Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluating How the Social Restriction, the Government Response, the Health, and Economic Indices Affected the Prediction of the Number of Deaths Provoked by COVID-19 in Brazil Using Classical Statistical and Machine Learning Models

The COVID-19 death predictions are helpful for the formulation of public policies, allowing the use of more effective social isolation strategies with less economic and social impact. This article evaluates a wide range of forecasting methods to identify the best models for predicting cumulative and daily deaths caused by COVID-19 in Brazil, considering a forecast for a seven-day horizon. With the seven-day horizon, the predictions have more accuracy. The dataset is from Oxford Covid-19 Government Response Tracker. The jackknife resampling technique was implemented, thus providing an accurate estimate for evaluating the predictive capacity of the models. Each model was fitted with 266 jackknife samples considering 30-day training bases. The comparison between predictions was made using the average results, considering R2, MAPE, RMSE, and MAE. Models from different classes were adopted: 1 ETS, 4 ARIMA, 18 regression models, and 7 machine learning algorithms. The cumulative death models produce better results than daily deaths, as the cumulative death models are less influenced by time series components: cycle and seasonality. The best results for predicting daily deaths were attained by the Ridge regression method. The best results for predicting cumulative deaths were obtained by the Cubist regression method © 2022 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY NC) license (https://creativecommons.org/licenses/by-nc/4.0/).
Research on Intelligent Multimedia Distance Teaching System considering Virtual Reality Technology

With the continuous growth of the social economy, teaching methods are constantly innovating and changing, from the traditional subjective single teaching mode to the new teacher-student interactive teaching mode supplemented by various network resources, but there are still some influencing factors in these teaching modes. In view of these deficiencies and needs, for the purpose of addressing the issues of the traditional teaching model such as lack of timeliness, inaccuracy, and high energy consumption, the virtual reality (VR) technology is applied to the intelligent multimedia distance teaching system. Combining the existing teaching requirements and the frame structure of the multimedia distance teaching system design, the hardware and software systems of the system are designed, respectively. User login can be realized through software and hardware system design. Through teaching resources, teaching management, and other functions, the VR technology can be used to complete the reasonable allocation of multimedia teaching resources to enhance multimedia teaching quality effectively. Finally, the test results are analyzed. Compared with other teaching systems, the proposed intelligent multimedia distance teaching system can lower the transmission energy and signal-to-noise ratio (SNR) of teaching resource data effectively, which is of certain practical value.
Influence of vegetation structure, seasonality, and soil properties on rodent diversi community assemblages in west Mount Kilimanjaro, Tanzania

Abstract Rodent diversity and community assemblages are affected by several biotic and abiotic factors such as vegetation structure and seasonality. Vegetation structure particularly ground cover influences rodent diversity and community assemblages through provision of food resources and protection from predators. Such information is important for understanding species–habitat relationships for management and conservation. This study was conducted to determine the influence of vegetation structure, seasonality, and soil properties on species richness, abundance, community assemblages, and habitat association of rodents in west Mt Kilimanjaro. Rodent trapping was conducted using removal and capture–mark–recapture (CMR) methods with medium‐sized Sherman's live traps, snap, and Havarhart traps. Rodents were trapped during wet and dry seasons for three consecutive nights at 4 weeks intervals from April 2020 to March 2021. Environmental variables including vegetation structure, soil physical properties, and disturbance levels were recorded for each habitat type. Fourteen species of rodents were trapped in 25,956 trap nights. Rhabdomys pumilio, Praomys delectorum, and Lophuromys verhageni were the most dominant species across all habitats and seasons. L.verhageni occurred in all habitats while R.pumilio was restricted from occurring in montane forests. Moreover, species richness and abundance were influenced by habitat types, seasonality, soil type, and ground cover. Generally, both species richness and abundance were higher in fallows and montane forests and significantly lower in plantation forest and agricultural fields. In addition, rodent diversity was highest in fallows, followed by montane forests, and lowest in agricultural fields. Furthermore, rodents were associated with habitat types and vegetation structure forming two major community assemblages that significantly differed between habitats. Our study conclude that, community assemblages of rodents on Mt. Kilimanjaro were affected by functional spatial heterogeneity of the habitats occupied. Therefore, use of different habitats by rodents may be indicative of the landscape integrity and ecosystem changes based on species assemblages.
Linguistic modifiers and measures of similarity or resemblance

On the one hand, linguistic modifiers can be used to express imprecise values of variables which are described around a given fuzzy set. On the other hand, measures of comparison of fuzzy sets, such as measures of satisfiability or resemblance for instance, enable us to establish the proximity between two imprecise values of variables. A formal connection between modifiers and measures of comparison is presented, starting from studies about similarity-based systems, on the basis of simple types of modifiers and measures of comparison.
A Novel Approach of SWATH-Based Metabolomics Analysis Using the Human Metabolome Database Spectral Library

Metabolomics is a potential approach to paving new avenues for clinical diagnosis, molecular medicine, and therapeutic drug monitoring and development. The conventional metabolomics analysis pipeline depends on the data-independent acquisition (DIA) technique. Although powerful, it still suffers from stochastic, non-reproducible ion selection across samples. Despite the presence of different metabolomics workbenches, metabolite identification remains a tedious and time-consuming task. Consequently, sequential windowed acquisition of all theoretical MS (SWATH) acquisition has attracted much attention to overcome this limitation. This article aims to develop a novel SWATH platform for data analysis with a generation of an accurate mass spectral library for metabolite identification using SWATH acquisition. The workflow was validated using inclusion/exclusion compound lists. The false-positive identification was 3.4% from the non-endogenous drugs with 96.6% specificity. The workflow has proven to overcome background noise despite the complexity of the SWATH sample. From the Human Metabolome Database (HMDB), 1282 compounds were tested in various biological samples to demonstrate the feasibility of the workflow. The current study identified 377 compounds in positive and 303 in negative modes with 392 unique non-redundant metabolites. Finally, a free software tool, SASA, was developed to analyze SWATH-acquired samples using the proposed pipeline.
Anisotropic stellar structure equations for magnetized stars

The fact that a magnetic field in a fermion system breaks the spherical symmetry suggest that the intrinsic geometry of this system is axisymmetric rather than spherical. In this work we analyze the impact of anisotropic pressures, due to the presence of a magnetic field, in the structure equations of a magnetized quark star. We assume a cylindrical metric and an anisotropic energy momentum tensor for the source. We found that there is a maximum magnetic field that the star can sustain, closely related to the violation of the virial relations.
An improved Dissimilarity-Based Sparse Subset Selection Algorithm

The newly proposed Dissimilarity-Based Sparse Subset Selection (DS3) algorithm can effectively perform clustering of data and select the representative for each cluster simultaneously. It can be formulated as a row-sparsity of membership matrix and minimizing coding loss problem. However, the DS3 algorithm is sensitive to regularization parameter due to the limitation of the used norm for measuring sparse term. To obtain the correct number of representatives and clusters, users need to choose the regularization parameter carefully. In view of this, we consider using the $l_{2,\mathrm{p}}$-norm to replace the norm used to measure the sparsity of membership matrix in DS3, and propose an improved DS3 (IDS3) algorithm. Compared with the original algorithm, IDS3 is more robust to the regularization parameter and can obtain a better clustering in a larger parameter value range. IDS3 can be solved by using the Fixed Point Iteration Method aided Alternating Direction Multiplier Method (FPIM-ADMM) framework. Experimental results on some applications such as video summarization and scene categorization demonstrate that the proposed method is superior to DS3.
SILICON APPLICATION AND MYCORRHIZA INOCULATION PROMOTED LEUCAENA LEUCOCEPHALA GROWTH IN A SOIL HIGHLY CONTAMINATED BY MANGANESE

ABSTRACT: Arbuscular mycorrhizal fungi (AMF) can increase the acquisition of silicon (Si) and, therefore, alleviate the problems caused by metallic toxicity in plants, but this effect remains poorly understood. The objective was to evaluate the influence of Si application on the growth of Leucaena leucocephala inoculated with AMF (Claroideoglomus etunicatum) in a soil contaminated by manganese (Mn). We exposed plants to increasing levels of Si (0, 100, 200 and 400 mg kg-1) in the soil for 90 days. Intermediate levels of Si and AMF inoculation significantly increased shoot and root dry mass, the number of sheets, root system length and mycorrhizal colonization. The abundance of AMF spores decreased linearly with increasing levels of Si applied to the soil, suggesting a low correlation with mycorrhizal colonization. In addition to the higher Mn contents in the shoots and, mainly, in the roots, the combined application of Si and inoculation with AMF significantly reduced foliar toxicity by more than 40%, when compared to the absence of Si and AMF inoculation. Our results demonstrated a synergistic effect of AMF and Si in improving the growth and tolerance of L. leucocephala plants in soil contaminated by Mn. Keywords: heavy metals; stress; remediation; AMF; Mn toxicity. Aplicação de silício e inoculação de micorriza promove crescimento de Leucaena leucocephala em solo altamente contaminado por manganês RESUMO: Os fungos micorrízicos arbusculares (FMA) podem aumentar a aquisição de silício (Si) e, portanto, amenizar os problemas causados ​​pela toxidez metálica nas plantas, mas esse efeito ainda é pouco conhecido. O objetivo foi avaliar a influência da aplicação de Si no crescimento de Leucaena leucocephala inoculada com FMA (Claroideoglomus etunicatum) em solo contaminado por manganês (Mn). Expusemos as plantas a níveis crescentes de Si (0, 100, 200 e 400 mg kg-1) no solo por 90 dias. Níveis intermediários de Si e inoculação de FMA aumentaram significativamente a massa seca da parte aérea e radicular, o número de folhas, o comprimento do sistema radicular e a colonização micorrízica. A abundância de esporos de FMA diminuiu linearmente com o aumento dos níveis de Si aplicados ao solo, sugerindo uma baixa correlação com a colonização micorrízica. Além dos maiores teores de Mn na parte aérea e, principalmente, nas raízes, a aplicação combinada de Si e inoculação com FMA reduziu significativamente a toxidez foliar em mais de 40%, quando comparada à ausência de Si e inoculação de FMA. Nossos resultados demonstraram um efeito sinérgico de FMA e Si na melhoria do crescimento e tolerância de plantas de L. leucocephala em solo contaminado por Mn. Palavras-chave: metais pesados; estresse; remediação; FMA; toxidez por Mn.
Implementation of an all-electron GW approximation based on the projector augmented wave method without plasmon pole approximation: Application to Si, SiC, AlAs, InAs, NaH, and KH

An implementation of the GW approximation (GWA) based on the all-electron projector-augmented-wave (PAW) method is presented, where the screened Coulomb interaction is computed within the random-phase approximation (RPA) instead of the plasmon-pole model. Two different ways of computing the self-energy are reported. The method is used successfully to determine the quasiparticle energies of six semiconducting or insulating materials: Si, SiC, AlAs, InAs, NaH, and KH. To illustrate the method the real and imaginary part of the frequency-dependent self-energy together with the spectral function of silicon are computed. Finally, the GWA results are compared with other calculations, highlighting that all-electron GWA results can differ markedly from those based on pseudopotential approaches.
Isolation of extended‐spectrum β‐lactamase‐producing Escherichia coli from Japanese red fox (Vulpes vulpes japonica)

Antimicrobial resistance is a global concern requiring a one‐health approach. Given wild animals can harbor antimicrobial‐resistant bacteria (ARB), we investigated their presence in 11 fecal samples from wild animals using deoxycholate hydrogen sulfide lactose agar with or without cefotaxime (CTX, 1 mg/L). Thus, we isolated CTX‐resistant Escherichia coli from two Japanese red fox fecal samples. One strain was O83:H42‐ST1485‐fimH58 CTX‐M‐55‐producing E. coli carrying the genes aph(3″)‐Ib, aph(3′)‐Ia, aph(6)‐Id, mdf(A), sitABCD, sul2, tet(A), and tet(B), whereas the other was O25:H4‐ST131‐fimH30 CTX‐M‐14‐producing E. coli carrying mdf(A) and sitABCD and showing fluoroquinolone resistance. Thus, the presence of extended‐spectrum β‐lactamase producers in wild foxes suggests a spillover of ARB from human activities to these wild animals.
Fast Grid State Estimation for Power Networks: An Ensemble Machine Learning Approach

For better managing modern power distribution networks with continuously and dynamically changing grid characteristic induced by e.g. adding new renewable generation or vehicle charging stations, state estimation solutions must be capable of dynamically adapting to such topology changes. However, these solutions use a hand-made static topology model as calculation basis which cannot be easily dynamically adapted to topology changes without editing the underlying network topology model. This process is time-consuming and computationally expensive especially for large grids. In the present paper, we address the problem of grid state estimation by proposing a new machine learning-based solution. It paves the road for generic, accurate and simple state estimation independent of the grid topology and with minimal number of grid parameters. To achieve this, four simulated datasets, namely Balanced Generation-Consumption, Unbalanced Generation, Unbalanced Consumption and Mixed datasets are created representing the most common cases existing in the grid. Unlike other research works in the field of grid state estimation, this work applies ensemble learning, namely boosting, bagging and stacking for predicting the grid state variables. The obtained results are very promising and show that our ensemble-based solution exhibits very good results in terms of time efficiency and accuracy.
Green Biosynthesis of Silver Nanoparticles from Moringa oleifera Leaves and Its Antimicrobial and Cytotoxicity Activities

The plant occupied the largest area in the biosynthesis of silver nanoparticles, especially the medicinal plants, and it has shown great potential in biotechnology applications. In this study, green synthesis of silver nanoparticles from Moringa oleifera leaves extract and its antifungal and antitumor activities were investigated. The formation of silver nanoparticles was observed after 1 hour of preparation color changing. The ultraviolet and visible spectrum, Fourier transform infrared spectroscopy, X-ray diffraction, scanning electron microscopy, and transmission electron microscopy techniques were used to characterize synthesis particles. Ultraviolet and visible spectroscopy showed a silver surface plasmon resonance band at 434 nm. Fourier transform infrared analysis shows the possible interactions between silver and bioactive molecules in Moringa oleifera leaves extracts, which may be responsible for the synthesis and stabilization of silver nanoparticles. X-ray diffraction showed that the particles were a semicubic crystal structure and with a size of 38.495 nm. Scanning electron microscopy imaging shows that the atoms are spherical in shape and the average size is 17 nm. The transmission electron microscopy image demonstrated that AgNPs were spherical and semispherical particles with an average of (50–60) nm. The nanoparticles also showed potent antimicrobial activity against pathogenic bacteria and fungi using the well diffusion method. Candida glabrata found that the concentration of 1000 μg/mL exhibited the highest inhibition. As for bacteria, the concentration of 1000 μg/mL appeared to be the inhibition against Staphylococcus aureus. Moringa oleifera AgNPs inhibited human melanoma cells A375 line significant concentration-dependent cytotoxic effects. The powerful bioactivity of the green synthesized silver nanoparticles from medical plants recommends their biomedical use as antimicrobial as well as cytotoxic agents.
Targeting of the Mitochondrial TET1 Protein by Pyrrolo[3,2-b]pyrrole Chelators

Targeting of epigenetic mechanisms, such as the hydroxymethylation of DNA, has been intensively studied, with respect to the treatment of many serious pathologies, including oncological disorders. Recent studies demonstrated that promising therapeutic strategies could potentially be based on the inhibition of the TET1 protein (ten-eleven translocation methylcytosine dioxygenase 1) by specific iron chelators. Therefore, in the present work, we prepared a series of pyrrolopyrrole derivatives with hydrazide (1) or hydrazone (2–6) iron-binding groups. As a result, we determined that the basic pyrrolo[3,2-b]pyrrole derivative 1 was a strong inhibitor of the TET1 protein (IC50 = 1.33 μM), supported by microscale thermophoresis and molecular docking. Pyrrolo[3,2-b]pyrroles 2–6, bearing substituted 2-hydroxybenzylidene moieties, displayed no significant inhibitory activity. In addition, in vitro studies demonstrated that derivative 1 exhibits potent anticancer activity and an exclusive mitochondrial localization, confirmed by Pearson’s correlation coefficient of 0.92.
Agrupamento de Imagens Tumorais de MRI utilizando Extração de Descritores baseados em Séries Temporais

Na categoria de tumores com localização primária no cérebro, os gliomas são os mais comuns e agressivos. A identificação desses tumores junto ao tratamento precoce é a chave para o bem estar do paciente. Neste artigo é proposto um método para a representação de imagens como séries temporais, descritores do formato do tumor, e a utilização de métodos de agrupamento utilizando as distancias euclidiana e DTW, obtendo um coeficiente de silhueta de 0,639 com a distancia DTW, agrupando 60% dos casos. Os experimentos realizados mostraram resultados preliminares que precisam ser avaliados por especialistas do domínio.
Topological supersymmetry breaking: The definition and stochastic generalization of chaos and the limit of applicability of statistics

The concept of deterministic dynamical chaos has a long history and is well established by now. Nevertheless, its field theoretic essence and its stochastic generalization have been revealed only very recently. Within the newly found supersymmetric theory of stochastics (STS), all stochastic differential equations (SDEs) possess topological or de Rahm supersymmetry and stochastic chaos is the phenomenon of its spontaneous breakdown. Even though the STS is free of approximations and thus is technically solid, it is still missing a firm interpretational basis in order to be physically sound. Here, we make a few important steps toward the construction of the interpretational foundation for the STS. In particular, we discuss that one way to understand why the ground states of chaotic SDEs are conditional (not total) probability distributions, is that some of the variables have infinite memory of initial conditions and thus are not “thermalized”, i.e., cannot be described by the initial-conditions-independent .
Pathology and Characterization of Fowlpox Virus Infection in a Turkey-Chicken Backyard Flock, Nigeria

Cutaneous scabs were seen on the nares and shanks in three grower turkeys in a mixed turkey-chicken flock in Langtang-north LGA of Plateau State, Nigeria. A chicken in the flock had diphtheritic membrane covering the mucous membranes of the oro-pharynx and the turkeys had cutaneous pox lesions on the nares and shank. Fowlpox virus infection was diagnosed by gross and histopathology and confirmed by isolation of the virus in chorioallantoic membrane of 9-12 weeks chicken embryonating eggs. The DNA of Fowl Pox Virus (FPV) was detected in the cutaneous scabs of the turkey and chicken using Polymerase Chain Reaction (PCR) which amplified a 578 base pairs fragment of the 4b core protein gene. Sequencing and phylogenetic analysis revealed that the fowlpox virus responsible for this infection clustered with the sublineage A1 genotype of clade A of fowlpox virus and shares 98% homology with the vaccine strain produced in Nigeria. The sequence has been deposited in the GenBank under the accession number MK435242. Our results confirmed the presence of FPV in the turkeys and suggest a predisposition by the chickens. We therefore suggest vaccination for small holder poultry to mitigate against mortality in turkeys and chickens and molecular epidemiology of fowlpox viruses in Nigeria to unravel viral evolution.
Contending with the unforeseen “messiness” of the qualitative data analysis process

Qualitative data analysis (QDA) is often depicted as a linear process that employs an organised structure to derive themes inductively or deductively. However, I realised the “messiness” of the process during my doctoral studies on primary teachers’ use of digital technologies in ESL classrooms in Maldivian schools. My own experience revealed that QDA is a nonlinear, iterative and recursive process. Adopting a phenomenological research design to capture my nine participants’ “lived” experiences, I gathered data from various sources over eight months. Shared through this paper is a selection of my experiences that exemplify the nonlinearity of QDA, including the emergent need to develop an NVivo-enhanced Spiral-QDA process to accommodate my unforeseen data analysis experience. Therefore, reflections from my doctoral research experiences may be edifying and helpful for postgraduate students and supervisors in their own QDA process.