Miracle-dz/UniFAR-FTUs huggingface dataset:
The effect of renewable energy consumption on economic growth in KSA: A bootstrap causality test

The majority of studies analyzed show a positive and statistically significant impact of renewable energy consumption on economic growth. Nevertheless, some studies suggest a limited effect, while others find no statistically significant effect. Faced with this problem, we conducted a study aimed at analyzing the impact of renewable energy consumption on economic growth in the Kingdom of Saudi Arabia for the period 1990–2020. To determine the integration properties of the variables, we utilized the sharp and smooth structural breaks unit root test developed by Shahbaz, Omay and Roubaud (SOR). We also used the bootstrap approach of testing ARDL limits to examine the cointegration between variables. Using the VECM model, we studied the causal relationship between economic growth and its determinants. The results show, in the short and long run, the existence of a bidirectional causality between renewable energy consumption and economic growth (Feedback Hypothesis). Thus, there is a bidirectional relationship between GDP and capital and also between GDP and labor, in the long run. Therefore, an important policy implication resulting from this analysis is that renewable energy can be considered as an important factor for sustainable economic development in Saudi Arabia. The findings for Saudi Arabia may also be relevant for oil exporting countries to achieve efficiency and promote the renewable energy sector beyond oil.
Development of a four stage continuous improvement framework to support business performance in manufacturing SMEs

ii Acknowledgements . iii List of Figures . x List of Tables. xii List of Appendices . xiii Publication List . xiv Abbreviations . xv Chapter 1: Introduction to the Research Project . 1 1.
The main pillars of Agile consolidation in newly Agile teams in Agile software development

Many software companies and teams use Agile methods as their main development approach. These methods promise higher team productivity, faster product delivery, a more flexible development process, and greater customer satisfaction. Nevertheless, a review of the literature shows that adapting to these methods, known as Agile transition, is not as easy as expected. However, several frameworks and models have been proposed to facilitate the Agile transition process. The challenging issue after the transition to agility is the behavior of companies and teams after the Agile transition and how to maintain agility in the long run. Very little research has been done on this issue, which has largely expressed concern. The present study tries to explore the hidden aspects of the transition to agility and provide a solution for Agile consolidation in newly Agile software teams. In this regard, using the grounded theory approach, the basic theory of Agile consolidation in these teams has been presented. Preliminary findings of the study indicate important factors that play an important role in Agile consolidation. Identification of challenges, facilitators, organizational culture structure, and human roles in Agile consolidation is the most important initial findings of this study.
GENDER NEUTRAL LANGUAGE USE AMONG UNIVERSITY LECTURERS: GENDER DIFFERENCES IN INSTITUTIONS WITH AND WITHOUT GENDER MAINSTREAMING POLICIES

Despite the wide spread awareness regarding the need to reduce gender bias in communication styles, it still exists in organizations and its negative effects on women’s behaviour and perceptions in the workplace remain a great concern. Consequently, the importance of gender neutral language (GNL) use in reducing gender stereotypes and discrimination cannot be overemphasized. Gender differences between gender and non-gender policy organizations has not been given much attention among university lecturers in the investigation of GNL use in Nigeria. This study examines the main and interaction effects of gender and institution type on GNL among public and private university lecturers. Using a two-way factorial design, 161 lecturers were randomly selected from four faculties and twelve departments while convenient sampling method was used to select the target respondents. A questionnaire focusing on socio-demographic profile and a GNL test was administered to the participants. Data were analyzed using descriptive statistics, t-test analysis and analysis of variance at 0.05 level of significance. Three hypotheses were tested. The results revealed that gender differences and institution type interacted to influence GNL use among the participants of the study. Gender and institution type are important in developing interventions for GNL use in academia. Article visualizations:
Strategic, operations, and evaluation planning for higher education distance education

Abstract Distance learning technology continues to grow and undergo significant changes in higher education settings. Applying strategic planning methods from organizational behavior and operations management can act as a useful guide for the implementation of a sustainable distance learning program. Strong planning can help ensure the distance learning program system’s operational readiness, effectiveness, and sustainability. Distance learning operations planning requires a defined strategy that examines organizational human and technical structures We discuss a distance education planning approach applied to three higher education cases with a goal of improving their distance education efforts. The research contexts were in the United States of America: a small Midwestern university seeking to grow online programs in support of its competitive strategy, a large western university with established distance programs, and a regional community college. This article will illustrate the use of business-oriented, systems thinking models for evaluation and distance education program improvement.
Assessment for Computer Programming Courses: A Short Guide for the Undecided Teacher

: As the large number of articles on teaching introductory programming seem to attest, teaching and learning computer programming is difﬁcult. However, perhaps surprisingly, the assessment design for those courses does not seem to be the most studied aspect. This short position paper provides a structured set of options and alternatives to consider when choosing the assessment elements for a programming course. The objective is to promote additional reﬂection on several alternatives for each assignment, exam, or other assessment elements. Along with this presentation, we point to eventually valuable references. We believe the resulting information should be helpful and applicable to many other disciplines, but the focus is on computer programming courses.
Real-Time Cloud-Based Patient-Centric Monitoring Using Computational Health Systems

In many sectors, including healthcare services, Internet of Things (IoT) systems are growing rapidly, providing promising technological, economical, and social potential. Healthcare services can be improved with IoT capabilities, including remote patient monitoring, diagnosis of medical issues in real-time, and more, all of which improves both the quality and the satisfaction of human users. The Internet of Medical Things (IoMT) is gaining momentum as wearable devices, and their numerous health monitoring applications increase popularity. The IoMT plays a significant role in reducing death rates by detecting diseases early. Prediction of heart disease is an essential challenge in clinical dataset analysis. The proposed research aim is to employ machine learning (ML) classification algorithms to predict heart disease. The IoMT-based cloud-fog diagnostics for heart disease have been proposed. Fog layer is used to quickly analyze patient data using ML classification techniques. The performance of the healthcare model is evaluated with different simulations and achieves 97.32% accuracy, 97.58% recall, 97.16% precision, 97.37% <inline-formula> <tex-math notation="LaTeX">$F1$ </tex-math></inline-formula>-measure, 96.87% specificity, and 97.22% <inline-formula> <tex-math notation="LaTeX">$G$ </tex-math></inline-formula>-mean, which has significant improvement as compared with previous models.
Copepods of the off-shore waters of Caribbean Colombian Sea and their response to oceanographic regulators

Abstract Seven oceanographic expeditions were conducted between the years 2013 and 2018 to determine the horizontal and vertical distribution schemes in the epipelagic and mesopelagic copepod community structure of the Caribbean Oceanic ecoregion (CAO) and the oceanographic variables that regulate it. Four indicator species are suggested for the North Equatorial Current and the Caribbean Surface Water (CSW) mass (Clausocalanus furcatus, Oncaea venusta, Temora stylifera and T. turbinate) and two indicator species for deep-water masses such as the Western North Atlantic Central Water (NACW) and the Antarctic Intermediate Water (AAIW) (Mormonilla phasma and Conaea rapax). The copepod assemblage responds to local oceanographic patterns that are regulated (24%) by the variability of dissolved oxygen and temperature in the water column. The horizontal structure of the copepod assemblage in offshore waters presented a spatial sectorization. Three zones were differentiated: (1) oceanic Colombian zone; (2) influence of the Magdalena River zone; and (3) offshore north-east zone. Water mass mixing processes and migration mechanisms favour the homogeneity of the vertical assemblage of copepods in the CAO ecoregion. This study provides relevant information on the structure and density of copepod species, providing key information to describe the ecological processes and the different responses to the oceanographic factors that modulate them.
Turkish Customers’ Perceptions of Dining Experience in Asian Restaurants in Istanbul

This paper analyzes the perceptions of Turkish customers regarding their experiences at Asian restaurants in Istanbul. Within the scope of the study, 1,348 online reviews written in Turkish on TripAdvisor for Asian restaurants operating in Istanbul were analyzed with the latent Dirichlet allocation (LDA) algorithm and sentiment analysis. As a result of the analysis nine dimensions affecting the experiences of Turkish customers at Asian restaurants were determined, four of which were specific to the restaurant (view, staff, place, order) and five of which were related to food (real taste, food, sauce and spice, sushi, flavor). It was found that flavor and food are the main dimensions that positively affect Turkish customers’ Asian restaurant experiences. Order was found to be the most important dimension that negatively affects them. To my knowledge, this is the first study interpreting the perception of Turkish customers’ experiences of Asian restaurants through online reviews in Turkish.
Research of coal and gangue identification and positioning method at mobile device

ABSTRACT A method of identifying and positioning coal and gangue on mobile devices is provided to address the difficulties of high complexity and difficult deployment of existing machine vision algorithms. Combining CSPDarknet53 and the GhostNet embedded with efficient channel domain attention to build a lightweight feature extraction network and using the Meta-ACON activation function to adapt the network’s nonlinearity at each layer. The detection head’s expression capability is enhanced using a decoupled head. The actual position coordinate relationship equation of coal and gangue is deduced by borrowing the center point object box positioning principle. Build an experimental setup, collect and construct coal and gangue datasets, and use Mixup data augmentation to improve the network’s ability to position coal and gangue for stacking cases. The models are trained, and tested for different lighting conditions, sizes, and stacking cases, then deployed on the mobile device. The results show that the model has the highest detection accuracy and can correctly identify and position both coal and gangue under complex conditions with a high confidence value. The FLOPs is 76.83% lower compared to the original network YOLOv5s. The mAP reaches 0.996 and the FPS is 40.11. The inference time on the mobile device is reduced to 228 ms, which basically meets the speed requirement of coal gangue identification and positioning.
Serological Biomarkers and Their Detection in Autoimmune Bullous Skin Diseases

Autoimmune bullous diseases (AIBDs) are a group of skin-related disorders that involve damage to structures maintaining cell-cell adhesion, such as desmosomes and hemidesmosomes. Key AIBDs include pemphigus related diseases, pemphigoid related conditions, acquired epidermolysis bullosa (EBA), and dermatitis herpetiformis (DH). Each group of conditions exhibits characteristic clinical lesion patterns and is associated with specific autoantibodies targeting epidermal and dermal structures involved in cell-cell adhesion and skin integrity. Pemphigus diseases primarily target desmoglein (Dsg) 3 and Dsg1 proteins but several non-Dsg autoantibodies have also been linked to pemphigus. Pemphigoid diseases typically target bullous pemphigoid (BP)180 and BP230; EBA is associated with antibodies directed against anti-type VII collagen and DH by IgA autoantibodies against tissue transglutaminase and deaminated gliadin. Investigation into the serological biomarkers found in AIBDs have allowed the development of diagnostic assessments (i.e. tissue antibody detection and serological testing) based on the unique autoantibody profiles of a particular disease group. The methods for the detection and quantification of disease-associated autoantibodies continue to evolve and improve.
European Journal of Physical Education and Sport Science-2501-1235

Pick and roll actions have become one of the most frequently used offensive cooperations in youth basketball games. The purpose of this study was to evaluate the variables of performance time of the pick and roll every five minutes, the pair of players who participated in the pick and roll and the offensive action of the ball handler after the screen, in the 2017 European U’20 Championship and how these affect its effectiveness. The sample of the study was the sixteen games of the second round of the Championship, taking place in Heraklion, Greece. The instrument used for the analysis of the matches was the SportScout STA Version 3.2. Analysis with ꭓ 2 (Chi-square) was used. A total of 658 pick and roll screens were found, of which 264 were successful (40.1%) and 394 (59.9%) failed. Furthermore, most pick and roll actions were performed in the first fiveminute span of the first quarter of the games (n=103, 15.7%). The guard as the ball handler and the forward as the screener was the pair of players who participated in the majority of pick and rolls (n=296, 45%). Regarding the actions that took place after the screen, about 60% of the pick and rolls the ball handler chose to finish the action himself in 63.1% of the pick and rolls recorded either by driving to the basket (n=225, 34.2%) or with a shot (n=190, 28.9%). Most successful pick and rolls resulted in a successful two-point shot field goal (n=144, 54.5%) and most failed pick and rolls resulted in a failed two-point field goal attempt (n=200, 50.8%). The results of this research can provide information to coaches and players so they can organize better their training and maximize the performance of their team’s offense.
Refining Glioblastoma Surgery through the Use of Intra-Operative Fluorescence Imaging Agents

Glioblastoma (GBM) is the most aggressive adult brain tumour with a dismal 2-year survival rate of 26–33%. Maximal safe resection plays a crucial role in improving patient progression-free survival (PFS). Neurosurgeons have the significant challenge of delineating normal tissue from brain tumour to achieve the optimal extent of resection (EOR), with 5-Aminolevulinic Acid (5-ALA) the only clinically approved intra-operative fluorophore for GBM. This review aims to highlight the requirement for improved intra-operative imaging techniques, focusing on fluorescence-guided imaging (FGS) and the use of novel dyes with the potential to overcome the limitations of current FGS. The review was performed based on articles found in PubMed an.d Google Scholar, as well as articles identified in searched bibliographies between 2001 and 2022. Key words for searches included ‘Glioblastoma’ + ‘Fluorophore’+ ‘Novel’ + ‘Fluorescence Guided Surgery’. Current literature has favoured the approach of using targeted fluorophores to achieve specific accumulation in the tumour microenvironment, with biological conjugates leading the way. These conjugates target specific parts overexpressed in the tumour. The positive results in breast, ovarian and colorectal tissue are promising and may, therefore, be applied to intracranial neoplasms. Therefore, this design has the potential to produce favourable results in GBM by reducing the residual tumour, which translates to decreased tumour recurrence, morbidity and ultimately, mortality in GBM patients. Several preclinical studies have shown positive results with targeted dyes in distinguishing GBM cells from normal brain parenchyma, and targeted dyes in the Near-Infrared (NIR) emission range offer promising results, which may be valuable future alternatives.
PlausMal-GAN: Plausible Malware Training Based on Generative Adversarial Networks for Analogous Zero-Day Malware Detection

Zero-day malicious software (malware) refers to a previously unknown or newly discovered software vulnerability. The fundamental objective of this paper is to enhance detection for analogous zero-day malware by efficient learning to plausible generated data. To detect zero-day malware, we proposed a malware training framework based on the generated analogous malware data using generative adversarial networks (PlausMal-GAN). Thus, the PlausMal-GAN can suitably produce analogous zero-day malware images with high quality and high diversity from the existing malware data. The discriminator, as a detector, learns various malware features using both real and generated malware images. In terms of performance, the proposed framework showed higher and more stable performances for the analogous zero-day malware images, which can be assumed to be analogous zero-day malware data. We obtained reliable accuracy performances in the proposed PlausMal-GAN framework with representative GAN models (i.e., deep convolutional GAN, least-squares GAN, Wasserstein GAN with gradient penalty, and evolutionary GAN). These results indicate that the use of the proposed framework is beneficial for the detection and prediction of numerous and analogous zero-day malware data from noted malware when developing and updating malware detection systems.
Specific features of the training seminar in order to improve the subjective well-being of students

The purpose of this research is to evaluate the specific features of the training seminar in order to improve the subjective well-being of university students. The qualitative research method was used in this study. The study group of the research consisted of 72 university students studying at various universities in Almaty, Kazakhstan in the 2021–2022 academic year. Research data were collected with a semi-structured interview form prepared by the researchers. As a result of the research, students defined subjective well-being as looking at life positively, living life in a planned way, socialising and being a good person. University students evaluated their subjective well-being at a moderate level with suggestions of university students participating in the research to improve subjective well-being, giving importance to personal development, establishing positive relations with the environment and benefiting from activities in universities. In addition, students’ opinions on the characteristics of the training seminars for the development of subjective well-being are that they are motivating, provide multidimensional development, have rich content and are held regularly. In line with the findings obtained from the research, it has emerged that the training seminars organised for the improvement of the subjective well-being of university students should be organised frequently, provide multidimensional development and be rich in content. Keywords: Subjective well-being, educational seminars, university students
Mass exchange networks for waste minimization : a simultaneous approach : Process design

The synthesis problem of mass-exchange networks is addressed, where a number of process streams, rich in terms of certain components (typically pollutants) are integrated with lean process or utility streams in order to meet process specifications (e.g. environmental regulations) on their final compositions. A mathematical programming approach is adopted, based on a hyperstructure representation of the mass exchange network. The synthesis problem is then formulated as a mixed integer nonlinear programming optimization problem (MINLP), where both network operating and investment cost are optimized simultaneously. In contrast to all previously published work that simplifies the problem by assuming decomposition based on the concept of pinch, we treat the synthesis of mass exchange networks without decomposition. In the first part, the case of a single component is examined, whereas mass exchange in multiple components can be handled in a straightforward manner. In the second part the approach is applied to reactive mass exchange networks, where chemical sorption takes place. In the third part, the mass exchange hyperstructure is extended to include regeneration of the lean streams. A number of examples illustrate the applicability of the proposed approach to several problems of waste minimization and demonstrate the impact of simultaneously minimizing operating and investment cost
Dietary Fatty Acid Regulation of the NLRP3 Inflammasome via the TLR4/NF-κB Signaling Pathway Affects Chondrocyte Pyroptosis

Dietary fatty acid (FA) content and type have different effects on obesity-associated osteoarthritis (OA), but the mechanisms underlying these differences are not fully understood. Inflammation activated by toll-like receptor 4 (TLR4)/nuclear factor- (NF-) κB signaling and pyroptosis induced by the NLRP3/caspase-1/gasdermin D (GSDMD) signaling pathway play important roles in OA development. Our aim in this study was to observe the effects of dietary FAs on the articular cartilage of obese post-traumatic OA model mice and on chondrocytes stimulated by lipopolysaccharide (LPS) and to determine whether the underlying mechanisms involve TLR4/NF-κB and NLRP3/caspase-1/GSDMD signaling pathways. Mice were fed high-fat diets rich in various FAs and underwent surgical destabilization of the medial meniscus to establish the obesity-related post-traumatic OA model. LPS-induced SW1353 chondrosarcoma cells were used to mimic OA status in vitro, and TLR4 inhibitors or TLR4 overexpressing lentivirus was administered. Analysis using weight-matched mice and multiple regression models revealed that OA was associated with dietary FA content and serum inflammatory factor levels, but not body weight. Diets rich in n-3 polyunsaturated fatty acids (PUFAs) attenuated OA and inhibited the TLR4/NF-κB and NLRP3/caspase-1/GSDMD signaling pathways, whereas diets rich in saturated fatty acids (SFAs), monounsaturated fatty acids (MUFAs), or n-6 PUFAs increased OA severity and activated these pathways. In vitro results for SFAs, n-6 PUFAs, and n-3 PUFAs were consistent with the animal experiments. However, those for MUFAs were not. FA effects on the NLRP3/caspase-1/GSDMD pathway were associated with the inhibition or activation of the TLR4 signaling pathway. In conclusion, diets rich in SFAs or n-6 PUFAs can exacerbate obesity-associated OA, whereas those rich in n-3 PUFAs have protective effects against this disease, due to their respective pro-/anti-inflammatory and pyroptotic effects. Further research on dietary FA supplements as a potential therapeutic approach for OA is needed.