old

Background and Objectives: Asthma constitutes a constant, prolonged, inflammation-related pulmonary disorder in childhood with serious public health concerns. Several maternal risk factors can enhance the prevalence of its development in this stage of life; however, the currently available data remain contradictory and/or inconsistent. We aim to evaluate the potential impacts of mothers’ sociodemographic, anthropometric and prenatal and perinatal factors on the prevalence of developing asthma in pre-school children. Materials and Methods: This is a retrospective cross-sectional survey, which includes 5133 women and their matched pre-school children. Childhood asthma was diagnosed using validated questionnaires. Statistical analysis was accomplished to evaluate whether maternal sociodemographic, anthropometric and prenatal and perinatal factors can increase the probability of childhood asthma in pre-school age. Results: A prevalence of 4.5% of childhood asthma was recorded in pre-school age. Maternal age and pre-pregnancy overweight and obesity, caesarean section, gestational diabetes and hypertension and not breastfeeding were associated with childhood asthma after adjustment for multiple confounding factors. Conclusion: Our research showed that several maternal factors increase the prevalence of childhood asthma in pre-school age. Suitable and effective health policies and strategies should be taken into account to confront the predominant maternal factors that increase its prevalence in pre-school age.
Dynamic Interplay between O2 Availability, Growth Rates, and the Transcriptome of Yarrowia lipolytica

Industrial-sized fermenters differ from the laboratory environment in which bioprocess development initially took place. One of the issues that can lead to reduced productivity on a large scale or even early termination of the process is the presence of bioreactor heterogeneities. This work proposes and adopts a design–build–test–learn-type workflow that estimates the substrate, oxygen, and resulting growth heterogeneities through a compartmental modelling approach and maps Yarrowia lipolytica-specific behavior in this relevant range of conditions. The results indicate that at a growth rate of 0.1 h−1, the largest simulated volume (90 m3) reached partial oxygen limitation. Throughout the fed-batch, the cells experienced dissolved oxygen values from 0 to 75% and grew at rates of 0 to 0.2 h−1. These simulated large-scale conditions were tested in small-scale cultivations, which elucidated a transcriptome with a strong downregulation of various transporter and central carbon metabolism genes during oxygen limitation. The relation between oxygen availability and differential gene expression was dynamic and did not show a simple on–off behavior. This indicates that Y. lipolytica can differentiate between different available oxygen concentrations and adjust its transcription accordingly. The workflow presented can be used for Y. lipolytica-based strain engineering, thereby accelerating bioprocess development.
Numerical prediction of the performance of a shrouded probe sampling in turbulent flow

A numerical simulation is presented for the performance of a shrouded probe sampling at a zero yaw angle to a turbulent flow stream. The mean turbulent flow is calculated using the standard κ-ϵ turbulence closure model. The trajectories of particles in the flow field are simulated by solving the corresponding Lagrangian equation of particle motion which includes such effects as inertia, drag, gravity, Saffman force, and turbulent diffusion. Three parameters describing the performance of a sampling probe—aspiration ratio, transmission ratio, and wall loss—are calculated by tracking a large number of particles. Computations are carried out for free stream velocities of 8.9, 15.6, and 21 m / s, and for particle sizes of 5, 10, and 15 μm aerodynamic equivalent diameter. A comparison is made between the numerically calculated and the experimentally measured values of wall loss and aspiration ratio. The agreement between the numerical prediction and the experimental data is good. The maximum difference is 6% fo.
Fully adiabatic changes in storm time relativistic electron fluxes

It has been suggested that much of the drop and subsequent recovery of storm time relativistic electron fluxes at geosynchronous orbit can be explained in terms of a fully adiabatic response (all three adiabatic invariants conserved) to magnetic field changes. To calculate this effect, we assume a prestorm electron flux distribution constructed from CRRES satellite data, we use modular magnetospheric magnetic field models to represent the magnetic field configuration before and during the storm, and we use Liouville's theorem to evolve the prestorm electron flux. In this work we focus on the important special case of equatorially mirroring electrons. During the main phase of a storm with a Dst minimum of -100 nT we find that the fully adiabatic effect can cause a flux decrease of up to 2 orders of magnitude, consistent with observed flux decreases. We also find that the magnitude of the fully adiabatic flux decrease is larger for lower energies, again in agreement with observations. The contribution of prestorm electron fluxes to the recovery phase flux increase at synchronous orbit is expected to be small because of losses to the dawnside magnetopause. A comparison of fully adiabatic fluxes with measured electron fluxes for the November 2-5, 1993, storm indicates that for this event the fully adiabatic effect may be contributing to the observed decrease but that nonadiabatic effects are clearly important. Overall we conclude that the fully adiabatic effect can account for a significant fraction of observed flux decreases and that differences between the observed and the fully adiabatic fluxes help to clarify when and where additional loss and source mechanisms exist.
Endometriosis and Opioid Receptors: Are Opioids a Possible/Promising Treatment for Endometriosis?

Endometriosis (EM), defined as the presence of endometrial-like tissue with surrounding smooth muscle cells outside the uterus, is a disregarded gynecological disease reported to affect 6–10% of women of reproductive age, with 30–50% of them suffering from chronic pelvic pain and infertility. Since the exact pathogenic mechanisms of EM are still unclear, no curative therapy is available. As pain is an important factor in EM, optimal analgesia should be sought, which to date has been treated primarily with non-steroidal anti-inflammatory drugs (NSAIDs), metamizole or, in extreme cases, opioids. Here, we review the pain therapy options, the mechanisms of pain development in EM, the endogenous opioid system and pain, as well as the opioid receptors and EM-associated pain. We also explore the drug abuse and addiction to opioids and the possible use of NOP receptors in terms of analgesia and improved tolerability as a target for EM-associated pain treatment. Emerging evidence has shown a promising functional profile of bifunctional NOP/MOP partial agonists as safe and nonaddictive analgesics. However, until now, the role of NOP receptors in EM has not been investigated. This review offers a thought which still needs further investigation but may provide potential options for relieving EM-associated pain.
The Development and Usability of a Mobile App for Parents of Children with ADHD

Background: Attention-Deficit/ Hyperactivity Disorder (ADHD) is one of the most prevalent mental health problems in children. Behavioral parent training (BPT) is the first-line treatment recommended by clinical guidelines; however, parental dropout is high. Mobile apps could be used as an adjunct to BPT in order to increase treatment adherence, homework compliance, and parental engagement. In this paper, we describe the development process of a mobile app for parents of children with ADHD. Methods: We conducted a study to investigate parents’ perceived usability of the ADHD Coping Card. Results: The mobile app developed has a high usability. Future improvements in the app were suggested by parents. Conclusions: Given the increasing importance of digital mental health interventions in psychotherapy, it is important that future research is conducted with a higher number of participants to investigate the key factors implicated in choosing such an intervention in the future, both by parents and by mental health specialists. A mobile app can be used as an add-on in psychotherapy with parents of children with ADHD. Digital health interventions could help surpass gaps in treatment access for child mental health problems.
Positivity of integrals of Bessel functions

Using results on multiply monotone functions, we establish the positivity of integrals of Bessel functions of the form \[ \int_0^x {\left( {x^\mu - t^\mu } \right)^\lambda } t^\alpha J_\beta (t)dt,\quad x > 0,\] where $0 < \mu \leq 1 \leq \lambda $ and $\alpha $, $\beta $ satisfy various conditions. In particular, the result holds if $ - \frac{1}{2} \leq \alpha = \beta \leq \frac{3}{2}$ or if $\frac{3}{2} = \alpha \leq \beta $.
Modelling observed X-ray pulsar profiles

Polar cap emission models for X-rays emitted by accreting neutron stars are constructed and compared to observed pulse profiles. This work is a generalization of the work of Leahy D. (1990, Mont Not. Roy. ast. Soc., 242). The intensity distribution from the neutron star is computed using a source region consisting of two annular polar-cap emission regions. These annuli are centred on the magnetic poles which are allowed to be offset from a single axis passing through the centre of the neutron star. Model profiles are generated from the calculated intensity distribution, then are least-squares fitted to the observed pulse profiles of 20 X-ray pulsars. Parameters such as orientation of neutron star spin and magnetic axes, polar cap size, and magnetic axis offset are derived