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The linguistic dynamics within a workplace play a pivotal role in shaping the organizational milieu, thereby significantly influencing the overall success or failure of the organization. Consequently, this investigation was crafted to scrutinize the impact of various linguistic elements, such as directive communication, empathetic discourse, proficiency in English language, and communication efficacy, on employee allegiance, mediated through the lens of trust. Employing a cross-sectional research design, data were gathered from employees within the banking sector of the Kingdom of Saudi Arabia (KSA). Utilizing questionnaires aligned with prior scholarly literature, the study employed simple random sampling techniques to solicit responses, amassing 231 usable questionnaires. The data analysis was conducted using Smart PLS 4 software. The results revealed that directive communication, empathetic discourse, English language proficiency, and communication effectiveness positively influence employee trust. Furthermore, the statistical analyses substantiated the significant impact of trust on employee loyalty. Notably, this study also confirmed the mediating role of employee trust. The implications and avenues for future research are expounded upon in detail within this investigation.

The purpose of this study is to investigate the relationship between Arabic Language Proficiency (ALP) and expatriate adjustment (EA), and job performance (JP) in Saudi Arabia. In addition, the moderating role of personal and environmental factors is investigated. This investigation employs a mixed-methods research design. The intended audience is the personnel of Saudi Arabia's Higher Educational Institutions (HEIs). A survey was conducted for quantitative data, while interviews were used for qualitative data. CFA and SEM were used for quantitative data analysis, while thematic analysis was used for qualitative data analysis. The results of this study indicate that Arabic language proficiency significantly affects job performance and expatriate adaptation. It was also discovered that several personal and environmental factors contribute to the impact, including language barriers, the workplace environment, training, and support. This study is novel because it examines the effects of ALP on EA and JP in Saudi Arabia, in addition to personal and environmental factors; no prior study of this nature has been conducted in Saudi Arabia. The study is limited to Higher Education Institutions (HEIs); thus, its generalizability is restricted. The study is significant for Saudi Arabia's Higher Education Institutions (HEIs) because it emphasizes the significance of training and support, which would aid in adapting foreign employees, and enhancing their job performance.

The primary aim of this research study was to examine the impact of informal digital English learning, facilitated by various online sources such as educational content, entertainment content, and socialisation content, on students' motivation to acquire English as a second language and their general attitude towards the process of learning English as a second language. In order to fulfil the intended goal, data was gathered from a sample of 316 students who were enrolled in an English course during their initial year of graduate studies or who had chosen to specialise in the English language during their graduate studies. The data that was gathered was subjected to analysis using the statistical software SPSS, specifically through the application of regression analysis. The findings of the study indicated a correlation between the availability of educational content on the internet and students' inclination to make efforts to learn English. Similarly, the presence of entertainment and socialisation content was linked to students' personal desire and motivation to learn English. Furthermore, all three aspects of informal digital learning, namely educational, entertainment, and socialisation content, were associated with social approval and a positive attitude towards the acquisition of the English language. This study makes significant contributions to the existing body of knowledge as it explores the relatively new concept of informal digital learning of English. Consequently, further research is necessary in this area. The present study also examined various forms of motivation, including intrinsic motivation and the desire for social validation, in relation to the acquisition of English as a second language. This particular aspect has not been previously investigated in prior research. In addition to this, the existing literature lacks sufficient studies on the attitude towards learning English as a foreign language, specifically in the realm of informal digital English learning. Consequently, this study serves as a noteworthy contribution to the academic discourse.

The increasing trend of studying abroad, driven by globalization, has led students to seek educational and professional opportunities in foreign countries. However, they face numerous challenges that affect their academic and social integration. This study aims to examine the factors influencing communication among Arab students studying in Malaysia. It adopts a positivist approach and a quantitative methodology, using a questionnaire to collect data from students in Malaysian universities in the Klang Valley, including Kuala Lumpur, Selangor, and Putrajaya. Convenience sampling was employed to distribute 450 questionnaires to students, resulting in 300 valid responses. SPSS and PLS-SEM were utilized for the data analysis. The study revealed that perceived discrimination at a university negatively impacts study-abroad experience, while homesickness has no significant influence. Teacher support, on the other hand, significantly influenced study-abroad experience. The research also explored the mediating role of study-abroad experience, finding significant mediation in all relationships except for the link between homesickness and willingness to communicate.

This scholarly investigation delves into the correlation among fundamental motifs in cross-cultural research. The inquiry specifically examines the impact of language impediments on the psychological well-being, social assimilation, and cultural adjustment of expatriates. Furthermore, the study endeavours to elucidate the nexus between language, culture, and social interactions within expatriate communities globally. These objectives are predicated on the premise that language functions bidirectionally, fostering convergence among individuals from diverse cultures while concurrently posing challenges to their assimilation into a shared cultural milieu. This research employs a qualitative methodology, utilizing in-depth, semi-structured interviews with expatriates residing within the cultural milieu of the Kingdom of Saudi Arabia. Thematic analysis serves as the analytical approach, facilitating a comprehensive exploration of various facets pertaining to linguistic challenges. This encompasses an examination of their impact on expatriates' social networks, engagement in community activities, and mental well-being. This investigation elucidates significant correlations between linguistic proficiency and social integration, demonstrating that adept language skills correlate with resilient social networks and active engagement within communities. Conversely, restricted language capabilities frequently give rise to sentiments of exclusion and impede social interactions within expatriate communities. Furthermore, the study accentuates the psychological strains emanating from linguistic challenges, emphasizing their repercussions on the mental well-being and self-efficacy of expatriates. This research addresses crucial gaps in the existing literature on language challenges encountered by expatriates globally. Through the utilization of real-life examples drawn from diverse social and cultural contexts, the study elucidates the multifaceted impact of language on expatriate experiences.

Abstract Influenza is a highly contagious acute viral illness that affects the respiratory system, posing a significant global public health concern. Influenza B virus (IBV) causes annual seasonal epidemics. The exploration of molecular biology and reverse genetics of IBV is pivotal for understanding its replication, pathogenesis, and evolution. Reverse genetics empowers us to purposefully alter the viral genome, engineer precise genetic modifications, and unveil the secrets of virulence and resistance mechanisms. It helps us in quickly analyzing new virus strains by viral genome manipulation and the development of innovative influenza vaccines. Reverse genetics has been employed to create mutant or reassortant influenza viruses for evaluating their virulence, pathogenicity, host range, and transmissibility. Without this technique, these tasks would be difficult or impossible, making it crucial for preparing for epidemics and protecting public health. Here, we bring together the latest information on how we can manipulate the genes of the influenza B virus using reverse genetics methods, most importantly helper virus-independent techniques.

Abstract Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver condition globally and the leading cause of liver-related death and morbidity. The goal of this study was to collect current data in order to calculate the pooled prevalence of NAFLD in Pakistan. We conducted a comprehensive literature search on four electronic databases until March 2024 to find studies on the prevalence of NAFLD in Pakistan. Pooled prevalence estimates of NAFLD were obtained using random-effects meta-analytic models. The chi-square test was used to account for study heterogeneity, whereas the I2 statistic was used to assess inconsistency. The data were stratified by the general population (average risk) and individuals with metabolic diseases (high risk). Two reviewers thoroughly and independently screened, reviewed, and assessed all studies. In total, 468 studies were reviewed, and 34 were included. The pooled NAFLD prevalence in the general population was 29.82% (95% CI 21.39–39.01%; prediction interval: 2.98–68.92%) based on 13 studies. In individuals with metabolic disorders, the prevalence of NAFLD in patients with diabetes, hypertension, and obesity, was 58.47% (95% CI 54.23–62.64%; prediction interval: 38.16–77.40%), 74.08% (95% CI 60.50–85.70%), and 47.43% (95% CI 30.49–64.66%), respectively. There was no evidence of publication bias, although a statistically significant level of heterogeneity was seen among the studies (I 2 ranged from 57.5 to 98.69%). The findings of this study indicate a substantial prevalence of NAFLD in the population of Pakistan. The Pakistani government must formulate a comprehensive approach and plan aimed at augmenting awareness, control, prevention, and treatment of fatty liver disease. Prospero Registration no: CRD42022356607.

This paper proposes an intelligent sensing framework for Internet-of-Things platforms, where sensor measurements stem from multiple causes. Sensors are selectively chosen for data collection to identify the cause with partial measurements. We employ variational deep embedding, a generative model capable of clustering and generation, to identify causes, cluster measurements accordingly, and determine causes for estimating complete measurements from partial data. These estimates aid in efficient sensor selection for data collection. Results demonstrate early and reliable cause sensing and complete measurement estimation using the proposed framework.

Abstract VANET is a category of MANET that aims to provide wireless communication. It increases the safety of roads and passengers. Millions of people lose their precious lives in accidents yearly, millions are injured, and others incur disability daily. Emergency vehicles need clear roads to reach their destination faster to save lives. Video streaming can be more effective as compared to textual messages and warnings. To address this issue, we proposed a methodology to use visual sensors, cameras, and OBU to record emergency videos. Initially, the frames are detected. After re-recording, the frames detection algorithm detects the specific event from the video frames. Blockchain encrypts an emergency or specific event using hashing algorithms in the second layer of our proposed framework. In the third layer of the proposed methodology, encrypted video is broadcast with the help of 5G wireless technology to the connected nodes in the VANET. The dataset used in this research comprises up to 72 video sequences averaging about 120 seconds per video. All videos have different traffic conditions and vehicles. The ResNet-50 model is used for the feature extraction process of extracted frames. The model is trained using Tensorflow and Keras deep learning models. The Elbow method finds the optimal K number for the K Means model. This data is split into training and testing. 70% is reserved for training the support vector machine (SVM) model and test datasets, while 30%. 98% accuracy is achieved with 98% precision and 99% recall as results for the proposed methodology.

To study the influence of an elbow inlet on the rotating stall characteristics of a waterjet propulsion pump (WJPP), a three-dimensional internal flow field in a WJPP under a straight-pipe inlet and elbow inlet is numerically simulated. By comparing the hydraulic performance of WJPP under the two inlet conditions, the internal relationship between the inlet mode and the flow pattern in the pump is clarified. Based on unsteady pressure fluctuation characteristics and wavelet analysis, the influence of the inlet mode on the rotating stall is revealed, and the stall transient propagation characteristics under critical stall conditions are analyzed. The disturbance effects of the inlet channel geometry disappear under low flow rate conditions, the main disturbance is induced by the high-speed countercurrent, and the flow pattern under the elbow inlet is better than that under the straight-pipe inlet. Under the straight-pipe inlet, the single-stall nucleus in the WJPP temporarily experiences a low-frequency and high-amplitude disturbance, which subsequently transforms into a mode of multi-stall nuclei with high-frequency circumferential disturbance. Under the elbow inlet, the rotating stall always maintains a mode of high-amplitude and low-frequency disturbance, which represents the transient characteristics of a single stall core propagating in the circumferential direction inside the channel. The results of this study have a reference value for structural design optimization in a WJPP.

Abstract Machine learning has emerged as a leading field in artificial intelligence, demonstrating expert-level performance in various domains. Astronomy has benefited from machine learning techniques, particularly in classifying and identifying stars based on their features. This study focuses on the spectra-based classification of 11,408 B-type and 2422 hot subdwarf stars. The study employs baseline correction using Asymmetric Least Squares (ALS) to enhance classification accuracy. It applies the Pan-Core concept to identify 500 unique patterns or ranges for both types of stars. These patterns are the foundation for creating Support Vector Machine (SVM) models, including the linear (L-SVM), polynomial (P-SVM), and radial basis (R-SVM) kernels. Parameter tuning for the SVM models is achieved through cross-validation. Evaluation of the SVM models on test data reveals that the linear kernel SVM achieves the highest accuracy (87.0%), surpassing the polynomial kernel SVM (84.1%) and radial kernel SVM (80.1%). The average calibrated accuracy falls within the range of 90–95%. These results demonstrate the potential of using spectrum-based classification to aid astronomers in improving and expanding their understanding of stars, with a specific focus on the identification of hot subdwarf stars. This study presents a valuable investigation for astronomers, as it enables the classification of stars based on their spectra, leveraging machine learning techniques to enhance their knowledge and insights in astronomy.

Abstract The transition from the Uniform Building Code (UBC-97) to the International Building Code (IBC-21) marked a major shift in the definition of seismic hazard. The term “seismic hazard” in the form of peak ground acceleration (PGA) is replaced by spectral acceleration. This paper investigates the effect of using new seismic hazards on the structural performance of reinforced concrete (RC) buildings. It also looks into the financial impact on the capital costs of new buildings. Useful insights are made to understand the structural performance and financial impact of adopting IBC 21 for structural design in contrast to UBC 97. This study was carried out from the perspective of a developing country, Pakistan. Reinforced concrete moment resisting and dual frames are used as the main structural system of a typical 7-story residential building to investigate the aforementioned effect. The frames are assumed to be located in two locations with high and low seismic hazards. The effect on structural performance is investigated via nonlinear pushover analysis. Financial impact is judged mainly through cost estimation for steel and concrete. A detailed discussion is also presented on the seismic design guidelines in both codes.

Denim is considered a versatile fabric due to its subsequent usage by the population of all ages. However, it also leads to a large amount of fabric wastage in the apparel industry. Therefore, this research explored 13 denim dress designs for women's top wear for fabric efficiency and sustainability. 2D patterns of all selected dress designs were drafted and virtual markers were generated through Garment Gerber Technology (GGT) to investigate the sustainable designs. Results revealed that denim bustier was ranked top with fabric efficiency (89.01%), while denim shirt dress ranked 2nd (88.64%), triple pleat blouse ranked 3rd (87.10%), denim bodysuit ranked 4th (86.88%), western style shirt ranked 5th (86.79%), long sleeve jacket ranked 6th (86.76%), rock and roll jacket ranked 7th (86.74%), light shade jacket ranked 8th (86.58%), fitted denim shirt ranked 9th (86.39%), denim dungaree 10th (86.16%), crop jacket ranked 11th (85.79%), lace-up ranked 12th (85.74%) and oversized jacket ranked 13th (85.59%). Denim bustier was ranked 1st style with minimum fabric consumption (7 meters) and fabric wastage (11%), while oversized jackets and lace-up shirts ranked last with fabric consumption (33 and 39 meters) and fabric wastage (14.41% and 14.26%). ANOVA test p-value shows that the results were close to significant. Thus, the research is beneficial to the apparel industry for the execution of sustainable and cost-effective dress designs

The Buongiorno nanofluid model serves as a foundational model for theoretical and experimental research in the field of nanofluids, and this model can be applied to various engineering problems, including heat exchangers, biomedical applications, solar collectors, nuclear reactors, and different cooling systems in the automotive and electronics industries. The use of nanofluids in the Eyring-Powell fluid over a squeezed sensing surfaces is a vital area of research for the design and improvement of microfluidic devices and sensors, which find widespread usage in industrial and medical applications. The main purpose of this work is to note the augmentation in thermal conductivity by using the Buongiorno nanofluid model along with the natural convective flow of non-Newtonian Eyring-Powell fluid that is moving on the squeezed sensory surface along with slip velocity. The viscosity of a fluid is assumed to be dependent on temperature. The Cattaneo-Christov heat and mass flux and chemical reaction are assumed to determine the combined effect of heat and mass transport. The governing model of equations is in the form of dimensional partial differential equations, and we have to convert these equations into ordinary differential equations; therefore, a set of similarity transformations is adopted for making the equations into dimensionless form. The numerical results were obtained by adopting the predictor and corrector multistep method, namely the ‘Adams-Bashforth’ technique, in Matlab software. The use of natural convective flow enhances the velocity region. The velocity slip parameter increases the velocity of the fluid, whereas the viscosity parameter drops the velocity profile. The thermophoresis and Brownian motion parameters are the sources of the increment in the temperature region. The thermal relaxation and solutal relaxation parameters are the sources of decline in the temperature region. The squeezing parameter is the source of reduction in the skin friction, whereas the result indicates that the fluid parameter, Grashof number, and viscosity coefficients increase the skin friction.