Miracle-dz/UniFAR-FTUs huggingface dataset:
Malassezia pachydermatis from brown bear: A comprehensive analysis reveals novel genotypes and distribution of all detected variants in domestic and wild animals

Malassezia pachydermatis (phylum Basidiomycota, class Malasseziomycetes) is a zoophilic opportunistic pathogen with recognized potential for invasive infections in humans. Although this pathogenic yeast is widespread in nature, it has been primarily studied in domestic animals, so available data on its genotypes in the wild are limited. In this study, 80 yeast isolates recovered from 42 brown bears (Ursus arctos) were identified as M. pachydermatis by a culture-based approach. MALDI-TOF mass spectrometry (MS) was used to endorse conventional identification. The majority of samples exhibited a high score fluctuation, with 42.5% of isolates generating the best scores in the range confident only for genus identification. However, the use of young biomass significantly improved the identification of M. pachydermatis at the species confidence level (98.8%). Importantly, the same MALDI-TOF MS efficiency would be achieved regardless of colony age if the cut-off value was lowered to ≥1.7. Genotyping of LSU, ITS1, CHS2, and β-tubulin markers identified four distinct genotypes in M. pachydermatis isolates. The most prevalent among them was the genotype previously found in dogs, indicating its transmission potential and adaptation to distantly related hosts. The other three genotypes are described for the first time in this study. However, only one of the genotypes consisted of all four loci with bear-specific sequences, indicating the formation of a strain specifically adapted to brown bears. Finally, we evaluated the specificity of the spectral profiles of the detected genotypes. MALDI-TOF MS exhibited great potential to detect subtle differences between all M. pachydermatis isolates and revealed distinct spectral profiles of bear-specific genotypes.
their ideals and their cardinal characteristics

For a free ultrafilter U on ω we study several cardinal characteristics which describe part of the combinatorial structure of U. We provide various consistency results; e.g. we show how to force simultaneously many characters and many π–characters. We also investigate two ideals on the Baire space ω ω naturally related to U and calculate cardinal coefficients of these ideals in terms of cardinal characteristics of the underlying ultrafilter.
Investigating the capability of Sentinel-2 and Worldview-3 SWIR to map the main mineralogical composition of bauxite through spectral unmixing. Case Study: Itea, Greece.

During the last decades, geological remote sensing, including hyperspectral/multispectral data, has grown rapidly in applications such as mineral/ore exploration and mineral resource mapping (Anifadi et al., 2022; Anifadi et al., 2019; van der Meer et al., 2014). Sentinel-2 (S-2) (12 spectral bands within the VNIR-SWIR region of the H/M spectrum), has added new significant capabilities in terms of spatial resolution and spectral information, especially in the VNIR region (Burns, 1993; Clark and Roush, 1984). In parallel, DigitalGlobe’s Worldview-3 (WV3) satellite provides very high spatial resolution (1.24m/pixel in the VNIR and 3.7m/pixel in the SWIR) and eight SWIR bands with valuable information on mineralogy, especially on alteration.
CAPITAL STRUCTURE AND FINANCIAL PERFORMANCE OF MICROFINANCIAL INSTITUTIONS IN NAIROBI CITY COUNTY KENYA

This research was intended to appraise ramification of the capital system on commercial return of micro-financial institutions in Kenya's Nairobi City County. The research was seeking to resolve the following problem. What are the capital structure features used by the MFI? Is there a connection between the composition of capital and the viability of firms? If the business size has an impact on earnings before tax? The study was motivated by the following capital structure theories, which are the theory of Modigliani and Miller, standard theory, the theory of net income method and the theory of net operating income approach. To define the independent variable, the researcher used a descriptive analysis design. To explicate sequel of predictor variables on the responding variables, explanatory research may also be used. The target demographic of the research is to be all 14 successful microfinance companies as recognized by the Kenya Microfinance Act as of 2020. The research therefore represents a census survey with a period of 5 years (from 2014-2018). The study's research model consisted of the independent variable debt ratio, the equity ratio and the size of the company as a moderating variable, determined by the company's gross asset value, and the following ratios as dependent variables: return on equity. To analyze the results, Stata will be used. There will be descriptive and inferential statistics execution. The gradation of correlation allying to covariate parameter and responding parameter used in the sample will be defined by regression analysis. A certain diagnostic result can be calculated before the study is completed. Out-turn in the form of tables and graphs will then be displayed. The inferential
Voice-Assisted Real-Time Traffic Sign Recognition System Using Convolutional Neural Network

—Traffic signs are important in communicating information to drivers. Thus, comprehension of traffic signs is essential for road safety and ignorance may result in road accidents. Traffic sign detection has been a research spotlight over the past few decades. Real-time and accurate detections are the preliminaries of robust traffic sign detection system which is yet to be achieved. This study presents a voice-assisted real-time traffic sign recognition system which is capable of assisting drivers. This system functions under two subsystems. Initially, the detection and recognition of the traffic signs are carried out using a trained Convolutional Neural Network (CNN). After recognizing the specific traffic sign, it is narrated to the driver as a voice message using a text-to-speech engine. An efficient CNN model for a benchmark dataset is developed for real-time detection and recognition using Deep Learning techniques. The advantage of this system is that even if the driver misses a traffic sign, or does not look at the traffic sign, or is unable to comprehend the sign, the system detects it and narrates it to the driver. A system of this type is also important in the development of autonomous vehicles.
The Construction of Formative Assessment Model for College English

: This thesis proposes a formative assessment model for College English learning. Based on the theory of the constructivism and the theory of multiple intelligences, the assessment model in this paper is a formative one focused on the performance, achievement, study strategy and attitude of the students in their daily learning process. Aiming on promoting the teaching ability of the teacher and the academic achievement of the students, this formative assessment model puts forward detailed methods on assessing the performance of students from four aspects: self-evaluation, peer evaluation; teacher evaluation and portfolio assessment.
Influence of perceived usefulness, perceived ease of use and brand name on online purchase intention among higher learning institutions students

Increasing on E-Commerce has become a popular trading method in the worldwide market. Online shopping is a growing phenomenon that has become a popular means of shopping among higher learning institutions students. However, online marketers do not understand the factors that influence the online purchase intentions among the higher learning institution students. The purpose of this study is to analyze the factors that influence the online purchase intentions among higher learning institutions students in Nilai, Negeri Sembilan, which measured three variables namely perceived usefulness, perceived ease of use, and brand name. A sample of this study included 358 respondents of higher learning institution students from Nilai, Negeri Sembilan, Malaysia. The data was analyzed using the SPSS 25 version and it was noted that the perceived usefulness, perceived ease of use and brand name has a significant influence to the online purchase intention among the higher learning institution students in Nilai, Negeri Sembilan. Therefore, this study also shows that Technology Acceptance Model has a positive effect to influence the higher learning institution students online purchase intention.
Factors influencing the initiation of smoking among Taif University students

Background: Tobacco is a leading source of death worldwide. Objective: estimating the prevalence, age groups, and factors influencing the initiation of smoking and varying types of tobacco. Subjects and methods: 1800 students, 18– 24 years of age, from Taif University voluntarily participated in this study. An electronic questionnaire was administered to all students’ whatsAap groups at Taif University between May and October 2020. Statistical measures were performed using the Statistical Package for Social Studies (SPSS; version 25 for Windows) Results: 1080 students (60%) were non-smokers, while 720 (40%) were smokers. 400 students (55.6%) were males. A significant association existed between gender and smoking as well as (p≤0.001). Males had a higher percentage of smoking. A significant association was existed between pocket money and smoking (p < 0.006). The most frequent places for smoking was at chalets with friends (64.3%), followed by public places (45.3%), the most frequent factors influencing smoking were friends (27.8%), family problems, and stress (22.2%). Conclusions: Reducing the general population's smoking and educating families by observing the friends of their sons and daughters and implementing strong polices were important to be better role models for juveniles.
Dynamics of the Coupled Moist Kelvin-Rossby Wave on an Equatorial

Abstract A simple theoretical analysis on the stability of a resting tropical atmosphere to semigeostrophic perturbations is given using a free atmosphere–boundary layer coupled model on an equatorial β-plane. An unstable mode emerges when sea surface temperature is higher than a critical value. The growing mode is a moist Kelvin wave modified through coupling with a Rossby wave of the lowest meridional index. The modified Rossby modes, however, remain damped even for high SST. The unstable mode selection can be explained in terms of wave energy generation due to the latent heating induced by frictional moisture convergence. The horizontal mode-coupling has profound impacts on wave instability. It favors the amplification of long planetary-scale waves, slows down eastward propagation, and suppresses unrealistically fast growth of the uncoupled moist Kelvin mode by creating substantial meridional flows. These effects make the coupled unstable mode more resemble observed equatorial intraseasonal disturbance.
I.—On a Problem concerning Matrices with Variable Diagonal Elements.

Suppose that in a given non-negative definite symmetric matrix R = [ r ij ] of order n the diagonal entries are replaced by arbitrary quantities x 1 , x 2 ,…, x n so that the matrix assumes the form Matrices of this type are met with in the statistical technique known as Factorial Analysis (Thurstone, 1935; Thomson, 1939); there the nondiagonal elements r ij ( i≠j ) are the correlation coefficients of certain tests and are given by observation. The diagonal entries of the “correlational matrix,” which is always non-negative definite, are originally all equal to unity, but, on the hypothesis which underlies the process of Factorial Analysis, it is permissible to diminish the diagonal entries arbitrarily provided the modified matrix is still non-negative definite , it being assumed that the amount which has been deducted from the diagonal cells is due to the variance of the specific factors, the investigation of which is not the primary aim of the theory.
Constraining the Black Hole Spin of Arakelian 120

A ~100ks Suzaku observation (4 April 2007) of the Arakelian 120 (Ark 120) bare Seyfert 1 galaxy produces an X-ray spectrum with features from a soft excess, hard excess, and extended structure in the iron line band (Nardini et al. 2011). We compare this to the previously examined (Patrick et al. 2011) ~112ks XMM-Newton observation (24 August 2003). We model the spectrum by first building a phenomenological model using blackbody, Gaussian, and accretion disk components with and without relativistic effects convolved. Then, we allow a black hole spin parameter to vary freely within a self-consistent physical model that assumes all three excess features result from the same Comptonization process. As bare Seyferts lack substantial volumes of photoionized gas near their central regions, the possibility of absorption features masking the intrinsic properties of our spectral continuum is remote. With the advantage of multi-epoch and multi-instrument data, we make constrain the spin of the supermassive black hole at the center of Ark 120 to be
Analysis of Neural Network on Bank Marketing Data

: This paper describes the implement of a typical neural network on a bank marketing data. We used both encrypted data and decrypted data to train the model, and comparisons were made from the results. We discussed about whether the decrypting technique improves the model. This paper also compared our method with another method that uses the same dataset. The comparisons were made and the results was discussed. By analyzing these comparisons, we made some conclusions and planned on the future work.
A NEW FINITE ELEMENT APPROXIMATION OF A STATE-CONSTRAINED OPTIMAL CONTROL PROBLEM

In this paper, we study numerical methods for an optimal control problem with point-wise state constraints. The traditional approaches often need to deal with the delta-singularity in the dual equation, which causes many difficulties in its theoretical analysis and numerical approximation. In our new approach we reformulate the state-constrained optimal control as a constrained minimization problems only involving the state, whose optimality condition is characterized by a fourth order elliptic variational inequality. Then direct numerical algorithms (nonconforming finite element approximation) are proposed for the inequality, and error estimates of the finite element approximation are derived. Numerical experiments illustrate the effectiveness of the new approach.
REALIZED VOLATILITY MODEL FOR MARKET RISKMEASUREMENT IN INDONESIA STOCK EXCHANGE

This paper discussed the testing of Realized Volatility (RV) model.The model was formulated based on intraday stock price data and interday stock price on the Indonesian Stock Exchange. At first, the idea of this research came when researcher looked back at the gambling factor in Indonesia Stock Market.The stocks price moved up and down with highly volatility and not in a normal pattern. Reflection of heteroskedasticity is in stocks price movement. For the investors in stock market it is the risk when the trend of market cannot be predicted, accurately and effectively. Of course investors will need tools to minimize market risk, optimally. In the first observation, found a signal that the behavioral finance of investor influenced the stock price trend, from morning session until the market closed in the afternoon. However, the available tools to measure the price volatility of the shares was originally known ARCH (autoregressive conditionally heteroskedasticity) model, the model by using the closing price of stocks. Based on the ARCH structure, it cannot be used to have the optimal results of lower risk in highly frequency data. To solve that problem, need to formulate the new approach by combining the intraday risk measurement with interday risk measurement which ARCH Model cannot provide it. The proposed model is Realized Volatility. Realize Volatility model is the model with combination between intraday volatility and interday volatility. This mathematical combination must use high frequency data, then the available tools cannot be used. In the process of research, not only the ARCH model, but also the ARIMA (Autoregressive Integrated Moving Average) as the tools to test the model also cannot be used because the data is high frequency data. In this research used ARFIMA (Autoregressive Fragtionally Integrated Moving Average) to test the accuracy of the models, to replace the ARIMA. The result of this research is that RV model provided more accurate measurement than ARCH model. RV model will be helpful for investors who want to select the stocks with lower market risk. RV model also can help a treasury manager in banking sector to assess and minimize market risk of foreign exchange, as well as can help fund manager select lower risk stocks and lower risk mutual fund.
Research Progress on Privacy-Preserving Techniques in Big Data Computing Environment

The widespread deployment and application of distributed big data computing environments, such as batch processing, streaming computing, and machine learning in cloud, have brought great convenience to users for efficiently processing massive amounts of data, but the accompanying leakage incidents of privacy data have intensified. How to protect data privacy in such a big data computing environment deployed in cloud has become a research hotspot. This paper provides a comprehensive overview of the latest research achievements and progress of big data privacy protection in this field, mainly including domestic and foreign research work in recent years. Firstly, we introduce the participating roles and application scenarios in the above-mentioned big data computing environment. Combining the adversary models of different roles, starting from the three links of data input, computation, and output involved in the distributed computing process, privacy issues are divided into three categories: privacy leakage of native individual data during the data input stage, private data being stolen by attacker during the data computation process, and sensitive information being maliciously inferred by
The Role of Emotions and Tensions

The research on teacher professional identity mostly focused on the process of teacher professional identity formation, the characteristics of teacher professional identity according to the teachers themselves as well as the researchers, and the representation of professional identity through teacher narratives in written and spoken discourse (Beijaard et al., 2004). However, there is much to explore in teachers’ tensions and emotions regarding the issues between teacher cognition, and personal and professional sides of teacher identity (Day & Leitch, 2001). In this chapter, we have reviewed the literature on teacher professional identity in relation to communities of practice, imagined identity, and imagined communities. Various definitions of emotions and tensions as well as their roles in teacher professional identity construction have been presented and relevant studies on teacher identity construction, emotions and tensions have been discussed.
Meniscus draw-up and draining

When a solid plate is removed from a pool of fluid, a film of fluid is attached to the plate. There are two possible outcomes. The edge of the fluid may be raised through a finite distance, with the edge slipping on the plate. Alternatively, a continuous film of a certain thickness may be drawn up. For plates which have a small slope, it is shown that the first alternative holds when the speed of withdrawal is sufficiently small, and that, when a critical speed is exceeded, the height of the edge above the fluid level in the pool increases with time. A related problem concerns the shape of a receding meniscus in a channel. If the static contact angle is small, lubrication theory can be applied to the film of fluid adjacent to the wall of the channel, and the results of this part of the solution can be matched to the central part of the meniscus, which is controlled by capillarity and gravity, but for which lubrication theory does not apply. As in the draw-up problem, for small speeds the shape of the meniscus is time-independent, but above a critical speed, a tail of fluid of increasing length remains in the tube.
Probiotic modulation of gut microbiota by Bacillus coagulans MTCC 5856 in healthy subjects: A randomized, double-blind, placebo-control study

Background: Probiotics are known to rebalance the gut microbiota in dysbiotic individuals, but their impact on the gut microbiome of healthy individuals is seldom studied. The current study is designed to assess the impact and safety of Bacillus coagulans (Weizmannia coagulans) microbial type culture collection 5856 (LactoSpore®) supplementation on microbiota composition in healthy Indian adults. Methods: The study participants (N = 30) received either LactoSpore (2 billion colony-forming units/capsule) or placebo for 28 days. The general and digestive health were assessed through questionnaires and safety by monitoring adverse events. Taxonomic profiling of the fecal samples was carried out by 16S rRNA amplicon sequencing using the Illumina MiSeq platform. The bacterial persistence was enumerated by quantitative reverse transcription-polymerase chain reaction. Results: Gut health, general health, and blood biochemical parameters remained normal in all the participants. No adverse events were reported during the study. Metataxonomic analysis revealed minimal changes to the gut microbiome of otherwise healthy subjects and balance of Bacteroidetes and Firmicutes was maintained by LactoSpore. The relative abundance of beneficial bacteria like Prevotella, Faecalibacterium, Blautia, Megasphaera, and Ruminococcus showed an increase in probiotic-supplemented individuals. The quantitative polymerase chain reaction analysis revealed highly variable numbers of B. coagulans in feces before and after the study. Conclusion: The present study results suggest that LactoSpore is safe for consumption and does not alter the gut microbiome of healthy individuals. Minor changes in a few bacterial species may have a beneficial outcome in healthy individuals. The results reiterate the safety of B. coagulans microbial type culture collection 5856 as a dietary supplement and provide a rationale to explore its effect on gut microbiome composition in individuals with dysbiosis.
Optical parametric oscillator based on the periodically poled MgO:LN crystal with 4.1 μm wavelength and varied pulse duration

ABSTRACT The generation of optical parametric oscillator (OPO) at 4.1 μm in the periodically poled MgO doped congruent lithium niobate (MgOLN) single crystal was studied and tested. The stable domain structure with period 28.48 μm was produced in 2-mm-thick wafer by multi-pulse periodical poling at elevated temperature. The Nd:YAG laser was used as a pumping source. The OPO was realized by single resonant scheme with two-mirror cavity. The average power at the generated idler wavelength 70 mW was achieved for 5 W average pump power and pulse duration 10 ns. The produced OPO can be used for diagnostic equipment.
Sibling and Peer Victimization

symptoms; Erath et al., 2007; Kochenderfer-Ladd, 2004; Machmutow et al., 2012; Singh & Bussey, 2011; Sugimura et al., 2014). Limited research indicates that coping strategies are associated with subsequent peer victimization (Cooley et al., 2022; Frisén et al., 2012; Smith et al., 2004a, b), and peer victimization is linked to subsequent coping strategy use (Kochenderfer-Ladd, 2004). However, more research examining bidirectional associations with peer victimization and sibling victimization is needed to understand the nature of these associations and refine prevention and intervention efforts. Accordingly, the current study examines bidirectional associations between both sibling and peer victimization and coping strategies over an academic year during middle childhood, allowing for the direct comparison between peer and sibling associations.