Miracle-dz/UniFAR-FTUs huggingface dataset:
Impacts of Soil and Water Management Measures on Crop Production and Farm Income of Rural Households in the Damota Area Districts, Southern Ethiopia

Improving crop productivity and farm income of rural households and ensuring food security through soil and water conservation (SWC) measures are one of the integral parts of sustainable livelihood approaches. The study aims to assess the impact of soil and water conservation measures on improving the rural livelihoods, which is measured in terms of annual crop production and farm income of rural households in the Damota area districts. The data was collected from 378 households (209 adopters and 169 nonadopters of SWC measures) using survey questionnaires, which were randomly chosen by using multistage sampling techniques. Descriptive and inferential statistics with propensity score matching (PSM) method were used to analyze the collected data. The propensity score matching method was used to assess the impacts of soil and water conservation measures by controlling unobserved heterogeneity and were matched with balanced observable characteristics. The result showed that the mean value of wheat production of adopter households was higher (654 kilograms per hectare) than that of nonadopters (496 kilograms per hectare). Similarly, the mean values of farm income of adopter households were higher (17372.67 Ethiopian Birr per year) than those of nonadopter households (13883.22 Ethiopian Birr per year). The result indicated that both crop production and annual farm income were more pronounced when farmers implemented sustainable soil and water conservation measures on their farming lands. This suggests that all rural households need to focus on the large-scale adoption, integration, and maintenances of damaged structures for better agricultural outcomes.
Enhancing The Inherent Coping Mechanism of Teachers in The Course of Health and Security Crisis

There is a limited number of studies on why people, specifically teachers, can immediately cope with health and security crisis, and continue to live their lives as normally as those who have not experienced such events in their lives, hence, the necessity to conduct this study. It explored the factors that influenced their coping mechanisms through exploratory sequential mixed method, involving respondents from seven schools district of Zamboanga Sibugay Division and from one school district of Lanao del Sur. The qualitative data gathered from 10 respondents through face-to-face interview and focused group discussion arrived at the factors that influenced the inherent coping mechanisms, namely: family, faith, profession, alliance, self-reliance, and service. The quantitative data gathered from 131 respondents through a researcher-made survey instrument were subjected to Pearson coefficient of correlation, t-test, weighted mean, and stepwise regression. It is concluded that faith, family, alliance, and profession wield a significant influence in the coping mechanisms of the respondents. Experience, and training were also found to have a differentiating performance in coping from health and security crisis; and that success in coping from catastrophic situations depends greatly on these factors. This study further proposed a model which can be used as basis in designing mental, spiritual, emotional, and social health programs to enhance the inherent coping mechanisms of teachers.
Research on PM2.5 Spatiotemporal Forecasting Model Based on LSTM Neural Network

Accurate monitoring of air quality can no longer meet people's needs. People hope to predict air quality in advance and make timely warnings and defenses to minimize the threat to life. This paper proposed a new air quality spatiotemporal prediction model to predict future air quality and is based on a large number of environmental data and a long short-term memory (LSTM) neural network. In order to capture the spatial and temporal characteristics of the pollutant concentration data, the data of the five sites with the highest correlation of time-series concentration of PM2.5 (particles with aerodynamic diameter ≤2.5 mm) at the experimental site were first extracted, and the weather data and other pollutant data at the same time were merged in the next step, extracting advanced spatiotemporal features through long- and short-term memory neural networks. The model presented in this paper was compared with other baseline models on the hourly PM2.5 concentration data set collected at 35 air quality monitoring sites in Beijing from January 1, 2016, to December 31, 2017. The experimental results show that the performance of the proposed model is better than other baseline models.
Rural Fire Risk Assessment in GIS Environment
Using Fuzzy Logic and the AHP Approaches

Fires all around the world have caused irreparable environmental and economic losses due to the increase in global warming. Risk assessments are curial for taking measures to keep negative effects of natural hazards to a minimum and to ensure sustainability of the nature. In this regard, the aim of this study is to evaluate rural area fire risk in the seven geographical regions of Turkey. Since fire sensitive areas in rural regions are generally composed of forest areas, data on the size of forest areas, number of forest fires and temperatures are the main starting points of this study. Analysis was carried out using the Analytical Hierarchy Process and Fuzzy Logic approaches. In this study the Analytical Hierarchy Process and Fuzzy Logic approaches were integrated with the Geographical Information Systems. The results obtained from the AHP and Fuzzy Logic approaches were compared and evaluated. The results of the study show that the Aegean, Mediterranean and Marmara regions have the highest rural area fire risk levels. The fire risk assessments results obtained by the AHP and Fuzzy Logic approaches overlap on the basis of geographical regions. Integrating the AHP and Fuzzy Logic with GIS for rural area fire risk assessment provide valid, reliable and very important results in making the necessary planning and ensuring sustainability of the environment.
Economic literacy among tertiary students in Ghana: Evidence from University of Cape Coast

Economic literacy measures the extent to which people can appreciate the forces that significantly influence the quality of their lives. Economically literate citizens may be able to make rational choices, understand and even form opinions on policies, and are likely to feel completely part of any public debate about the economy of a country. There have not been many studies on economic literacy, especially at the tertiary level in Ghana. It is in light of this that this paper seeks to investigate the factors influencing economic literacy among undergraduate students in the University of Cape Coast, Ghana. The study addresses two research questions: 1) What is the level of economic literacy among tertiary students in Ghana? and 2) What factors influence undergraduate students’ understanding of economic issues? The study employed a regression model on data collected from a sample survey of 1,366 undergraduate students in the University of Cape Coast. The results indicate that economic literacy is positively influenced by the level of the tertiary student, their SHS elective courses taken, their Cumulative Grade Point Average, interest in politics, and attendance of business/ economics conferences. The study recommends that the fundamentals of economics could be introduced into the Social Studies discipline at the SHS so that all students benefit from this knowledge. The youth must be encouraged to be involved in business and politics, while Colleges and Universities should make business/economic seminars part of their curriculum.
On the Training of Deep Neural Networks for Automatic Arabic-Text Diacritization

Automatic Arabic diacritization is one of the most important and challenging problems in Arabic natural language processing (NLP). Recurrent neural networks (RNNs) have proved recently to achieve state-of-the-art results for sequence transcription problems in general, and Arabic diacritization in specific. In this work, we investigate the effect of varying the size of the training corpus on the accuracy of diacritization. We produce a cleaned corpus of approximately 550k sequences extracted from the full dataset of Tashkeela and use subsets of this corpus in our training experiments. Our base model is a deep bidirectional long short-term memory (BiLSTM) RNN that transcribes undiacritized sequences of Arabic letters with fully diacritized sequences. Our experiments show that error rates improve as the size of training corpus increases. Our best performing model achieves average diacritic and word error rates of 1.45% and 3.89%, respectively. When compared with state-of-the-art diacritization systems, we reduce the word error rate by 12% over the best published results. Keywords—Arabic text; automatic diacritization; bidirectional neural network; long short-term memory; natural language processing; recurrent neural networks; sequence transcription
The Effects of WordWall Online Games (WOW) on English Language Vocabulary Learning Among Year 5 Pupils

In the effort to upgrade pupils' vocabulary learning experience, the potential of interactive educational games is increasingly explored as supplementary teaching and learning materials. While the eagerness to integrate mobile technology into English language education is noticeable, there is a lack of evidence on Malaysian English as Second Language (ESL) learners' views of the feasibility of online games in vocabulary learning. This study aims to determine the degree of improvement in pupils' vocabulary performance. The quantitative data was analysed using descriptive and dependent t-test analysis. The cross-sectional survey was adapted from the ACRS-V model. The questionnaire was distributed to Year 5 pupils from a national primary school in Negeri Sembilan who are using the syllabus of The English Language Curriculum for Primary Schools (KSSR). The findings show a moderate level of Satisfaction, Attention, Relevance, Confidence and Volition. In addition, a paired sample t-test indicates a significant improvement in the pupils’ vocabulary scores after using WordWall (WOW) as a vocabulary learning supplementary material. The effect size demonstrated is also larger regarding its effects in behavioural sciences. This study provides important insights as a guide for primary school English teachers in integrating online games as a learning tool for English language learning, especially in developing pupils’ English vocabulary repertoire.
ComparativeEfficacyandSafetyofTargetedTherapies forChronic Thromboembolic Pulmonary Hypertension: A Systematic Review and Network Meta-Analysis

Background. (ere is significant controversy relating to whether chronic thromboembolic pulmonary hypertension (CTEPH) can be treated with pulmonary arterial hypertension(PAH-) targeted therapies and which therapy is the optimal choice for patients. A large number of randomized controlled trials (RCTs) have compared PAH-targeted therapies with placebo or conventional therapies. In this study, we aimed to compare all of the PAH-targeted medications that are used to treat CTEPH and rank their efficacy by the application of network meta-analysis (NMA). Methods. We searched PubMed, EMBASE, Web of Science, the Cochrane Central Register, https://clinicaltrials.gov, and who.int/trialsearch/, for relevant RCTs published up to January 2020. In addition to traditional meta-analysis, we also performed NMA in our systematic review, as deployed in a previous protocol (PROSPERO: CRD42020173765). Results. Our study identified eight eligible RCTs that evaluated seven PAH-targeted therapies in 703 patients with CTEPH. NMA revealed that riociguat was ranked first as the most optimized therapy for ameliorating the 6minute walk distance with a probability of 80.4%. Bosentan was significantly better than others with regard to reducing brain natriuretic peptide/N-terminal pro-B-type natriuretic peptide with a probability of 84.3%. Sildenafil was identified as the best drug in terms of improving the New York Heart Association/World Health Organization functional class with a probability of 87.3%. Treprostinil and macitentan were more beneficial than other drugs in reducing pulmonary vascular resistance and lowering the incidence of clinical worsening with probabilities of 86.2% and 79.2%, respectively. Conclusion. Analysis revealed positive advantages for the use of PAH-targeted drugs in patients with CTEPH. Overall, treprostinil and riociguat were superior to all other PAH-targeted medications in most of the outcomes investigated.
Ten Simples Rules on How to Organise a Bioinformatics Hackathon

The completion of the human genome sequence triggered worldwide efforts to unravel the secrets hidden in its deceptively simple code. Numerous bioinformatics projects were undertaken to hunt for genes, predict their protein products, function and post-translational modifications, analyse protein-protein interactions, etc. Many novel analytic and predictive computer programmes fully optimised for manipulating human genome sequence data have been developed, whereas considerably less effort has been invested in exploring the many thousands of other available genomes, from unicellular organisms to plants and non-human animals. Nevertheless, a detailed understanding of these organisms can have a significant impact on human health and well-being.New advances in genome sequencing technologies, bioinformatics, automation, artificial intelligence, etc., enable us to extend the reach of genomic research to all organisms. To this aim gather, develop and implement new bioinformatics solutions (usually in the form of software) is pivotal. A helpful model, often used by the bioinformatics community, is the so-called hackathon. These are events when all stakeholders beyond their disciplines work together creatively to solve a problem. During its runtime, the consortium of the EU-funded project AllBio - Broadening the Bioinformatics Infrastructure to cellular, animal and plant science - conducted many successful hackathons with researchers from different Life Science areas. Based on this experience, in the following, the authors present a step-by-step and standardised workflow explaining how to organise a bioinformatics hackathon to develop software solutions to biological problems.
Determinants of Organizational Citizenship Behavior of Contract Employees

This study aims to analyze the effect of intrinsic motivation on job satisfaction and OCB and the effect of job satisfaction on OCB. This study also aims to analyze the indirect effect of intrinsic motivation on OCB through job satisfaction. The study was conducted at the Secretariat of the Regional People’s Representative Council (DPRD) of Badung Regency. Data were collected by means of questionnaire using five scales, distributed to 143 contract employees. Before being fully disseminated, data quality testing was carried out using SPSS 20 to ensure the questionnaire was valid and reliable. The data collected were analyzed using descriptive and inferential analysis with WarpPLS. The results shows that intrinsic motivation plays an important role in increasing job satisfaction and OCB. Additionally, job satisfaction is also proven to be able to increase OCB. Furthermore, intrinsic motivation indirectly has an important role in increasing OCB through job satisfaction.
Higher Order Statistics and Phase Synchronization as Features in a Motor Imagery Paradigm

The paper proposes an approach based on higher order statistics and phase synchronization for detection and classification of relevant features in electroencephalographic (EEG) signals recorded during the subjects are performing motor tasks. The method was tested on two different datasets and the performance was evaluated using k nearest neighbor classifier. The results (classification rates higher than 90%) have shown that the method can be used for discriminating right and left motor imagery tasks as an offline analysis for EEG in a brain computer interface system. Keywords—Brain computer interface; motor imagery; higher order statistics; phase synchronization; EEG
Monitoring the Tropospheric Monitoring Instrument (TROPOMI) short-wave infrared (SWIR) module instrument stability using desert sites

Abstract. Since its launch in 2017, Tropospheric Monitoring Instrument (TROPOMI) on S-5P has provided very high quality data using daily global coverage for a number of key atmospheric trace gases. Over its first 1000 d in operation, the short-wave infrared (SWIR) module has been very stable, and the continuously monitored calibration has remained of high quality. This calibration relies on a combination of extensive pre-launch and post-launch measurements, complemented by regular monitoring of internal light sources and background measurements. In this paper we present a method and results for independent validation of the SWIR module calibration and instrument stability by examining the signal stability of a sample of 23 pseudo-invariant calibration desert sites. The data covers over 2 years of operational data. With a Lambertian surface assumption, the results show that the SWIR module has little to no instrument degradation down to an accuracy of about 0.3 % yr−1, validating results obtained from the internal calibration suite. The method presented here will be used as ongoing validation of the SWIR calibration.
Key Insights into What Makes Public Organizations Learn from Training Programs

Public organizations often operate in rigid environments with standardized procedures that are not conducive to learning, yet it is crucial that they continuously improve at solving their societal tasks in a satisfactory way. There is a lack of knowledge about what factors are important for learning to occur in public organizations. Based on a questionnaire, this study looks at how different factors condition the way in which employees perceive standardized training programs in public organizations. The study demonstrates how a training program was perceived by two different professional groups, one being more accustomed to and accepting of standardized procedures than the other. The results show that the child welfare services had a more positive attitude toward the program than did the family counseling services. Employees working in an environment that is positive to employee feedback also perceived the program as more relevant, important and useful. Employees working in an environment that prioritized competence development perceived the program to be better organized and implemented and to be relevant to their work tasks. The article argues that these factors contribute positively to organizational learning and stresses the importance for leaders to develop an environment that is positive to employee feedback.
The anthropometric, physical, and relative age characteristics of an English Premiership rugby union academy

Long-term athlete development is a primary focus for the England Rugby Football Union (RFU). The purpose of this study was to explore the anthropometric, physical, and relative age characteristics of rugby union academy players based on age group and playing position. Seventy-eight participants were examined for height, body mass, 10 and 20 m sprint, countermovement jump, reactive strength index, aerobic capacity, isometric hip extension, dominant handgrip strength, and birth quartile (BQ) across three age categories (i.e., under-16, under-18, and under-21) and two positions (forwards and backs). ANOVA and Kruskall–Wallis analysis were used to examine differences across each age category and position. TukeyHSD and Dunn’s test with Bonferroni correction was used for further post-hoc analysis. BQ distributions were compared against national norms using chi-square analysis. Results revealed that both older forwards (P=0.005) and backs (P=0.002) had significantly greater body mass, maximal aerobic capacity, and power compared to younger players. However, older forwards had slower 10 m sprint times compared to younger forwards. Moreover, relatively older players were significantly overrepresented across all age groups when compared to relatively younger players. Findings suggest that: (a) players should aim to develop greater parameters of body mass and aerobic capacity; (b) forwards should aim to develop acceleration and strength; (c) backs should aim to develop power and quickness; (d) players need to develop anthropometric and physical qualities and differences are apparent by age and position; and, (e) coaches should consider relative age when recruiting and developing young players. Key words: Talent identification; Talent development; Expertise; Physical development; Physiological profile; Rugby football
Estimation of the Basic Reproduction Number (R0) for Covid-19 Epidemic at District Level in Rewa, Madhya Pradesh

Introduction: COVID-19 was announced as a global pandemic by World Health Organization (WHO) owing to its highly contagious and pathogenicity that has been rapidly spreading throughout the world since its first reported outbreak in China in December 2019. Aim: To estimate the basic reproduction number (R0) and forecast the situation to understand the future transmission dynamics of the COVID-19 outbreak in the Rewa district. Materials and Methods: It was a retrospective cohort study. We used two data sources for the study. Firstly, contact history of laboratory-confirmed SARS-CoV-2 infected individuals & Secondly, the publicly available daily case count data were used together by applying an approach named population-level model (PLM) for estimating R0 and project the size of the epidemic over the next 365days as per the SIR model with help of python. Results: The peak of the R0 = 2.3 was attained in September 2020. Then subsequent reduction toward the end of September can be attributed to aggressive testing, more contact tracing, and isolation measures implemented in the Rewa district during that month so currently, in November up to 22nd R0=1.8 reported according to our study. Conclusion: A combination of Public health measures such as social distancing, rigorous contact tracing & testing, and isolation of contacts and the vulnerable should be effective to reduce the instantaneous R0 value and could thereby reduce the final outbreak size.
An enigmatic new archosauriform from the Carnian– Norian, Upper Triassic, Ischigualasto Formation of northwestern Argentina

In this contribution we introduce a new Late Triassic archosaur, Incertovenator longicollum gen. et sp. nov., with an unusual combination of character states that are present in certain early avemetatarsalian and pseudosuchian archosaur clades. The holotype consists of a partial postcranial skeleton, preserving most of the axial skeleton and displaying a marked anteroposterior elongation in the cervical vertebrae. We include I. longicollum gen. et sp. nov. into one of the most comprehensive early archosaur phylogenetic data sets available, and recover it as either an early diverging avemetatarsalian, closely associated with the clade Aphanosauria and Ornithodira, or as an early diverging loricatan closely related to Mandasuchus tanyauchen in the most parsimonious trees. We further evaluate which alternative phylogenetic positions can I. longicollum gen. et sp. nov. take in the suboptimal trees, and determined which character states support those alternative positions in comparison with those of the unconstrained analysis. The analyses recover the new taxon in three main general phylogenetic placements within Archosauria, as well as one position outside this clade, highlighting widespread morphological evolutionary convergence towards neck elongation in several clades of Triassic archosauriforms.