Miracle-dz/UniFAR-FTUs huggingface dataset:
THE COMBINED EFFECT OF ISLAMIC WORK ETHICS, HIGH-PERFORMANCE WORK PRACTICE, AND PROJECT GOVERNANCE ON PROJECT SUCCESS

Purpose: This study aims to observe the effect of religion-based work ethics, i.e., Islamic work ethics (IWE) and High-performance work practices (HPWP), on the success of projects in the development sector of Pakistan. Further, the study proposes project governance as a moderator between IWE, HPWP, and project success. Methodology: This is a quantitative study and used a convenience sampling technique to collect the data. The data was collected from the project-based organization in Rawalpindi, Islamabad, and Muzaffarabad, and 239 questionnaires were circulated to the employees of project-based organizations. For data analysis, SPSS was used. Results: Results indicate that IWE and HPWP significantly contribute towards project success. Likewise, the results of moderated regression analysis show that project governance enhances the positive relationship between IWE, HPWP, and project success. These results have been discussed. Practical Implications: The results carry significant implications for managers of project-based organizations. Our results point towards the importance of work ethics, high-performance work practices, and governance mechanisms towards the success of projects. Managers should thus be vigilant toward these mechanisms. Originality: The contribution of this study is that first time we see the impact of Islamic work ethics on project success. Islamic work Ethics is an essential and worthwhile concern for an organization because it allows employees to work honestly and ethically to achieve project success.
A Hybrid Method to Diagnose 3D Rotor Eccentricity Faults in Synchronous Generators Based on ALIF_PE and KFCM

This paper proposed a new hybrid diagnosis method for the generator’s 3D static eccentricity faults which include the axial eccentricity, the radial eccentricity, and the mixed eccentricity composed of the former two. Firstly, adaptive local iterative filtering (ALIF) method was used to decompose the vibration signals of the generator under eccentricity faults. Then, in order to figure out the intrinsic mode function (IMF) components with the upmost feature information, the correlation coefficient was calculated. Finally, the components’ permutation entropy (PE) is extracted to construct the eigenvector matrix which can be used to input the kernel fuzzy C-means (KFCM) algorithm to obtain the result of clustering. The result indicates that the classification coefficient based on ALIF and KFCM behaves closer to 1, while the average fuzzy entropy (FE) is closer to 0, showing that this method is able to detect different eccentricity faults more accurately.
Use of heparin in patients with severe COVID-19: What is the evidence?

The rapid spread of coronavirus disease (COVID-19) worldwide urges the need for studies on the illness and its management. The COVID-19 infection leads to hypercoagulation due to inflammatory cytokine release and D-dimer increase in critically ill patients, resulting in pulmonary thromboembolism (PE) and venous thromboembolism (VTE) evolving to sepsis and death. The study evaluated the currently existing evidence on heparin administration in patients with severe COVID-19. An integrative literature review was done by searching for scientific studies in the PubMed, Scopus, Embase, and Web of Science databases. The analyzed studies showed that heparin use in critically ill patients could efficiently prevent thrombotic events and reduce the exacerbated inflammatory process. However, further investigation on the effect on patients is still needed. The use of heparin in critically ill COVID-19 patients has been prescribed increasingly by doctors. But its use has not yet had its outcomes well established in the literature. Therefore, deeper investigations and new research development are needed to clarify potential beneficial effects.
Description of red soils in a semi-arid climate and evaluation for vineyard (Vitis vinifera L.) use.

Three profiles along the slope of a quartzite hill have been studied and characterized. Pedological (e.g. horizons, depth, shape of boundary, stoniness and structure), physical (color, texture and nature of clays) and chemical (pH, conductivity, nutrient content and balance) parameters have been studied. For centuries, vineyards have been widely cultivated in regions with a semiarid climate, such as La Mancha (Central Spain). However, very few studies into viticole soils have been carried out to determine their suitability for the production of quality wine. The results show that the soils investigated here are different from the Calcisols, which are traditionally associated with vineyards in La Mancha. The studied soils are mildly acidic (pH 6.37.3 in exceptional cases), have a high clay content (21-52%) and have a low basis saturation (29.1%, but increasing with depth to saturation in the lower profile). The different properties enable these soils to be classified as Luvisols (FAOISSS) with rhodic or chromic character due to the presence of iron oxides (2.8% in argilic horizons). Alternative soil management practices are suggested to improve organic matter and biological activity, and to minimize erosion, which could be the biggest problem for the use of these soils for woody cultures.
Development and Validation of an Online Analyzer for Particle Size Distribution in Conveyor Belts

Online measurement of particle size distribution in the crushing process is critical to reduce particle obstruction and to reduce energy consumption. Nevertheless, commercial systems to determine size distribution do not accurately identify large particles (20–250 mm), leading to particle obstruction, increasing energy consumption, and reducing equipment availability. To solve this problem, an online sensor prototype was designed, implemented, and validated in a copper ore plant. The sensor is based on 2D images and specific detection algorithms. The system consists of a camera (1024 p) mounted on the conveyor belt and image processing software, which improves the detection of large particle edges. The algorithms determine the geometry of each particle, from a sequence of digital photographs. For the development of the software, noise reduction algorithms were evaluated and selected, and a routine was designed to incorporate morphological mathematics (erosion, dilation, opening, lock) and segmentation algorithms (Roberts, Prewitt, Sobel, Laplacian–Gaussian, Canny, watershed, geodesic transform). The software was implemented (in MatLab Image Processing Toolbox) based on the 3D equivalent diameter (using major and minor axes, assuming an oblate spheroid). The size distribution adjusted to the Rosin Rammler function in the major axis. To test the sensor capabilities, laboratory images were used, where the results show a precision of 5% in Rosin Rambler model fitting. To validate the large particle detection algorithms, a pilot test was implemented in a large mining company in Chile. The accuracy of large particle detection was 60% to 67% depending on the crushing stage. In conclusion, it is shown that the prototype and software allow online measurement of large particle sizes, which provides useful information for screening equipment maintenance and control of crushers’ open size setting, reducing the obstruction risk and increasing operational availability.
Natural resources in Africa; a gift or curse: The case of Nigeria

This paper examines the link between natural resources wealth, agriculture, oil and economic growth in Nigeria. We use co-integration method to examine the relationship between the economic growth and economic indicators in control in this study. The result shows a significant relationship between economics growth and economic indicators in the long-run. However, the relationship between economics growth and economics indictors does not exist in the short-run. The policy makers in Nigeria should take this result into consideration when they implement a policy. They have to ensure that the policy closes the gap in order to have a positive effect on the economic growth in the short-run and long-run. Key words: Economic growth, co-integration, natural resources.
Assessing the Genetic Diversity and Population Structure of a Tunisian Melon (Cucumis melo L.) Collection Using Phenotypic Traits and SSR Molecular Markers

The assessment of genetic diversity and structure of a gene pool is a prerequisite for efficient organization, conservation, and utilization for crop improvement. This study evaluated the genetic diversity and population structure of 24 Tunisian melon accessions, by using 24 phenotypic traits and eight microsatellite (SSR) markers. A considerable phenotypic diversity among accessions was observed for many characters including those related to agronomical performance. All the microsatellites were polymorphic and detected 30 distinct alleles with a moderate (0.43) polymorphic information content. Shannon’s diversity index (0.82) showed a high degree of polymorphism between melon genotypes. The observed heterozygosity (0.10) was less than the expected heterozygosity (0.12), displaying a deficit in heterozygosity because of selection pressure. Molecular clustering and structure analyses based on SSRs separated melon accessions into five groups and showed an intermixed genetic structure between landraces and breeding lines belonging to the different botanical groups. Phenotypic clustering separated the accessions into two main clusters belonging to sweet and non-sweet melon; however, a more precise clustering among inodorus, cantalupensis, and reticulatus subgroups was obtained using combined phenotypic–molecular data. The discordance between phenotypic and molecular data was confirmed by a negative correlation (r = −0.16, p = 0.06) as revealed by the Mantel test. Despite these differences, both markers provided important information about the diversity of the melon germplasm, allowing the correct use of these accessions in future breeding programs. Together they provide a powerful tool for future agricultural and conservation tasks.
Hybrid evolutionary intelligent system and hybrid time series econometric model for stock price forecasting

In this paper, a hybrid evolutionary intelligent system is proposed for dimensionality reduction and tuning the learnable parameters of artificial neural network (ANN) that can forecast the future (1‐day‐ahead) close price of the stock market using various technical indicators. Although the ANN possesses the ability to model highly uncertain and complex nonlinear data but the key challenge in ANN is tuning its parameters and minimizing the feature set that can be used in the input layer. The backpropagation approach used for training the ANN has a limitation to get trapped in local minima and overfitting the data. Motivated by this, we proposed a hybrid intelligent system for optimizing the initial parameters and for reducing the dimensions of the feature set. The proposed model is a combination of feature extraction technique, namely principal component analysis (PCA), particle swarm optimization (PSO), and Levenberg‐Marquardt (LM) algorithm for training the feed‐forward neural networks (FFNN). This paper also compares the forecasting efficiency of the proposed model with PSO‐FFNN, regular FFNN, two standard benchmark approaches viz. GA and DE and another hybrid model obtained by the combination of PCA and a time series econometric model viz. auto‐regressive distributed lag model. The presented technique has been tested to predict the close price of three stock indices viz. Nifty 50, Sensex, and S&P 500. Simulation results indicate that the proposed model shows superior forecasting accuracy as compared with other methods.
Anxiety and Depression in Physical Therapists during the COVID-19 Pandemic: A Cross-sectional Survey in Gwangju, South Korea

PURPOSE: Physical therapists are at risk of becoming infected because they are in contact with or within 2 meters of the patient while treating them. The purpose of this study is to investigate the anxiety and depression of physical therapists during the coronavirus disease 2019 (COVID-19) pandemic and to identify the factors that affect anxiety and depression. METHODS: A cross-sectional survey was conducted during the pandemic. The survey were completed by 84 physical therapists in 24 local hospitals in Gwangju, South Korea. The Generalized Anxiety Disorder-7 (GAD-7) scale and the Patient Health Questionnaire-9 (PHQ-9) were used to evaluate their anxiety and depression status. Logistic regression models were used to identify the general characteristics factors related to anxiety or depression. RESULTS: It was found that 40 (47.6%) respondents had anxiety, and 37 (44%) had depression. If there was a child under the age of seven in the physical therapist’s family, a high probability of anxiety (p < .05) prevailed. Physical therapists in their 30s had a higher risk of depression than those in their 40s (p < .05). The risk of anxiety and depression in physical therapists who were with patients who did not wear masks was higher than for those who were with patients who wore masks (p < .05). CONCLUSION: The anxiety and depression status of physical therapists in Gwangju, South Korea, during the pandemic of COVID-19 was poor. It is necessary to wear a mask for all people during physical therapy.
First report of Lema bilineata Germar (Coleoptera: Chrysomelidae) damaging Physalis peruviana (L.) in Brazil

ABSTRACT: Increased production of the Cape gooseberry (Physalis peruviana L.) in Brazil has given rise to interest in identifying the phytophagous species that might damage this crop to inform preventive control and integrated pest management strategies. In this study, we report the occurrence and describe the damage that larvae and adults of Lema bilineata Germar (Coleoptera: Chrysomelidae) cause in P. peruviana. The number of L. bilineata individuals, both larvae and adults, significantly affected the total consumption of P. peruviana leaves. We also report, for the first time, three natural enemies, including a fungus, a fly, and an ant, which are associated with this pest in Brazil and may play a role in biological control strategies.
Long-term Changes in Creatinine Clearance and Renal Parenchymal Volume with Dosimetric Parameters in Gastric Cancer Patients with Treated Chemoradiotherapy

RESULTS The median Ccr significantly decreased from 82.8 mL/min to 78.4 mL/min at 24 months and to 75.3 mL/ min at 48 months after radiotherapy (RT) (p=0.034). Both RPR were significantly decreased 4 years after RT (p=0.001). Ccr reductions were >10 mL/min in 16 (47%) patients. The total kidney dose, bilateral kidney V20, bilateral kidney V25, and right kidney V20 doses were significantly higher in patients with decreased Ccr more than 10 mL/min at 48 months after RT than those who did not decrease (p=0.003, p=0.037, p=0.029, and p=0.013, respectively).
Neurological disorders associated with impaired gut microbiota

A growing field of studies is focusing on the microbiota-gut-brain axis in order to better understand the bidirectional communication pathways between gut bacteria and the CNS. The pathophysiology of neurological disorders including Alzheimer's disease and autism has been attributed to dysregulation of gut-brain axis. Fecal microbiota transplantation is the method of transferring faeces from a healthy donor into the intestine of a recipient in order to restore the recipient's weakened intestinal flora. It's been used to treat a wide range of conditions, including recurrent Clostridium difficile infection and inflammatory bowel disease. Gut-brain psychology will aid studies on subjects such as character, memory and behaviour and will contribute to the advancement of general psychology as well as will add more light in the field of neuropsychology. Lactobacillus and Bifidobacterium, for example, are essential components of the gut microbiota. Oligosaccharides, unsaturated fatty acids, dietary fibers and polyphenols are the most popular prebiotics. Traditional fermented foods including yoghurt, natto and pickles help to balance the gut bacteria. The gut microbiota is shaped by a person's diet and gut-brain function is controlled by it. Different types of microbiota have different effects on the brain and actions through the microbiota–gut–brain axis. Via the microbiota-gut-brain axis, a healthy diet leads to a healthy gut microbiota and brain and mental health. Dysbiosis of the gut microbiota has been shown to trigger depression-like behaviours in GF mice. Proinflammatory mediators such as iNOS, ROS, COX2 and NF-B are released by microglia, resulting in neuroinflammation in Alzheimer's disease. It is becoming more widely recognized as a symptom of Autism Spectrum Disorder. The establishment of gut-brain psychology is expected to have a significant impact on psychology and related disciplines.
DEVELOPING DILEMMA DISCUSSION METHOD IN AKHLAQ LEARNING TO PROMOTE STUDENT’S MORAL REASONING

Abstract:Enhancing moral reasoning is the main goal of education in the perspective of cognitive-developmental theory. Strategies, approaches or learning methods are chosen based on the effectiveness in changing the level of moral reasoning of students from level of pre-conventional, to conventional and post-conventional. Dilemma Discussion Method has proven its effectiveness in increasing moral reasoning. Therefore, in order to be used in Akhlak learning (part of Pendidikan Agama Islam material) of the classroom, it is important to develop the steps of implementation (syntax) by using the principle of cognitive developmental theory. The results of this Research and Development (R & D) Design indicate that the product in the form of learning syntax from Dilemma Discussion Method is declared as valid with a mean score of 4.38 (greater than the criteria). Thus the product of development research in the form of a dilemma discussion method in learning Akhlaq is worth for being implemented.Abstrak:Peningkatan penalaran moral peserta didik merupakan tujuan utama pendidikan dalam perspektif teori cognitive-developmental. Strategi, pendekatan ataupun metode pembelajaran seharusnya dipilih berdasarkan keefektifannya dalam mengubah level penalaran moral peserta didik dari pre-conventional, menuju level conventional dan post-conventional. Metode diskusi dilema telah dibuktikan keefektifannya dalam meningkatkan penalaran moral. Oleh sebab itu, agar dapat digunakan dalam pembelajaran akhlak/moral (bagian dari mata pelajaran Pendidikan Agama Islam) di kelas, perlu diupayakan pengembangannya berupa langkah-langkah pelaksanaannya (sintak) metode tersebut dengan menggunakan prinsip-prinsip belajar cognitive developmental theory. Hasil penelitian pengembangan (Research & Development) ini menunjukkan bahwa produk berupa sintak pembelajaran dari metode diskusi dilemma dinyatakan valid karena telah memenuhi persyaratan validitas produk yakni mendapatkan skor rerata 4,38. Dengan demikian produk penelitian pengembangan berupa metode diskusi dilema dalam pembelajaran akhlaq layak untuk diimplementasikan.
A high‐gain circular polarization beam scanning transmit array antenna

Wu Ren, School of Information and Electronics, Beijing Institute of Technology, No. 5, South Zhongguancun Street, Haidian District, Beijing 100081, China. Email: renwu@bit.edu. cn Abstract A high‐gain circular polarization (CP) beam scanning antenna based on planar transmit array (TA) is proposed. The planar TA is implemented using rectangular patches and square rings, and it has different frequency responses to two orthogonal polarized incident waves owing to different phase distributions in x‐ and y‐direction. The TA can convert a linearly polarized spherical incident wave into a circularly polarized transmitted plane wave. In addition, beam scanning is achieved by in‐plane translation of the feed antenna. The procedure is demonstrated for high‐gain beam steering implementation operating in CP at the Ku‐band. Full‐wave simulation results demonstrate that the designed antenna enables elevation beam scanning from −33.6° to +33.6°, with a peak gain of 26.4 dBi. Scanning loss is better than 5 dB and the axis ratio remains below 3 dB for the entire scanning range in the frequency band of 13.9–14.9 GHz. Moreover, a prototype is fabricated and the measured results have good agreement with the simulated results, which confirms the feasibility of using this technology to achieve a high‐gain, CP, low‐cost and low cross‐polarization beam scanning antenna.
An adaptive real‐time energy management system for a renewable energy‐based microgrid

This paper proposes an adaptive real-time energy scheduling method (RT-EMS) for a microgrid, using a Lyapunov optimization -based real-time approach. Inaccuracy in day-ahead predictions can result in non-optimal solutions to the energy scheduling problem. Although the real-time optimization method eliminates the need to deal with the prediction uncertainties, it ignores the valuable statistical information used in day-ahead stochastic approaches and provides suboptimal solutions to the problem. The proposed adaptive approach combines the advantages of both the stochastic day-ahead and the RT-EMS and reduces the real-time operational cost of the microgrid. The proposed method moves the RT-EMS solution towards the optimal solution, by adding a penalty term to the objective function. Numerical results are provided to demonstrate the improved performance of the proposed adaptive method.
Detecting Malicious Domain Names with Abnormal WHOIS Records Using Feature-Based Rules

Millions of new domain names are registered every day, but a large proportion of them are malicious and usually discovered and blacklisted after the crime has been committed. In order to improve the security of domain name registration, this paper proposes a lightweight detection method based on the AdaBoost to identify malicious domain names, which focuses on proactively detecting malicious domain names by exploring the abnormal WHOIS records. The domain name registries and registrars can adopt the proposed method as the first layer of defense to identify malicious domains on the domain registration stage. Extensive experiments on a large-scale database demonstrate that the proposed approach achieves satisfactory results on various malicious domain names.