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Abstract The bond between concrete and reinforcing steel bars in reinforced concrete structures is crucial. Prestressing strands with a diameter of 17.8 mm (0.7 in) transfer higher compression per unit area than smaller strands, improving moment capacity and shear strength and extending the girder span. However, limited research on the bond performance of these 17.8 mm diameter prestressing strands has restricted their widespread use despite their advantages. This study presents a methodology to determine the transfer length of pretensioned members numerically. The influence of pretension force and bond strength on a 17.8 mm diameter strand was assessed through the validation of a finite element model using experimental results from a standardized pretensioned pull-out test. Analytical calculations using different code formulas were also conducted, encompassing strands of varying diameters. Our finite element analysis suggests that a 50.8 mm spacing between adjacent 17.8 mm diameter strands is applicable, ensuring there is no stress overlap in the transfer zones, which can lead to concrete cracking and reduced structural integrity. Existing code formulas, such as ACI 318–19 and AASHTO LRFD 9th edition, require longer transfer lengths when compared with the numerical results. The fib MC 2010 and EC2 formulas offer closer results to numerical results of smaller diameter strands but underestimate the transfer length for the 17.8 mm diameter strand. Therefore, improvements to code formulations may be necessary for more accurate transfer length predictions for this specific strand size.

Introduction: The Gymnastics Functional Measurement Tool is comprised of 10 tests. The purpose of this study was to investigate the relationship between the overall score on the gymnastics functional measurement tool and the technical skill class of competitive male gymnasts.Methods: This field design research was conducted on 25 boy gymnasts, aged 7 to 17, from Guilan province, who competed in a two-part gymnastics competition (floor exercise and vaulting). The sample was selected by a non-random sampling method. The results of the competition in the technical skill classification of the athletes were obtained with the coordination of the Guilan Province Gymnastics Federation and after one week of the competition and having enough time for physical recovery and intervention avoidance, a functional movement measurement test (GFMT) was taken for each participant on their usual training day and time and after proper warm-up. Pearson and Spearman correlation tests were used to check the relationship between variables. The data were analyzed using SPSS software, with a significance level of P≤0.05.Results: The correlation coefficient tests revealed a positive and significant relationship between the gymnastics functional measurement tool scores and the technical skill score of ground movements, as well as the overall technical score of the competition. There was no significant relationship between the gymnastics functional measurement tool scores and the vaulting technical skill score.Conclusion: It seems that the gymnastics functional measurement tool evaluation score, which assessed gymnasts’ technical skill, had an adequate level of accuracy.

Nvidia’s Omniverse platform represents a paradigm shift in the realm of virtual environments and simulation technologies. This paper presents a comprehensive examination of the Omniverse platform, a transformative force in virtual environments and simulation technologies. We offer a detailed systematic survey of the Omniverse’s impact across various scientific fields, underscoring its role in fostering innovation and sculpting the technological future. Our focus includes the Omniverse Replicator for generating synthetic data to address data insufficiency, and the utilization of Isaac Sim with its Issac Gym and software development kit (SDK) for robotic simulations, alongside Drive Sim for autonomous vehicle emulation. We further investigate the Extended Reality (XR) suite for augmented and virtual realities, as well as the Audio2Face application, which translates audio inputs into animated facial expressions. A critical analysis of Omniverse’s technical architecture, user-accessible applications, and extensions are provided. We contrast existing surveys on the Omniverse with those on the metaverse, delineating their focus, applications, features, and constraints. The paper identifies potential domains where the Omniverse excels and explores its real-world application capabilities by discussing how existing research papers utilize the Omniverse platform. Finally, we discuss the challenges and hurdles facing the Omniverse’s broader adoption and implementation, mitigating the lack of surveys solely focusing on the Omniverse.

This study aimed to analyze the relationship between financial literacy and mobile banking ‎usage, considering the moderating role of demographic characteristics among commercial ‎bank clients in the Jordanian southern provinces of Jordan. Using a sample of 1,380 commercial bank clients from ‎Jordan's southern region. To achieve the study's objective and test its hypotheses, the authors employed the quantitative method and utilized SPSS software version 28 for data analysis. The results revealed a strong positive relationship between ‎the level of financial literacy and mobile banking usage, with a moderating role of ‎demographic characteristics on the relationship between the level of financial literacy and ‎mobile banking usage. The study found that male clients and individuals with higher income levels were more inclined to utilize mobile banking services compared to female clients and those with lower income levels. On the other hand, age and educational level did not show a ‎moderating effect on this relationship. Based on the findings, the study recommends enhancing financial literacy through the development of programs and diverse digital banking products to meet client's needs, thereby promoting the adoption of mobile banking services. ‎

The current study aims to examine how creditworthiness criteria based on the (5Cs) model with its dimensions (character, capacity, capital, conditions, and collateral) on the credit decision in the presence of intellectual capital as a moderating variable applied to the branches of Jordanian commercial banks in the southern governorates of Jordan. The study included 449 populations from these branches, with a sample size of 205 employees. The authors employed a quantitative approach and utilized Macro PROCESS v4.2 by Andrew F. Hayes for analysis within SPSS v.28 software to achieve the study objective and test its hypotheses. According to the findings of the study, there is a positive effect of creditworthiness criteria based on the (5Cs) model on the credit decision. Furthermore, the study discovered that there is a presence of a moderating role of intellectual capital on the relationship between creditworthiness criteria based on the (5Cs) model and the credit decision. The study recommends that banks should prioritize investing in training programs for employees to improve their ability to assess credit risk accurately.

Abstract Background Accurate preoperative molecular and histological risk stratification is essential for effective treatment planning in endometrial cancer. However, inconsistencies between pre- and postoperative tumor histology have been reported in previous studies. To address this issue and identify risk factors related to inaccurate histologic diagnosis after preoperative endometrial evaluation, we conducted this retrospective analysis. Methods We conducted a retrospective analysis involving 375 patients treated for primary endometrial cancer in five different gynaecological departments in Germany. Histological assessments of curettage and hysterectomy specimens were collected and evaluated. Results Preoperative histologic subtype was confirmed in 89.5% of cases and preoperative tumor grading in 75.2% of cases. Higher rates of histologic subtype variations (36.84%) were observed for non-endometrioid carcinomas. Non-endometrioid (OR 4.41) histology and high-grade (OR 8.37) carcinomas were identified as predictors of diverging histologic subtypes, while intermediate (OR 5.04) and high grading (OR 3.94) predicted diverging tumor grading. Conclusion When planning therapy for endometrial cancer, the limited accuracy of endometrial sampling, especially in case of non-endometrioid histology or high tumor grading, should be carefully considered.

Hemodialysis patients are susceptible to excess volume accumulation, particularly over the 2-day interval (long interdialytic gap), resulting in higher interdialytic weight gain (IDWG). We thought to determine whether a novel device designed to enhance fluid and salt loss by activating the eccrine sweat glands can mitigate IDWG. Patients eligible for the study were undergoing regular hemodialysis for ≥3 months, without residual renal function, and with IDWG (as a percentage of IDWG/dry body weight) ≥2.5%. Treatments were administered at the patient’s home. The primary performance endpoint was differences in weight gain over long interdialytic period with the device compared to the control period. Secondary exploratory endpoints included the need for ultrafiltration (UF) rate > 10 mL/kg/h in the post-interval dialysis. Five patients were enrolled into the pilot study (age range 26 to 69 years, 3 women). The hourly mean weight loss from sweat was 186 ± 45 g/h. The average procedure length was 4.5 h with an average fluid loss of 899 ± 283 grams per procedure. The average least-squares mean absolute difference of IDWG between the control and treatment periods was −2.0%; (95% confidence interval [CI], −2.9% to −1.2%, p

Addressing harmonics, voltage sags, voltage swells, and asymmetrical variations is essential to seamlessly integrate renewable energy sources, electric vehicle charging stations, and power electronics devices into electric power grids. These issues can significantly impact the sinusoidal symmetry of voltage waveforms. Series Active Power Filters (APFs) present a promising solution that can dramatically improve power quality (PQ) by effectively addressing voltage distortions. This paper first identifies several topology-related impracticalities in the existing literature on series APFs, such as using nonlinear loads or linear loads with a current source. Secondly, to understand the motivations behind these impracticalities, commonly used reference extraction methods, namely, Instantaneous Reactive Power Theory (IRPT) and Synchronous Reference Frame (SRF), are tested on a practical topology consisting of a distorted voltage source and a linear RL load. Results conducted in the MATLAB/Simulink environment show that IRPT fails to extract the reference signal under the practical topology, and SRF leads to unacceptable THDs surpassing the 5% threshold mandated by relevant standards set forth for such applications. Thirdly, the matrix pencil method (MPM), a model-based parameter estimation technique that exploits a voltage waveform's underlying exponential signal model to extract the series APF's reference voltage, is proposed. Extensive simulations showcase the superior performance of the MPM-based series APF. It successfully reduces voltage total harmonic distortion (THD) to below 1.13% across various scenarios, including situations involving harmonic-polluted voltage sources, incorporating nonlinear loads, sag and swell phenomenon, and capacitor utilization in DC link implementation.

This work addresses the significant issue of plasma waves interacting with non-linear dynamical systems in both perturbed and unperturbed states, as modeled by the generalized Whitham–Broer–Kaup–Boussinesq–Kupershmidt (WBK-BK) Equations. We investigate analytical solutions and the subsequent emergence of chaos within these systems. Initially, we apply advanced mathematical techniques, including the transform method and the G′G2 method. These methods allow us to derive new precise solutions and enhance our understanding of the non-linear processes dominating plasma wave dynamics. Through a systematic analysis, we identify the conditions under which the system transitions from orderly patterns to chaotic behavior. This investigation provides valuable insights into the fundamental mechanisms of non-linear wave propagation in plasmas. Our results highlight the dynamic interplay between non-linearity and variation, leading to chaos, which may be useful in predicting and potentially controlling similar phenomena in practical applications.

Generally, the monostrand anchor, which is made of cast iron and used in the global market, has a rectangular shape. It is commonly used when low concrete stresses are induced and minimum slab thickness is needed. Multiple monostrand anchors can be used adjacent to each other at one or more horizontal levels in slabs to replace a multistrand anchor system, which combines two or more strands in the same anchor. Monostrand anchor has a proper stress distribution, while the multistrand has greater overlap zone stresses in post tension slabs. An experimental study was conducted on round monostrand anchors to investigate anchorage and anchor bearing zones. Concrete blocks were prepared, and tested at different ages. The goal is to evaluate the contribution of the concrete's strength improvement against bursting pressure caused by jacking forces at the edge zone of a flat slab. The blocks were stressed using jacking machine. Strands with two diameter sizes (12.7 mm and 15.7 mm) were used. A rigid steel framework was developed as an abutment that can withstand all jack's response forces on the tested concrete blocks. On the other hand, this framework serves as a fixation for the cables' dead ends. The concrete blocks were attached to this framework. After that, they were stressed up to failure. Hairpin reinforcement were used to strengthen the blocks, and resist the applied stresses. Multiple round monostrands were also placed adjacent to each other to produce stress concentration in the concrete blocks. Numerical models were also constructed using finite element to simulate the experimental tests and validate the obtained results. The results were also compared to ACI provision.

Marine transportation is a significant contributor to overall energy consumption among transportation sectors and is responsible for producing a considerable amount of greenhouse gases. A potential solution for alternative applications involves implementing combined heat integration, thereby enabling the production of additional utilities and mitigating emissions. The current work introduces an innovative heat integration process for a marine engine, focusing on implementing an optimal thermal matching technique to minimize overall irreversibility in producing liquefied hydrogen and coolant. The process incorporates an organic flash-bi-evaporator cooling cycle, a humidification dehumidification desalination, a polymer electrolyte membrane water electrolysis process, and a Claude cycle. The generated freshwater is delivered to the electrolyzer to produce gaseous hydrogen. This product and the cooling for freezing are utilized in the Claude cycle for hydrogen liquefaction. The study utilizes an advanced thermo-environmental multi-criteria investigation and optimization, considering sensitivity analysis and optimization based on artificial intelligence method. The optimization process incorporates the training and testing of artificial neural networks, NSGA-II method, and TOPSIS decision-making. The primary objective functions include exergetic efficiency and carbon dioxide emission. The findings demonstrate that the specified objectives are computed to be 0.121 and 2.67 kg/MWh, correspondingly. Besides, this condition exhibits a liquefied hydrogen flow rate of 6.44 L/h and a cooling output of 43.61 kW, showing an energy efficiency of 0.1145. Also, the total exergy destruction rate associated with the arranged structure is 124.5 kW. Furthermore, the optimum state reveals an exergoenvironmental index of 0.840 and an exergetic stability factor of 0.869.

Synthetic organic dyes and herbicide pollutants pose a significant threat to water quality due to their high solubility in water and widespread industrial discharge. In water conservation developments, the Metal-Organic Frameworks (MOFs) are considered confident and substantial for the exclusion of toxic organic dyes, due to their multi-potential assets of cost-effective, high pore volume, high thermal stability, easy adaptation to toxic dye molecules, and most of them are stable in water, etc. Hence, the green synthetic methodology was employed for the combination of Cu3(BTC)2 MOF, which is draped with carboxylate functionality ligands, as an adsorbent to remove the hazardous dyes of Methyl Orange (MO), Acid Yellow (AY), and toxic herbicide of Atrazine (ATZ) from contaminated wastewater. As-reported Cu3(BTC)2 was evidently characterized by XRD, FTIR, TGA, XPS, SEM, and EDAX analysis. The equilibrium adsorption capacity (Qe) value of as-reported Cu3(BTC)2 for AY, MO, and ATZ was better in comparison with the formerly reported adsorbent. The high adsorption capacity of Cu3(BTC)2 for AY (777 mg/g), MO (903 mg/g), and ATZ (484 mg/g) is principally explained by π-π and electrostatic interaction. As a result, Cu3(BTC)2 is reported and proposed as a suitable adsorbent for the abolition of toxic dyes and herbicides from contaminated water.

Due to the optical properties of the electron transport layer (ETL) and hole transport layer (HTL), inverted perovskite solar cells can perform better than traditional perovskite solar cells. It is essential to compare both types to understand their efficiencies. In this article, we studied inverted perovskite solar cells with NiOx/CH3NH3Pb3/ETL (ETL = MoO3, TiO2, ZnO) structures. Our results showed that the optimal thickness of NiOx is 80 nm for all structures. The optimal perovskite thickness is 600 nm for solar cells with ZnO and MoO3, and 800 nm for those with TiO2. For the ETLs, the best thicknesses are 100 nm for ZnO, 80 nm for MoO3, and 60 nm for TiO2. We found that the efficiencies of inverted perovskite solar cells with ZnO, MoO3, and TiO2 as ETLs, and with optimal layer thicknesses, are 30.16%, 18.69%, and 35.21%, respectively. These efficiencies are 1.5%, 5.7%, and 1.5% higher than those of traditional perovskite solar cells. Our study highlights the potential of optimizing layer thicknesses in inverted perovskite solar cells to achieve higher efficiencies than traditional structures.

To comprehend the thermal regulation within the conical gap between a disk and a cone (TRHNF-DC) for hybrid nanofluid flow, this research introduces a novel application of computationally intelligent heuristics utilizing backpropagated Levenberg–Marquardt neural networks (LM-NNs). A unique hybrid nanoliquid comprising aluminum oxide, Al2O3, nanoparticles and copper, Cu, nanoparticles is specifically addressed. Through the application of similarity transformations, the mathematical model formulated in terms of partial differential equations (PDEs) is converted into ordinary differential equations (ODEs). The BVP4C method is employed to generate a dataset encompassing various TRHNF-DC scenarios by varying magnetic parameters and nanoparticles. Subsequently, the intelligent LM-NN solver is trained, tested, and validated to ascertain the TRHNF-DC solution under diverse conditions. The accuracy of the LM-NN approach in solving the TRHNF-DC model is verified through different analyses, demonstrating a high level of accuracy, with discrepancies ranging from 10−10 to 10−8 when compared with standard solutions. The efficacy of the framework is further underscored by the close agreement of recommended outcomes with reference solutions, thereby validating its integrity.

BACKGROUND: Increased body weight is common among university students; transitioning from high school to university may increase perceived stress levels, thus changing dietary habits and metabolism to promote overweight or obesity. The current study investigates the association between stress and dietary habits among university students in Jordan. MATERIALS AND METHODS: A cross-sectional study was conducted among 221 university students aged between 20 and 25 at Applied Science Private University [ASU]. A self-reported questionnaire was distributed to university students. The questionnaires were divided into three sections: the first was about general characteristics, body weight, change in body weight, and stress eating. RESULT: The survey of 208 participants showed that 64.3% were females, and 84.2% of students lived with their families. Results showed that more than half [51.1%] of the respondents were dissatisfied with their eating habits. Females [57.7%] monitored their food intake more than males did. However, most males [77.2%] reported less eating during stress compared to females. In addition, the data analysis revealed that those who ate more were less likely to monitor their food intake [χ2 =9.734, df = 1, P = .002] or quantity [χ2 =16.704, df = 1, P < .001]. Only 20.8% of the participants preferred sports or hobbies as a stress reduction activity; 29.4% took showers, while 51.1% ignored what made them stressed. Finally, 56.3% of participants reported increased weight after starting university, and it was significantly correlated with stress eating while studying for exams [χ2 =8.762, df = 2, P = .013]. Stress affects university students and can lead to unhealthy eating habits and health issues like obesity. CONCLUSION: Many students face stress during their academic years, which affects their dietary choices. Policies promoting healthy eating habits and stress-reducing activities are important for university students.

Inflammatory bowel disease (IBD), comprising Crohn’s disease and ulcerative colitis, is a lifelong disease that manifests with chronic intestinal inflammation, sequential fibrosis, and an increased risk of colitis-associated colon cancer (CAC). The combined effects of genetic, immunological, environmental, and microbial factors render it difficult to determine the specific mechanism underlying the induction and perpetuation of IBD. Various animal models of IBD have contributed enormously to the understanding of IBD pathogenesis in terms of genomics, transcriptomics, proteomics, microbiome, and drug development of novel therapeutics. Although comprehensive research on IBD has been enabled by advanced technologies, such as genetically engineered models, there is a great need to develop relevant in vivo models of colitis and fibrosis. Here, we review 4 categories of animal models of acute and chronic intestinal inflammation, fibrosis, and CAC: chemically induced, genetically engineered, T cell transfer, and spontaneous gene mutation models.

The vulnerability of patients on hemodialysis (HD) to infections is evident by their increased susceptibility to infections in general and to resistant organisms in particular. Unnecessary, inappropriate, or suboptimal antimicrobial prescribing is common in dialysis units. This underscores the need for dedicated antimicrobial stewardship (AMS) interventions that can be implemented both in the inpatient and outpatient settings. In this review, we provide a comprehensive approach for clinicians with the most updated coordinated AMS principles in HD setting in six areas: prevention, diagnosis, treatment, education and empowerment, monitoring, and research.

The current article is devoted to the development of a theoretical model investigating heat transfer analysis of MHD blood flow through renal tubules. For this purpose, we consider the transport of Newtonian fluid inside a non-uniform tube whose lateral surface is kept at constant temperature. The walls of tube are considered to admit the variable permeation and the flow is actuated by an externally applied magnetic field. The solution of the problem is formulated analytically in terms of axial and radial velocities and temperature distribution under the presumption of lubrication approximation in the inertia free flow field. Implication of Darcy’s law for fluid seepage across the tubular membrane results in an ordinary differential equation having variable coefficients for the unknown pressure, which is successfully computed numerically using RK45 routine. Performance of velocity, pressure and temperature distributions has been investigated for various values of the physical parameters involving in the model. Moreover, flow rate behavior, fluid reabsorption and the leakage flux has been analyzed through graphs and tables. The characteristics of heat transfer in the flow field is also evaluated for various values of Brinkman number. A significant discovery reported in the results of present model reveals that the axial flow exhaustion and radial flow reversal are significantly influenced by the tube converging/diverging parameter and the Hartmann number as well. By employing a strong magnetic field, exhaustion and reversal phenomena in the flow field can be restrained up to a certain limit. Moreover, with an increasing wall permeability, there is a significant exhaustion of axial flow in a divergent tube and a prominent assistance takes place in the radial flow reversal for convergent tube. It is hoped that the present model will bear the potential to study flow in renal tubules and in hemodialyzer.

Abstract Hate speech has become a phenomenon on social media platforms, such as Twitter. These websites and apps that were initially designed to facilitate our expression of free speech, are sometimes being used to spread hate towards each other. In the Arab region, Twitter is a very popular social media platform and thus the number of tweets that contain hate speech is increasing rapidly. Many tweets are written either in standard, dialectal Arabic, or mix. Existing work on Arabic hate speech are targeted towards either standard or single dialectal text, but not both. To fight hate speech more efficiently, in this paper, we conducted extensive experiments to investigate Arabic hate speech in tweets. Therefore, we propose a framework, called arHateDetector, that detects hate speech in the Arabic text of tweets. The proposed arHateDetector supports both standard and several dialectal Arabic. A large Arabic hate speech dataset, called arHateDataset, was compiled from several Arabic standard and dialectal tweets. The tweets are preprocessed to remove the unwanted content. We investigated the use of recent machine learning and deep learning models such as AraBERT to detect hate speech. All classification models used in the investigation are trained with the compiled dataset. Our experiments shows that AraBERT outperformed the other models producing the best performance across seven different datasets including the compiled arHateDataset with an accuracy of 93%. CNN and LinearSVC produced 88% and 89% respectively.

Globally, cancer is one of the primary causes of both morbidity and mortality. To prevent cancer from getting worse, more targeted and efficient treatment plans must be developed immediately. Recent research has demonstrated the benefits of natural products for several illnesses, and these products have played a significant role in the development of novel treatments whose bioactive components serve as both chemotherapeutic and chemo-preventive agents. Phytochemicals are naturally occurring molecules obtained from plants that have potential applications in both cancer therapy and the development of new medications. These phytochemicals function by regulating the molecular pathways connected to the onset and progression of cancer. Among the specific methods are immune system control, inducing cell cycle arrest and apoptosis, preventing proliferation, raising antioxidant status, and inactivating carcinogens. A thorough literature review was conducted using Google Scholar, PubMed, Scopus, Google Patent, Patent Scope, and US Patent to obtain the data. To provide an overview of the anticancer effects of several medicinal plants, including Annona muricata, Arctium lappa, Arum palaestinum, Cannabis sativa, Catharanthus roseus, Curcuma longa, Glycyrrhiza glabra, Hibiscus, Kalanchoe blossfeldiana, Moringa oleifera, Nerium oleander, Silybum marianum, Taraxacum officinale, Urtica dioica, Withania somnifera L., their availability, classification, active components, pharmacological activities, signaling mechanisms, and potential side effects against the most common cancer types were explored.

Objective Neck imbalance negatively affects body aesthetics of adolescent idiopathic scoliosis (AIS) patients. The evaluation of neck imbalance is currently limited to radiographic parameters, but lacks visual indicators. Therefore, the purpose of this study was to establish indexes of neck imbalance based on body image and to investigate whether these indexes can truly reflect neck imbalance in AIS patients. Methods We performed a cross‐sectional study at a single institution between June 2017 and September 2020 and there were 115 subjects involved in this research. All patients were diagnosed with adolescent idiopathic scoliosis, Lenke type I/II. Radiographic parameters measured included cervical axis tilt (CAT), T1 tilt, first rib angle (FRA), clavicle angle (CA), radiographic shoulder height (RSH), proximal thoracic curve (PTC), apical vertebra translation of proximal thoracic (AVT of PT), main thoracic curve (MTC), apical vertebra translation of main thoracic (AVT of MT) and coronal balance (CB/C7PL‐CSVL). Neck imbalance indexes were obtained and measured following a standardized manner. Intra‐class correlation coefficient (ICC) analysis was performed for neck imbalance indexes to determine their intra‐observer and inter‐observer reliability, and correlation tests were performed for neck imbalance indexes with the radiographic parameters mentioned above. Results Strong intraobserver and interobserver reliability were observed in neck imbalance index (NII) 1 (0.91 and 0.88), neck imbalance index 2 (0.85 and 0.81) and NII 3 (0.82 and 0.80), P

Geopolymer (GMR) paste with micro-fibres and nanoparticles is an excellent alternative for reducing cement production for environmental sustainability. Therefore, the performance of fibre-reinforced (FR) GMR pastes containing nanoparticles must be further explored. The goal of this study is to incorporate varying amounts of nano titanium dioxide (NTD) into micro carbon-FR fly ash-based GMR pastes to increase microstructure, impact strength, toughness, fracture, and mechanical performance. Four different dosages of NTD, ranging from 1 to 4% by the weight of the mix to cast GMR mixes including a constant dosage of micro carbon fibre (CF) (0.5% by weight of mix). A reference mix with 0.5% micro-CF having no dosage of NTD was also manufactured. Scanning Electron Microscopy (SEM) was used to assess the internal structure of GMR. The average findings of six specimens from each paste were taken to determine the different features of GMR pastes. The outcomes of this investigation revealed that using 3% NTD in a carbon-FR-GMR mix produced the best results in terms of hardness, impact strength, and compressive stress while using 2% NTD produced the best results in terms of flexural stress and fracture toughness of pastes. The compressive and flexural strengths of GMR improved by 23% and 40% while the impact strength and hardness were improved by 53% and 10%, respectively.

Background: Despite the increasing prevalence of obesity in the United States, negative attitudes toward obese individuals are widespread. Health-care providers, including dietetics and nutritionists, are not exempt from showing bias toward obese individuals, which may lead to subsequent psychological and health problems. Objectives: The purpose of this study was to measure the extent of weight bias among dietetics and nutrition students and investigate its determinants. Materials and Methods: A cross-sectional survey (316) was conducted among undergraduate dietetics and nutrition students at a large Midwestern University to assess weight bias using the Fat Phobia Scale. Eating competence was measured using the ecSI 2.0 and body dissatisfaction using the Stunkard Figure Rating Scale. Other variables included experience with obesity, media exposure to health and nutrition information, and demographic characteristics. Results: About 36% of the participants had weight bias, 64% were unsatisfied with their body image and none of the participants had eating competence. Media exposure to health information, body dissatisfaction, and eating competence was related to fat phobia (P < 0.05). Conclusion: These findings highlight that weight bias is an apparent issue among students enrolling in health-related programs. Considering their future role in clinical and community settings, this issue should be addressed properly.

Trust is a fundamental element in human relationships, playing a crucial role in decision-making processes. Despite its significance, numerous dimensions of perceived trustworthiness remain unexplored and warrant further investigation. Previous literature has highlighted the influence of emotions and sentiments on how individuals perceive trustworthiness, with visual, vocal, and behavioral cues serving as essential markers. This preliminary study aims to expand the existing knowledge in the field by investigating trustworthiness traits manifested through facial and gesture expressions in emotional videos across diverse cultural contexts. To address this objective, an annotation platform was developed to collect annotation data using the benchmarked One-Minute-Gradual Emotion (OMG) audiovisual corpus, enabling the annotation of actors’ perceived trustworthiness levels alongside other inquiries related to emotional state, gesture, activeness, comfort, and speech integrity. The findings of this study demonstrate a positive correlation between higher levels of speaker activity, faster gesturing, and a relaxed demeanor with increased levels of trust gained from audiences. The proposal presented in this paper holds potential for future studies focused on trustworthiness annotation, facilitating the measurement of trust-related features. Moreover, this research serves as a critical step towards understanding the foundations of trustworthiness in the development of synthetic agents that require perceived trustworthiness, particularly in domains involving negotiations or emergency situations where rapid data collection plays a pivotal role in saving lives.

In this article, the effect of local mechanical stress on the properties of monocrystalline and polycrystalline silicon-based p-n junctions under illumination is studied and analyzed experimentally and theoretically. Results from the experiments showed that when the local mechanical force was increased from 4 N to 20 N, the short-circuit current of the monocrystalline silicon-based p-n junction changed nonlinearly from 24 mA to 43 mA, and that of the polycrystalline silicon-based p-n junction changed linearly from 14.7 mA to 16.7 mA. Experimental results shows that the ideality coefficient of the p-n junction based on monocrystalline silicon decreased from 1.274 to 0.807 and that of polycrystalline from 1.274 to 1.102. Therefore, when the mechanical force applied on monocrystalline silicon increased, the dominant recombination changed from Shockley-Read-Hall to Auger. On the other hand, in polycrystalline silicon, the dominant Shockley-Read-Hall recombination did not change due to the grain boundaries. So, it means that mechanical force causes the narrowing of the band gap of the silicon not increasing of number of recombination centers. When mechanical force increases from 4 N to 12 N, fill factor of monocrystalline increased by 5.75% and that of polycrystalline decrease by 1.1%. In the range of 4 N and 20 N mechanical force, saturation current of monocrystalline and polycrystalline silicon p-n junction changed from $8~\mu \text{A}$ to $41~\mu \text{A}$ . and $22~\mu \text{A}$ to $97~\mu \text{A}$ , respectively.

Purpose – The objective of this research study is to examine the complicated relationship between work motivation, job satisfaction, job dissatisfaction, and turnover intention of the housekeeping staff in selected four and five-star hotel properties in Jordan by using Herzberg’s Two-Factor theory. Design – A survey design was implemented in this research study. The sample for this research study consists of individuals working in the housekeeping departments of four and five star international hotels in Jordan. Methodology – Cluster analysis, correlation, and t-test were utilized for data analysis. The two-step clusters method was used to cluster groups based on the mean values of job dissatisfaction, as it is a unique concept that explains Herzberg’s Two-Factor Theory and also the work-related behaviour of employees. Approach – The validity of Herzberg’s Two-Factor Theory will be examined as well as examining the complicated relationship among work motivation, job satisfaction, job dissatisfaction, and turnover intention. Findings – The results of this study revealed that there is no relationship between job dissatisfaction of housekeeping staff and job satisfaction, and between job dissatisfaction and job motivation. However, there was a positive relationship between their job satisfaction and work motivation and also between their job dissatisfaction and turnover intention. No relationship was found between their work motivation and turnover intention and between their job satisfaction and turnover intention. Among all fourteen motivational factors, work itself (4.25 out of 5.00) and achievement (4.24 out of 5.00) were ranked at the top, which is consistent with Herzberg’s findings. Salary was the least satisfied/preferred factor in this study. Originality of the research – Having a separate job dissatisfaction construct in a research study is a very unique concept that Herzberg’s Two-Factor Theory (1959) developed and which also contributes to the uniqueness and originality of this study

Protein-rich energy bars are known as an excellent nutritional supplement for athletes that help to build and repair connective tissues. The study is, therefore, aimed at developing high-protein bars using lupine seeds, wheat germ, and selected dried fruits including raisins, dates, apricots, and cranberries. Different formulations (F1, F2, F3, and F4) were performed at different ratios of ingredients to produce high-protein bars and compared them with a control bar made of whey-protein concentrate and oat flakes. For this purpose, a proximate analysis, total phenol content, total flavonoid content, DPPH radical scavenging activity, water content, nutritional, and sensory analysis was performed to evaluate the results. The proximate analysis of the produced protein bars showed a significantly higher protein content (22 ± 2) and total phenolic activity (57 ± 33) in formulation group 4 as compared to the other groups. Furthermore, the least water activity content was found in formulation group 1 (1 ± 0.0) when compared with the control group (1 ± 0.0). The results from the sensory evaluation revealed that T3 had the highest average scores in overall consumer acceptability. Our study found that total phenolic, flavonoid, and fiber content were significantly higher in the prepared protein bars indicating prospective health benefits when compared to the control group. Overall, the study demonstrates that high-protein bars using functional ingredients like dried fruit can provide enriched nutritionally valuable food options for consumers.

In this investigation, we employ a numerical simulation approach to model a hydrogenated lead-free Cs2AgBiBr6 double perovskite solar cell with a p-i-n inverted structure, utilizing SCAPS-1D. Contrary to traditional lead-based perovskite solar cells, the Cs2AgBiBr6 double perovskite exhibits reduced toxicity and enhanced stability, boasting a maximum power conversion efficiency of 6.37%. Given its potential for improved environmental compatibility, achieving higher efficiency is imperative for its practical implementation in solar cells. This paper offers a comprehensive quantitative analysis of the hydrogenated lead-free Cs2AgBiBr6 double perovskite solar cell, aiming to optimize its structural parameters. Our exploration involves an in-depth investigation of various electron transport layer materials to augment efficiency. Variables that affect the photovoltaic efficiency of the perovskite solar cell are closely examined, including the absorber layer’s thickness and doping concentration, the hole transport layer, and the absorber defect density. We also investigate the impact of the doping concentration of the electron transport layer and the energy level alignment between the absorber and the interface on the photovoltaic output of the cell. After careful consideration, zinc oxide is chosen to serve as the electron transport layer. This optimized configuration surpasses the original structure by over four times, resulting in an impressive power conversion efficiency of 26.3%, an open-circuit voltage of 1.278 V, a fill factor of 88.21%, and a short-circuit current density of 23.30 mA.cm−2. This study highlights the critical role that numerical simulations play in improving the chances of commercializing Cs2AgBiBr6 double perovskite solar cells through increased structural optimization and efficiency.

Abstract Event detection from social media aims at extracting specific or generic unusual happenings, such as, family reunions, earthquakes, and disease outbreaks, among others. This paper introduces a new perspective for the hybrid extraction and clustering of social events from big social data streams. We rely on a hybrid learning model, where supervised deep learning is used for feature extraction and topic classification, whereas unsupervised spatial clustering is employed to determine the event whereabouts. We present ‘Deep-Eware’, a scalable and efficient event-aware big data platform that integrates data stream and geospatial processing tools for the hybrid extraction and dissemination of spatio-temporal events. We introduce a pure incremental approach for event discovery, by developing unsupervised machine learning and NLP algorithms and by computing events’ lifetime and spatial spanning. The system integrates a semantic keyword generation tool using KeyBERT for dataset preparation. Event classification is performed using CNN and bidirectional LSTM, while hierarchical density-based spatial clustering was used for location-inference of events. We conduct experiments over Twitter datasets to measure the effectiveness and efficiency of our system. The results demonstrate that this hybrid approach for spatio-temporal event extraction has a major advantage for real-time spatio-temporal event detection and tracking from social media. This leads to the development of unparalleled smart city applications, such as event-enriched trip planning, epidemic disease evolution, and proactive emergency management services.

Over the past few years, the on-demand transport services (e.g., Uber) have witnessed an unprecedented popularity due to its easy-to-adopt model (i.e., a passenger orders a taxi, a request is sent to all drivers in the vicinity, drivers accept/reject the order). Nonetheless, such a service is affected directly by multiple urban factors such as traffic, number of existing drivers en-route, and local weather which may cause a huge delay. Dial-A-Ride Problem with Transfers (DARPT) allows passengers to change vehicles during their trip in a bid to minimize the delay. However, DARPT relies solely on using the existing Global Positioning System (GPS) that suffers from delay in propagating raw traffic data (e.g., route coordinates, geodesic distance, and time stamp) on time and ultimately causes traffic disruption and increases ride time constraint. To this end, this work introduces a novel interactive Fog-based navigation simulator, PRYORTIE. PRYORTIE uses roadside smart units in the form of fog nodes as a means for collecting and sharing real-time traffic data comprising of vehicles’ location and speed within the area, they each cover. These nodes can calculate an optimal route for a vehicle using a novel path recommender algorithm that utilizes a vehicle's current position, its destination, and current traffic data. The nodes can update the route in real-time using the same algorithm if traffic conditions within their radius change. A package delivery case study has been implemented and simulated in PRYORTIE to demonstrate the impact of using fog nodes in routing and navigation. Compared with the state-of-the-art, the proposed approach shows on average 46.34% improvement in saving travel time. The proposed method clearly demonstrates tangible benefits of communicating real-time data to drivers and lays the ground for subsequent future work in smart transportation and navigation especially in the context of last mile delivery. It can easily be extended to autonomous vehicles and can be easily integrated into existing transportation frameworks that employ a fog-cloud paradigm for smart transportation.

This study aims to test the role of digital marketing as a mediating variable in the relationship between financial technology and financial inclusion. The researcher applied the descriptive analytical approach to the data collected by developing a questionnaire distributed to 375 employees in the Jordanian banking sector. The researcher also used structural equation modeling to test the study hypotheses through SmartPLS software 3. One of the study’s most important findings is that digital marketing partially mediates the relationship between financial technology and financial inclusion. The study recommends that the Jordanian commercial banking sector should use advanced strategies that enhance technological innovation and digital marketing through the existence of an evolved environment for financial technology that is optimally exploited.

تناول هذا البحث تحضير مسرى انتقائي من عجينة الكربون المعدلة لتحديد تركيز أيون الكلوريد في المحاليل المائية, وذلك بمزج كلوريد الفضة بنسبة , الغرافيت وبودرة زيت البرافين , يعمل مسرى الكلوريد المحضر عند درجة حموضة وفي درجة حرارة المخبر, باستجابة خطية أي استجابة نرنستية بميل ضمن مجال يقع بين , ومعامل ارتباط قوي , وزمن استجابة يتراوح بين , وزمن ثبات واسترجاعية %(102.50-99.28), وانحراف معياري نسبي مئوي %(8.345-4.179), كما بلغ حد الكشف التحليلي وحد الكشف الكمي, , و تميزت بمجال ثقة تراوحت قيمته ما بين , طبقت الطريقة المقترحة على عينات قياسية ثم قورنت بطريقة مرجعية وتم التأكد من دقة وصحة الطريقة المتبعة, من خلال اختبارات كلاً من ((''t'' , (f-test) حيث كانت قيمة ''t'' أقل من القيمة الجدولية t-tab وحسب قيمة F-test وقورنت مع Ftab عند مستوى ثقة 95% فتبين أنه لا يوجد فرق واضح بين الطريقتين, وأن الطريقة المقترحة تمتاز بالسهولة والدقة, الصحة, الكلفة المنخفضة.

There are many factors that may affect the concrete-strand and concrete-duct bond behavior in post-tensioned (PT) concrete slabs and beams. The importance of bond strength is to ensure a proper transfer of stresses from strands and ducts to the surrounding concrete. This research focused on bonded post-tensioned (PT) concrete elements, which includes the use of grout and ducts to provide the link between the strand and the concrete. The strength of the grout, the type and geometry of the ducts, and the embedment length of both strands and ducts were investigated through an experimental testing program to disclose the average interface shear stress within the embedded length of PT elements. This work helped in a better understanding of the bond behavior and the corresponding related parameters involved in the design process.

Lolwa AlRajeh,1 Amr Zaher,1 Amal alghamdi,2 Rasha Alsheikh,2 Osama AlSultan3 1Department of Pathology, College of Medicine, Imam Abdulrahman University, Dammam, Saudi Arabia; 2Family and Community Medicine Department, College of Medicine, Imam Abdulrahman University, Dammam, Saudi Arabia; 3Internal Medicine Department, King Fahd University Hospital, Al Khobar, Saudi ArabiaCorrespondence: Lolwa AlRajeh, Email lrajeh@iau.edu.saBackground: Iron deficiency plays an important role in our body’s immunity. Several studies have shown that it is frequently associated with infections.Objective: This study aimed to discover the effect of iron deficiency on immunity by demonstrating changes occurring in lymphocyte subsets among patients with an established diagnosis of iron deficiency.Methods: A total of 64 iron-deficient patients and 19 healthy controls were included. Complete blood counts, serum iron, ferritin, and total iron-binding capacity were assessed. Lymphocyte subsets were evaluated by flow cytometry.Results: Among iron-deficient patients, the anemic ones (Hb ≤ 11 g/dL) showed significantly lower absolute lymphocyte counts (p=0.013), lower relative and absolute NK-cell counts (p=0.025 and p=0.003, respectively), higher relative T-cell and CD4+-cell counts (p=0.026 and p=0.002, respectively). B cells and CD8+ T cells were not affected by any iron-deficiency indicators. Iron-deficient anemia patients showed a three- to fourfold increase in risk of having recurrent infections.Conclusion: Iron deficiency has an obvious effect on lymphocyte subsets. Changes in lymphocyte subsets started mainly in response to decreased hemoglobin, rather than decreased ferritin and/or iron. Synchronously decreased hemoglobin and increased total iron-binding capacity led to absolute decreases in total lymphocytes, mainly NK cells, and relative increases in T cells, mainly the helper ones. Monitoring changes in lymphocyte subsets may be helpful in identifying patients at risk of recurrent infections.Keywords: iron deficiency, lymphocyte subsets, immunity, flow cytometry

ناقش هذا البحث موقف ابن طفيل من الدين عموماً, ومن التعددية الدينية خصوصاً, وكان لابد إذن من تناول طبيعة المعرفة الدينية عنده وأشكال الوصول إليها, وكل ذلك من خلال قصته الشهيرة وهي قصة حي بن يقظان التي أظهر فيها ابن طفيل اشكال هذه المعرفة وتعددها وطرقها, ولهذا فقد تناولنا مفهوم التعددية الدينية اصطلاحاً ولغة, أي كيف تم تعريفها في المعاجم والأدبيات الفلسفية الغربية والعربية, وبعد ذلك ناقش البحث دور التعددية في فكر ابن طفيل, وكان الهدف من ذلك الوصول إلى مناقشة مفهوم النجاة في فلسفة ابن طفيل, التي يمكن أن نجده في جميع أشكال التدين وطرق الوصول إلى هذه النجاة

Emotion recognition is the process to detect, evaluate, interpret, and respond to people's emotional states and emotions, ranging from happiness to fear to humiliation. The COVID- 19 epidemic has provided new and essential impetus for emotion recognition research. The numerous feelings and thoughts shared and posted on social networking sites throughout the COVID-19 outbreak mirrored the general public's mental health. To better comprehend the existing ecology of applied emotion recognition, this work presents an overview of different emotion acquisition tools that are readily available and provide high recognition accuracy. It also compares the most widely used emotion recognition datasets. Finally, it discusses various machine and deep learning classifiers that can be employed to acquire high level features for classification. Different data fusion methods are also explained in detail highlighting their benefits and limitations.

The source of objective meaning is a controversial topic. For most of human history, religion had a monopoly on meaning, truth, and values. But from the nineteenth century onwards and with relativism gaining more popularity, this began to change, leaving most people divided into two main camps: those who believe in the existence of objective meaning and truth and those who maintain that such concepts simply do not exist. The resulting impossibility of finding shared meaning is very problematic, especially when it comes to intercultural communication. In fact, to speak of communication is to speak of common meaning. In this paper, I attempt to provide a definition for intercultural communication, explore the issue of shared meaning, and propose a culture-free approach to the latter—one that is based on reverting to an axiomatic understanding of the notion of meaning. My aim is to conclude that the failure of both dogmatism and relativism to sustain intercultural communication should not be interpreted pessimistically. Quite the opposite, it should be viewed as an opportunity to investigate other promising alternatives, mainly Sam Harris’s science of morality.

يرمي هذا البحث إلى الوقوف على شِعْريَّةُ القلقِ الوجوديِّ في "قصيدة الجبل" لابن خفاجة الأندلسي (450 ــ 533هــ)، والتي تُعد إحدى أهم اللّوامع الشّعرية في الشعر العربي عامة، وقيمة شعرية ضمن المخزون الشعري في الأدب الأندلسي خاصة، وما تزال تستأثر باهتمام النقاد والمناهج النقدية الحديثة والمعاصرة، وتخلق جدلًا في التّلقي النقديّ، إذ يُقاربها كل ناقد من وجهة نظره النقدية الخاصة، الأمر الذي يكشف قيمة شعرنا العربي القديم مشرقًا ومغربًا، وهو ما اتَّضح لنا عند شاعرِ الطّبيعة الأندلسية الأول، إذ توحَّد بالطبيعة، واستطاع أن يعبر عن أدق تفاصيلها وتقلباتها. لذا؛ فإن هذه القراءة تسعى إلى مقاربة المتن الشعري الأندلسي مقاربة نصية، تكشف عن أبعاد القلق الوجودي في الشعر الأندلسي باتخاذ قصيدة "الجبل" متْنًا وموضوعًا، مُتكئة على المنهج البنيوي التكويني، وطروحات الوجودية وبلورها الفلاسفة الوجوديون؛ ونظَّر لها النقد الحديث، مع انفتاحها على الطروحات العلمية المختلفة بدءًا من علم النفس إلى الأنثروبولوجيا والسيميولوجيا والدراسات اللغوية والثقافية، في محاولة الإجابة عن الطّرح الإشكالي التّالي: ما أبرز المؤثرات السوسيوثقافية لملمح القلق الوجودي في شعر ابن خفاجة؟، كيف يتجلى القلق الوجودي في قصيدة الجبل لابن خفاجة؟ وما إستراتيجياته الشّعرية؟

Previous research has shown the importance of conducting early interventions in mathematics in disadvantaged children. Solving arithmetical word problems is a field in which children particularly fail. In this study, preschoolers from disadvantaged French public schools (n = 101; M[subscript age] = 5-6) were taught strategies for using fingers to solve arithmetic word problems and compared with a control group. The intervention consisted of collective rituals based on learning finger patterns and 7 sessions spread over 4 weeks, for about 20 min, focusing on explaining how to use the fingers to solve problems. The results showed that the intervention has a significant post-test impact on the targeted transformation problem-solving skill and that children with lower performances in problem-solving at the pre-test benefited more from the intervention. The intervention also indirectly benefited the other problem-solving skills. However, there was no intervention effect on the arithmetic addition task. Our research highlights that an intervention focused on the explicit teaching of finger strategies for problem-solving can be successfully implemented into ecological learning contexts, especially in disadvantaged areas.

A new type of perovskite solar cell based on mixed tin and germanium has the potential to achieve good power conversion efficiency and extreme air stability. However, improving its efficiency is crucial for practical application in solar cells. This paper presents a quantitative analysis of lead-free FA0.75MA0.25Sn0.95Ge0.05I3 using a solar cell capacitance simulator to optimize its structure. Various electron transport layer materials were thoroughly investigated to enhance efficiency. The study considered the impact of energy level alignment between the absorber and electron transport layer interface, thickness and doping concentration of the electron transport layer, thickness and defect density of the absorber, and the rear metal work function. The optimized structures included poly (3,4-ethylenedioxythiophene)polystyrene sulfonate (PEDOT:PSS) as the hole transport layer and either zinc oxide (ZnO) or zinc magnesium oxide (Zn0.7Mg0.3O) as the electron transport layer. The power conversion efficiency obtained was 29%, which was over three times higher than the initial structure. Performing numerical simulations on FA0.75MA0.25Sn0.95Ge0.05I3 can significantly enhance the likelihood of its commercialization. The optimized values resulting from the conducted parametric study are as follows: a short-circuit current density of 30.13 mA·cm−2), an open-circuit voltage of 1.08 V, a fill factor of 86.56%, and a power conversion efficiency of 28.31% for the intended solar cell.

Abstract Background This trial evaluates interventions that utilize data entered at point-of-care in the Palestinian maternal and child eRegistry to generate Quality Improvement Dashboards (QID) for healthcare providers and Targeted Client Communication (TCC) via short message service (SMS) to clients. The aim is to assess the effectiveness of the automated communication strategies from the eRegistry on improving attendance and quality of care for pregnant women. Methods This four-arm cluster randomized controlled trial will be conducted in the West Bank and the Gaza Strip, Palestine, and includes 138 clusters (primary healthcare clinics) enrolling from 45 to 3000 pregnancies per year. The intervention tools are the QID and the TCC via SMS, automated from the eRegistry built on the District Health Information Software 2 (DHIS2) Tracker. The primary outcomes are appropriate screening and management of anemia, hypertension, and diabetes during pregnancy and timely attendance to antenatal care. Primary analysis, at the individual level taking the design effect of the clustering into account, will be done as intention-to-treat. Discussion This trial, embedded in the implementation of the eRegistry in Palestine, will inform the use of digital health interventions as a health systems strengthening approach. Trial registration ISRCTN Registry, ISRCTN10520687 . Registered on 18 October 2018

Electronic Health Records (EHRs) are aggregated, combined and analyzed for suitable treatment planning and safe therapeutic procedures of patients. Integrated EHRs facilitate the examination, diagnosis and treatment of diseases. However, the existing EHRs models are centralized. There are several obstacles that limit the proliferation of centralized EHRs, such as data size, privacy and data ownership consideration. In this paper, we propose a novel methodology and algorithm to handle the mining of distributed medical data sources at different sites (hospitals and clinics) using Association Rules. These medical data resources cannot be moved to other network sites. Therefore, the desired global computation must be decomposed into local computations to match the distribution of data across the network. The capability to decompose computations must be general enough to handle different distributions of data and different participating nodes in each instance of the global computation. In the proposed methodology, each distributed data source is represented by an agent. The global association rule computation is then performed by the agent either exchanging some minimal summaries with other agents or travelling to all the sites and performing local tasks that can be done at each local site. The objective is to perform global tasks with a minimum of communication or travel by participating agents across the network, this will preserve the privacy and the security of the local data. The proposed association rule mining methodology will be used for heart disease prediction using real heart disease data. These real data exist at different clinics and cannot be moved to a central site. The proposed model protects the patient data privacy and achieves the same results as if the data are moved and joined at a central site. We also validate the extracted association rules from all the data providers using an independent test datasets.