Miracle-dz/UniFAR-FTUs huggingface dataset:
Statistical Analysis on Factors That Hinders the Effectiveness of Junior Athletics Projects in North Wollo Zone, Ethiopia

Background: This study was conducted to assess factors that affect the effectiveness of junior athletics projects in north Wollo zone. The main objective of the study was identifying factors affecting the effectiveness of junior athletics projects in north Wollo zone. Methods: The study used stratified sampling method to select the samples. Both primary and secondary source of data were used to gather reliable data. Mixed types of research approach (quantitative and qualitative) were employed. To achieve the objective of the study, cross-sectional study designed were employed. The collected data was organized, tabulated, and analyzed using descriptive and inferential method of data analysis. Results: The results of Proportional Odds Model reveal that training year or duration on the training of the athlete, that are trained between 2.1 to 3 year and 3.1 to 4 years are 0.855 and 0.985 times respectively smaller in performance than those athletes who trained in the project for less than 1 year. The result showed that athletes who haven’t the training field are 0.792 times less in performance than those athletes who have training field. In this study, those athletes who have well, bad and very bad relationship with their coach are 0.707, 0.989 and 0.979 times respectively lower in performance than athletes having very good relationship with their coach. In addition athletes who don’t participate in planning with their coach are 0.849 times lower in performance as compare to those athletes who participate. Those athletes who don’t get payment in the project are 0.952 times low in performance than athletes who get payment. Conclusion: The study identified factors related to sport offices related, coach related factors, athlete related. Regarding to sport office related factors such as shortage of training equipment and facilities, non-availability of training fields, lack of supervision and follow up for coaches and athletics projects, shortage of competition opportunities for athletes. Among coach related factors inability to prepaid peridized and scientific training plan, lack of providing proper demonstration for athletes, not recruiting the athletes based on talent identification. Considering athlete related factors lack of motivation on athletics sport.
PRELIMINARY SCREENING OF PHYTOCHEMICAL CONSTITUENTS, ANTIOXIDANT AND ANTIMICROBICIDAL ACTIVITIES IN THE METHANOLIC LEAF EXTRACT OF COUROUPITA GUIANENSIS

Objective: The objective of the study was the preliminary screening of the methanolic leaf extract of Couroupita guianensis for various phytochemical constituents, its antioxidant, antibacterial, and antifungal activities. Methods: Phytochemical screening of 18 qualitative, 6 quantitative constituents, antioxidant activity, alpha-amylase inhibitory activity, and alpha-glucosidase inhibitory activity of the methanolic extract of the leaf of C. guianensis was performed adopting the standard protocols. The disk diffusion methods were used for assessing the antibacterial and antifungal activities of the extract. Results: The preliminary studies revealed the presence of alkaloids, saponin, flavonoids, phenol, tannin, and terpenoids in the methanolic extract of the leaf of C. guianensis. Potent antioxidant, free radical scavenging activity, and inhibitory activity against α-amylase and α-glucosidase activity of the methanolic extract were also evident. Conclusions: The preliminary studies in the methanolic extract of the leaf of C. guianensis are suggestive of the therapeutic potentials of the methanolic extract of leaves of C. guianensis.
HIV-infected patients on cART had similar level of arterial stiffness to the patients with ST-segment elevation myocardial infarction

The cardiovascular disease has become very common among HIV-infected patients.The aim was to compare the arterial stiffness and the endothelial dysfunction in healthy HIV-infected patients to non-HIV-infected patients in week 4 after ST-segment elevation myocardial infarction (STEMI). The arterial stiffness was calculated by Endo-PAT 2000 (ITAMAR®) and the endothelial function by Peripheral Arterial Tonometry (PAT®). The correct endothelial function was defined for natural logarithm of reactive hyperaemia index (lnRHI) > 0.51. Arterial stiffness was assessed as the AI and corrected for heart rate of 75 bpm (AI@75). Sixty three patients were recruited to this study, 34 subjects with HIV infection (18 on cART) and 29 HIV-negative subjects after recent STEMI. AI was significantly higher in STEMI group than in HIV group. However, after AI@75 standardisation, no statistically significant difference was found between two studied groups. HIV-positive patients on cART had equally high values of arterial stiffness as persons after STEMI. The observed lnRHI results were significantly lower in STEMI group in comparison to HIV-positive patients, and the biggest significant difference was seen between STEMI group and ARV-treated HIV-infected patients.ARV-treated HIV-infected patients may have similarly high values of arterial stiffness as non-HIV-infected persons in week 4 after STEMI. More larger studies are required to assess our observation concerning arterial stiffness and elevated risk of cardiovascular disease development in this group of patients, independently of age, smoking status and concomitant chronic diseases.
A study on the impact of psychological empowerment on motivation and satisfaction among the faculty working in the technical educational institutions in India based on age and work

The purpose of this study is to investigate how the impact of PE on motivation and satisfaction varies according to the faculty member's age and work experience. Data were collected from 402 faculty members employed at technical institutions across India. From the results of the study, it is evident that faculty members with above average age exhibited higher PE, motivation and satisfaction. Subsequently, faculty members with above average experience possessed higher level of PE and satisfaction. Further, the implication of these findings suggests that the proposed framework will act as a benchmarking tool to measure the psychological empowerment among the faculty members.
From Biosecurity to Security Ecologies: An Analysis between Old Dairy Farming Traditions and Routines and Veterinary Recommendations in Spain

Biosecurity has gained significant interest in farm animal health in recent years. However, in dairy cattle farms, there is slight, or no implementation of biosecurity practices recommended by official authorities and techno-scientific experts. This situation might be explained by the tension between old farming traditions and routines and veterinary recommendations. We draw upon Lefebvre’s three-fold model of space, which addresses spatial practices (old traditions and routines), representations of space (recommendations) and representational space (final implementation of biosecurity measures), constituting security ecologies to understand what might be happening by using an ethnographic approach on two farms in Galicia and two in Catalonia in Spain. The three biosecurity practices considered are management of dead animals; control of vectors and pests; and animal management. The results show that farms have different specific contexts, and that the reasons behind the positions of farmers and veterinarians, effective communication and common sense need to be considered. Security ecologies based on Lefebvre’s model could therefore be a positive mechanism for ensuring the implementation of biosecurity, beyond the visions of authorities or specialists.
Emotion Regulation in Teachers for Students with Special Needs in Inclusive Islamic Elementary School: An Interpretative Phenomenological Analysis

Being a teacher means performing an emotional endeavor. Especially for teachers working with special needs students. This research aims to explore the emotion regulation strategies used by teachers while working with special needs students. A total of 5 individuals, special needs teachers in inclusive Islamic elementary school (Madrasah Ibtidaiyah) participated in the study. Using interpretative phenomenological analysis (IPA), the emerging themes from teacher’s experiences indicate that awareness and belief in emotional experiences encouraged teachers to apply emotion regulation strategies. As emotion regulation being implemented continuously, teacher’s efficacy and well-being will also be developed during the process. These findings provide deeper understanding about emotion regulation as a skill that enriches teacher’s emotional competencies. Thus, it needs to be developed, especially for teachers in special education or inclusive schools, not only to support children behavior and classroom management, but also teacher’s well-being and mental health.
Beyond investigation-relevant information: a content analysis of police questioning

ABSTRACT There are two primary investigative interview objectives: gathering information to determine what happened and who did it and assessing the witness’s reliability. The present study examined to what extent investigative interviewers gather investigation-relevant information (IRI) compared to interviewee details (ID) to assess witness reliability. As part of a training course, 42 police officers participated as interviewers and mock witnesses by viewing a crime video. The interviews were recorded and rated for question type and question content through thematic analyses. IRI questions accounted for 78% of the questions asked, while ID questions accounted for 22% of the questions asked. The police officers assessed the way witnesses perceived this information and the attendant meta-processes and used more inappropriate questions than appropriate questions. These results help to elucidate the objectives of police interviews that should be considered when evaluating witness performances in laboratory settings and when developing effective interviewing protocols.
PCR Instrument-assisted Acidolysis for Monosaccharide Composition Analysis of Serum Glycans

This protocol describes the procedures where a PCR instrument-assisted acidolysis is used for releasing monosaccharides from serum glycans. The monosaccharide composition analysis is subsequently obtained by a HPLC method that separates and quantifies all 1-phenyl-3-methyl-5-pyrazolone (PMP)-labeled monosaccharides in 10 μl serum in 20 minutes. The rapid heating, precise temperature control, and gradient heating properties of PCR instrument provides with consistent acidolysis and derivatization conditions for up to 96 samples simultaneously. The described workflow takes approximately 4–5 h, up to 72 serum samples can be analyzed with one HPLC instrument per day.
An electrochemical algal biosensor based on silica coated ZnO quantum dots for selective determination of acephate

An electrochemical biosensor for the determination of the acephate pesticide was developed based on algal modified silica coated ZnO quantum dots (QDs). The surface active alkaline phosphatase enzyme on the Chlorella sp. algal cell wall dephosphorylates substrate p-nitrophenyl phosphate (pNPP) and release p-nitrophenol (pNP), which being electroactive gets oxidized on the modified working electrode to generate current equivalent to the amount of pNP released from the substrate. The presence of acephate would inhibit the formation of pNP and hence decrease in current, which indirectly corresponds to the concentration of the pesticide present. The biosensor responds linearly in the concentration range of 10−11 M to 10−3 M for acephate and showed that QDs strongly influenced the biosensor performance as they increased sensitivity and improved the detection limit.
Parallel Multiphysics Simulation of Package Systems Using an Efficient Domain Decomposition Method

With the continuing downscaling in feature sizes, the thermal impact on material properties and geometrical deformations can no longer be ignored in the analysis of the electromagnetic compatibility or electromagnetic interference of package systems, including System-in-Package and antenna arrays. We present a high-performance numerical simulation program that is intended to perform large-scale multiphysics simulations using the finite element method. An efficient domain decomposition method was developed to accelerate the multiphysics loops of electromagnetic–thermal stress simulations by considering the fact that the electromagnetic field perturbations caused by geometrical deformation are small and constrained in one or a few subdomains. The multi-level parallelism of the algorithm was also obtained based on an in-house developed parallel infrastructure. Numerical examples showed that our algorithm is able to enable simulation with multiple processors in parallel and, more importantly, achieve a significant reduction in computation time compared with traditional methods.
Application of IoT in Current Pandemic of COVID-19

As we know that Internet, a rebellion innovation has transformed everything, Internet of Things has made a hope for excellent future of Internet with Machine-Machine (M2M) type of communication. This review paper has also shown that it is possible and affordable to construct these smart systems based on Internet of Things (IoT). IoT delivers exceptional advancement in the healthcare domain. This paper explores the roles of IoT that revolutionize the healthcare domain by providing enormous healthcare benefits to the mankind by offering affordable and practical healthcare solutions. The main focus of this paper is to discuss the role of IoT in smart hospitals and its significance to deal with pandemics is also highlighted. For serving the community-specific needs during spread of pandemic, various smart devices can be utilized that can provide varied functionalities including proper monitoring of high-risk patients, tracking their bio-metric measurements and capturing real-time data. We have also studied various blueprints which can sense unforeseen happenings using numerous sensors and reveal the facts accumulated on LED display. Observational outcomes have shown good agreement with the hypothetical statements.
Simultaneous Roadside and Urban Background Measurements of Submicron Aerosol Number Concentration and Size Distribution (in the Range 20–800 nm), along with Chemical Composition in Strasbourg, France

The adverse health impact of particles and ultrafine particles (UFP) is proven, highlighting the need of measuring the particle number concentration (PNC) dominated by UFP. So far, PNC had never been measured in the Strasbourg urban area (France). The present study on particle size distribution and PNC measurements by an UFP-3031 analyzer was conducted during winter 2019 on a background and a roadside multi-instrumented sites (Black Carbon, chemical speciation, particulate matter 10 μm or less in diameter—PM10 mass). This paper shows significantly higher particle number concentrations of particles below 100 nm at the traffic site compared to the background site. The presence of a road axis thus mainly influences UFP, contrary to larger particles whose levels are more homogeneous over the agglomeration. During the measurement period, the nature of the particles (particle size contribution and chemical composition) was different between periods of high PM10 mass concentrations and periods of high PNC. High PM10 mass concentrations were associated with a high contribution of particles larger than 100 nm but they did not show specific chemical signature. On the other hand, during the periods with high PNC, the chemical composition was modified with an increase of the primary carbonaceous fraction compared to the periods with low PNC, but there was then no clear change in size distribution. Overall, this study illustrates that PM10 mass concentrations were barely representative of UFP and PNC variations, confirming that the monitoring of the latter metrics is necessary to better evaluate the particles toxicity, knowing that this toxicity also depends on the particle’s chemical composition.
Electrodeposition and Characterization of Lanthanide Elements on Carbon Sheets

Electrochemical coating and recovery by electrodeposition have been invaluably employed for facial thin film fabrication and the recycling of used materials. Herein, we have established a full data set of lanthanide (Ln: La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, and Yb) elements electrodeposited on carbon sheets. Cyclic voltammetry was performed for 10 mM Ln(III) ions in a 0.1 M NaClO4 electrolyte over a carbon sheet between +0.5 V and −1.7 V (vs. Ag/AgCl). Amperometry was performed at a given potential to electrodeposit the Ln element on the carbon sheet. Their physicochemical properties were fully investigated by scanning electron microscopy, Fourier-transform infrared spectroscopy, energy-dispersive X-ray spectroscopy, and X-ray photoelectron spectroscopy. The newly established full data set for Ln(III) ions over carbon electrodes provides useful fundamental information for the development of coating and recovery methods of Ln elements.
Weighted infinitesimal unitary bialgebras on free monoid algebras

Abstract. The concept of a weighted infinitesimal unitary bialgebra is an algebraic abstraction of the non-homogeneous associative classical Yang–Baxter equation. In this paper, we equip the free monoid algebra with a suitable coproduct which makes it a weighted infinitesimal unitary bialgebra. Furthermore, by exploring the relationship between weighted infinitesimal unitary bialgebras and pre-Lie algebras, we construct a preLie algebra on free monoid algebras. Finally, we show that the weighted infinitesimal unitary bialgebra on free monoid algebras has an infinitesimal unitary Hopf algebra structure in the sense of Aguiar.
A Survey of Machine Learning Techniques Used on Indian Stock Market

Stock market provides nonlinear time series data that has been difficult for making any kind of predictions. Since the advent of various Machine Learning techniques lot of research is covered in this area. Researches have mostly been carried out using Supervised Machine Learning algorithms on predicting the price of a particular stock and also on predicting the stock index movement. The studies also cover various unsupervised machine learning algorithms as well as some statistical methods used in the stock price prediction. Study has been covered on generating portfolio of stocks that maximizes the profit with minimum risk. Social Media today generates a large amount of data and has a significant impact on the buy/sell decision made by experts. Specifically, research has been carried out on how tweets and news have an impact on stock price movement. Recent researches focus more on neural networks, deep learning and hybrid models. This study tries to identify the different approaches used by researchers in order to improve the accuracy of machine learning algorithms on the India Stock Market. The survey emphasizes that all aspects related to stock market need to be considered before making any kind of prediction.
Direct-Quadrature Sequence Models for Energy-Function Based Transient Stability Analysis of Unbalanced Inverter-Based Microgrids

The reliability of supply in distribution networks can be improved by islanding (parts of) the network as autonomous microgrids in case of a contingency. Microgrids are commonly fed by inverter-based distributed energy resources, which causes transient stability challenges due to the lack of inertia and strongly coupled dynamics. The transient stability of inverter-based microgrids is conventionally analyzed by time-domain analysis. However, energy-function based transient stability analysis has advantages over time-domain analysis, as it provides a stability result for all initial conditions and allows uncertainty to be taken into account with the domain of attraction. Microgrids are generally unbalanced, however models for unbalanced energy-function based transient stability analysis are lacking in the literature. In this paper, coupled sequence components models of distributed energy resources and load devices in the $dq$ reference frame are proposed, and experimentally validated with unbalanced voltage transients. The validated models are used for energy-function based transient stability analysis of an unbalanced inverter-based case study microgrid. Finally, the impact of unbalanced connection of devices on transient stability is analyzed. The results indicate that the proposed models accurately represent the behavior of physical devices and that the unbalanced connection of devices significantly impacts the transient stability of inverter-based microgrids.
Sparse Pose Graph Optimization in Cycle Space

The state-of-the-art modern pose-graph optimization (PGO) systems are vertex based. In this context, the number of variables might be high, albeit the number of cycles in the graph (loop closures) is relatively low. For sparse problems particularly, the cycle space has a significantly smaller dimension than the number of vertices. By exploiting this observation, in this article, we propose an alternative solution to PGO that directly exploits the cycle space. We characterize the topology of the graph as a cycle matrix, and reparameterize the problem using relative poses, which are further constrained by a cycle basis of the graph. We show that by using a minimum cycle basis, the cycle-based approach has superior convergence properties against its vertex-based counterpart, in terms of convergence speed and convergence to the global minimum. For sparse graphs, our cycle-based approach is also more time efficient than the vertex-based. As an additional contribution of this work, we present an effective algorithm to compute the minimum cycle basis. Albeit known in computer science, we believe that this algorithm is not familiar to the robotics community. All the claims are validated by experiments on both standard benchmarks and simulated datasets. To foster the reproduction of the results, we provide a complete open-source C++ implementation1 of our approach.
External Benefit Assessment of Urban Utility Tunnels Based on Sustainable Development

Urban utility tunnels (UUTs) can have great external benefits in terms of social and environmental aspects for the sustainable development of a city. However, the high initial construction cost has been the main obstacle to the promotion of UUT projects for a long time. Although several evaluation methods for the benefits of UUTs have been proposed, most of them focus on the cost assessment during the construction period and are limited in terms of their scientificity, the feasibility of the valuation methodology and the comprehensiveness of external categories. The external benefit assessment of UUTs during their service life remains lacking, leading to an incomplete insight into UUT projects. Therefore, a scientific evaluation method of the long-term external benefits of UUTs is still needed from the perspective of urban sustainable development. This paper proposes a composite market price method to carry out a simple but systematic evaluation of the positive externalities of UUTs in monetary terms. Detailed instructions on the operation of the method are also elucidated to further improve its practicability. The feasibility and validity of the method is then demonstrated through a case study of the UUT project in Xiong’an New Area, China. It is also concluded that UUTs can benefit all social subjects and that a classification of externalities based on different social subjects can foster better development and broader support for the implementation of UUTs.