Miracle-dz/UniFAR-FTUs huggingface dataset:
The Utilization of Modified Chitosan from Shrimp Shell As Photodegradation of Pesticides Paraquat Dichloride

In this study, the chitosan modification of shrimp shell has been made by impregnated the chitosan from shrimp shell with Ti/ZrO2 and ZrO2 to formed composite of chitosan-Ti/ZrO2 and chitosan-ZrO2. These composites were made by immobilization technique and characterized by FTIR and SEM-EDX. The chitosan-Ti/ZrO2 and chitosan-ZrO2 composite were used as a catalyst to degrade the pesticide paraquat dichloride in the presence of UV light (? = 257 nm). The photodegradation process of paraquat dichloride takes place under 10 watts UV light irradiation and was measured using spectrophotometer UV. The maximum degradation percentage of pesticide paraquat dichloride photodegradation by chitosan-Ti/ZrO2 and chitosan-ZrO2 composites are 61.97% and 57.97% within 30 minutes irradiation time.
The Role of Chia Seeds Oil in Human Health: A Critical Review

Chia, Salvia hispanica L. , is emerging as an important functional food ingredient because of its rich contents of dietary fiber, omega‐3 fatty acids and an indicative source of bioactive peptides owing to its high concentration of proteins and essential amino acids. The use of food with nutraceutical and functional properties for management of lifestyle diseases like diabetes, obesity, and cardiovascular problems is now gaining momentum among the public. Current research findings reveal high nutritive value for chia seeds and their oils validating their massive health-promoting properties. Currently chia is consumed as seeds and oil with similar effects. The oil is rich in in polyunsaturated fatty acid, α-linoleic acid, the biological precursor to docosahexaenoic acid and eicosapentaenoic acid. It has been scientifically established that chia is an immune improver and has therapeutic effects on control of diabetes, dyslipidemia, hypertension, as anti-inflammatory, antioxidant, anti-blood clotting, laxative, antidepressant, antianxiety, analgesic and vision. This article provides a review of the role of chia seeds oil in human health. The Phytochemical characteristics of chia oil is presented and the effect of their consumption on human health is discussed.
COST RISK’S RELIABILITY AND VALIDITY OF RESIDENTIAL BUILDING PROJECT’S WHOLE LIFE CYCLE IN THE UNITED ARAB EMIRATES

Purpose – Project management cost and risk modelling is experiencing the challenge of identifying cost risks values to maintain accurate modelling, estimating, and assessment. Latest research focused on cost and risk modelling and estimation. The significance of cost risks numerical values come from its ability to be used in many different analysis and approaches. This article aims to identify residential building projects’ whole life cycle cost risks numerical values in UAE at the preconstruction stage and ensure its reliability and validity. Methodology – The approach of this research is pure quantitative. The methodology of this research is to collect data though conducting face-to-face interviews quantitatively (i.e., cost risks values). The survey is using PMBOK risk matrix (i.e., probability vs. impact). Finally, data correlation and regression modelling ware done to ensure the reliability and validity of each cost risk value. Findings – This paper was able to deliver reliable and valid residential project’s whole life cycle cost risks values (i.e., 117 cost risks) for direct use in future research or practical professional cost analysis. Unique contribution to theory, practice and policy – This article contribution to the project management body of knowledge is to collect all relevant cost risks (i.e., 117 cost risks) and obtain their values from UAE field experts for the first time. The provided values are for residential project in UAE only. The perspective of how to look to cost risks values in this article (i.e., contractors’ and clients’ views) should be considered at the time of using the data. The consultancy services organizations will have different cost risks because they do not deal with delivering the final product, but they provide supporting services (i.e., design and supervision) to facilitate delivering the project.
The Use of Sports Apps for Engaging in Physical Activity

Background. As healthy lifestyle and physical activity become more relevant, sports apps are receiving more attention as one of the most convenient tools for monitoring one’s physical condition. While activity-related apps are thought to be effective tools for health care and management, there is still a lack of information on the key factors that motivate individuals to download and use them. Seeing the large selection of different sports apps with similar functions, it can be assumed that other factors, such as certain characteristics of the apps or the user’s characteristics can also influence the consumer’s choice. Methods. The study included 410 physically active subjects who were using sports apps (137 men and 273 women). To establish sports app usage, the questionnaire developed by Ha, Kang, and Ha (2015) was used. The statistical analysis of the data was performed using SPSS. Results. In the analysis of different factors, the perception of sports apps was assessed the most positively. All these factors were more likely to be assessed positively by women than by men (p ≤ .05). The strongest correlations with intentions were found between perceptions of sports apps (enjoyment, ease of use, usefulness, reliability) (r > .5, p ≤ .01) while with other variables correlations were slightly lower. Conclusions. Women are more positive about the use of sports apps, in their perceptions and their connection to the smart device. Intentions to use sports apps are most influenced by perceptions of sports apps and personal innovativeness, which not only directly affects the intentions themselves, but also influences the perceptions that influence the intentions. Keywords: smartphones, smart devices, sports involvement, innovation, perception.
Plausible role of Arq Ajīb in combating COVID-19: A multi-faceted review

The current pandemic caused by SARS-CoV-2 has led to a massive change in every aspect of our lives. It has grossly affected the healthcare system, business and world trade, disruption of movement and supply of essential goods and has crippled the global economy. Although few vaccines have been approved for the control of disease, targeted therapy options for this virulent disease still remain limited and elusive. Exhaustive search for potent therapeutic candidate is in progress, for which herbal armory are also being explored. Medicinal plants and their products play a vital role in alleviating various diseases and have been reported to exhibit a wide range of biological activities. Plant-based drugs with antiviral, anti-inflammatory and immunomodulotry activities were hypothetically considered as potential drugs to prevent and mitigate the prevailing situation caused by SARS-CoV-2. Arq Ajīb ‘a Unani formulation’ presents compelling approach in treating numerous diseases. The ingredients of Arq Ajīb and their phytocompounds have been reported for wide-ranging pharmaco-biological activities including antiviral, anti-inflammatory, immunomodulotry, anti-allergic, antitussive and bronchodilatory activities. Scientific data available on the formulation ingredients and their phytocompounds indicates that the formulation may have a significant role in augmenting the immune status of individual, protecting them from infection and providing symptomatic relief to patients affected with COVID-19. Hence, it may be considered as a potential drug for the development of novel therapeutic candidate for SARS-CoV-2 infection. This multi-faceted review highlights the therapeutic significance and pharmacological actions of Arq Ajīb and its ingredients to demonstrate the plausible role of the formulation in combating COVID-19. Keywords: Arq Ajīb, COVID-19, Pudina, Ajwain, Camphor, Unani formulation
Prediction of IPL Match Outcome Using Machine Learning Techniques

India's most popular sport is cricket and is played across all over the nation in different formats like T20, ODI, and Test. The Indian Premier League (IPL) is a national cricket match where players are drawn from regional teams of India, National Team and also from international team. Many factors like live streaming, radio, TV broadcast made this league as popular among cricket fans. The prediction of the outcome of the IPL matches is very important for online traders and sponsors. We can predict the match between two teams based on various factors like team composition, batting and bowling averages of each player in the team, and the team's success in their previous matches, in addition to traditional factors such as toss, venue, and day-night, the probability of winning by batting first at a specified match venue against a specific team. In this paper, we have proposed a model for predicting outcome of the IPL matches using Machine learning Algorithms namely SVM, Random Forest Classifier (RFC), Logistic Regression and K-Nearest Neighbor. Experimental results showed that the Random Forest algorithm outperforms other algorithms with an accuracy of 88.10%.
Estudio pedagógico sobre prácticas orientadas a la formación de futuros docentes

El objetivo de esta investigación es analizar la participación académica del instructor que se prepara en el tema de instrucción competente, una unidad curricular que forma parte de las titulaciones sobre instrucción impartidas en el Colegio Nacional (Kazajstán). El diseño de esta investigación es el modelo del estudio de caso, que es uno de los diseños de investigación cualitativa. Los participantes de la investigación consistieron en cincuenta estudiantes de pregrado kazajos de la ciudad de Aktau (Kazajistán). En la investigación, el “Formulario de entrevista semiestructurado” y la “Evaluación de la cartera” se utilizaron como instrumentos de recopilación de datos. En esta investigación, los datos se analizaron mediante la técnica de “Análisis descriptivo”, que es uno de los métodos de análisis de datos cualitativos. Coincidiendo con la investigación, se encontró el reconocimiento de las alteraciones individuales a niveles imperativos para la obtención de información y competencias, así como una organización de la idea de instruir a partir del pensamiento básico de su naturaleza inherentemente moral e intersubjetiva.
PATH TRACKING FOR AN AUTONOMOUS VEHICLE DURING EMERGENCY CONDITION

An autonomous vehicle's primary function is detecting and tracking the road course precisely and correctly without a driver's assistance. As a result, implementing appropriate controllers is critical for improving the vehicle's stability and movement responsiveness. The performance of adaptive Stanley controlled is evaluated in this paper using numerical simulations. The Stanley controller's most common geometric controller for vehicle path tracking algorithms is compared based on their trajectory tracking analyses on various vehicle speed maneuvers. Stanley calculates steering based on the difference between the vehicle's lateral position and heading angle. The difference between desired coordinates and present coordinates of the vehicle along the path is used to calculate lateral, longitudinal, and vehicle heading orientation angle using the future prediction control technique. The results demonstrate that the Stanley controller outperforms the emergency trajectory with more consistent trajectory tracking and steady-state error.
THE SENSE OF SELF EFFICACY OF PRE-SERVICE ENGLISH TEACHERS IN EFL CONTEXT

This study aims to describe the sense of self-efficacy of pre-service teachers in the context of EFL. This issue needs to be discussed because of the importance of self-efficacy in teaching for the pre-service teacher. The study used the Teacher Sense of Efficacy Scale (TSES) questionnaire as the instrument. There were 103 respondents participated in this study. The results showed that pre-service English teachers were more effective on instructional strategy with an average score of 3.7840 of the overall sense of efficacy. Then, followed by student engagement efficacy with an average score of 3.7561, and the last one is class management with an average score of 3.7318. Based on the data obtained, it shows that the students' sense of efficacy is at a moderate level.
Detection of Dengue Serotypes by Two Molecular Techniques, qPCR and LAMP

Background: Dengue virus is a mosquito-borne flavivirus and the most widely prevalent arbovirus in tropical and subtropical regions. Detection of this virus by a new molecular technique named Loop-mediated isothermal amplification (LAMP) is a very sensitive, easy, and less time-consuming diagnostic method. It can amplify up to 109 copies in less than 1 hour under isothermal conditions (65°C). Aims: To establish a dengue LAMP as simple, less time-consuming, more specific, and sensitive than the qPCR to detect dengue serotypes. Materials and Methods: This prospective analytical study was conducted from January- December 2017 at the Department of Virology, BSMMU, Dhaka, Bangladesh. A total of 290 serum samples were used, confirmed by ICT (immune chromatographic test). These samples were used to perform qPCR for the detection of dengue serotypes. After that, dengue LAMP was performed using the same samples to establish the LAMP technique as a suitable, time-saving molecular technique that is more sensitive than qPCR. Results: A total of 290 dengue confirmed samples by ICT were used for qPCR to detect dengue serotypes. Among which 137 dengue I and 113 dengue II RNA positive serum samples were confirmed by qPCR, and those were also positive by LAMP assay. Besides, 20 both dengue NS1 and dengue IgM negative by ICT were tested by qPCR, and 01 positive dengue II serotype was detected by qPCR, whereas 02 dengue II serotypes were detected by dengue LAMP technique from the same samples. Conclusion: RT-LAMP assay had been developed in this study which allowed the rapid and accurate identification of dengue virus serotypes. TAJ 2021; 34: No-1: 01-04
Quantitative assessment of the dynamics and attribution of arable land water scarcity for arid and semiarid areas based on water footprint framework: the Inner Mongolia case

Growing water shortages have been a systemic risk around the world, especially in arid and semi arid areas, seriously threatening global food security and human well-being. Reasonable and accurate evaluations of the water shortages of cultivated lands provide scientific reference for irrigation strategies. In this study, to better understand the distribution and cause of water scarcity for arid and semiarid areas, we used the arable land water scarcity index (AWSI), based on water footprint theory, to accurately estimate the temporal and spatial patterns of the AWSI of Inner Mongolia in China over 1999–2018, and further reveal the key factors influencing the AWSI distribution. The AWSI distribution pattern of Inner Mongolia was high in the southwest and low in the northeast, with an average value of 0.63 and indicating high water stress for a long time. The AWSI presented an increasing trend in 1999–2018, being slow in the west (change rate2%) and fast in the east (2%). The main factors that significantly affected the AWSI were precipitation, relative humidity, and agricultural planting area. This study can provide scientific reference for the formulation of agricultural water management and sustainable use strategies in arid and semiarid areas.
Do explanatory notes explain? Risk management disclosure analysis using text mining

The study aimed to analyze the effectiveness of risk management communication in the explanatory notes considering text mining techniques. Based on the analysis of 241 text excerpts from 32 financial institutions, we used the cosine similarity as a distance measurement to assess the relationship between the variability of the texts and the Basel and Inad 90 risk indices. The results indicate that the analyzed notes are not in compliance with OCPC 07, as their content does not reflect the fluctuation of risk indices. The benefit of the notes for the user in decision-making processes may be impaired, given the evidence of disconnection between the texts and the risk policy. Cases of complete repetition of the text excerpts are presented. As a contribution, this article advances in the textual studies of financial statements, going beyond lexical and volumetric analyses, bringing the semantic content in volume and its relationship with finance indicators.
Volumetric data of normal nucleus accumbens from magnetic resonance imaging scans

Backgrounds and aims The nucleus accumbens (AcN) belongs to the ventral striatum and it is involved in several neuropsychiatric disorders. In contrast to other subcortical structures, the number of morphometric studies that concern the healthy nucleus is limited. This study aims to investigate the normal volumetric data of the AcN as derived from a large number of manually segmented magnetic resonance imaging (MRI) scans. Methods The measurements were performed in 106 MRI scans of healthy adults. The resulting volumes have been analyzed for differences related to hemisphere, sex and age. Results The mean AcN volume was estimated at 473.3 mm3 (SD=±106.8). A slight interhemispheric difference in favor of the left side was found, the value of which was, however, within the limits of the method error. There were no sexual dimorphism signs concerning both the raw and the normalized volumes. A negative correlation between volumes and age was observed only in males. Conclusions The study provides normal volumetric data of the AcN, useful in the conduct of comparative imaging and post-mortem studies in pathological conditions.
Narcissistic Leadership and Project Success in IT Industry: Moderating the role of Risk Management Technology

Narcissistic leaders supersede others opinions while dealing with different projects is an area of concern because they create the risk of various projects' success. However, risk management technology can balance this leadership to mitigate the project failure risk. Therefore, this study aims to examine the impact of narcissistic leadership on project success with the moderating role of risk management technology. A self-administrated questionnaire measured the narcissistic leadership constructs with two dimensions (i) admiration, (ii) rivalry as antecedents, risk management technology as moderating construct, and project success with five dimensions (i) cost (ii) schedule (iii) quality (iv) performance and (v) operating environment as an outcome from 242 IT professionals working in IT firms. Using structural equation modelling, the results reveal that narcissistic admiration has a negative significance, but the narcissistic rivalry has no significant impact on project success. Therefore it suggests that narcissistic admiration associated with positive attributes such as high esteem, envy, forgiveness, etc., with an overall motivation to focus on achievements may benefit in success of the project. The results further reveal that risk management technology has no moderating role between narcissistic admiration and rivalry with project success, which suggests risk management technology is not enough to reduce the narcissism leadership to contribute to project success. Further, the results do show the positive impact of risk management technology on project success. The study is helpful for organizational development (OD) professionals, project leaders, and IT firms. The study also provides a new avenue of investigation for academic researchers to tighten up the gap in narcissistic leadership.
Lessons Learned from EVALITA 2020 and Thirteen Years of Evaluation of Italian Language Technology

to 5 (for maximally concrete). The task is structurally similar to word sense disambiguation, whereas the input consists of a word marked in a sentence, and the systems have to predict a numeric value on a 7-point scale indicating its abstractness (or concreteness). Participants were invited to employ external resources of all kinds, e.g., knowledge bases, and indeed several of them did so. In fact, the top-ranked system is a hybrid of neural architectures and knowledge extracted from databases such as behavioral norms. DANKMEMES Multimodal Artefacts Recognition (Miliani et al. 2020). This is the first multimodal task for Italian, where participants were asked to create models for several classification tasks on Italian Internet memes about the 2019 Italian Government Crisis, namely Meme Detection, Hate Speech Identification, and Event Clustering. The task was mainly approached with multi-task learning frameworks, leveraging the multimodality, and therefore showcasing similarities and differences between the natural language and the image domains. Interestingly, data augmentation was also used by several systems, in both areas, producing robust classification systems, in particular for the first two subtasks. Ghigliottin-AI Evaluating Artificial Players for the Language Game “La Ghigliottina” (Basile et al. 2020). The task challenges researchers to develop a system able to defeat human players at the language game “La Ghigliottina”, a highly popular and appreciated quiz game in Italian television. The task is a re-run of the homonym 2018 task also at EVALITA. The system proposed by the task organizers was the only one to sufficiently solve this hard task, as for the 2018 edition as well. Such a solution is based on handcrafted patterns based on domain expertise, whereas the competitor system, based on word embeddings, performed poorly in comparison. PRELEARN Prerequisite Relation Learning (Alzetta et al. 2020). The task is devoted to automatically inferring prerequisite relations from educational texts collected from the Italian Wikipedia. The task consists of classifying prerequisite relations between pairs of concepts distinguishing between prerequisite pairs and nonprerequisite pairs. In this task, a “concept” is identified by a Wikipedia page, and the abstract of its page is provided as training material. Variants of the main task are proposed to explore the impact of external resources (constrained vs. unconstrained tasks) and domain (in-domain vs. cross-domain). The prevalent approach was neural, with recent transformer-based models achieving the best performance.
Spectral Learning Methods for Latent Variables

Latent variable models(LVM) are prevalent for dealing with problems pertaining to Structured Prediciton as they offer flexibility in modelling observed data by introducing conditional independence between observed variables, which allows us to compute the marginal distribution of the observed variables by integrating out the latent variables. Hence, we can represent complex distributions of interrelated observed variables more tractably by modelling them with latent variables. Also, introducing latent variables offers flexibility of probabilistic modeling and helps in addressing a diverse range of problem such as topic modeling(Blei et al., 2003), social network modeling(Hoff et al., 2002) etc.
Regional Competition and Sustainable Development of Tourism Industry in the Synthesis of Game Theory

It is the premise and effective means to realize the sustainable development of rural tourism industry to understand and analyze the connotation of rural tourism correctly and to plan rural tourism reasonably. Grounded on the theoretical synthesis of rural tourism development and planning at home and abroad, this study combined game theory to analyze the environmental protection problems in rural tourism development as well as planning, the interest behavior and development among the core stakeholders of tourism community, to provide valuable guidance for rural tourism development and planning in Fujian Province.