Miracle-dz/UniFAR-FTUs huggingface dataset:
Revealing the Microbiome of Four Different Thermal Springs in Turkey with Environmental DNA Metabarcoding

Simple Summary The physicochemical conditions of thermal springs are one of the most significant barriers for detecting microbial life. According to the findings of various studies, high-throughput DNA sequencing technology can be utilized to perform more precise and detailed microbiome assessments. The main goal of this paper was to determine the microbiome in a thermal spring by metabarcoding environmental DNA obtained from four different sources and revealing how temperature and chemical composition affect the microbiome. This research also aimed to gather information that will aid in determining the best gene region and bioinformatic pipeline. The findings revealed a link between four different thermal springs’ physicochemical parameters and microbial composition and we found various manipulable steps in this study. This research is also first comprehensive thermal spring metabarcoding study conducted in Turkey. Abstract One of the most significant challenges for detecting microbial life in thermal springs by conventional techniques such as culturing is these places’ physicochemical (temperature, heavy metal content, pH, etc.) conditions. Data from several studies suggest that high-throughput DNA sequencing technologies can be used to perform more accurate and detailed microbiome analyses. The primary aim of this paper was to determine the microbiome in the thermal source by metabarcoding environmental DNA isolated from four different sources and reveal the reflection of differences caused by temperature and chemical content on the microbiome. DNA was extracted from water filtered with enclosed filters and using the Illumina high-throughput sequencing platform, V3 and V4 regions of the 16S rRNA gene were sequenced. The results showed a correlation between physicochemical conditions and microorganism composition of four different thermal springs. Springs with extremely high temperature (89–90 °C) were dominated by hyperthermophiles such as Hydrogenobacter and Thermus, while a spring with a high temperature (52 °C) was dominated by thermophiles such as Thermoanaerobaculum and Desulfurispora, and a spring with a low temperature (26 °C) and high salinity was dominated by halophiles and sulfur-oxidizers such as Hydrogenovibrio and Sulfirimonas. With this research, we observed many manipulable steps according to the work of interest. This study sought to obtain data that will help decide the right gene region and choose the optimal bioinformatic pipeline.
IS THE FINANCIAL PERFORMANCE AFFECTED BY BOARD CHARACTERISTICS DURING COVID-19? EVIDENCE FROM THE ENERGY INDUSTRY

This paper aims to examine the impact of board’s characteristics on the financial performance of firms operating in the energy industry, during a certain and uncertain time. For this purpose, we chose four board’s characteristics: duality of the CEO, size of the board, the board meetings and board’s independence, which represent our independent variables. For measuring financial performance, we chose the Return of Assets (ROA) and Return of Equity (ROE) ratios. The data used was collected from Refinitiv Eikon database and includes a sample of 359 companies, for the period 2018-2021. The SPSS statistical program was used to run the regression model on the selected sample. This study provides mixed results on the impact on board’s characteristics on the financial performance of companies operating in the energy industry. During certain time, CEO duality and board’s meetings are negatively correlated with ROE, but positively correlated with ROA. The size and board’s independence negatively affect the financial performance of companies for both ROA and ROE before and during COVID-19. This article contributes to previous studies conducted on the link between corporate governance and firm financial performance, showing mixed results. The results obtained may help management companies to carry out their corporate governance.
A method for discriminating travel reviews from commercial speech

This paper presents a computational method for discriminating travel reviews from commercial speech. Today many travel reviews can be found on the Web. Mining useful information from these reviews is important not only for consumers but also for companies like travel agencies. Travel reviews written by ordinary people are essentially different from commercial speech like advertisements generated by companies and individuals for the intent of making a profit. We propose a computational method for discriminating travel reviews from commercial speech. Assuming that subjective words often occur in travel reviews rather than commercial speech texts, we define the subjectivity score of each word in a document. Evaluating the total subjectivity score of a document using all the words in the document, the proposed method identifies whether the document is classified as travel review or not. From experiments, we have confirmed the proposed method can accurately classify documents into travel reviews and commercial speech texts.
Study on fluid mobility in sandwich-type shale oil reservoir using two-dimensional nuclear magnetic resonance approaches

ABSTRACT Regarding sandwich-type shale oil reservoir characterized by diversified lithologies and complex fluid mobility, we combined one- and two-dimensional (1D and 2D) nuclear magnetic resonance (NMR) core analysis techniques to quantitatively study the movable oil and fluid saturations of rock samples with different lithologies. First, we used 2D T1-T2 NMR to analyze the spectrum curve of the dolomitic mudstone and siltstone samples from a sandwich-type shale oil reservoir at initial and oil-saturated states. We evaluated the occurrence of movable oil saturations in source and reservoir rocks. Then, we analyzed samples of the siltstone serving as the reservoir rock using a centrifuge combined with 1D NMR approach to evaluate the characteristics of movable fluid saturations inside the reservoir. The results showed that the samples of dolomitic mudstone serving as the source rock in the sandwich-type shale oil reservoir in the Lucaogou Formation in Jimsar had the occurrence of kerogen and bitumen signals, the development of small- and medium-scale organic matter pores, and an average movable oil saturation of 15.6%. The siltstone serving as the reservoir rock had an average movable oil saturation of 53.8%, and its movable fluid saturation was positively correlated with porosity and permeability. For samples whose porosity was greater than 12% and permeability was greater than 0.1 mD, their movable fluid saturations usually were higher than 40%. Therefore, siltstone was the preferable diagenetic facies for the development of high-quality reservoirs.
Informal mentorship of new engineers in the workplace

Despite the long history of apprenticeship in engineering (Wilson, 1965), little is understood about the transition from school to work in the modern engineering workforce. How do new engineers gain experience and knowledge while also gaining trust and establishing themselves with more senior engineers and their company? In this work we draw on a large ethnographic study of new engineers in their first year on the job to characterize the role and nature of apprenticeship-like training in the modern engineering workforce. In our analysis, apprenticeship on the job appears to be mostly ad hoc and fleeting with rare instances of direct intentional instruction (as opposed to in-the-moment correction or feedback). Furthermore, learning arrangements between new and more senior engineers are constrained by several factors, including the rigidity of organizational hierarchy, the thoroughness of division of labor, and the senior engineers willingness to actively mentor. For example, we see how new engineers attempt to gain knowledge and experiences from more senior engineers, but are often rebuked due to corporate structure and hierarchy. Yet, at the same time, we see examples of new engineers successfully finding senior co-workers who recognize the importance of training them to navigate these restrictive structures and hierarchies for the benefit of not only the new engineer, but also the senior engineer and the company itself. We find a variety of learning arrangements, including isolated new engineers struggling to find a place in their new work, while also learning new skills, and fully collaborative work between new and senior engineers. We use these findings to suggest ways that engineering schools and companies can help support and enrich the learning of new engineers in the workforce.
A Review on Concurrency Control Techniques in Database Management Systems

: Conflicts, deadlock and rolled-back transactions are being considered as the most recent challenges related to executing the transaction concurrently on different environments of Database Management Systems (DBMS). More precisely, in distributed database systems, to handle and avoid these challenges, there are different techniques and protocols are utilized. In this paper, we highlight some of these techniques which includes Two-Phase Commit (2PC) protocol and Three-Phase Commit (3PC) protocol) as well as and Deadlock-Free Cell lock (DFCL) algorithm. Moreover, the paper surveys all these protocols and demonstrate the pros and cons of each techniques. Afterwards, we proposed the solution of some important problems related to concurrency control techniques in DBMS
Regular Use of Cannabis in Female Athletes Is Associated With a Reduction in Early Anaerobic Power Production

Abstract Lisano, JK, Flores, VA, Kisiolek, JN, and Stewart, LK. Regular use of cannabis in female athletes is associated with a reduction in early anaerobic power production. J Strength Cond Res 37(3): 616–622, 2023—Despite a growing number of claims related to the ability of cannabis use to affect health and performance, there is limited research available, especially in female athletes. This cross-sectional study aimed to determine whether chronic cannabis use in physically active female athletes is related to altered health and performance. Healthy, physically active, female cannabis users (CU: n = 12) and noncannabis users (NU: n = 12) with an average age of 23.8 ± 3.7 years and 19.3 ± 4.2% body fat completed athletic performance and health assessments. Significance was set at alpha = 0.05. The age of onset of regular cannabis use was 20.1 ± 2.8 years in CU with an average duration of cannabis use of 5.8 ± 3.1 years. There were no differences between groups with respect to body size, body composition, pulmonary function, cardiorespiratory function, or muscular strength. Cannabis users produced significantly less power in the first 2 stages of the Wingate assessment, but CU experienced significantly less anaerobic fatigue. Although body composition and cardiovascular fitness were comparable, average C-reactive protein concentration classified CU with higher risk for cardiovascular disease (CVD). Athletes and coaches who rely heavily on anaerobic performance should consider these findings because they indicate that regular cannabis use may affect early power production and CVD risk.
What Makes People Reoffend? Predictors of Reconviction – A 2-year Longitudinal Study

ABSTRACT Male offenders constitute a substantial proportion of the whole male prison population. A comparison of recidivism rates in the entire world shows that the return to criminal behavior ranges from 9% to even 79%. Recent studies indicate that a risk for criminal reoffending is based on many different factors. The aim of the study was to determine the influence of personality, criminal thinking styles, stress coping styles, moral feelings, some aspects of socialization and crime characteristics on reoffending. This longitudinal study was conducted twice over the course of two years and involved 247 male prison inmates housed in 20 Polish prisons. Recidivism and other penitentiary data were obtained from administrative records. Independent sample t-tests were used to indicate differences between recidivists and non-recidivists. Logistic multiple linear regression analyses were used to test the potential predictive value of the potential risk factors for recidivism. The overall recidivism rate was 35%. The study findings showed that sentimentality, shame, the type of the correctional facility, the criminal record, and the type of the inmate’s upbringing had an impact on recidivism while therapeutic methods and a sense of contrition could decrease the probability of reoffending.
Optically Transparent Polydimethylsiloxane-Ethylene Oxide-Propylene Oxide Multiblock Copolymers Crosslinked with Isocyanurates as Organic Compound Sorbents

New crosslinked (polydimethylsiloxane-ethylene-propylene oxide)-polyisocyanurate multiblock copolymers (MBCs) were synthesized, and their supramolecular structure and sorption characteristics were studied. It was found that the interaction of PPEG and D4 leads to polyaddition of D4 initiated by potassium-alcoholate groups. The use of the amphiphilic silica derivatives associated in an oligomeric medium (ASiPs) leads to structuring of the MBC due to the transetherification reaction of the terminal silanol groups of the MBC with ASiPs. It was established that the supramolecular structure of an MBC is built according to the “core-shell” structure. The obtained polymers were tested as sorbents for the development of new methods for the concentration and determination of inorganic compounds. The efficiency of sorption of reagents increased with an increase in the “thickness” of the polydimethylsiloxane component of the “shell” and with a decrease in the size of the polyisocyanurate “core”. The use of the obtained polymers as adsorbents of organic reagents is promising for increasing the efficiency of field methods of chemical testing and inorganic analysis, including the determination of the elemental composition and the detection of traces of contamination.
Dose Conversion Between Animals and Humans: A Practical Solution

Selecting the most appropriate first-in-human and pharmacologically active dose for any new drugs or biologicals is a crucial step before starting a clinical trial investigation in adult healthy human subjects. Extrapolation of dose between various rodent and non-rodent animal species is critical for biomedical researchers during initial drug development. The objective of this review is to provide practical guidance on how allometric scaling based on the body surface area normalization can be effectively utilized for dose conversion between various animal species. The standard conversion factors are included to allow dose translation between animals to humans and humans to animals expressed either in mg/kg or mg/m 2 . The estimation of a safe starting dose is important to ensure the safety and tolerability of humans during phase-I clinical trials.
Evaluation of Machine Learning Algorithms for Classification of EEG Signals

In brain–computer interfaces (BCIs), it is crucial to process brain signals to improve the accuracy of the classification of motor movements. Machine learning (ML) algorithms such as artificial neural networks (ANNs), linear discriminant analysis (LDA), decision tree (D.T.), K-nearest neighbor (KNN), naive Bayes (N.B.), and support vector machine (SVM) have made significant progress in classification issues. This paper aims to present a signal processing analysis of electroencephalographic (EEG) signals among different feature extraction techniques to train selected classification algorithms to classify signals related to motor movements. The motor movements considered are related to the left hand, right hand, both fists, feet, and relaxation, making this a multiclass problem. In this study, nine ML algorithms were trained with a dataset created by the feature extraction of EEG signals.The EEG signals of 30 Physionet subjects were used to create a dataset related to movement. We used electrodes C3, C1, CZ, C2, and C4 according to the standard 10-10 placement. Then, we extracted the epochs of the EEG signals and applied tone, amplitude levels, and statistical techniques to obtain the set of features. LabVIEW™2015 version custom applications were used for reading the EEG signals; for channel selection, noise filtering, band selection, and feature extraction operations; and for creating the dataset. MATLAB 2021a was used for training, testing, and evaluating the performance metrics of the ML algorithms. In this study, the model of Medium-ANN achieved the best performance, with an AUC average of 0.9998, Cohen’s Kappa coefficient of 0.9552, a Matthews correlation coefficient of 0.9819, and a loss of 0.0147. These findings suggest the applicability of our approach to different scenarios, such as implementing robotic prostheses, where the use of superficial features is an acceptable option when resources are limited, as in embedded systems or edge computing devices.
The Roles of Entrepreneurial Skills, Financial Literacy, and Digital Literacy in Maintaining MSMEs during the COVID-19 Pandemic

The COVID-19 pandemic has negatively impacted the economic growth of Indonesia. Government regulations to limit large-scale social activities has caused marketing and financial difficulties for micro, small and medium enterprises (MSMEs). Digital and financial literacy have the potential to overcome the problems. This study attempts to identify the determinants of MSME sustainability during the pandemic. By using a questionnaire, this study collected 204 data from MSMEs for further analyses. MSME sustainability is influenced by the digital and financial literacy of MSME owners and is a cause for concern. The implementation of health and safety measures (HSM) has an insignificant impact on business sustainability, but HSM affects financial and digital literacy. Entrepreneurial skills are important to improve HSM and owners’ digital and financial literacy. The government and other parties need to provide more soft loans and facilitate MSMEs to develop entrepreneurial skills, digital and financial literacy to improve business sustainability during the pandemic.
Integration of a thermal energy storage as a dynamic load into the electrical grid of an urban quarter

This paper focuses on the implementation of a thermal energy storage as a dynamic load in the electrical grid of an urban quarter. First, the electrical grid of the quarter and a use case for the thermal energy storage in the grid is presented. Then an approach to model the thermal energy storage together with a heat pump as a thermal generator is described. In this case the heat pump is directly connected to the busbar of a power supply unit. Based on an already existing thermal energy storage the necessary storage capacity is approximated. Furthermore, a control strategy is proposed to use the heat pump to decrease the transformer loading within the grid by producing thermal energy in times of high transformer loading and storing the produced thermal energy in the thermal energy storage. The proposed control strategy in conjunction with different storage sizes is used to simulate the transformer loading for a given network load based on real measurement data in order to evaluate the approach.
PROBLEMS OF EDUCATION IN INDONESIA AND ALTERNATIVE SOLUTIONS

Today, education in Indonesia is assessed by various groups, both at home and abroad, has been facing various challenges and problems so that it has a negative impact on low quality of education in Indonesia. For this reason, this research was deliberately carried out as a contributive step to identify various challenges and problems faced by the world of education in Indonesia and recommend several solution steps so that they can contribute ideas to improve education in Indonesia. This research uses the qualitative approach by applying the literature study method as well as collecting primary data and various secondary sources through documentation, followed by analysis of the data obtained. From the research conducted, it can be found that there are several challenges and problems of education in Indonesia, including unbalanced education output, low quality of facilities and infrastructure, low quality and behavior of teachers, student moral behavior, and tolerance for racial intolerance. In order to overcome the problems above, it is necessary to have mutual cooperation and collaboration from all parts of nation as the key to implementing several alternative solutions, including improving the welfare of education, building a world view and improving the mindset of teachers and students, developing a comprehensive curriculum design, overseeing budget allocations, increase the contribution of the business world and others.
Application of the GOES-16 Advanced Baseline Imager: Morphology of a Preconvective Environment on 17 April 2019

Thunderstorms formed in the afternoon of 17 April 2019 over northern Mexico. Satellite data are used to highlight several features associated with convective preconditioning over portions of Coahuila, Mexico. Satellite imagery was used to identify two preconvective features over northern Coahuila: 1) A relatively moist boundary layer inferred from channel differencing of imagery near 10.3 µm and 12.3 µm, and 2) Upward vertical motion inferred from decreasing values of brightness temperatures near 7.34 µm (low-level water vapor). Due to the approach of a trough at 500 hPa, a larger region of cooling was evident in low-level water vapor imagery. Evidence of blowing dust in imagery was used to highlight a wind-shift boundary along with a possible region of enhanced horizontal convergence. A demonstration of a time-of-arrival tracking feature is used to show a benefit to a forecaster in determining the arrival of a region of blowing dust, possible enhanced horizontal convergence and subsequent convective initiation. Assimilation of satellite data that contains key features and potential benefits to numerical weather prediction is addressed. Convective preconditioning of an environment outside of the United States, but adjacent to a U.S. county warning area, is an important situation to monitor as subsequent convection may move into a forecaster’s region of responsibility.
A Simple and Efficient Technique to Generate Bounded Solutions for the Generalized Assignment Problem: A Guide for OR Practitioners

The generalized assignment problem (GAP) is a NP-hard problem that has a large and varied number of important applications in business and industry. Approximate solution approaches for the GAP do not require excessive computation time, but typically there are no guarantees on solution quality. In this article, a methodology called the simple sequential increasing tolerance (SSIT) matheuristic that iteratively uses any general-purpose integer programming software is discussed. This methodology uses a sequence of increasing tolerances in conjunction with optimization software to generate a solution that is guaranteed to be within a specified percentage of the optimum in a short time. SSIT requires no problem-specific coding and can be used with any commercial optimization software to generate bounded solutions in a timely manner. Empirically, SSIT is tested on 51 GAP instances (24 medium and 27 large) in the literature. The performance of CPLEX versus Gurobi on these 51 GAP test instances is also statistically analyzed.
Assessment of models based on GPS data to identify buses skipping formal stops

In Santiago’s public transport system, several users’ complaints are received daily. In 2016, 40% of the 28 thousand complaints received by the corresponding agency (DTPM) corresponded to buses non stopping at a bus stop even though there were passengers waiting for the bus. To avoid this undesirable behavior, a fine is issued to bus operators any time they incur in such a behavior. Nonetheless, from the legal point of view, users’ complaints are not enough to issue the fine. A fine is issued only when enforcement officers observe this behavior in situ. In 2015, a total of 1200 inspections were performed, resulting in 138 fines issued. Compared to the more than 10 thousand complaints received that year (DTPM, 2016), the total number of fines is very low.