Miracle-dz/UniFAR-FTUs huggingface dataset:
The Research on the Interactions between the Emerging and Developed Markets: From Region and Structural Break Perspectives

This study utilizes a bivariate BEKK-EGARCH model with the setting of a structural break to investigate whether the interactions between stock indices in emerging and developed markets are different in terms of region, emerging stock indices, and subperiod. Then, this study investigated how the results of interactions vary with geographical location, emerging stock indices, and subperiod. Empirical results show that the interactions between emerging and developed markets indeed vary with geographical location and emerging stock indices, but are almost the same in the two subperiods. For example, for the paired stock indices in ‘Asia-America’ and ‘Asia-Europe’, or related to ‘XU100’, ‘SSE’ and ‘BSE’, the developed market mainly spills into the emerging market in terms of return and volatility. The findings from these empirical results can help investors and fund managers undertake different investment strategies in different regions and subperiods, and make effective investments.
BA_EnCaps: Dense Capsule Architecture for Thermal Scrutiny

Remote sensing integrated with deep learning (DL) improves wildfire assessment. The research has been done to scrutinize the areas affected by disastrous wildfires in Yunnan using DL. Wildfire identification and demarcation of the affected area have been limited to primitive thresholding and outdated machine learning classification techniques. Therefore, the research work incorporated DL in the wildfire scrutiny, and several of the most important considerations are investigated. The proposed research objective is to exploit the recent advancement of capsule-based DL together with the wildfire domain. The proposed dense structure provides highly efficient detection and segmentation of the burned area (BA). The BA dense capsule network (BA_EnCaps) is employed to extract and localize the burned zone with an overall accuracy of 98%. The model is evaluated quantitatively using accuracy, binary_cross-entropy, dice_loss, and mean square error (mse). The research aims to utilize the segmentation model to estimate the BA with great results. BA-EnCaps shows excellent accuracy in discriminating the spectral indices for the burned zone. The proposed method surpasses other segmentation benchmark techniques (U-Net, U-Net3p, SegCaps, Deep U-Net, and U-Net+) by substantially lessening the computing power. Finally, BA_EnCaps is compared with standard segmentation techniques and shows that DL-based models can assess wildfire better than conventional algorithms.
Food chain model with logistic growth and selective optimal harvesting under fuzzy environment

: A multispecies food chain harvesting model is formulated based on Lotka-Voltera model with three species which are affected not only by harvesting but also by the presence of prey, predator and the super predator. In order to understand the dynamics of the system, it is assumed that the all three species follows the logistic law of growth. Further, there is demand for prey predator species in the market and hence selective harvesting of two species is performed. We derive the condition for global stability of the system using a suitable Lyapunov function. The possibility of existence of bioeconomic equilibrium is discussed. The optimal harvest policy is studied and the solution is derived under imprecise inflation in fuzzy environment using Pontryagin’s maximal principle. Finally some numerical examples are discussed to illustrate the model.
Deep Learning Video Analytics Through Online Learning Based Edge Computing

Video analytics demand intensive computation resources, which means long processing delay when running on mobile devices. Although offloading computation to the cloud can partially solve the problem, transferring videos to the cloud introduces high transmission delay. With mobile edge computing, computation can be offloaded to the nearby edge servers to reduce the delay. However, the computation resources of the edge servers are usually limited and highly dynamic, and then server selection should be adaptive in order to improve the performance of video analytics. Also, frame resolution should be selected to achieve a better tradeoff between accuracy and frame processing rate. In this paper, we study the server resource-aware offloading problem for video analytics, where the goal is to maximize the utility which is a weighted function of accuracy and frame processing rate. The major challenge to solve this problem is the lack of server and network knowledge and the dynamic system environment. To overcome these challenges, we formulate the problem as a contextual Multi-armed Bandit problem, and propose a Bayesian Optimization based online learning algorithm to gradually learn the server status and the optimal solution, and make it adaptable for time-varying environments. Both theoretical analysis and evaluation results demonstrate the superior performance of our proposed algorithm.
On the Comparison of Ordinary Least Squares and Quantile Regression with Nigerian Financial Data on Trade Balance, Foreign Inflow and Imports

This research work compared the Ordinary Least Squares Regression and Quantile Regression models, as well as the differences between them thereby examining the compared models in terms of goodness of fit statistic and also recommend a suitable fit model for the data collected. These methods were applied to the Nigerian Financial Data on Trade Balance, Foreign Inflow and Imports on the Nigerian Gross Domestic Product. The results via this study, shows that the influence of Trade Balance, Foreign Inflow and Imports vary on the Nigerian Gross Domestic Product depending on the quantile one is looking at. This study recommends the robustness and stability of the Quantile regression model considered as an alternative to the Ordinary Least Square Model.
Dobór języka reprezentacji wiedzy w ontologiach dziedzinowych

W artykule podjeto problem doboru jezyka reprezentacji wiedzy dla ontologii dziedzinowych. Przedstawiono w nim zastosowania ontologii jako narzedzia reprezentacji wiedzy oraz analize formalizmow logicznych, takich jak: ramy, programowanie logiczne, logika opisowa, logika I rzedu i logika wspolna. Nastepnie analizie poddano szereg, klasycznych i opartych na znacznikach, jezykow reprezentacji wiedzy: Ontolingua, LOOM, OCML, FLogic, SHOE, RDF(S), OWL oraz OWL 2. Na podstawie analizy literatury usystematyzowano rowniez związki i zalezności pomiedzy poszczegolnymi wersjami i profilami jezyka OWL. Artykul konczy nastepująca konkluzja: jezyk OWL 2 DL jest najbardziej ekspresywnym jezykiem zachowującym rozstrzygalnośc, w związku z czym charakteryzuje sie on najwyzszą stosowalnością w budowie ontologii dziedzinowych, umozliwiających wnioskowanie.
Tangshen Decoction Enhances Podocytes Autophagy to Relieve Diabetic Nephropathy through Modulation of p-AMPK/p-ULK1 Signaling

Traditional Chinese medicine has certain advantages in the prevention and treatment of diabetic nephropathy (DN); thus, Chinese medicine therapy is considered as a promising strategy for treating DN. Here, the diabetic nephropathy model was established and intervened with Tangshen Decoction to explore its repair effect on diabetic kidney injury and the mechanism of autophagy. Different doses (10, 20 g·kg−1) of Tangshen Decoction (so-called Tangshen Jian, TSJ) or metformin were used to intervene for 16 weeks. The body weight (BW) and fasting blood glucose (FBG) of rats in each group were regularly monitored; a urine protein test kit (CBB method) was used to detect changes in urine protein (UP) content. The serum biochemical indicators, including Cr (creatinine), BUN (blood urea nitrogen), TC (total cholesterol), and TG (triglyceride), were detected by an automatic biochemical analyzer. HE (hematoxylin-eosin) staining, PAS, and electron microscopy were used to observe the podocyte damage. We showed that administration of TSJ or metformin prevented the increases in FBG level, serum Cr, BUN, TC, and TG level, and urine protein excretion in diabetic nephropathy. Simultaneously, the foot process fusion and fall-off were partially reversed after TSJ treatment. TSJ or metformin markedly upregulated the level of nephrin and podocin, accompanied by evident enhancement of podocyte autophagy and activation of p-AMPK/p-ULK1 signaling in the diabetic nephropathy. Therefore, TSJ may enhance podocyte autophagy to relieve diabetic nephropathy through modulation of p-AMPK/p-ULK1 signaling, which has important application prospects in the clinical treatment of diabetic kidney damage in the future.
Drawing Random Floating-point Numbers from an Interval

Drawing a floating-point number uniformly at random from an interval [a, b) is usually performed by a location-scale transformation of some floating-point number drawn uniformly from [0, 1). Due to the weak properties of floating-point arithmetic, such a transformation cannot ensure respect of the bounds, uniformity or spatial equidistributivity. We investigate and quantify precisely these shortcomings while reviewing the actual implementations of the method in major programming languages and libraries, and we propose a simple algorithm to avoid these shortcomings without compromising performances.
Implementation of Project Based Learning on The Sanitation of Public Places Course

The Public Places Sanitation (STTU) is a compulsory course in the field of Occupational Safety and Health/ Environmental Health of the undergraduate program, Faculty of Public Health. Evaluation of learning outcomes in the previous year showed students had low interpersonal skills . The objectives of this class action research are to improve and change the measures to solve the problems and to find models and procedures that provide reassurance against troubleshooting efforts by making modifications or adjustments as necessary. This class action research was conducted in the Public Places Sanitation course in Academic Year 2021/2022 in the Undergraduate Program, Faculty of Public Health, Andalas University for 2 months from September to October 2021 using quantitative method. Based on the results of the data analysis, there was an increase in students' midterm exam scores when compared to achievements in the previous year. This research has limitations, among others, online learning situations make it difficult for students to create projects together. Moreover, the time duration of implementation this method is considered too short. In addition, the project results are not in accordance with the target, namely a model made by students.
Molecular Dynamics and Evolution of Centromeres in the Genus Equus

The centromere is the chromosomal locus essential for proper chromosome segregation. While the centromeric function is well conserved and epigenetically specified, centromeric DNA sequences are typically composed of satellite DNA and represent the most rapidly evolving sequences in eukaryotic genomes. The presence of satellite sequences at centromeres hampered the comprehensive molecular analysis of these enigmatic loci. The discovery of functional centromeres completely devoid of satellite repetitions and fixed in some animal and plant species represented a turning point in centromere biology, definitively proving the epigenetic nature of the centromere. The first satellite-free centromere, fixed in a vertebrate species, was discovered in the horse. Later, an extraordinary number of satellite-free neocentromeres had been discovered in other species of the genus Equus, which remains the only mammalian genus with numerous satellite-free centromeres described thus far. These neocentromeres arose recently during evolution and are caught in a stage of incomplete maturation. Their presence made the equids a unique model for investigating, at molecular level, the minimal requirements for centromere seeding and evolution. This model system provided new insights on how centromeres are established and transmitted to the progeny and on the role of satellite DNA in different aspects of centromere biology.
KLASIFIKASI CITRA TEKSTUR KAYU MENGGUNAKAN GRAY LEVEL CO-OCCURANCE MATRIX DAN LOCAL BINARY PATTERN

Kayu merupakan bahan mentah yang akan diproses untuk dijadikan perabotan rumah tangga atau untuk kebutuhan manusia lainnya. Permasalahannya adalah karena banyaknya jenis kayu yang mempunyai corak atau bentuk tekstur yang cenderung sama akan menyulitkan manusia untuk mengenali jenis kayu tersebut. Dalam penelitian ini pengolahan citra digital akan digunakan untuk melakukan ekstraksi fitur dari tekstur kayu kemudian dilakukan pengklasifikasian untuk mengetahui, mengenali dan memastikan jenis kayu. Kayu yang digunakan terbagi menjadi tiga jenis kayu, proses ekstraksi menggunakan dua metode yaitu Gray Level Co-Occurance Matrix dan Local Binary Pattern sedangkan untuk klasifikasi menggunakan K-Nearest Neighbor. Pengujian berdasarkan perbedaan dan kesamaan jumlah data training prosentase keakurasian 78,33%. Pengujian berdasarkan jumlah k memiliki ratarata akurasi dengan menggunakan nilai k yang berbeda mencapai 77,6%. Pengujian menggunakan citra sama dengan data latih tingkat keakurasiannya adalah 100%. Pengujian menggunakan citra diluar data latih mencapai keakurasian 78%. Pengujian menggunakan perbedaan jumlah bit pada level keabuan, 5 bit mendapatkan keakurasian 76% dan yang menggunakan 7 bit mendapatkan keakurasian sebesar 81%.
Dentist's Knowledge, Attitude and Practice towards Obstructive Sleep Apnea in Central India: A Questionnaire Based Survey

Context: Obstructive sleep apnea is a very usual sleep disorder that frequently goes undetected. In dental training enough significance aren’t inclined to the various sleep disorders existing. Dentists take a crucial role in assessing, diagnosing, management and referring of OSA patients. Aim: To evaluate the knowledge, attitude and practice about obstructive sleep apnea among dentists in Central India. Study design: This cross-sectional study was carried out in Central India from January 2021 to June 2021 for duration of six months at Nagpur. Methodology: 185 dentists participated in the survey. A questionnaire consisting of 23 items, evaluating the knowledge, attitude, and practice with respect to nine distinct domains concerning obstructive sleep apnea and circulated through a web designed program. Good/poor remarks were given to knowledge and practice questions and favorable/unfavorable for attitude questions. Study data was analyzed using descriptive and inferential statistics using chi square test. Results: Overall dentists were observed to have good knowledge for domains of awareness, general findings and risk factors. Good knowledge was found in MDS for domains of screening and diagnosis (64.65% and 50.51%) and treatment and referral (65.66% and 57.58%) in comparison to the BDS group. Favorable attitude for all the domains was reported while poor practice in all domains. Conclusion: Dentists had favorable attitude towards OSA but poor knowledge in certain domains about OSA which may be linked to lacked clinical experience and hurdle in their practice. They were passionate about further education on OSA.
Utilization of Reformed Coconut Fiber and Banana Stem Fibre as Green Oil Sorbent

ABSTRACT Oil spillage is one of the significant wellsprings of contamination. It can happen in both land and water. Their expulsion from marine and land environment is regularly difficult. This investigation considers the utilization of coconut and banana stem fibers as a feasible sorbent material for marine and land oil spill recuperation. Coconut and banana stem fibers have lumens, which increases their specific surface area available for oil sorption. These fibers are cheap and have low bulk density, which makes them reasonable for oil spill recuperation. Moisture content in coconut and banana stem fiber were found to be 4.44% and 5.44%, respectively. The oil sorption limit of coconut and banana stem fiber was improved by coating it with chitosan. The treated fibers showed a considerable enhancement in oil sorption capacity for coconut fiber (9.87%) and banana stem fiber (6.59%), according to the results. The characterization of the natural and coated fibers was completed utilizing scanning electron microscopy and Fourier transform infrared spectroscopy. Moisture content and oil sorption limit of the fibers were estimated. The test has confirmed that both cocont and banana stem fibers can be utilized as a potential sorbent material for oil spillage tidy up.
Eliciting Activity Goals With a Self-Administered Survey Among Patients With Hip or Knee Osteoarthritis

Background: Success of treatment for hip or knee osteoarthritis (OA) should be evaluated relative to patients’ personal activity goals. Questions/Purposes: We sought to ascertain important principles for collecting such goals and developed a survey informed by those principles to facilitate better shared decision-making. Methods: From a series of 100 patient interviews inquiring about specific activity goals, we identified 6 principles for goal collection that are important to patients and physicians and could practically facilitate better shared decision-making (phase 1). Incorporating these principles, we designed a self-administered survey to measure specific pretreatment activity goals, piloting in 1 surgeon’s office (phase 2). During office visits, the feasibility of achieving stated goals was discussed between the surgeon and the patient, and goal modifications were recorded. Results: The phase 2 survey was administered to 252 patients, among whom 130 were women (51.6%); 215 (85.3%), white; mean age, 58.5 years; mean body mass index, 30.2 kg/m2; and 92.9% had 1 or more goals, totaling 106 unique goals. Patient demographics were associated with having goals for walking, running, exercising, golfing, tennis, and stairs. Hip and knee patients could last perform their goal on average 21.7 and 38.6 months prior (P = .002). Patient and surgeon agreed to modify goals 19% of the time, more often among younger patients (P = .001) and for running (64% modified, P < .0001) and skiing (42%, P = .0026), but less often for walking (14%, P = .0430) and golf (0%, P = .0204). Conclusions: Patients’ activity goals can be captured by a self-administered survey, collected before an office visit, and used to facilitate shared decision-making.
Climate Change Accountability, Including TCFD in the Nordic Arctic Countries

Collectively, Finland, Norway and Sweden have some of the most ambitious commitments for combatting climate change, with Finland’s goal to be carbon neutral by 2035, Norway’s goal to reduce greenhouse gas emissions by 40% by 2030 and Sweden’s goal to have zero net greenhouse gas emissions by 2045 at the latest. Recent attempts on the international level to address climate change have resulted in setting up in 2015 the FSB (Financial Stability Board) Task Force on Climate-related Financial Disclosures (TCFD). In 2017 TCFD introduced recommendations on voluntary, consistent climate-related financial risk disclosures for companies to provide information to investors and other stakeholders about risks and opportunities related to the transition to a lower-carbon economy. The article addresses climate change accountability by states and by companies in the Nordic Arctic countries. Climate change accountability or willingness to take responsibility is proxied by companies’ reporting in compliance with TCFD. First, I investigate institutional mechanisms of TCFD adoption in the Nordic Arctic, including Finland, Norway and Sweden. To achieve that, I study Finnish, Norwegian, and Swedish institutions that endorse or provide practical guidelines for implementing TCFD, e.g., stock market regulators. The study results provide an overview of governance structures and practical implementation of TCFD in the Nordic Arctic (Finland, Norway and Sweden). Furthermore, the study contributes to the discussion on how to balance ambitious climate change targets with sustainable economic development in the Arctic regions.
Chinese language learners evaluating machine translation accuracy

With increasingly rapid advances in machine translation (MT) technology, such as Google Translate, MT has become an indispensable learning resource for second or additional language learners. Many studies indicate that MT or post-editing of MT (PEMT) can be an effective tool for L2 learning and teaching. Nevertheless, little research illustrates how language learners judge or evaluate the accuracy of MT output. The judgement of MT accuracy is essential because MT is not yet error-free. Therefore, the aim of this research is to explore how L2 learners attempt to judge the accuracy of MT output when using MT or PEMT. This study was undertaken through a teaching intervention in an online English-Chinese translation course. Student participants included L2 learners of Chinese studying at a university in Taiwan. Findings from observations of screen recordings and focus group discussions reveal that students use different MT tools and additional online-based resources as complementary strategies to better judge MT accuracy. These include: 1) using more than one MT tool to cross-check MT output; 2) using dictionaries to check word meaning and word usage by looking at example sentences; 3) using search engines to check word definitions, translations, and collocations. effect, making the transformation of education an unavoidable necessity, with ‘adaptive learning’ forming the basis of education reform.
Telemedicine and Its Application in Healthcare Management: Telemedicine Management

1- MUSTAFA ALMAHDI ALGAET received the B.S. degrees in electrical engineering from Altahdi university of Libya, in 2004 and the M.S. degree in information and Communication technology from University Utara Malaysia, Malaysia (UUM), in 2006. Currently, he is PhD student at UTeM. His research interest is Quality of service (QoS) in wireless telemedicine. 2-DR. ZUL AZRI BIN MUHAMAD NOH is a Senior Lecturer teaching Advanced High Performance Networks, Network Routing, Implementing and Administering Active Directory, and Wireless Network and Mobile Computing. Dr. Zul Azri's education was first in Bachelor of Engineering in Electrical and Computer Engineering, then Masters of Engineering in Communication and Computer Engineering, then Doctor of Engineering in Communication and Computer Engineering, all from Nagoya Institute of Technology Japan. In October 2007, while pursuing his PhD, he joined UTeM as lecturer at Faculty of Information and Communication Technology. Currently, he is head of Advanced Networking and Distributed System research cluster. His current research interests include quality of service (QoS), wireless LAN, packet scheduling algorithm, and multimedia communication 3-DR. ABDUL SAMAD SHIBGHATULLAH is a Senior Lecturer in faculty of information and communication Technology UTeM, and his PhD Degree in computer science (Brunel University, UK) 2008, Msc Computer science (UTM) 2001, B.Acc (UKM) in 1999, and his field is Scheduling and Agent Technology 4-ALI AHMAD MILAD received the B.S. degrees in computer science from Almergib University in 2005, and the M.S. degree in computer science from University Putra Malaysia, Malaysia (UPM) 2009, currently; He is Ph.D. student at UTeM. His research interest is Very High Speed Wireless LANs. MAC protocols. 5-DR. AOUACHE MUSTAPHA . Was born in Frenda, Algeria; received the B.Sc. (2000) in Control and Automation from University of Boumerdes (UMBB), Algeria; M.Sc (2006) and PhD (2012) in Electrical, Electronic & Sys