Miracle-dz/UniFAR-FTUs huggingface dataset:
Implementation and Effectiveness of a Pharmacotherapeutic Follow-Up Service for People with Tuberculosis in Primary Healthcare

Tuberculosis (TB) is a disease of great relevance, responsible for 1.5 million deaths worldwide. Therefore, actions to control TB are necessary, and pharmacists may play an important role, especially in primary healthcare (PHC), where the diagnosis and management of this infection occurs. In a large Brazilian city, pharmacotherapeutic follow-up in PHC has been offered by pharmacists to people with TB since 2018. The objective of this study was to evaluate the implementation and effectiveness of this service though a longitudinal type 1 effectiveness–implementation hybrid study. Data were collected from January 2018 to February 2020 in the pharmaceutical services system. The service indicators were described and effectiveness was evaluated using Poisson regression analysis to compare the incidence of cure among patients using and not using the service. The service was performed in 148 PHC units by 82 pharmacists. Of the total of 1076 treatments, 721 were followed up by pharmacists, and TB was cured more frequently in these cases (90.4% attended vs. 73.5% unattended). The adjusted hazard ratio of cure among patients enrolled in the pharmacotherapeutic follow-up service was 2.71 (2.04–3.61; p < 0.001). Pharmacotherapeutic follow-up for people with TB significantly increased the incidence of cure and should be encouraged.
Analysis techniques for complex field radiation pattern measurements

Complex field measurements are increasingly becoming the standard for state-of-the-art astronomical instrumentation. Complex field measurements have been used to characterize a suite of ground, airborne, and space-based heterodyne receiver missions,1-6 and a description of how to acquire coherent field maps for direct detector arrays was demonstrated in Davis et. al. 20177. This technique has the ability to determine both amplitude and phase radiation patterns from individual pixels on an array for direct comparison to optical simulations. Phase information helps to better characterize the optical performance of the array (as compared to total power radiation patterns) by constraining the fit in an additional plane.4 This is a powerful technique to diagnose optical alignment errors through the optical system, as a complex field scan in an arbitrary plane can be propagated either forwards or backwards through optical elements to arbitrary planes along the principal axis. Complex radiation patterns have the advantage that the effects of optical standing waves and alignment errors between the scan system and the instrument can be corrected and removed during post processing. Here we discuss the mathematical framework used in an analysis pipeline developed to process complex field radiation pattern measurements. This routine determines and compensates misalignments of the instrument and scanning system. We begin with an overview of Gaussian beam formalism and how it relates to complex field pattern measurements. Next we discuss a scan strategy using an offset in z along the optical axis that allows first-order optical standing waves between the scanned source and optical system to be removed in post-processing. Also discussed is a method by which the co- and cross-polarization fields can be extracted individually for each pixel by rotating the two orthogonal measurement planes until the signal is the co-polarization map is maximized (and the signal in the cross-polarization field is minimized). We detail a minimization function that can fit measurement data to an arbitrary beam shape model. We conclude by discussing the angular plane wave spectral (APWS) method for beam propagation, including the near-field to far-field transformation.
Prognostic Model of COVID-19 Severity and Survival among Hospitalized Patients Using Machine Learning Techniques

We conducted a statistical study and developed a machine learning model to triage COVID-19 patients affected during the height of the COVID-19 pandemic in Hong Kong based on their medical records and test results (features) collected during their hospitalization. The correlation between the values of these features is studied against discharge status and disease severity as a preliminary step to identify those features with a more pronounced effect on the patient outcome. Once identified, they constitute the inputs of four machine learning models, Decision Tree, Random Forest, Gradient and RUSBoosting, which predict both the Mortality and Severity associated with the disease. We test the accuracy of the models when the number of input features is varied, demonstrating their stability; i.e., the models are already highly predictive when run over a core set of (6) features. We show that Random Forest and Gradient Boosting classifiers are highly accurate in predicting patients’ Mortality (average accuracy ∼99%) as well as categorize patients (average accuracy ∼91%) into four distinct risk classes (Severity of COVID-19 infection). Our methodical and broad approach combines statistical insights with various machine learning models, which paves the way forward in the AI-assisted triage and prognosis of COVID-19 cases, which is potentially generalizable to other seasonal flus.
LOW-TEMPERATURE CRYSTALLIZATION OF AMORPHOUS SILICATE IN ASTROPHYSICAL ENVIRONMENTS

We construct a theoretical model for low-temperature crystallization of amorphous silicate grains induced by exothermic chemical reactions. As a first step, the model is applied to the annealing experiments, in which the samples are (1) amorphous silicate grains and (2) amorphous silicate grains covered with an amorphous carbon layer. We derive the activation energies of crystallization for amorphous silicate and amorphous carbon from the analysis of the experiments. Furthermore, we apply the model to the experiment of low-temperature crystallization of an amorphous silicate core covered with an amorphous carbon layer containing reactive molecules. We clarify the conditions of low-temperature crystallization due to exothermic chemical reactions. Next, we formulate the crystallization conditions so as to be applicable to astrophysical environments. We show that the present crystallization mechanism is characterized by two quantities: the stored energy density Q in a grain and the duration of the chemical reactions τ. The crystallization conditions are given by Q>Qmin and τ < τcool regardless of details of the reactions and grain structure, where τcool is the cooling timescale of the grains heated by exothermic reactions, and Qmin is minimum stored energy density determined by the activation energy of crystallization. Our results suggest that silicate crystallization occurs in wider astrophysical conditions than hitherto considered.
RESOLVING THE FAN-SPINE RECONNECTION GEOMETRY OF A SMALL-SCALE CHROMOSPHERIC JET EVENT WITH THE NEW SOLAR TELESCOPE

Jets are ubiquitously present in both quiet and active regions on the Sun. They are widely believed to be driven by magnetic reconnection. A fan-spine structure has been frequently reported in some coronal jets and flares, and has been regarded as a signature of ongoing magnetic reconnection in a topology consisting of a magnetic null connected by a fan-like separatrix surface and a spine. However, for small-scale chromospheric jets, clear evidence of such structures is rather rare, although it has been implied in earlier works that showed an inverted-Y-shaped feature. Here we report high-resolution (0.″16) observations of a small-scale chromospheric jet obtained by the New Solar Telescope (NST) using 10830 Å filtergrams. Bi-directional flows were observed across the separatrix regions in the 10830 Å images, suggesting that the jet was produced due to magnetic reconnection. At the base of the jet, a fan-spine structure was clearly resolved by the NST, including the spine and the fan-like surface, as well as the loops before and after the reconnection. A major part of this fan-spine structure, with the exception of its bright footpoints and part of the base arc, was invisible in the extreme ultraviolet and soft X-ray images (observed by the Atmosphere Imaging Assembly and the X-Ray Telescope, respectively), indicating that the reconnection occurred in the upper chromosphere. Our observations suggest that the evolution of this chromospheric jet is consistent with a two-step reconnection scenario proposed by Török et al.
Mediating Influence of Self Esteem in the Prediction between Personality Traits and Alcohol Abuse Anong Ebonyi State University Students

Alcohol Abuse among students has become a serious public health issue in Nigeria. Research documentation of alcohol abuse has only been concentrated in the developed world with little or no empirical evidence to account for the perceptions from the developing world, especially sub-Saharan Africa. Therefore, the aim of this study is to examine the mediating effect of self esteem in the predictive relationship between personality traits and alcohol abuse among Ebonyi State University students. , Abakalilki. A Cross-sectional survey design was used for the study. Three hundred and twelve (312) Ebonyi State University students from the faculty of Health Sciences, Presco Campus were selected for this study. They comprised 208 (63.2%) males and 104 (32.3%) females with an age range between 19 years and 33 years. Their mean age was 23.36 which the SD was 6.36. This study made use of multi-stage sampling technique which comprised simple balloting and purposive sampling technique. Measures of the personality traits in this study were based on the Big Five Inventory (BFI), Index of Self-Esteem (ISE) was used to measure global indices of self-esteem and the McAndrew Alcoholism Scale was used to measure destructive drinking. Results showed that, personality trait significantly predicted alcohol abuse in this manner Extroversion (R= .087; β; 28 p< .01), Agreeableness (R= .087; β; 11, p< .01), Conscientiousness (R= .087; β; .03, p< .01), openness (R= .087; β; .24, p< .01), Finally neuroticism (R= .087; β.32, p< .01). The result also indicated that personality characteristics (i.e., extraversion, agreeableness, conscientiousness, openness and neuroticism), combined significantly predicted alcohol abuse among Ebonyi State University students (R= .087; β; .33, p< .01). Finally Self-esteem significantly predicted alcohol abuse (β -.14, t -2.99, p< .01). Post-Hoc Sobel test that was conducted reveled that perceive self-esteem significantly mediated the relationship between personality trait and alcohol abuse (Ƶ = 2.31, p., <. 05). Based on the findings of this study, it is recommended that academic institutions at all levels should try as much as possible to engage in reward systems that increase student’s propensities which will enhance the psycho-emotional perspectives of the students and able to cope with social pressures with campuses, and also effort should be made to reduce to minimal access to alcoholic beverages within the university environment. Also, symposiums and seminars including workshops should be organized to sensitize and students at all levels on social acceptable best practices. Also, therapies and interventions should be conducted for students who report or show behavioural problems which are linked to alcoholism and abuse of illicit drugs. This study portends several implications for the academia, in that research studies can be harnessed to help in policy formation and implementation concerning the sale and accessibility of alcoholic beverages within university campuses.
Empathy Display and Suppression among Ultra-Orthodox Male Teachers: The Influence of Culture and Religion

Abstract The purpose of the current study was to explore the meanings, regulation, and sources of male teacher empathy in the ultra-Orthodox Jewish schools in Israel from a cultural perspective. More specifically, the study posed three questions: (1) What are the particular meanings attached to empathy by ultra-Orthodox teachers? (2) How do ultra-Orthodox teachers regulate their empathy at work? (3) What are the cultural-social factors that affect these teachers’ constructions of teacher empathy? Based on semi-structured interviews with 12 male teachers working in the ultra-Orthodox educational system in Israel, three major themes arising in the data analysis are presented: the teachers’ meanings of empathy, empathy display and suppression, and the cultural/religious sources of the teacher empathy in the ultra-Orthodox society. Suggestions for further research on teacher empathy in religious and minority communities are provided.
The role of single oxygen or metal induced defect and correlated multiple defects in the formation of conducting filaments

We study the dependence of the formation energies of oxygen and metal induced defects in Ta 2 O 5 , TaO 2 , TaO, TiO 2 and Ti 4 O 7 on the chemical potential of electron and atomic constitutes. In the study of single defect, metal induced defects are found to be preferable to oxygen induced defects. This is against the experimental fact of the dominant role of oxygen induced defects in the RS process. A simple multiple defects picture without correlated atomic rearrangement does not cure this problem. The problem is resolved under the correlated multiple defect picture where the multiple defects result in correlated atomic rearrangement and the final products show certain atomic ordering.
Prediction of a Weyl Semimetal in Hg$_{1-x-y}$Cd$_x$Mn$_y$Te

We study strained Hg$_{1-x-y}$Cd$_x$Mn$_y$Te in a magnetic field using a $\bm{k}\cdot\bm{p}$ model and predict that the system is a Weyl semimetal with two nodes in an experimentally reasonable region of the phase diagram. We also predict two signatures of the Weyl semimetal phase which arise from tunability of the Weyl node splitting. First, we find that the Hall conductivity is proportional to the average Mn ion spin and thus is strongly temperature dependent. Second, we find an unusual magnetic field angle dependence of the Hall conductivity; in particular, we predict a peak in $\sigma_{xy}$ as a function of field angle in the $xz$-plane and a finite $\sigma_{yz}$ as the $x$-component of the field goes to 0.
Mattig's relation and dynamical distance indicators

We discuss how the redshift (Mattig) method in the Friedmann cosmology relates to dynamical distance indicators based on Newton's gravity (Teerikorpi 2011). It belongs to the class of indicators where the relevant length inside the system is the distance itself (in this case the proper metric distance). As the Friedmann model has a Newtonian analogy, its use to infer distances has instructive similarities to classical dynamical distance indicators. In view of the theoretical exact linear distance-velocity law, we emphasize that it is conceptually correct to derive the cosmological distance via the route: redshift (primarily observed) space expansion velocity (not directly observed) metric distance (physical length in “cm”). Important properties of the proper metric distance are summarized. (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim)
Lateral Flow Microimmunoassay (LFµIA) for the Reliable Quantification of Allergen Traces in Food Consumables

Quality assurance and food safety are of great concern within the food industry because of unknown quantities of allergens often present in food. Therefore, there is an ongoing need to develop rapid, sensitive, and easy to use methods that serve as an alternative to mass spectrometry and enzyme-linked immunosorbent assay (ELISA) for monitoring food safety. Lateral flow immunoassay is one of the most used point-of-need devices for clinical, environmental, and food safety applications. Compared to traditional methods, it appears to be a simple and fast alternative for detecting food allergens. However, its reliability is frequently questioned due to the lack of quantitative information. In this study, a lateral flow microimmunoassay (LFµIA) is presented that integrates up to 36 spots in microarray format in a single strip, providing semi-quantitative information about the level of allergens, positive and negative controls, internal calibration, and hook effect. The LFµIA has been evaluated for the on-site simultaneous and reliable quantification of almond and peanut allergens as a proof of concept, demonstrating high sensitivity (185 and 229 µg/kg, respectively), selectivity (77%), and accuracy (RSD 5–25%) when analyzing commercial allergen-suspicious food consumables.
Pathways, Scaling Laws and Analytical Solutions for Crease Formations in a Gel Layer

An analytical study on crease formations in a swelling gel layer is conducted. By exploring the smallness of the layer thickness and using a method of coupled series-asymptotic expansions, the original nonlinear eigenvalue problem of partial differential equations is reduced to one of ordinary differential equations. The latter problem is then solved analytically to obtain closed-form solutions for all the post-bifurcation branches. With the available analytical results, a number of deep insights on crease formations are provided, including the unveiling of three pathways to crease (depending on the layer thickness), determination of the bifurcation type, establishment of a lower bound for mode numbers and two scaling laws. Also, a number of experimental results are captured, which are then nicely interpreted based on the analytical solutions. In particular, it is shown that some critical physical quantities are invariant with respect to the thickness at the moment of crease formation. It appears that the present work offers a comprehensive understanding on crease formation, a widely-spread phenomenon.
Evidence for the Growth Superiority and Delayed Ovarian Development in Tetraploid Loach Misgurnus anguillicaudatus

The diploids and tetraploids of cyprinid loach Misgurnus anguillicaudatus coexist in many natural habits. The tetraploids generally exhibit superior growth performance and delayed gonadal development compared with diploids. To investigate the regulation mechanism of growth superiority and ovarian development in tetraploids, we first conducted a long-term culture experiment and histological observation. The tetraploids exhibited a higher growth performance and delayed ovarian development. Meanwhile, at a genetic level, an average of 6891 differentially expressed genes (DEGs) between diploids and tetraploids were identified from the brain, pituitary, liver, gonad and muscle using the RNA-seq method. Among these DEGs, as expected, some candidate genes, including IGF family genes, somatostatin, leptin, cyp19a1b, gthα, lhβ and fshβ, were detected, which play critical roles in the regulation of growth and gonad development of fish. In particular, the genes related to GH/IGF axis and growth factors, signal transduction, gonadal hormone and appetite were significantly increased in tetraploids. The clustering analyses of the key candidate genes showed that most key genes were up-regulated in the pituitary and gonad of tetraploids instead of other tissues. The dynamics of these key genes provide valuable genetic evidence for clarifying the growth superiority and delayed gonadal development of tetraploids. Moreover, this study also provides some clues for unveiling the genetic superiority of polyploidy species in other phenotypes.
The Best Option Pricing Model for KOSPI 200 Weekly Options

This study finds the best option pricing model for KOSPI 200 weekly options. It examines the in-sample pricing, out-of-sample pricing and hedging performances of the short-term options with a maximum maturity of seven days or less, which have not been analyzed in previous studies. The Black and Scholes (1973) model, Ad Hoc Black-Scholes model, and stochastic volatility and jumps models are compared. As a result, one of the Ad Hoc BlackScholes models, the absolute smile model using the strike price as an independent variable shows the best performance. However, its performance is not significantly different from that of the Black and Scholes (1973) model. In the early days of the KOSPI 200 weekly options market, it is confirmed that the Black and Scholes (1973) model continues to show the excellent performance in pricing and hedging options.
The Effect of Dynamic Fracture Strain on the Structural Response of Ships in Collisions

As ship collisions and grounding accidents lead to human injury and damage to the environment and property, more accurate predictions of structural damage to ships under impact loads are needed. Currently, to determine structural behaviors, finite element analysis (FEA) is frequently adopted. However, it is recommended to pay attention to material properties in FEA because structural damage is sensitive to material properties such as yield strength, fracture strain, etc. While the strain rate (impact speed) is automatically considered for dynamic yield stress using the Cowper–Symonds equation or other methods, the pre-defined fracture strain is generally used as the dynamic fracture strain (DFS), which is not dependent on strain rate during the simulation. This assigned value of fracture strain may affect the extent of damage and structural response. In this study, the effect of the DFS on the structural damage from collisions was investigated to determine the relationship between the DFS and damage. Empirical formulas based on predictions of damage by various events were developed as a function of the DFS and initial impact speed. The results of this study explained the effect of the DFS on the structural damage and determined the upper and lower bounds of damage by collisions.
The elephant in the Zoom: the role of virtual safaris during the COVID-19 pandemic for conservation resilience

ABSTRACT The economic turmoil and restrictions on human movement precipitated by the COVID-19 pandemic severely impacted conservation efforts. Many conservation actors rapidly implemented various adaptive measures in response to the cessation of the nature-based tourism industry, the primary revenue source for much of conservation in sub-Saharan Africa. This timely preliminary study examined the innovative use of virtual safaris, a form of virtual nature-based tourism, as an adaptive response to the crisis. Eight in-depth semi-structured interviews and two written responses from a range of ‘conservation operators’ provided insight into motivations, benefits, and challenges associated with using virtual safaris. This novel study found three mechanisms through which virtual safaris helped to alleviate the effects of COVID-19 with the potential to develop conservation resilience: 1) as a stopgap measure, 2) for revenue diversification, and 3) as a means of scaling ecosystem services. Virtual safaris provided a critical lifeline for conservation operators, created a new tool to connect with distant audiences, and strengthened relationships with donors. However, this research highlighted a need to re-evaluate the role of sustainable tourism within conservation, with transformative changes essential to enhance future conservation resilience.
Unified Dark Energy-Dark Matter model with Inverse Quintessence

We consider a model where both dark energy and dark matter originate from the coupling of a scalar field with a non-canonical kinetic term to, both, a metric measure and a non-metric measure. An interacting dark energy/dark matter scenario can be obtained by introducing an additional scalar that can produce non constant vacuum energy and associated variations in dark matter. The phenomenology is most interesting when the kinetic term of the additional scalar field is ghost-type, since in this case the dark energy vanishes in the early universe and then grows with time. This constitutes an ``inverse quintessence scenario'', where the universe starts from a zero vacuum energy density state, instead of approaching it in the future.