Miracle-dz/UniFAR-FTUs huggingface dataset:
The Emotion Regulation Questionnaire: Psychometric Properties and Prediction of Posttraumatic Consequences during the COVID-19 Pandemic in Chilean Adults

The Emotion Regulation Questionnaire (ERQ) is widely used to assess the use of cognitive reappraisal and expressive suppression strategies to regulate negative emotions. The present study evaluates the psychometric properties, reliability and validity of a Chilean adaptation of the ERQ in a large sample of 1543 participants aged between 18 and 87 (38% male, 62% female). The results of the confirmatory factor analysis showed the expected two-factor structure and factorial invariance in relation to gender. Results also indicated adequate internal consistency, test–retest reliability, convergent and predictive validity in predicting posttraumatic stress symptoms and posttraumatic growth six months after the first measurement in a subsample of students exposed to the COVID-19 pandemic. The use of reappraisal was positively associated with general well-being, whereas the use of suppression was positively associated with depressive symptomatology. In terms of posttraumatic consequences, the use of reappraisal was negatively associated with posttraumatic symptomatology and positively associated with posttraumatic growth six months later; in turn, suppression was positively associated with posttraumatic symptomatology and negatively associated with posttraumatic growth six months later. This study demonstrates that the ERQ is a valid and reliable instrument to measure emotional regulation strategies in Chilean adults.
Numerical indefinite integration using the sinc method

In this thesis, we study the numerical approximation of indefinite integrals with algebraic or logarithmic end-point singularities. We show the derivation of the two quadrature formulas proposed by Haber based on the sinc method, as well as, on the basis of error analysis, by means of variable transformations (Single and Double Exponential), the derivation of two other formulas: Stenger’s Single Exponential (SE) formula and Tanaka et al.’s Double Exponential (DE) sinc method. Important tools for our work are residue calculus, functional analysis and Fourier analysis from which we state some standard results, and give the proof of some of them. Next, we introduce the Paley-Wiener class of functions, define the sinc function, cardinal function, when a function decays single and double exponentially, and prove some of their interesting properties. Since the four formulas involve a conformal transformation, we show how to transform from the interval (−∞, ∞) to (−1, 1). In addition, we show how to implement the four formulas on two computational examples which are our test problems, and illustrate our numerical results by means of tables and figures. Furthermore, from an application of the four quadrature formulas on two test problems, a plot of the maximum absolute error against the number of function evaluations, reveals a faster convergence to the exact solution by Tanaka et al.’s DE sinc method than by the other three formulas. Next, we convert the indefinite integrals (our test problems) into ordinary differential equations (ODE) with suitable initial values, in the hope that ODE solvers such as Matlab ode45 or Mathematica NDSolve will be able to solve the resulting IVPs. But they all failed because of singularities in the initial value. In summary, of the four quadrature formulas, Tanaka et al.’s DE sinc method gives more accurate results than the others and it will be noted that all the formulas are applicable to both singular and non-singular integrals.
Right Ventricular Morphology and Function after Exercise Training in People with Systemic Sclerosis: A Randomized Controlled Pilot Study

Background: Vascular dysfunction and its concomitant multi-organ involvement, including cardiac involvement, affects prognosis in systemic sclerosis (SSc) patients. Regular exercise has demonstrated to be able to improve vascular function in SSc. However, the effects of an exercise program on the heart and specifically in right ventricular (RV) morphology and function in SSc have yet to be explored. The study aimed to examine whether a 3-month combined exercise program can affect RV morphology and function in SSc patients. Methods: Twenty-eight SSc patients were randomly allocated to either the exercise training (ET) or the control (CON) group. Baseline and follow-up assessments consisted of a cardiopulmonary exercise test along with both a conventional and a two-dimensional speckle tracking echocardiography (2DSTE) focused on RV morphology and function. Following the baseline assessments, Group ET participated in a supervised combined exercise program for 12 weeks, while group CON received their usual care. Results: The ET group demonstrated increases in peak oxygen consumption by 25.1% (p < 0.001), global RV free wall longitudinal systolic strain by 6.69% (p < 0.03), RV free wall longitudinal systolic strain of the basal segment by 13.5% (p < 0.001), and global RV four-chamber longitudinal systolic strain by 6.76% (p < 0.03) following the exercise program. No differences were observed in group CON. Conclusions: Combined exercise improved cardiorespiratory efficiency and indices of RV systolic function, as assessed by the 2DSTE, in SSc patients.
Study of the complex atomic susceptibility of erbium-doped fiber amplifiers

A study of the complex atomic susceptibility of erbium-doped fiber amplifiers operating near the 1.53- mu m transition (/sup 4/I/sub 13/2/-/sup 4/I/sub 15/2/) developed from a semiclassical theoretical description is presented. Expressions for the emission cross section sigma /sub e/( lambda ) and absorption cross section sigma /sub a/( lambda ) of erbium:glass as a quasi-three-level laser system with Stark-split sublevel manifolds are derived. The results are used to calculate the cross sections of aluminosilicate erbium-doped fibers at low temperatures (T=4.2, 77 K) and at room temperature. It is demonstrated that an expression for the gain coefficient of the fiber amplifier can be derived from the expression of the susceptibility. Using Kramers-Kronig relations, an expression for the refractive index change in the fiber is derived. The theoretical spectral gain profile of the fiber amplifier and concurrent refractive index changes are analyzed for different pumping regimes. >
Environmental and Nesting Variables Associated with Atlantic Leatherback Sea Turtle (Dermochelys coriacea) Embryonic and Hatching Success Rates in Grenada, West Indies

Simple Summary Leatherback sea turtle (Dermochelys coriacea) populations are experiencing significant declines and are at risk of global extinction. Sustaining reproductive success is vital to the recovery of populations. This study quantified nests and egg production between 2015–2019 on Levera Beach, Grenada and explored the association of select environmental variables with leatherback sea turtle embryonic development and hatching success rates. Annual variation was observed for the number of eggs per nest and embryo and hatching success rates. Nest location on the beach was found to be an influencing factor and development and hatching success rates decreased when nest depths were relatively shallow and when there was higher frequency of eggs with microbial growth and inspissated yolk. Relatively high temperatures recorded in a subset of nests suggest hatchling sex ratios may be skewed towards females and that increased temperatures are a risk to hatchling survival. Histopathology identified bacterial bronchopneumonia as a likely cause of morbidity and mortality in hatchlings. These findings help guide conservation strategies to support leatherback sea turtle hatchling survival. Abstract Annual monitoring of leatherback sea turtle (Dermochelys coriacea) nesting grounds in Grenada, West Indies has identified relatively low hatch rates compared to worldwide trends. This study investigated the impact of selected environmental variables on leatherback sea turtle embryonic development and hatching success rates on Levera Beach in Grenada between 2015–2019. The mean number of nests per year and eggs per nest were 667.6 ± 361.6 and 80.7 ± 23.0 sd, respectively. Within excavated nests, 35.6% ± 22.0 sd of eggs successfully developed embryos and 30.6% ± 22.6 sd of eggs successfully hatched. The number of eggs per nest, along with embryo and hatching success rates, differed by nesting year. Embryo development success rate was associated with nest location, and both embryo development and hatching success rates were positively associated with nest depth and negatively associated with the percentage of eggs exhibiting microbial growth and with the presence of inspissated yolk. There was no embryo development or hatchling success association with month of the nesting season, distance from the high-water mark, distance from vegetation, nor maternal carapace length. The mean nest temperature was 31.7 °C ± 1.64 sd and mean temperatures during the middle third of egg incubation suggest clutches are highly skewed towards a preponderance of female hatchlings. Histopathologic findings in hatchling mortalities included severe, acute, multifocal, heterophilic bronchopneumonia with intralesional bacteria in 4/50 (8%) hatchlings. Data from this study guide conservation strategies by identifying risk factors and further avenues of research needed to support reproductive success of leatherback sea turtles in Grenada and the greater Caribbean region.
On the effects of predictor misclassification in multiple linear regression analysis

Unweighted least squares regression analysis procedures are frequently used to model the relationship between a continuous response variable and one or more categorical predictor variables. Very commonly, these categorical predictors are subject to misclassification error. The majority of research in the area of mismeasurement of predictors in linear regression analysis has focused on continuous predictors (i,e., on errors-in-variables models). The theory developed for these situations relies on assumptions that do not apply to categorical predictors. We examine the impact of categorical predictor misclassification on unweighted least squares regression analysis results based on models that may also include any number of perfectly measured continuous or categorical predictors, Distributional properties of the response variable conditional on the potentially misclassified observed data are determined, These properties are used to examine the bias properties of estimators of regression coefficients and thei.
Modeling Human Brain Tumors and the Microenvironment Using Induced Pluripotent Stem Cells

Simple Summary Induced pluripotent stem cells (iPSCs) are crucial for disease modeling and cell-based therapy because they serve as an infinite source of specific human cell types. The use of iPSCs in cancer immunotherapy and cell transplantation therapy has garnered much attention in personalized medicine. To improve the efficacy and specificity of brain cancer treatment, iPSCs can be used to derive human brain tumor models for therapeutic evaluation. This review summarizes the utilization of human iPSCs to generate brain-specific cells, organoids, and tumor models for brain cancer modeling and drug testing. In addition, current challenges, limitations, and future prospects to find a more efficacious approach for treating human brain cancers are discussed. Abstract Brain cancer is a group of diverse and rapidly growing malignancies that originate in the central nervous system (CNS) and have a poor prognosis. The complexity of brain structure and function makes brain cancer modeling extremely difficult, limiting pathological studies and therapeutic developments. Advancements in human pluripotent stem cell technology have opened a window of opportunity for brain cancer modeling, providing a wealth of customizable methods to simulate the disease in vitro. This is achieved with the advent of genome editing and genetic engineering technologies that can simulate germline and somatic mutations found in human brain tumors. This review investigates induced pluripotent stem cell (iPSC)-based approaches to model human brain cancer. The applications of iPSCs as renewable sources of individual brain cell types, brain organoids, blood–brain barrier (BBB), and brain tumor models are discussed. The brain tumor models reviewed are glioblastoma and medulloblastoma. The iPSC-derived isogenic cells and three-dimensional (3D) brain cancer organoids combined with patient-derived xenografts will enhance future compound screening and drug development for these deadly human brain cancers.
Finding the keystone for Deaf doctoral students’ success: Does mentoring matter?

ABSTRACT Mentoring has been an effective strategy that contributed to personal, academic, and career success on all levels. It has played an integral role in doctoral students’ journeys to successfully complete their degrees. Due to limited research regarding the emic experiences and perspectives of Deaf doctoral students and graduates with mentorship during their doctoral studies, data was collected and analyzed from focus groups. A grounded theory methodology with the method of constant comparative analysis identified eight common themes, which were synthesized to four categories; access, relationships, collaboration, and locus of control. The overarching theme using the in vivo codes was determined to be a ‘safe space’ which was the keystone to doctoral students’ overall success to complete the program. To support future Deaf doctoral students with mentoring, insights and recommendations for future research are shared.
Stocking Practices of Anti-Tuberculosis Medications among Community Pharmacists and Patent Proprietary Medicine Vendors in Two States in Nigeria

Background: Evidence has shown that non-fixed-dose combination (non-FDC) anti-TB drugs could promote the spread of drug-resistant tuberculosis (DR-TB). We aimed to determine anti-TB medication stocking and dispensing practices among patent medicine vendors (PMVs) and community pharmacists (CPs) and their determinants. Method: This was a cross-sectional study using a structured, self-administered questionnaire among 405 retail outlets (322 PMVs and 83 CPs) across 16 Lagos and Kebbi local government areas (LGAs) between June 2020 and December 2020. Data were analyzed with Statistical Program for Social Sciences (SPSS) for Windows version 17 (IBM Corp., Armonk, NY, USA). Chi-square test and binary logistic regression were used to assess the determinants of anti-TB medication stocking practices at a p-value of 0.05 or less for statistical significance. Results: Overall, 91%, 71%, 49%, 43% and 35% of the respondents reported stocking loose rifampicin, streptomycin, pyrazinamide, isoniazid and ethambutol tablets, respectively. From bivariate analysis, it was observed that being aware of directly observed therapy short course (DOTS) facilities (OR 0.48, CI 0.25–0.89, p < 0.019) and having previous training on TB (OR 0.32, CI 0.14–0.73, p < 0.005) reduced the odds of stocking anti-TB medication, while operating more than 1 shop (OR 3.32, CI 1.44–7.57, p = 0.004), having 3 or more apprentices (OR 5.31, CI 2.74–10.29, p < 0.001) and seeing over 20 clients/day (OR 3.02, CI 1.18–7.71, p = 0.017) increased the odds of stocking loose anti-TB medications. From multivariate analysis, it was observed that only the variable having three or more apprentices (OR 10.23, CI 0.10–0.49, p = 0.001) significantly increased the odds of stocking anti-TB medications. Conclusions: The stocking of non-FDC anti-TB medications was high and largely determined by the number of apprentices among PMVs and CPs in Nigeria, and this may have serious implications for drug resistance development. However, the results linking the stocking of anti-TB to the number of apprentices should be interpreted cautiously as this study did not control for the level of sales in the pharmacies. We recommend that all capacity-building and regulatory efforts for PMVs and CPs in Nigeria should include not just the owners of retail premises but also their apprentices.
Thermal conductivities of single-walled carbon nanotubes calculated from the complete phonon dispersion relations

The thermal conductivity of an individual single-walled carbon nanotube is calculated with the analysis of all possible combining and splitting umklapp scattering processes based on complete phonon dispersion relations. The relaxation rate for the transverse acoustic phonons that undergo the combination umpklapp process is found to increase with many singularities as temperature rises. The calculated mean free path suggests that the combining (splitting) umklapp process is predominant in the low (high) frequency regime. The phonons with a very high frequency contribute little to thermal conduction due to the splitting umklapp process. The calculated thermal conductivity for (10,10) carbon nanotube is $474\phantom{\rule{0.3em}{0ex}}\mathrm{W}∕\mathrm{m}\phantom{\rule{0.2em}{0ex}}\mathrm{K}$ at $300\phantom{\rule{0.3em}{0ex}}\mathrm{K}$.
Geometry of the Katok examples

Abstract We consider examples of Finsler metrics symmetric or not) on Sn, Pnℂ, Pnℍ, and P2Ca with only finitely many closed geodesies or with only few short closed geodesies. The number of closed geodesies in these examples and properties of the closed geodesies are considered.
The Knowledge, Attitude, and Practice of Core Values in a Learning Institution in the Philippines: A Basis for a Plan of Action

This study aimed to assess the respondents’ knowledge, attitude, and practice regarding stewardship, empowerment, empathy, discipleship, and solidarity. It provides a concrete discussion as to how the learning institution in Nueva Ecija, Philippines, was able to affect their students and how they internalised these core values. A descriptive research design was used in this study. The respondents comprised 61% male and 39% female students from the junior high, senior high, and college departments. Statistical data analysis technique was used. Results significantly revealed that the student’s knowledge, attitude, and practice in the core values under investigation are highly evident. This means that the learning institution was effective and efficient in conducting activities that integrated these core values so that the students could internalise and practice them through their thoughts, feelings, and actions. The findings suggest that programs and activities must be crafted in the future to ensure that the core values are still effectively integrated for their continuous realisation.
Evaluation of Machine Learning Algorithms for Supervised Anomaly Detection and Comparison between Static and Dynamic Thresholds in Photovoltaic Systems

The use of photovoltaic systems has increased in recent years due to their decreasing costs and improved performance. However, these systems can be susceptible to faults that can reduce efficiency and energy yield. To prevent and reduce these problems, preventive or predictive maintenance and effective monitoring are necessary. PV health monitoring systems and automatic fault detection and diagnosis methods are critical for ensuring PV plants’ reliability, high-efficiency operation, and safety. This paper presents a new framework for developing fault detection in photovoltaic (PV) systems. The proposed approach uses machine learning algorithms to predict energy power production and detect anomalies in PV plants by comparing the predicted power from a model and the measured power from sensors. The framework utilizes historical data to train the prediction model, and live data is compared with predicted values to analyze residuals and detect abnormal scenarios. The proposed approach has been shown to accurately distinguish anomalies using constructed thresholding, either static or dynamic thresholds. The paper also reports experimental results using the Matthews correlation coefficient, a more reliable statistical rate for an imbalanced dataset. The proposed approach leads to a reasonable anomaly detection rate, with an MCC of 0.736 and a balanced ACC of 0.863.
An Impact of the Discrete Representation of the Bubble Size Distribution Function on the Flow Structure in a Bubble Column Reactor

The purpose of the present study is to analyze the effect of different discrete representations of the continuous bubble size distribution function on the flow structure in a bubble column reactor. Poly- and monodisperse media were considered, such that the mathematical expectation of the bubble size in the polydisperse case was equal to the bubble size in the monodisperse case at the same volumetric bubble contents. For these computations the normalized variances of the velocity profiles of the carrier and the disperse phases, the volume fraction of the disperse phase, and the specific area of the interfacial surface were determined. The normalized variances were calculated from a reference scenario with a detailed resolution of the bubble size distribution function with ten bubble classes. It was shown that with increase of the average bubble sizes mono- and polydisperse approaches provide converging solutions. A modified hybrid discretization of the bubble size distribution function with four classes of bubbles was shown to predict the flow structure with normalized variance less than 5% over the entire computational domain for all monitored parameters.
Effects of Blade Wrap Angle Influencing a Pump as Turbine

A pump is not ideally designed to operate as a turbine. To improve the efficiency of a pump as turbine (PAT), the redesign of the PAT, according to the flow of the turbine, is required. The blade wrap angle is one of the main geometric parameters in impeller design. Therefore, an investigation into the blade wrap angle to the PAT’s influence can be useful. In order to understand blade wrap angle to the influence of the PAT, this paper numerically investigated three different specific speeds of PATs with different blade wrap angles. The validity of numerical simulation was first confirmed through a comparison between numerical and experimental results. The performance change of the PATs with the blade wrap angle was acquired. A detailed hydraulic loss distribution and a theoretical analysis were performed to investigate the reasons for performance changes caused by the blade wrap angle. The results show that there is an optimal blade wrap angle for a PAT to achieve the highest efficiency and the optimal blade wrap angle decreases with an increasing specific speed. A performance analysis shows the PAT’s flow versus pressure head (Q-H) and flow versus generated shaft power (Q-P) curves are lowered with the decrease of the blade wrap angle. The hydraulic loss distribution and theoretical analysis illustrate that it is the decrease of hydraulic loss within the impeller, together with the decrease of the theoretical head, that results in the performance decrease. The decrease of hydraulic loss within the impeller is attributed to the shortened impeller blade passage and the reduced velocity gradient within the impeller flow channel. With the decrease of the blade wrap angle, the slip factor of the PAT’s impeller is decreased; therefore, its theoretical head is also decreased.
Approximations of Bayes Classifiers for Statistical Learning of Clusters

It is rarely possible to use an optimal classifier. Often the classifier used for a specific problem is an approximation of the optimal classifier. Methods are presented for evaluating the performance of an approximation in the model class of Bayesian Networks. Specifically for the approximation of class conditional independence a bound for the performance is sharpened. The class conditional independence approximation is connected to the minimum description length principle (MDL), which is connected to Jeffreys’ prior through commonly used assumptions. One algorithm for unsupervised classification is presented and compared against other unsupervised classifiers on three data sets.