Miracle-dz/UniFAR-FTUs huggingface dataset:
Efficacy and Safety of Different Drug Regimens for Tuberculosis Preventive Treatment: A Systematic Review and Meta-Analysis

Tuberculosis prevention treatment (TPT) is crucial to the eradication of tuberculosis (TB). Through a comprehensive review and meta-analysis, we compared the efficacy and safety of different TPT regimens. We searched PubMed, Google Scholar, and medrxiv.org with search terms Tuberculosis Preventive Treatment, TPT, efficacy, safety, and drug regimens for TPT and all RCT, irrespective of age, setting, or co-morbidities, comparing at least one TPT regimen to placebo, no therapy, or other TPT regimens were screened and those reporting either efficacy or safety or both were included. The meta-analysis data were synthesized with Review Manager and the risk ratio (RR) was calculated. Out of 4465 search items, 15 RCTs (randomized-controlled trials) were included. The TB infection rate was 82/6308 patients in the rifamycin plus isoniazid group (HR) as compared to 90/6049 in the isoniazid monotherapy (H) group (RR: 0.89 (95% CI: 0.66, 1.19; p=0.43). A total of 965/6478 vs 1065/6219 adverse drug reactions (ADRs) occurred in HR and H groups respectively (RR: 0.86 (95%CI: 0.80 0.93); P<0.0001). Efficacy analysis of the rifampicin plus pyrazinamide (RZ) vs H showed that the risk ratio of infection rate was not considerably varied (RR: 0.97 (95% CI: 0.47, 2.03); P=0.94). Safety analysis showed in 229/572 patients developed ADRs in rifampicin plus pyrazinamide as compared to 129/600 ADRs in the isoniazid group. (RR: 1.87 (95% CI: 1.44, 2.43)). Safety analysis of only rifamycin (R) vs H group showed 23/718 ADRs in R vs 57/718 ADRs in H group (RR: 0.40 (95% CI: 0.25 0.65); P=0.0002). Rifamycin plus isoniazid (3HP/R) has no edge over other regimens in terms of efficacy but this regimen was found significantly safer as compared to any other regimens used for TPT. Rifampicin plus pyrazinamide (RZ) was found equally efficacious but less safe as compared to other regimens.
Ependyma in Neurodegenerative Diseases, Radiation-Induced Brain Injury and as a Therapeutic Target for Neurotrophic Factors

The neuron loss caused by the progressive damage to the nervous system is proposed to be the main pathogenesis of neurodegenerative diseases. Ependyma is a layer of ciliated ependymal cells that participates in the formation of the brain-cerebrospinal fluid barrier (BCB). It functions to promotes the circulation of cerebrospinal fluid (CSF) and the material exchange between CSF and brain interstitial fluid. Radiation-induced brain injury (RIBI) shows obvious impairments of the blood–brain barrier (BBB). In the neuroinflammatory processes after acute brain injury, a large amount of complement proteins and infiltrated immune cells are circulated in the CSF to resist brain damage and promote substance exchange through the BCB. However, as the protective barrier lining the brain ventricles, the ependyma is extremely vulnerable to cytotoxic and cytolytic immune responses. When the ependyma is damaged, the integrity of BCB is destroyed, and the CSF flow and material exchange is affected, leading to brain microenvironment imbalance, which plays a vital role in the pathogenesis of neurodegenerative diseases. Epidermal growth factor (EGF) and other neurotrophic factors promote the differentiation and maturation of ependymal cells to maintain the integrity of the ependyma and the activity of ependymal cilia, and may have therapeutic potential in restoring the homeostasis of the brain microenvironment after RIBI or during the pathogenesis of neurodegenerative diseases.
Context awareness based Sketch-DeepNet architecture for hand-drawn sketches classification and recognition in AIoT

A sketch is a black-and-white, 2-D graphical representation of an object and contains fewer visual details as compared to a colored image. Despite fewer details, humans can recognize a sketch and its context very efficiently and consistently across languages, cultures, and age groups, but it is a difficult task for computers to recognize such low-detail sketches and get context out of them. With the tremendous increase in popularity of IoT devices such as smartphones and smart cameras, etc., it has become more critical to recognize free hand-drawn sketches in computer vision and human-computer interaction in order to build a successful artificial intelligence of things (AIoT) system that can first recognize the sketches and then understand the context of multiple drawings. Earlier models which addressed this problem are scale-invariant feature transform (SIFT) and bag-of-words (BoW). Both SIFT and BoW used hand-crafted features and scale-invariant algorithms to address this issue. But these models are complex and time-consuming due to the manual process of features setup. The deep neural networks (DNNs) performed well with object recognition on many large-scale datasets such as ImageNet and CIFAR-10. However, the DDN approach cannot be carried out for hand-drawn sketches problems. The reason is that the data source is images, and all sketches in the images are, for example, ‘birds’ instead of their specific category (e.g., ‘sparrow’). Some deep learning approaches for sketch recognition problems exist in the literature, but the results are not promising because there is still room for improvement. This article proposed a convolutional neural network (CNN) architecture called Sketch-DeepNet for the sketch recognition task. The proposed Sketch-DeepNet architecture used the TU-Berlin dataset for classification. The experimental results show that the proposed method beats the performance of the state-of-the-art sketch classification methods. The proposed model achieved 95.05% accuracy as compared to existing models DeformNet (62.6%), Sketch-DNN (72.2%), Sketch-a-Net (77.95%), SketchNet (80.42%), Thinning-DNN (74.3%), CNN-PCA-SVM (72.5%), Hybrid-CNN (84.42%), and human recognition accuracy of 73% on the TU-Berlin dataset.
Efeitos da migração na infância sobre a mobilidade intergeracional de educação

Conhecer a influência do background familiar na acumulação de capital humano é essencial para que se possa desenhar políticas públicas voltadas à elevação do nível de escolaridade da população. Este trabalho analisa a mobilidade intergeracional de educação no Brasil segundo a condição de migração. Verificam-se as mudanças no status educacional dos indivíduos que migraram na infância ou início da adolescência do Nordeste para o Sudeste entre as décadas de 1950 e 1980, tendo em vista a importância desse fluxo migratório na história recente do país. Os dados utilizados são provenientes da Pesquisa Nacional por Amostra de Domicílios (PNAD/IBGE) de 2014, que contou com um suplemento de mobilidade sócio-ocupacional. A metodologia do estudo compreende a estimação do grau de persistência intergeracional de educação, mediante um modelo de regressão linear, e o ajuste de um modelo logit ordenado para os níveis de escolaridade alcançados pelos indivíduos. Os resultados contrastam com os obtidos na maior parte da literatura internacional e mostram que o migrante na infância ou primeiros anos da adolescência NE-SE entre as décadas de 1950 e 1980 possuía menor mobilidade intergeracional de educação, quando comparado ao nativo tanto região de origem como de destino.
Modeling Electric Fields in Transcutaneous Spinal Direct Current Stimulation: A Clinical Perspective

Clinical findings suggest that transcutaneous spinal direct current stimulation (tsDCS) can modulate ascending sensitive, descending corticospinal, and segmental pathways in the spinal cord (SC). However, several aspects of the stimulation have not been completely understood, and realistic computational models based on MRI are the gold standard to predict the interaction between tsDCS-induced electric fields and anatomy. Here, we review the electric fields distribution in the SC during tsDCS as predicted by MRI-based realistic models, compare such knowledge with clinical findings, and define the role of computational knowledge in optimizing tsDCS protocols. tsDCS-induced electric fields are predicted to be safe and induce both transient and neuroplastic changes. This could support the possibility to explore new clinical applications, such as spinal cord injury. For the most applied protocol (2–3 mA for 20–30 min, active electrode over T10–T12 and the reference on the right shoulder), similar electric field intensities are generated in both ventral and dorsal horns of the SC at the same height. This was confirmed by human studies, in which both motor and sensitive effects were found. Lastly, electric fields are strongly dependent on anatomy and electrodes’ placement. Regardless of the montage, inter-individual hotspots of higher values of electric fields were predicted, which could change when the subjects move from a position to another (e.g., from the supine to the lateral position). These characteristics underlines the need for individualized and patient-tailored MRI-based computational models to optimize the stimulation protocol. A detailed modeling approach of the electric field distribution might contribute to optimizing stimulation protocols, tailoring electrodes’ configuration, intensities, and duration to the clinical outcome.
Setting Patient-Centered Priorities for Cardiovascular Disease in Central Appalachia: Engaging Stakeholder Experts to Develop a Research Agenda

The disproportionate burden of cardiovascular diseases (CVD) and associated risk factors continues to exist in the Central Appalachian Region (CAR) of the United States. Previous studies to gather data about patient-centered care for CVD in the region were conducted through focus group discussions. There have not been any studies that used a collaborative framework where patients, providers, and community stakeholders were engaged as panelists. The objective of this study was to identify patient-centered research priorities for CVD in the CAR. We used a modified Delphi approach to administer questionnaires to forty-two stakeholder experts in six states representing the CAR between the fall of 2018 and the summer of 2019. Their responses were analyzed for rankings and derived priorities by research gaps. Six of the fifteen research priorities identified were patient-centered. These patient-centered priorities included shorter wait times for appointments; educating patients at their level; empowering patients to take responsibility for their health; access to quality providers; heart disease specialists for rural areas; and lifestyle changes. The participants’ commitments to identify patient-centered research priorities indicate the potential to engage in community-based collaboration to address the burden of CVD in the CAR.
Examining the factors influencing fintech adoption behaviour of gen Y in India

Abstract The main impetus of the research is to inquire into the fintech adoption behaviour of India’s GenY population. The focus of this research paper is to enlarge the scope of the planned behaviour theory by including other exogenous variables, information quality (IQ), and readiness to pay for privileges. Responses from the 349 selected higher education students based on judgmental sampling were collected from various institutes of repute in India. The suggested framework was evaluated using the Smart PLS 4 software bootstrapping method. It was found that multiple hypotheses framed in the study exert notable impact besides the belief that there is a direct linkage between observed behavioural control (OBC) and actual intention (AI). The paper confirms the application of the theory of planned behaviour for the effective implementation of fintech in India. It was observed that information quality is one of the crucial elements which influences the fintech adoption behaviour. The research enriches past studies by expanding the blueprint of a theory of planned behaviour by identifying the information quality factor as the influencing intent and behaviour. The reliability and validity of the suggested framework were analyzed after keeping in mind the impact of a business environment’s constantly changing dynamic forces. The study identified the primary constructs affecting the fintech adoption behaviour with a particular focus on the GEN Y population of India. It will also help the financial technocrats to optimally utilize the immense underlying capabilities of the fintech users and strategically launch more user-friendly products and services.
100-Gb/s/λ PAM-4 EAM-Integrated DBR-LD Supporting Multiple Sub-Channels Within 1.29 μm Window

We present a distributed Bragg reflector-laser diode (DBR-LD) monolithically integrated with an electroabsorption modulator (EAM) offering a 100-Gb/s pulse amplitude modulation 4-level (PAM-4) signal per sub-channel under a CWDM window of 1.29 μm. For the integrated structure, the DBR-LD and EAM were implemented using a trenched waveguide in the tuning sections for achieving energy-efficient wavelength-tuning and a deep ridge waveguide with an optimized structure for a 100-Gb/s PAM-4 operation, respectively. The fabricated chip shows a threshold current of approximately 12 mA and a tuning range of greater than 13 nm, which corresponds to a wavelength band capable of supporting 16 channels with a 150-GHz grid, while maintaining a side mode suppression ratio of greater than 40 dB. In dynamic tests, the results show clear 100-Gb/s PAM-4 eye openings with an outer extinction ratio of more than 4 dB and a transmitter dispersion eye closure quaternary of less than 1.5 dB for all measured channels.
Determination of Chemical Composition and Antimicrobial Activity of the CO2 Extract of Eryngium planum L.

The article presents parameters for obtaining a carbon dioxide extract from the subterranean part of Eryngium planum that contains a valuable set of organic substances and has a certain antimicrobial effect. Methods. Raw materials were collected in the Almaty region (Republic of Kazakhstan). The CO2 extract of Eryngium planum herbs was obtained under subcritical conditions. A gas chromatograph with a mass spectrometric detector was used to determine the compositional breakdown of the extract. Antimicrobial activity was determined by two methods: the micromethod of serial dilutions and the disk-diffusion method. Three microbial test strains were used: Staphylococcus aureus ATCC 6538-P, Escherichia coli ATCC 8739, and Candida albicans ATCC 10231. Results. To extract biologically active substances from the subterranean part of Eryngium planum L. , we have chosen carbon dioxide extraction technology, a technology for processing carbon dioxide (CO2) raw materials, which allows us to extract various substances in high concentrations. Carbon dioxide extraction technology is an effective and environmentally safe way to isolate various biologically active substances contained in medicinal plant raw materials. In the composition of the CO2 extract of Eryngium planum L. 43 components were identified, the main of which are α-linolenic acid, 8.30%; myristic acid, 6.40%; caryophyllene, 6.92%; spatulous, 6.62%; and other main identified compounds and their percentage. Conclusions. The study showed that the CO2 extract of Eryngium planum L. contains biologically active compounds that have a pronounced antimicrobial effect against clinically significant microorganisms, such as Escherichia coli, Staphylococcus aureus, and Candida albicans.
Integrating Solar Photovoltaic Power Source and Biogas Energy-Based System for Increasing Access to Electricity in Rural Areas of Tanzania

Renewable energy is the best option for the challenge of dwindling natural resources and energy scarcity. The utilization of solar photovoltaic (PV) systems is the best option for eliminating the energy deficit in Tanzania due to the available great potential of solar energy. Animal manure is a significant source of waste in rural locations which can be transformed into biogas fuel by an anaerobic process. Livestock and agriculture greatly support economically the majority of the sub-Saharan African (SSA) region’s rural population including Tanzania, and excreta from cattle are beneficial for biogas fuel production. Unfortunately, the high potential of animal waste for generating electricity is underutilized. Integrating solar energy sources and biogas fuel derived from animal manure is useful for mitigating energy shortage, power instability, and environmental issues. Off-grid solar PV biogas-based hybrid microgrid systems for rural electrification applications in the Tanzanian environment are limited, and also, most of the studies are extensively carried out using soft computing tools especially hybrid optimization of multiple energy resources (HOMER) software with limited applications of artificial intelligence (AI) optimization techniques. This paper presents technoeconomic viability analysis for a hybrid renewable energy supply system (HRESS) for the Simboya village in Mbeya region, Tanzania. Off-grid HRESS is designed and optimized to meet the load of the chosen location executed using HOMER software and the grey wolf optimization (GWO) method. The microgrid is anticipated to supply daily maximum demand of 63.41 kW. The residential load profile equals 30 kW representing 50% of the daily demand. Optimization results by the HOMER platform indicate that the system has a total net present cost (NPC) and levelized cost of energy (LCOE) of $106,383.50 and $0.1109/kWh, respectively. Furthermore, this paper presents the optimization and sensitivity analysis results acquired by the GWO method under varied values of Loss of Electrical Power Probability (LEPP). Total NPC and LCOE based on LEPP values of 0, 0.04, and 0.06 are $85,106.8, $79,545.99, and $71,747.36 and $0.0887/kWh, $0.0316/kWh, and $0.0102/kWh, respectively. HRESS is economically and environmentally beneficial for supplying electricity to the selected area and worldwide in similar situations.
Stability of an Underactuated Passive Biped Robot Using Partial Feedback Linearization Technique

This paper discusses the problem of achieving stable walking of a compass gait biped robot on a slope. A reference trajectory for stable walking is generated using Lagrangian dynamics of the biped robot. It is shown that an underactuated robot can follow the reference trajectory using a control law based on feedback linearization with respect to both hip and ankle joints. The results are compared in terms of Mean Square Error (MSE). The validity of the proposed controller is carried out using simulation studies.
Kompetitive Allele Specific PCR Genotyping of 89 SNPs in Romanian Spotted and Romanian Brown Cattle Breeds and Their Association with Clinical Mastitis

Simple Summary In order to improve animals’ resistance to mastitis in subsequent generations and to reduce disease prevalence, one feasible approach could be the genomic selection of cows with the most potentially protective immune responses. In this study, 298 cattle were genotyped for 89 single nucleotide polymorphisms through the Kompetitive Allele Specific PCR. Our findings reveal a significant association of a molecular marker in the BOLA-DRB3 gene with mastitis prevalence in the investigated breeds. This supports previous studies that the BOLA-DRB3 gene represents an important locus affecting resistance to mastitis in cattle. These results contribute to an increase in knowledge and available data regarding the genetic variability of SNPs for udder health in cattle. Abstract Mastitis is the most common production disease in the dairy sector worldwide, its incidence being associated with both cows’ exposure to bacteria and the cows’ genetic make-up for resistance to pathogens. The objective of our study was to analyse 89 missense SNPs belonging to six genes (CXCR2, CXCL8, TLR4, BRCA1, LTF, BOLA-DRB3), which were found to be associated with genetic resistance or susceptibility to mastitis. A total of 298 cattle (250 Romanian Spotted and 48 Romanian Brown) were genotyped by Kompetitive Allele Specific PCR (KASP) and a chi-squared test was used for genetic association studies with clinical mastitis. A total of 35 SNPs (39.3%) among the selected 89 SNPs were successfully genotyped, of which 31 markers were monomorphic. The polymorphic markers were found in two genes: TLR4 (rs460053411) and BOLA-DRB3 (rs42309897, rs208816121, rs110124025). The polymorphic SNPs with MAF > 5% and call rates > 95% were used for the association study. The results showed that rs110124025 in the BOLA-DRB3 gene was significantly associated with mastitis prevalence (p ≤ 0.05) in both investigated breeds. Current results show that the SNP rs110124025 in the BOLA-DRB3 gene can be used as a candidate genetic marker in selection for mastitis resistance in Romanian dairy cattle.
Impacts of Ice Clouds on GPS Radio Occultation Measurements

AbstractMathematical solutions accounting for the effects of liquid and ice clouds on the propagation of the GPS radio signals are first derived. The percentage contribution of ice water content (IWC) to the total refractivity increases linearly with the amount of IWC at a rate of 0.6 (g m−3)−1. Measurements of coincident profiles of IWC from CloudSat in deep convection during 2007–10 are then used for estimating the ice-scattering effects on GPS radio occultation (RO) measurements from the Constellation Observing System for Meteorology, Ionosphere and Climate (COSMIC). The percentage contribution of IWC to the total refractivity from CloudSat measurements is consistent with the theoretical model, reaching about 0.6% at 1 g m−3 IWC.The GPS RO refractivity observations in deep convective clouds are found to be systematically greater than the refractivity calculated from the ECMWF analysis. The fractional N bias (GPS minus ECMWF) can be as high as 1.8% within deep convective clouds. Compared with ECMWF anal.
Issues in the identification, assessment and treatment of children and adolescents with ADHD

Many studies into Attention-Deficit/hyperactivity Disorder (ADHD) have documented that this neurodevelopment disorder may be under-identified. Early diagnosis of children and adolescents with ADHD is important, and consequently school-based interventions represent an essential tool for work in this area. To identify issues in the diagnosis, assessment and treatment of children and adolescents with ADHD, is reviewed here research findings which could lead to significantly better outcomes for children and adolescents with ADHD. Accordingly, we briefly review studies retrieved in a MEDLINE search, using the terms “ADHD”, “identification”, prevalence”, “assessment”, “treatment”, “learning disabilities” and “ADHD” and “comorbidity” combined, as these pinpoint diagnosis, for the years 2009 to 2022. In this respect, the literature reviewed suggests that multiple aspects associated with psychometric features, as well as clinical and/or pharmacological factors should be considered of highly clinical significance in identifying, assessing and treating individuals diagnosed with ADHD. For this reason, it is important to investigate about difficulties immersed in identifying, assessing and treating to children and adolescents with ADHD in different settings.
Automatic recognition and interpretation of finite state automata diagrams

An application capable of reading graphically-encoded information is beneficial to blind or visually impaired students. Such a system needs to recognize and understand visual markings and their arrangement as presented in a diagram image. In that light, this thesis examines the practical possibility of a real world system for the automatic recognition and interpretation of machine-printed Finite State Automata diagrams. The suggested system uses known image processing and pattern recognition methods to extract the visual markings from the diagram image pixels. A second stage, to interpret the meaning of the diagram, is based on modeling the language of Finite State Automata diagrams using Constraint Multiset Grammars. Our results show that a practical application for automatic interpretation of Finite State Automata diagrams is possible. iii Stellenbosch University https://scholar.sun.ac.za