Miracle-dz/UniFAR-FTUs huggingface dataset:
Which is a stronger predictor of the abundance of Dorcas Gazelle, Gazella dorcas in the Eastern desert of Egypt: human or natural factors?

The Dorcas Gazelle, Gazella dorcas, has lost 86% of its global historical range, and is regionally categorized as endangered by the IUCN. The factors that caused this decline have never been quantified. In this work, field and remotely sensed data were used to examine the ecological and anthropogenic factors affecting the abundance of Dorcas Gazelle within Wadi El-Gemal Protected Area in the Eastern desert of Egypt, using Generalized Linear Mixed Models (GLMM). The species’ abundance is shaped by anthropogenic activities (number of car trails and proximity to the coastal road) more than ecological factors (vegetation and wetness indices). Dorcas Gazelle is avoiding more humid and greener areas because of human disturbance. Such suitable habitats may be perceived by gazelles as too dangerous, and the animals therefore prefer less suitable but safer habitats that are further away or less frequented by humans. Moreover, an easy to conduct, cheap monitoring tool, the Kilometric Abundance Index (KAI), was devised and implemented for baseline information to be used for future monitoring of Dorcas Gazelle.
Microspherical Lasing of an Erbium-Ion-Doped Glass Particle

Green upconversion lasing induced by the microspherical cavity effect of an erbium-ion-doped fluorozirconate glass particle was demonstrated. Periodic narrow peaks of the emission spectra corresponding to the whispering gallery modes were observed and the lasing threshold was determined from the excitation power dependence to be 4 mW. Large depletion of the red emission process was also observed at the threshold power of the green lasing.
Exploring the Design of Teaching Mental Health of College Students Based on Data-Driven Learning

Chinese contemporary college students, this generation has been pampered since childhood, growing up under the wings of their parents, most of them are flowers in the hothouse, now stepping into the university and carrying the double expectations of society and family. With the rapid development of modern technology and social culture, people in modern society are facing fierce competition, frequent stress, fast pace, and unprecedented psychological pressure, which has a significant impact on human health. Therefore, the construction of a university psychological wellness education model has become the focus of theoretical research. As a new type of mental health teaching and learning model, data-driven learning (DDL) not only provides learners with rich, diverse, and realistic mental health data, but also creates an ideal learning environment for learners due to its corpus-based teaching and learning characteristics. This paper explores the design of DDL-based mental health teaching and learning for students, combining theoretical research, and empirical analysis from the actual university, and constructing a comprehensive system of psychological wellness education in college while building a local system of DDL-based psychological wellness education. The experimental results show that the Q-learning algorithm and SA-Q algorithm have no environmental triggering mechanism, while the data-driven control algorithm has the step number of formula 24, 19, and 17, respectively, thus reaching the optimal path. Therefore, in the data-driven psychology classroom, students change from participating in activities according to the course teaching objectives and mental health teachers’ requirements to inquiry-based learning and interactive experiences that focuses on problem solving and task completion.
Oral Lesions Following Anti-SARS-CoV-2 Vaccination: A Systematic Review

Increasing evidence relate anti-SARS-CoV-2 vaccinations to orofacial adverse reactions, therefore, the present systematic review aimed to evaluate primary oral lesions diagnosed in adult subjects, following the WHO Emergency Use Listing approved and EMA authorized vaccines, also in relation to cases’ age, gender, comorbidities, and history of COVID-19, and in relation to vaccine type and doses. The study protocol, registered on PROSPERO (CRD42022339032) and compliant with the PRISMA statement, included an electronic search across Scopus, MEDLINE/PubMed, BioMed Central databases, and PROSPERO, ended on 18 June 2022 and succeeded by a manual search, an independent data extraction, and arisk of bias evaluation through ROBINS-I tool. Qualitatively synthesized data from the 13studies included showed an overall low prevalence (16 cases), though higher in females (68.8%), of oral lesions, mainly erosions and ulcers (34.5%). Nine cases were diagnosed following Pfizer-BioNTech, two Moderna, and one AstraZeneca, Serum Institute of India, Sinopharm, and Johnson&Johnson vaccines, respectively; specifically, eight after the first dose and seven after the second. In one case, vaccine type and dose were not specified. Considering newly developing vaccines, presented findings may be updated and further studies needed to highlight factors affecting oral lesion occurrence and specific macro-microscopic phenotypes in relation to cases’ and vaccines’ characteristics.
Intrapartum cardiotocography trace pattern pre-processing, features extraction and fetal health condition diagnoses based on RCOG guideline

Context The computerization of both fetal heart rate (FHR) and intelligent classification modeling of the cardiotocograph (CTG) is one of the approaches that are utilized in assisting obstetricians in conducting initial interpretation based on (CTG) analysis. CTG tracing interpretation is crucial for the monitoring of the fetal status during weeks into the pregnancy and childbirth. Most contemporary studies rely on computer-assisted fetal heart rate (FHR) feature extraction and CTG categorization to determine the best precise diagnosis for tracking fetal health during pregnancy. Furthermore, through the utilization of a computer-assisted fetal monitoring system, the FHR patterns can be precisely detected and categorized. Objective The goal of this project is to create a reliable feature extraction algorithm for the FHR as well as a systematic and viable classifier for the CTG through the utilization of the MATLAB platform, all the while adhering to the recognized Royal College of Obstetricians and Gynecologists (RCOG) recommendations. Method The compiled CTG data from spiky artifacts were cleaned by a specifically created application and compensated for missing data using the guidelines provided by RCOG and the MATLAB toolbox after the implemented data has been processed and the FHR fundamental features have been extracted, for example, the baseline, acceleration, deceleration, and baseline variability. This is followed by the classification phase based on the MATLAB environment. Next, using the guideline provided by the RCOG, the signals patterns of CTG were classified into three categories specifically as normal, abnormal (suspicious), or pathological. Furthermore, to ensure the effectiveness of the created computerized procedure and confirm the robustness of the method, the visual interpretation performed by five obstetricians is compared with the results utilizing the computerized version for the 150 CTG signals. Results The attained CTG signal categorization results revealed that there is variability, particularly a trivial dissimilarity of approximately (+/−4 and 6) beats per minute (b.p.m.). It was demonstrated that obstetricians’ observations coincide with algorithms based on deceleration type and number, except for acceleration values that differ by up to (+/−4). Discussion The results obtained based on CTG interpretation showed that the utilization of the computerized approach employed in infirmaries and home care services for pregnant women is indeed suitable. Conclusions The classification based on CTG that was used for the interpretation of the FHR attribute as discussed in this study is based on the RCOG guidelines. The system is evaluated and validated by experts based on their expert opinions and was compared with the CTG feature extraction and classification algorithms developed using MATLAB.
ERRATUM: Dirac equation with Hulthen potential: an algebraic approach

The energy levels of the Dirac equation with scalar and vector Hulthen type potentials are obtained by means of algebraic perturbation calculations which are based upon the dynamical group structure SO(2, 1). Numerical results are given for the particular case when the strengths of the vector and scalar potentials are equal.
Associations between age‐related macular degeneration and sleep dysfunction: A systematic review

Age‐related macular degeneration, a prevalent degenerative retinal disease, is associated with non‐visual and psychosocial impairments that may affect sleep. In this systematic review, we evaluated associations between age‐related macular degeneration (AMD) and sleep, highlighted knowledge gaps and provided evidence‐based recommendations to clinicians to enable holistic management of AMD patients.
From demon to deity: Forging a new iconography for Mahishasur

This article focuses on the forging of a new iconography for Mahishasur, a ‘demon’ in Hindu mythology who was reclaimed by indigenous communities both as a ‘god’ and as a champion of their political autonomy. The public political ritual of venerating Mahishasur was deemed blasphemous by the Hindu nationalist party in power. Among clay-modellers of Bengal, the dominant ‘demon’ image of Mahishasur embodies the highly-valued skill of Naturalistic sculpture; but the movement needed a new benevolent image. Through interviews with image-makers and organisers of this political ritual in several villages of West Bengal, I will show how local aesthetic ideals of masculinity, virtue, and political ideology are expressed in the new aesthetic form(s) and iconographies of this emerging hero of Indian politics.
Investigation of Thermoelastic Damping in the Longitudinal Vibration of a Micro Beam

In the design of high Quality factor (Q) micro or nano beam resonators, different dissipation mechanisms may have damaging effects on the quality factor. One of the major dissipation mechanisms is the thermoelastic damping (TED) that needs an accurate consideration for prediction. In this paper, thermoelastic damping of the longitudinal vibration of a homogeneous micro beam with both ends clamped have been investigated. A Galerkin method has been used to analyze thermoelastic damping for the first mode of vibration of the micro beam. Then the quality factor and longitudinal vibrations frequency are obtained. Changing of Quality factor versus geometrical properties and ambient temperature for different materials are plotted.
Insulin Receptor-Related Receptor Regulates the Rate of Early Development in Xenopus laevis

The orphan insulin receptor-related receptor (IRR) encoded by insrr gene is the third member of the insulin receptor family, also including the insulin receptor (IR) and the insulin-like growth factor receptor (IGF-1R). IRR is the extracellular alkaline medium sensor. In mice, insrr is expressed only in small populations of cells in specific tissues, which contain extracorporeal liquids of extreme pH. In particular, IRR regulates the metabolic bicarbonate excess in the kidney. In contrast, the role of IRR during Xenopus laevis embryogenesis is unknown, although insrr is highly expressed in frog embryos. Here, we examined the insrr function during the Xenopus laevis early development by the morpholino-induced knockdown. We demonstrated that insrr downregulation leads to development retardation, which can be restored by the incubation of embryos in an alkaline medium. Using bulk RNA-seq of embryos at the middle neurula stage, we showed that insrr downregulation elicited a general shift of expression towards genes specifically expressed before and at the onset of gastrulation. At the same time, alkali treatment partially restored the expression of the neurula-specific genes. Thus, our results demonstrate the critical role of insrr in the regulation of the early development rate in Xenopus laevis.
Adaptive neural sliding mode control of uncertain robotic manipulators with predefined time convergence

In this article, a predefined time convergence adaptive tracking control scheme is designed for a class of uncertain robotic manipulators with input saturation. First, a novel auxiliary dynamic system is proposed to handle the influence of input saturation. Radial basis function neural networks are used to approximate the uncertainty of the closed‐loop system and the neural adaptive law is designed by using the given time constant so that the neural networks have a fast convergence rate. The adaptive tracking controller is constructed by utilizing a nonsingular terminal sliding mode surface. Different from the finite‐time and the fixed‐time sliding mode control methods where the upper bound of the convergence time is related to system parameters, the convergence time upper bound of the proposed sliding mode controller is a given constant. Finally, numerical simulations are performed to illustrate that the proposed control scheme possesses the advantages of fast convergence rate and input saturation elimination.
Natural Language Processing of Aviation Safety Reports to Identify Inefficient Operational Patterns

With the growth in commercial aviation traffic and the need for improved environmental performance, strategies to lower emissions that can be implemented in the near term are necessary. Since novel technology takes time to enter the market, operational improvements that employ existing aircraft and require no new infrastructure are fit for this goal. While quantified data collected throughout aviation, such as arrival/departure statistics and flight data, have been well-utilized, text data collected through safety reports have not been leveraged to their full extent. In this paper, a methodology is presented that can use aviation text data to identify high-level causes of flight delays and cancellations, using delays as a metric of operational inefficiency. The dataset is extracted from the Aviation Safety Reporting System (ASRS), which includes voluntary safety incident reports in text narrative and metadata formats. The methodology uses natural language processing tools, K Means clustering, and dimensionality reduction by t-Distributed Stochastic Neighbor Embedding (t-SNE) to categorize and visualize narratives. The method identified 7 major clusters and a total of 23 sub-clusters. A comparison between the subclusters’ topics and the causes of flight delays revealed by the quantified data shows that the ASRS database provides a unique safety perspective to delay cause identification, as illustrated by the method’s identification of maintenance as the main cause of delays, rather than weather.
Developing 14 animated characters for non-verbal self-report of categorical emotions

Graphical self-report tools are increasingly used to collect data on users' emotional responses to products, yet most of these tools have only undergone minimal validation. A systematic set of animations was developed to allow participants in design research and other fields to report their feelings without relying on the nuances of a particular language's affective lexicon. The animations were revised based on eight studies across four countries (total N = 826). The set includes well-recognised animations representing desire/love, satisfaction/approval, pride/self-esteem, hope/optimism, interest/curiosity, surprise/excitement, disgust/aversion, embarrassment/shyness, fear/shock and boredom/dullness. Two other emotions (joy/happiness and contempt/disrespect) were recognised by about half of the participants in the final study.
Carbon Footprint and Performance of Quoted Insurance Firms in Sub-Saharan African Countries

Purpose: This study examined the effect of the rate of carbon footprints in an economy on the financial performance of listed insurance companies in selected countries in the sub-Saharan African region. It is argued in the study that factors that are external to the insurance industry (carbon footprint) intensify risks faced by the insurance firms.Methodology: The study employs secondary data from the sampled insurance firms’ annual audited financial statements. Data was collected from forty-five (45) insurance firms in eight (8) selected sub-Saharan African countries from 2010 to 2019. A dynamic estimation procedure was adopted based on the system GMM estimation technique using dependent variables (ROA, ROE and Tobin’s Q), explanatory variable CO2 emission and moderating variables of firm’s size, economic growth and inflation rate.Results/Findings: The results from the study reveal that the pattern of effects of carbon footprints differ in terms of the measurement used for a performance indicator. In particular, the study found that the level of carbon footprint in the economy exerts significant negative effects on all the performance indicators of insurance firms. Optimal risk and sustainable insurance procedures are therefore recommended in the study.
Influência da energia de compactação na curva de retenção de um solo típico de Cruz das Almas/BA

Genuchten Como resultado, constatou-se que o solo possui predominancia da fração areia, podendo ser classificado como areia argilo-siltosa. curva retenção do solo é afetada pelo incremento energia Entretanto, solo fração areia, plasticidade material. ABSTRACT: This paper evaluated the compaction energy influence on water retention curve of a soil from Cruz das Almas city (Ba). The geotechnical characterization was carried out by granulometry, liquid and plasticity limits, specific gravity and compaction tests to determine w ót e ρ dmáx to different energies: Standard, intermediate and Modified Proctor. Was performed using 30mm specimen were used to determine the water retention curve by filter paper method, using non contact filter and soil (total suction measurement). The filter paper, Whatman’s 42, was previously calibrated by Chandler et al. (1992) method and the soil water retention curves were fit by van Genuchten (1980). The results show that the investigated soil is a clayey-silty sand and the increment of compaction energy has a little influence on the water retention curve, because of its sandy characteristic and the low soil plasticity.
Hyperprolactinemia Associated with Attentional Processing and Interference Control Impairments in Patients with Prolactinomas

The cognitive impairment of pituitary adenomas (PAs) has received increasing attention. Hyperprolactinemia and tumor mass effect are the potential causes. The aim of this study was to identify possible cognitive impairment and to further explore the correlation between these indices and prolactin (PRL) levels, based on the control of tumor size. Twenty-seven patients with prolactinomas (patient group) and twenty-six matched health control group (HC group) were enrolled in this study. All participants performed the flanker task while we continuously recorded electroencephalography data. On the behavioral performance level, patients showed a significantly slower reaction time (RT) in both flanker types. Concerning the event-related potentials level, patients elicited reduced P2 and enhanced N2 amplitudes compared with the HC group, suggesting an impairment of attentional processing (P2) and conflict monitoring (N2). Moreover, the patient group also induced lower P3 amplitudes relative to the HC group in both types, indicating that there were deficits in attentional resource allocation ability. We also found a significant correlation between the P3 amplitudes and incongruent condition RTs, as well as the subsequent PRL levels in the patient group. In conclusion, this is an innovative study that reveals the impaired cognition abilities in prolactinomas, and also proposes the possible cognitive toxicity of oversecreted PRL levels, which provides evidence for further research on the cognitive decline in PAs.
Modeling Reactive Mixtures: Case Study for Spills of Formaldehyde Solutions

When a liquid mixture, such as an aqueous formaldehyde solution, is released into the environment, the rate of evaporation into the atmosphere depends strongly on chemical reactions that regulate the evolution of formaldehyde vapors. Most of the consequence modeling methods and models currently used in the industry usually ignore any reaction phenomena. This article describes a dynamic model developed using the Aspen® Custom Modeling (ACM) tool kit. In the case of formaldehyde solutions, the thermodynamics and reaction kinetics of a mixture of formaldehyde (HCHO), water and methanol (CH3OH) are computed from models available in the open literature. The liquid‐phase, reversible, chemical reactions between water and formaldehyde, as well as methanol and formaldehyde, form oligomers—most of which are nonvolatile. The mass transfer and heat transfer coefficients between the surface of the spill and the atmosphere are computed by established correlations for flow over a semi‐infinite flat surface.
Retail Cost and Energy Adjusted Cost Are Associated with Dietary Diversity and Nutrient Adequacy for Diets of 6–24 Months Children

Poor nutrition during the first two years of life has long term consequences, but resource-poor households often do not have the means to access nutrient-dense and diverse diets. Pooled data of 24-h dietary recalls (n = 3336) and 2019 retail food prices were analyzed to determine associations of retail cost and energy cost (per 100 kcal) with diet quality indicators for diets of 6–24-month-old South African children who were breastfed (BF-diet) and not breastfed (NBF-diet) during the 24-h recall period. Compared to the BF-diet, retail cost for the NBF-diet was three times higher for age 6–11 months, and double for age 12–17 months. Higher retail cost and energy cost were both associated with higher mean adequacy ratios and dietary diversity scores for BF and NBF diets, except energy cost for the NBF-diet for age 6–11 months. Overall, inclusion of flesh foods, vitamin A-rich fruits and vegetables, and other fruit and vegetables increased from the lowest to the highest retail cost tertile. The higher cost of more nutritious diets highlights the importance of the affordability of diets in interventions aimed at improving diet quality. Possible strategies include: identifying the most-affordable foods within each food group, focusing on foods that provide multiple key micronutrients, and the inclusion of locally available indigenous foods.
The Effectiveness of Interventions to Reduce Sedentary Time in Different Target Groups and Settings in Germany: Systematic Review, Meta-Analysis and Recommendations on Interventions

Background: Sedentary behavior is an important risk factor for several chronic diseases and is associated with an increased risk of mortality. We assessed the effectiveness of interventions to reduce sedentary time in Germany and provide recommendations on interventions to reduce sedentary time in children and adults. Methods: We comprehensively searched PubMed, Web of Science and the German Clinical Trials Register up to April 2022 for intervention studies targeting sedentary behavior in Germany. We performed a systematic review and qualitative synthesis of the interventions and a meta-analysis in children. Results: We included 15 studies comprising data from 4588 participants. The results of included primary studies in adults and children showed inconsistent evidence regarding change in sedentary time, with a majority of studies reporting non-significant intervention effects. The meta-analysis in children showed an increase in sedentary time for children in the control and intervention groups. Conclusion: We found inconsistent evidence regarding the effectiveness of interventions to reduce time spent sedentary and our meta-analysis showed an increase in sedentary time in children. For children, we recommend physical and social environment interventions with an active involvement of families. For adults, we recommend physical environment interventions, such as height-adjustable desks at work.