Long COVID comprises persistent symptoms which extend beyond four weeks post-SARS-CoV-2 infection. The potential association between long COVID and the endorsement of COVID-19 conspiracy theories has not been explored, particularly in Arab countries where high endorsement of these theories has been reported. This study aimed to explore the association between endorsing COVID-19 conspiracy theories and the prevalence of self-reported long COVID symptoms among adults in Jordan and Kuwait in addition to other Arab countries. The study employed a cross-sectional design using an electronic self-administered survey in Arabic language. Recruitment utilized snowball sampling via social media and the survey was distributed in July 2024. The survey instrument included sections on demographic information, the history of COVID-19 infection, and vaccination status. Long COVID manifestations were assessed using a score reflecting the frequency and intensity of ten recognized long COVID symptoms with subsequent categorization into three categories: low, middle, and high. The beliefs in COVID-19 conspiracy theories were measured via a 5-point Likert scale across five items. The final study sample comprised 756 respondents, the majority of whom self-reported a history of confirmed COVID-19 diagnosis at least once (n = 493, 65.2%). The results indicated a neutral average attitude towards COVID-19 conspiracy theories (mean score = 15.18±4.64 out of 30.00). Participants with high conspiracy theories scores were significantly more likely to report high (aOR = 6.85, 95% CI: 2.90–16.13, p < 0.001) and middle long COVID symptoms (aOR = 2.82, 95% CI: 1.32–6.06, p = 0.008) compared to those with lower scores. Additional predictors of higher long COVID reporting included female sex and lower self-reported household income. Frequent COVID-19 infections and hospitalizations were also associated with higher long COVID symptom reporting. The study results revealed a significant correlation between the endorsement of COVID-19 conspiracy theories and the higher frequency and magnitude of long COVID symptom reporting. The findings also highlighted the influence of sociodemographic factors and COVID-19 infection history on long COVID reporting, which suggests that public health strategies should address these factors to mitigate long COVID challenges effectively.

The severe climate changes due to global warming pushed the world to strive to reduce carbon emissions. This study aims to minimize the carbon emissions for a proposed smart energy hub. This paper prioritizes the minimization of carbon emissions, taking into consideration the minimization of operation running costs, and the maximization of profit. In this paper two optimization scenarios were studied, to compare the results. In the first scenario, the minimization of carbon emissions was achieved, in the second scenario, the minimization of running costs and maximization of profit from the hub assets were studied. The proposed model was designed in MATLAB. Then the results were verified by CPLEX and validated by RTDS. The multi-objective model was presented to obtain the optimal operation. The mitigation of data uncertainty was achieved by applying the Kalman filter. In this work, a novel method was proposed for the estimation of the quarter-hour resolution data from the hourly one via the Kalman filter rather than applying the classic polynomial interpolation methods.

Cybercrime Threat Intelligence (CTI) allows us to change our actions from reactive to proactive in the fight against threat actors, and to make more informed, data-driven security decisions. Thus this study proposes the practical implementation of CTI in the Arab world. This study focuses on strengthening CTI by integrating Indicators of Compromise (IoCs) and collecting realistic security alerts from honeypot systems and open source intelligence. The collected data is stored in the Malware Information Sharing Platform (MISP), an open source platform that allows users to create and share IoCs with other organizations while staying informed about new threats. It features an intuitive interface for data analysis and threat identification, facilitating sharing, storage, and correlation of IoCs. Therefore, we leveraged MISP to generate IoCs based on the collected data and analyzed the results to identify potential cyber threats. The implemented platform aims to provide organizations with actionable information to prevent, detect and respond to cybercrime. This study presents a practical approach to strengthening CTI in the Arab world and provides an opportunity to strengthen the region’s security posture.

Agriculture is a vital component of Egypt's economy; therefore, using Digital Elevation Models (DEMs) in agricultural planning in Egypt has significant benefits regarding water management, site appropriateness assessment, flood risk mitigation, and infrastructure construction. It is also essential for planners to make more informed decisions, optimize resource allocation, and support sustainable farming practices. This research paper investigates the accuracy of obtaining DEM data from four free global models (STRM30, ALOS30, COP30, and TanDEM-X90). The global DEM data has been compared to an actual GNSS-RTK DEM data surveyed onsite for two agricultural block areas in Aswan, the southern Government of Egypt. The two blocks are a part of a national project. For Block I and II, the RMSE of the Model STRM30 was 2.92 m and 3.59 m, respectively, indicating a poorer solution. Regarding accuracy, the ALOS30 model ranks third, reporting an RMSE of 2.58 m for block II and 3.30 m for block I. COP30 has an RMSE value of 1.06 m for blocks I and II and.91 m overall. TanDEM-X90 is the most accurate model in this investigation; block I provided an RMSE of 0.90 m with an SD of 0.58 m (SD95% = 0.38 m). After removing the anomalies, the model's stated RMSE for block II was 0.34 m, with an SD value of 0.62 m and 1.03 m. According to the classification using machine learning algorithms, with an accuracy of 84.7% for block I and 85% for block II, TanDEM-X90 is the best solution.

The mechanism of ciprofloxacin action involves interference with transcription and replication of bacterial DNA, which results in elevated oxidative stress, and bacterial cell death. Vorinostat was shown to induce oxidative DNA damage. In the current work, the possibility for interactive effect of vorinotat on ciprofloxacin-induced cytotoxicity against a number of reference bacteria was investigated. Standard bacterial strains were Escherichia coli ATCC 35218, Staphylococcus aureus ATCC29213, Pseudomonas aeruginosa ATCC 9027, Staphylococcus epidermidis ATCC 12228, Acinetobacter baumannii ATCC 17978, Proteus mirabilis ATCC 12459, Klebsiella pneumoniae ATCC 13883, methicillin-resistant Staphylococcus aureus (MRSA) (ATCC 43300), and Streptococcus pneumoniae (ATCC 25923). The antibacterial activity of ciprofloxacin with or without pretreatment of bacterial cells by vorinostat was examined using disc diffusion procedure and determination of the minimum inhibitory concentration (MIC) and zones of inhibition of bacterial growth. All tested bacterial strains showed sensitivity to ciprofloxacin. When pretreated with vorinostat, significantly larger zones of inhibition and smaller MIC values were observed in all bacterial strains compared ciprofloxacin alone. As a conclusion, current results showed the possible agonistic properties for vorinostat when it is used together with ciprofloxacin. Future research will be focus on molecular mechanisms possible for such interactive effect.

Survivability is a critical concern in WSNs, heavily influenced by energy efficiency. Addressing severe energy constraints in WSNs requires solutions that meet application goals while prolonging network life. This paper presents an energy optimization approach (EOAMRCL) for WSNs, integrating the Grey Wolf Optimization (GWO) for enhanced performance. EOAMRCL aims to enhance energy efficiency by selecting the optimal duty-cycle schedule, transmission power, and routing paths. The proposed approach employs a centralized strategy using a hierarchical network architecture. During the cluster formation phase, an objective function, augmented with GWO, determines the ideal cluster heads (CHs). The routing protocol then selects routes with minimal energy consumption for data transmission to CHs, using transmission power as a metric. In the transmission phase, the MAC layer forms a duty-cycle schedule based on cross-layer routing information, enabling nodes to switch between active and sleep modes according to their network allocation vectors (NAV). This process is further optimized by an enhanced CSMA/CA mechanism, which incorporates sleep/activate modes and pairing nodes to alternate between active and sleep states. This integration reduces collisions, improves channel assessment accuracy, and lowers energy consumption, thereby enhancing overall network performance. EOAMRCL was evaluated in a MATLAB environment, demonstrating superior performance compared to EEUC, DWEHC, and CGA-GWO protocols, particularly in terms of network lifetime and energy consumption. This highlights the effectiveness of integrating GWO and the updated CSMA/CA mechanism in achieving optimal energy efficiency and network performance.

The field of construction materials is pivotal in developing sustainable and resilient infrastructure. This demands continuous research to understand the properties and behaviors of these materials under diverse conditions. Although advancements in material science and numerical modeling have been significant, experimental testing remains indispensable for a thorough comprehension of material characteristics, particularly under extreme stresses and environmental factors. This need has forced the development of a wide array of testing techniques, each designed to evaluate specific engineering properties, thus creating a complex and varied landscape of experimental methodologies. This study provides a comprehensive overview of both conventional and innovative experimental testing techniques used to characterize construction materials. It explores the related methodologies and identifies potential gaps in their application within the industry. The spectrum of testing covered includes mechanical, chemical, thermal, microstructural, durability, physical, rheological properties, and non-destructive testing methods. Mechanical tests assess strength, hardness, and fatigue, whereas chemical analyses utilize techniques such as spectroscopy and chromatography. Thermal properties are examined using thermogravimetric analysis, and microstructural characteristics are explored through advanced imaging techniques. Durability testing focuses on materials’ resistance to environmental challenges, while physical properties tests evaluate aspects like porosity and water absorption. Rheological and non-destructive tests further examine materials’ behavior and integrity without causing damage. By discussing these methodologies, the study sheds light on various approaches to material evaluation and aims to enhance the selection, application, and development of testing standards. This overview seeks to inform and inspire future research and innovation in the science of construction materials, contributing to the development of more resilient and sustainable construction practices.

Herein, we examined the effects of weather parameters and individual clinicodemographic risk factors on hemorrhagic stroke (HS) incidence, severity on admission, and disability at discharge in a harsh desert climate. In a retrospective design we studied patients admitted to a stroke unit in Arab Emirates in 2016-2019. With a distributed lag nonlinear model we explored immediate and delayed effects of weather on stroke incidence. Supervised machine learning was used to build models predictive of scores in NIHSS and mRS scales. We assessed model performance by calculating ROC AUC, F1 scores, specificity, and sensitivity. HS risk increased after a significant change in any weather parameter. The risk was reduced below baseline after 1-week adjustment to environmental changes. Climate input from the previous 3 days yielded reliable classification models. Humidex was a better predictor of severity than air temperature, whereas body mass index, age, and time of day at stroke onset were the strongest clinical predictors. Weather parameters before admission were stronger predictors of disease severity than individual clinical factors. We addressed limitations of previous studies by analyzing a full set of climate parameters: ambient temperature, relative humidity, humidex, atmospheric pressure, and wind speed. Predictive models may help to optimize patient management and develop preventative strategies.

Urban rivers and waterfronts play a vital role in the ecological, social, and economic fabric of cities, providing not only aesthetic value but also serving as important ecosystems that contribute to the overall well-being of urban environments. However, many urban rivers, including the Beirut River in Lebanon, face challenges such as pollution, neglect, and the loss of recreational and ecological value due to urbanization and industrialization. According to the Lebanese MOE (Ministry of Environment), almost 70% of Lebanese rivers are polluted due to untreated waste management systems and which leads to undrinkable water and possible flooding disasters if not treated. This study addresses the problem of abandoned and degraded spaces along the Beirut River riverside through the application of urban acupuncture, a strategic approach that targets specific points in the urban environment to stimulate positive change and regeneration. The aim of the study is to assess the effectiveness of implementing small-scale ‘sensitive urban points’ known as urban acupuncture as the method for regenerating the Beirut River riverside, with the hypothesis that targeted interventions through Blue Urban Acupuncture or Aqua-puncture- can lead to significant improvements in the ecological, social, and economic aspects of the area that re-connect the people of Beirut with its river. The methodology involves a multidisciplinary approach that integrates urban design, and community engagement, and analysing similar examples of different approaches through creating a comparative table. Data collection includes environmental assessments of water quality, biodiversity, and ecosystem health, as well as social surveys to understand community needs and perceptions. By applying urban acupuncture principles to the Beirut River riverside, this study seeks to demonstrate how strategic interventions can lead to the regeneration of abandoned spaces, improve the overall quality of the urban environment, and create sustainable and inclusive riverside landscapes that benefit both the environment and the community.

Digital recruitment systems have revolutionized the hiring paradigm, imparting exceptional efficiencies and extending the reach for both employers and job seekers. This investigation scrutinizes the efficacy of classical machine learning methodologies alongside advanced large language models (LLMs) in aligning resumes with job categories. Traditional matching techniques, such as Logistic Regression, Decision Trees, Naïve Bayes, and Support Vector Machines, are constrained by the necessity of manual feature extraction, limited feature representation, and performance degradation, particularly as dataset size escalates, rendering them less suitable for large-scale applications. Conversely, LLMs like GPT-4, GPT-3, and LLAMA, adeptly process unstructured textual content, capturing nuanced language and context with greater precision. We evaluate these methodologies utilizing two datasets comprising resumes and job descriptions to ascertain accuracy, efficiency, and scalability. Our results reveal that while conventional models excel with structured data, LLMs significantly enhance the interpretation and matching of intricate textual information. This study highlights the transformative potential of LLMs in recruitment, offering insights into their application and future research avenues.

Apart from their obvious educational mission, public schools provide health, psychological, emotional, and social development grounding for students. Thus, the educational system is special in that it combines multiple integrated responsibilities and duties beyond the scope of any other social welfare program. As such, social workers are a very important constituent of this system, and they ostensibly serve to attend to the wellbeing of students while ensuring educational system performance. In light of this extremely steep set of demands, this work assesses and compares social workers’ authentic roles in UAE schools during and after the COVID-19 pandemic so that we may contribute to the improvement of educational systems worldwide. The results are nuanced and will better illuminate the important capabilities of social workers in the continually changing educational system, as well as the challenges they face and ameliorate during emergency scenarios.

In this paper, several classes of rough Marcinkiewicz integral operators along surfaces of revolution on product spaces are investigated. We prove the Lp boundedness of these operators when their kernels functions belong to a class of functions related to a class of functions introduced by Grafakos-Stefanov. The results in this paper extend and improve several known results on Marcinkiewicz integrals.

In this study, the olive pomace was considered because of its importance in the environment. So, this study carried out to estimate the total nitrogen content and the fatty acids profile of olive pomace. The olive pomace samples were collected from Irbid, Jarash, Ajloun and Mafraq during the harvesting season 2014 to study the biochemical characteristics of fatty acid composition and the total nitrogen (TN) content. The total nitrogen content was determined by standard Kjeldahl method and the fatty acid profile was detected by gas chromatography (GC). The results show that the total nitrogen content ranged from (0.39 ± 0.0) to (0.62 ± 0.02) with statistically significant difference suggesting that the composition of matrices and their percentage may be responsible for composition of amendments. The calculated total protein percentage ranged between (2.43 ± 0.00) to (3.87 ± 0.17). Also, 13 different fatty acids were quantitatively profiled and quantitated. Oleic acid (C 18:1) was found to be the highest percentage of all other fatty acids and ranged between (59.03%) and (63.81%), moreover the C 18:1/C 18:2 (oil quality) was calculated and C.V% showed variation meaning that nutritional implication could affect the oxidative stability of oils. In conclusion, OP by-product could give a sustainable and alternative-cheap source for fertilizers, pharmaceutical industries, cosmetics and other industries.

This comprehensive review digs into the complex landscape of the Metaverse, focusing on user perceptions and the critical roles of usability, social influence, and interoperability. The paper integrates various scholarly insights, underscoring the Metaverse's evolving significance in the digital realm and its implications across diverse sectors. Central to the findings is the importance of usability. The influence of social factors is also prominent, shaping user behavior and decision-making within these virtual spaces. Interoperability becomes a big problem, showing how important it is to have standard protocols and technologies so that experiences on different Metaverse platforms are smooth and seamless. The review further reveals insights into user experience and accessibility, emphasizing the need for inclusive, ergonomic, and user-friendly design to enhance engagement and reduce barriers. Moreover, the paper discusses the ethical and societal implications of the Metaverse, including issues like digital harassment, aggressive marketing, and privacy concerns, which call for responsible development and robust regulatory frameworks. Additionally, the review identifies gaps in current research, particularly in user experience in healthcare applications, the impact of the Metaverse on educational outcomes, and the need for more empirical studies on the long-term effects of Metaverse interactions on user behavior and psychology. This synthesis offers a detailed overview of current user perceptions and challenges within the Metaverse and sets the stage for future research directions, aiming to foster a secure, inclusive, and interoperable Metaverse environment that aligns with ethical standards and societal needs.

Enzymatic degradation of organic pollutants is a new and promising remediation approach. Peroxidases are one of the most commonly used classes of enzymes to degrade organic pollutants. However, it is generally assumed that all peroxidases behave similarly and produce similar degradation products. In this study, we conducted detailed studies of the degradation of a model aromatic pollutant, Sulforhodamine B dye (SRB dye), using two peroxidases—soybean peroxidase (SBP) and chloroperoxidase (CPO). Our results show that these two related enzymes had different optimum conditions (pH, temperature, H₂O₂ concentration...etc.) for efficiently degrading SRB dye. High-performance liquid chromatography and LC-mass spectrometry analyses confirmed that both SBP and CPO transformed the SRB dye into low molecular weight intermediates. While most of the intermediates produced by the two enzymes were the same, the CPO treatment produced at least one different intermediate. Furthermore, toxicological evaluation using lettuce (Lactuca sativa) seeds demonstrated that the SBP-based treatment was able to eliminate the phytotoxicity of SRB dye, but the CPO-based treatment did not. Our results show, for the first time, that while both of these related enzymes can be used to efficiently degrade organic pollutants, they have different optimum reaction conditions and may not be equally efficient in detoxification of organic pollutants.

Emerging pollutants (EPs) encompass natural or synthetic substances in the environment that pose potential risks but have only recently been recognized or monitored. EPs consist of various categories including pesticides, pharmaceuticals, hormones, mycotoxins, and endocrine disrupting chemicals (EDCs). Through several pathways, EPs can access food, potentially leading to health impacts when their safe concentrations are exceeded. Milk, being a highly nutritious and a heavily consumed food product by many consumers of different ages, is a crucial food matrix where EPs should be regularly monitored. In literature, large number of studies was dedicated for the determination of different EPs in dairy milk, employing different analytical techniques. Chromatographic based techniques were the most prevalent means for analysis of EPs in milk, which demonstrated significant efficiency, sensitivity and accuracy for this specific purpose. Prior to chromatographic analysis, extraction of EPs from a complex matrix like milk, is essential. This review comprehensively covers relevant research papers on extraction and subsequent detection and determination of EPs in milk by chromatographic methods from 2018 and until 2023.

Nano Silicon carbide reinforced aluminum (Al/nanoSiC) metal matrix composites are attractive because of their superior properties such as high strength and stiffness, Application of aluminum in technological and structural application is growing steadily. The major limitation for metal matrix nano composites, however, is their propensity to brittle fracture. The new technologies and new materials are two basic aims for companies. In this research, the effect of addition Al/SiC nano particles on microstructure and mechanical properties of pure aluminum has been investigated. Pure aluminum powder and various fractions of SiC particles with an average diameter of 50 nm were milled by a high-energy planetary ball mill to produce nanocrystalline Al–SiC nanocomposite powders. Pressing and sintering applied to consolidate powders to tablet shape. Then the samples were rolled to cylindrical shape. The nano SiC Percentage were 0%, 2.5%, 5%, 7.5%, 10% , 12,5% and 15%. Mechanical tests such as tensile, hardness, fracture toughness and young’s modules measurement carried out to study the mechanical behavior of each alloy. Scanning electron microscopy was used to study the morphology and microstructure of nanocomposite powders and bulk samples. The role of wt% fraction of SiC nanoparticles was investigated. The results shows that the addition of SiC nano particles has significant influence on the microstructure and mechanical properties of composites and usually the optimum properties depends on wt% SiC.

Machine-learning methods used for classification are challenged by the class imbalance problem, where a certain class is underrepresented. Over/under-sampling the majority/minority class observations or model selection for ensemble methods alone might not be effective if the class imbalance ratio is very high. To address this concern, a novel method is presented for generating synthetic data for minority class observations in conjunction with an optimal tree ensemble classifier (OTEC). This novel synthetic method first generates minority class instances to balance the training data. Then it applies OTEC, where models are selected based on their performance using out-of-bag observations and training subsamples. A total of 20 benchmark problems on binary classification with moderate to extreme class imbalance are used to assess the efficacy of the proposed method against other well-known methods, including optimal tree ensemble, smote random forest, under-sampling random forest, oversampling random forest, k-nearest-neighbor, support vector machine, tree, and artificial neural network, using classification error rate, sensitivity, specificity, precision, recall and F1-score as performance metrics to assess the efficacy of the proposed method. The analyses presented in this study revealed that the proposed method based on data balancing and model selection yielded better results than other methods.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by the loss of dopaminergic neurons and the buildup of misfolded alpha-synuclein proteins. While its exact cause remains unknown, several factors may influence its development. This review examines how factors like chronic constipation, head injuries, cholesterol and uric acid levels, pesticide exposure, smoking, NSAIDs, and caffeine intake may affect PD risk. Chronic constipation appears to be linked to a higher risk of PD, potentially serving as an early warning sign. Head injuries, especially mild-to-moderate ones, may also play a role in increasing PD risk. Surprisingly, higher levels of cholesterol seem to protect against PD, while lower levels of uric acid might increase the risk in the presence of some differences according to gender type. Exposure to certain pesticides is associated with a higher PD risk. NSAIDs, on the other hand, may or may not have a protective effect, with conflicting evidence. Interestingly, caffeine and tobacco smoking appear to lower the PD risk. Further studies are needed to fully understand the complex interplay between these factors and PD. It's also important to remember that these are just general trends, and individual risk factors will vary depending on a person's unique genetic makeup, medical history, and overall health.

This paper addresses the conceptual exploration of various issues that form an integral part of the ethical dimensions surrounding the use of artificial intelligence (AI) in the field of marketing. We critically review some of the main ethical challenges AI poses to humanity: privacy, data security, bias, transparency, and accountability. Therefore, we will discuss the delicate balance between exploiting the transformation potential of AI for personally designed marketing strategies and ethical imperatives to safeguard the rights of consumers to retain trust. Then, the present regulatory landscape responding to these ethical challenges will be assessed by building on effective regulation, like the GDPR, existing proposed legislative frameworks, and industry guidelines. To underscore the role of an ongoing dialogue between marketers, technologists, ethicists, and regulators for developing a responsible AI ecosystem in marketing. Further, strategic recommendations for implementing company-based ethical AI marketing practices. The further strong guidelines provide enhancement transparency to consumers and investment in research to remove biases from algorithms. It also underscores principal scopes of further research and development, focusing on the need for new-age solutions to guide the ethical quagmires that AI-led marketing throws up. We suggest that integration should be done proactively and collaboratively. Thus, if attention is paid more to ethics and multidisciplinary dialogue, only such hyperbolic promises can be realized by AI-driven marketing. There are such promises through which AI-driven marketing will meet business goals and be huge at societies' values.

This research aims to explore the complex interplay between supply chain resilience (SCR), digital supply chain (DSC), and sustainability, focusing on the moderating influence of supply chain dynamism. The goal is to understand how these elements interact within the framework of contemporary supply chain management and how they collectively contribute to enhancing sustainability outcomes. The sample size is 300 CEOs and managers. The study approach integrates quantitative research methods. Structural equation modeling (SEM) is utilized to quantitatively analyze the direct and indirect effects of SCR and DSC on sustainability. The numerous surveys we conduct among supply chain ecosystem stakeholders provide a rich picture of practical implications and contextual nuances. In sum, our early findings generally support a positive relationship between SCR and sustainability in and of itself decrying the need for more resilient supply networks for sustainability. We further find the beneficial impact of digital technologies in promoting sustainability via enhancing environmental control and controlling for efficiency in supply chains. We also offer evidence to show that supply chain dynamism compounds the positive logic between SCR and DSC and sustainability. As a final word, it must be noted that our work speaks to the burgeoning Supply Chain Dynamism as moderator literature by examining the direct and contingent effects of SCR and DSC on not only performance but sustainability. By shedding light on the moderating role of dynamism, the study provides fresh insights into the multifaceted nature of supply chain management and sustainability practices. The study's findings enhance theoretical understanding by elucidating the synergistic effects of SCR, DSC, and sustainability in dynamic supply chain settings. It augments existing theoretical frameworks by integrating concepts of resilience, digitalization, and sustainability into a comprehensive model. Practical and economical, the research offers actionable guidance for organizations aiming to improve sustainability performance through resilient and digitally advanced supply chains. By acknowledging the role of supply chain dynamism, managers can tailor strategies to manage disruptions effectively and leverage digital innovations. Economically, adopting sustainable practices can result in cost savings and competitive advantages. The research emphasizes the importance of aligning supply chain strategies with sustainability goals to drive long-term value and societal impact.

Food safety in dairy shops has gained increasing attention. Consequently, this study aims to evaluate dairy handlers' knowledge of food safety practices, assess compliance with food safety codes regarding facility maintenance and personal hygiene, and understand retail dairy shops' capacity to implement food safety standards. This research involved surveys and interviews with 110 dairy retail workers to gauge their grasp of food safety principles, their recognition of its importance, and the obstacles they encounter in implementing proper food safety measures. Among the participants, 93% were males under 35 years old, with experience ranging from 1 to 8 years. The study revealed that while over 83% of participants were familiar with standard procedures ensuring dairy product safety, only 37% understood “HACCP” in relation to food safety. Additionally, 42% believed that freezing food at -18°C eliminates food bacteria, and 56% thought food contamination could be identified by taste, indicating misconceptions among respondents. Results showed that 90% of survey participants had a strong awareness of food safety, with 98% emphasizing the importance of regular inspection of production areas for cleanliness to ensure a safe dairy production environment. However, less than 45% had received formal training on dairy-specific food safety practices, and only 53.6% had a documented system for correctly labeling and providing production dates for dairy products. These findings have significant implications for public health and food safety policies in Jordan. Furthermore, the study provides valuable insights to enhance food safety practices among dairy retail vendors.

This study aimed to introduce a novel machine learning (ML) model designed to predict the need of interventions during endoscopy in patients with upper gastrointestinal bleeding (UGIB). The risk stratification tools in current use, such as the Glasgow Blatchford Score (GBS) and pre-endoscopic Rockall score, have limitations in accurately predicting the need for endoscopic interventions. All patients diagnosed with UGIB from January 2013 to October 2023 who underwent endoscopy were included in the study. Variables extracted included demographics, social history ,clinical history, clinical presentation and symptoms, drug history, management prior to endoscopy, findings during endoscopy, laboratory variables and vitals, and post-endoscopic results. Three machine learning models including Random Forest Classifier (RFC), Gradient Boosting Classifier (GBC), and AdaBoost Classifier were used to evaluate the need for intervention during endoscopy in our study. A total of 1372 patients were included from three major hospitals in Jordan, of whom 242 underwent endoscopic intervention. The GBC outperformed all other models and pre-endoscopic scores in predicting the need for endoscopic intervention with an area under the curve of 0.861. Findings during endoscopy, platelet count, pulse rate and systolic blood pressure during admission were the most contributing features in predicting the need for the need of endoscopic intervention. This study highlights the potential of machine learning models in enhancing decision making for UGIB management.

In this paper, two double Jordan-type inequalities are introduced based on the papers [1]-[5]. These inequalities generalize the inequalities obtained in [1]-[5]. As a result, some new upper and lower bounds of the sinc function are obtained. This extension of Jordan’s inequality is enabled by considering the corresponding inequalities through the concept of stratified families of functions elaborated in [6]. Based on this approach, some optimal approximations of the sinc function are derived by determining corresponding minimax approximants, also described in the paper [6].

The rise in precocious puberty cases can be attributed to a combination of genetic and environmental factors. Genetic factors play a significant role, with studies identifying genetic abnormalities in genes such as KISS1, KISS1R, MKRN3, DLK1, GABRA1, LIN28B, NPYR, TAC3, and TACR3, which are associated with central precocious puberty (CPP). Epigenetic factors like DNA methylation and histone modifications may mediate the relationship between genetic and environmental influences on CPP development. Environmental factors such as exposure to secondhand smoke, cesarean section, and BMI have also been linked to precocious puberty, particularly in girls, highlighting the multifactorial nature of this phenomenon. Understanding the interplay between these genetic and environmental factors is crucial in addressing the increasing prevalence of precocious puberty in children. The published literature in the past five years was systematically reviewed and summarized highlighting the interplay of genetic and environmental factors for the rise in the precocious puberty.

Background: Recent studies have found forward head posture (FHP) to be associated with altered physiology, however, there is a lack of research into whether FHP is associated with altered gait parameters when cognitively challenged. The current study was undertaken to investigate the changes in gait parameters in asymptomatic individuals with FHP when a cognitive dual task is introduced during walking. Methods: Ninety asymptomatic participants were recruited, 45 having FHP defined as having a craniovertebral angle (CVA) < 50, and 45 sex and age-matched controls having normal head posture (NHP) defined as CVA > 55. All participants walked along a 10 meter platform under a control condition (no cognitive load) with 3 consecutive trials while an optical motion-capture system consisting of 8 infrared cameras was used to assess gait kinematics. Secondly, participants were assessed under a dual task cognitive load condition (3 trials while performing simple addition, counting backwards, and answering yes or no questions) to identify the impact on gait kinematics compared to the control condition. Results: Under the single task condition, there were no significant differences for any gait parameter, however, under the dual task condition, 12/13 gait parameters were significantly altered for the FHP group compared to the NHP group (p < .01). A calculation of dual task cost (DTC) percentage showed significant increases in all gait parameters in participants with FHP (p < .02). Correlations between the CVA and gait parameters were not significant for the single task condition, but all gait parameters were correlated to CVA for the dual task condition (p < .01). The correlation between CVA and DTC for all gait variables were also significant (p < .04). Conclusions: This study demonstrates that FHP significantly increases the cognitive cost during walking, highlighting the importance of proper postural alignment for maintaining cognitive function under a dual task condition. Addressing FHP through targeted interventions could improve both physical and cognitive health, enhancing overall well-being and daily functioning.

Background: Studies have tried to identify predictors of functional markers of keratoconus progression, whereas structural outcomes of collagen cross-linking have not been properly investigated. Objective: find and set up a combination of diagnostic modalities and measurements to reliably reflect CXL efficiency. Material and methods: We retrospectively reviewed the medical histories of 107 KC patients (131 eyes) who underwent CXL in a medical center from January 2018 to December 2022. The dataset included preoperative examinations and follow-up results, which provided a total of 796 observations. The cases of other corneal diseases, repeated CXL, pregnancy, and observations without follow-up examinations were excluded. Results: The study findings revealed a significant drop in the central and corneal thickness during 14.01±9.98 months of observations. Linear and polynomial equations suggested different trends in pachymetry change after CXL. The linear model showed corneal thinning, and according to the polynomials, pachymetry findings return to baseline values two years after CXL. Conclusion: The most reliable prognosis of postoperative corneal thickness is achieved with the models trained on keratometry readings and topography indices. BAD indices are also reliable predictors of the corneal thickness after CXL. A combination of the aforementioned structural parameters and their derivatives can reliably predict CXL efficiency.

Presently, Jordan confronts a double substantial challenge of enhancing energy security and mitigating greenhouse gas emissions. One of the most encouraging avenues to attain the objectives of sustainable development, energy security, and environmental conservation is to enhance the integration of renewable energy into the generation of electricity. In pursuit of this goal, the Jordanian government intends to expand investments in the green energy sector, with solar and wind energy poised to play a key role in satisfying energy demands and cultivating an environmental sustainability. This paper aims to examine the distinctive dynamics, challenges, obstacles, and potential solutions corresponding to the establishment of community solar and wind farms in Jordan suburban areas. It aims to highlight the opportunities and barriers influencing the track of sustainable energy adoption in the country. Through a comprehensive analysis of the Jordanian context, the goal is to extract insights that can guide policies and practices. Additionally, the findings may serve as a valuable benchmark for other regions confronting similar challenges on their pursuit for a sustainable energy future.

Sleep quality is known to affect automatic and executive brain functions such as gait control and cognitive processing. This study aimed to assess the effect of dual tasks on gait spatiotemporal parameters among young adults with good and poor sleep quality in the United Arab Emirates. In total, 65 young adults with a mean age of 21.1±2.5 were assessed for gait analysis during single-task and dual-task conditions. The participants’ sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), and gait was assessed using the BTS Gaitlab System. The participants were asked to walk at natural speed as a single-task condition, followed by walking while performing a cognitive task as a dual-task condition. The parameters assessed included the gait velocity (m/s), cadence (steps/min), step width (m), and stride length (m). The DTC on each gait parameter was calculated. The Mann–Whitney U test was used to compare the differences in the DTC on gait variables between the good and poor sleep quality groups, and the Spearman correlation test was used to assess the correlation between total PSQI scores and the DTC. At a significance level of p<0.05, a significant difference in cadence between the two sleep quality groups was observed, in addition to a positive correlation between sleep quality and the DTC effect on gait mean velocity, cadence, and stride length. Our findings also revealed a greater DTC on participants with poorer sleep quality. These findings contribute to our understanding of the significance of sleep quality in gait performance while multitasking in younger populations.

This study introduces a novel nanocomposite coating composed of PANI/CeO2 nanocomposite films, aimed at addressing corrosion protection needs. Analysis through FTIR spectra and XRD patterns confirms the successful formation of the nanocomposite films. Notably, the PANI/CeO2 nanocomposite films exhibit a hydrophilic nature. The bandgap energy of the PANI composite film measures at 3.74 eV, while the introduction of CeO2 NPs into the PANI matrix reduces the bandgap energy to 3.67 eV. Furthermore, the electrical conductivity of the PANI composite film is observed to be 0.40 S.cm-1, with the incorporation of CeO2 NPs leading to an increase in electrical conductivity to 1.07 S.cm-1. To evaluate its efficacy, electrochemical measurements were conducted to assess the corrosion protection performance. Results indicate a high protection efficiency of 92.25% for the PANI/CeO2 nanocomposite film.

The recently approved maternal vaccination against respiratory syncytial virus (RSV) can reduce its burden among infants. Vaccine hesitancy/resistance can undermine the beneficial impact of RSV vaccination. The aim of this study was to assess the willingness of pregnant women in Jordan to receive RSV vaccination and its associated determinants. Face-to-face interviews were conducted in obstetrics/gynecology clinics in Jordan during January-February 2024, with convenience sampling. Attitude to RSV vaccination was assessed using the previously validated ABCDEF scale. A total of 404 pregnant women participated in the study with a mean age of 30 years. A majority of the participants showed willingness to receive RSV vaccination (n=313, 77.5%), with hesitancy among 25 participants (6.2%), and resistance among 66 participants (16.3%). Variables that were significantly associated with a higher RSV vaccine acceptance in multivariate analysis were: age <30 years (aOR: 2.45, p=0.010), undergraduates (aOR: 3.27, p=0.026), being a healthcare worker (aOR: 4.50, p=0.036), and the history of previous COVID-19/influenza vaccine uptake (aOR: 2.47, p=0.045). Two out of the six ABCDEF constructs were significantly associated with RSV vaccine acceptance, namely the “Advice” construct (aOR: 10.38, p<0.001) and the “Fear” construct (aOR: 21.49, p<0.001). This study highlighted the multifaceted nature of attitude towards maternal RSV vaccination among pregnant women. The study showed the role of demographic variables, prior vaccination experience, trust in credible health institutions and vaccine safety, and fear of RSV disease consequences in infants in shaping maternal attitude to RSV vaccination. Addressing these factors can help to effectively promote RSV vaccine uptake, subsequently helping to protect infants from the significant RSV disease burden.

Our paper deals with an advanced statistical tool for the volatility prediction problem in financial (crypto) markets. Firstly, we consider the conventional GARCH involved volatility models. We next extend the corresponding GARCH based forecasting and calculate a specific probability associated with the predicted volatility levels. Since the probability evaluation is based on a stochastic model, we next develop an additional data-driven estimation of this probability. The proposed advanced statistical estimation uses real (historical) market data. The obtained theoretic results for the statistical probability of levels are also discussed in the framework of the integrated volatility concept. A possible application of the established probability estimation to the volatility clustering problem is also mentioned. Our paper includes a concrete practical implementation of the resulting (combined) volatility prediction tool and considers a novel module for trading and volatility estimation in crypto markets recently developed by 1ex Trading Board group in collaboration with the GoldenGate Venture. Moreover, we discuss shortly a possible using of the proposed model based and data-driven volatility prediction methodology in the financial risk management.

Deep cavity configurations are common in various industrial applications, including automotive windows, sunroofs, and many other applications in aerospace engineering. Flows over such a geometry can result in an Aero-Acoustic coupling between the cavity shear layer and the acoustic modes of the surrounding. This phenomenon can lead to significant noise and may cause damage to structures due to resonance caused by high-pressure fluctuations produced nearby the cavity. The aims when employing a passive control device is to disturb the cavity flow in order to reduce or eliminate the involved resonance. An experimental set up was developed to study the effectiveness of using either a cylinder or a profiled cylinder positioned upstream from the cavity. A decrease of as high as 30 dB was obtained in the Sound Pressure Levels (SPL). Additionally, Particle Image Velocimetry (PIV) technique was employed to get the kinematic fields of the flow past the cavity for both controlled and non-controlled configurations. A Snapshot Proper Orthogonal Decomposition (POD) was applied to better understand the cavity flow dynamics in both controlled and non-controlled cases. Furthermore, the interaction of the wake of the control mechanisms with the shear layer of the cavity and its consequence on the Aero-Acoustic coupling was investigated and new flow physics is revealed.

The accurate prediction of heat load profiles with a daily resolution is required for a broad range of applications such as potential studies, design, or predictive operation of heating systems. If the heat demand of a consumer is mainly caused by (production) processes independent of the ambient temperature, existing load profile prediction methods fail. To close this gap, this study develops two ex post machine learning models for the prediction of the heat demand with a daily resolution. The selected input features are commonly available to each consumer connected to public natural gas and electricity grids or operating an energy monitoring system: Ambient temperature, weekday, electricity consumption, and heat consumption of the last seven days directly before the predicted day. The study’s database covers electricity and natural gas consumption load profiles from 82 German consumers over a period of two years. Electricity and heat consumption correlate strongly with individual patterns for many consumers. Both, shallow and deep learning algorithms are evaluated. The highest accuracy is achieved by a Long Short Term Memory (LSTM) model with a median of R² of 0.94. The ex post model architecture makes the model suitable for automated anomaly detection in energy monitoring systems.

This paper is based on a talk given at the 14-th International Workshop on Differential Geometry and Its Applications, hosted by the Petroleum Gas University from Ploiesti, between July 9-th and July 11-th, 2019. After presenting some historical facts, we will consider some geometry problems related to unification approaches. Jordan algebras and Lie algebras are the main non-associative structures. Attempts to unify non-associative algebras and associative algebras led to UJLA structures. Another algebraic structure which unifies non-associative algebras and associative algebras is the Yang-Baxter equation. We will review topics relared to the Yang-Baxter equation and Yang-Baxter systems, with the goal to unify constructions from Differential Geometry.

Customs law and procedures are important part of the trade system in Jordan. They regulate the flow of goods across the borders. The purpose of this paper is to examine Jordan's import regime by analyzing customs law, rules of origin, free trade zones, and tariffs reform.

In Ethiopia, farmers have changed cropland to Eucalyptus globulus plantations for construction, fuelwood and economic benefits. However, it has adverse effects on soil properties. The investigation was, therefore, to evaluate the impact of Eucalyptus globulus plantations on soil properties in northwestern Ethiopia. About 30 soil samples were collected from two soil depths (0-20 and 20-40 cm) and three land uses (Eucalyptus globulus plantations, cropland and grazing land) with five replications. Soil properties were analyzed using a two-way analysis of variance (ANOVA). Based on the result, soil properties such as silt particles, moisture content (MC), organic matter (OM), total nitrogen (TN) and cation exchange capacity (CEC) were significantly higher under the soil of Eucalyptus globulus plantations than in cropland and grazing land. Whereas the lower contents of bulk density (BD), soil pH, available phosphorus (AP), electrical conductivity (EC) and exchangeable bases (Ca, Mg, K, and Na) were recorded in Eucalyptus globulus plantations. Besides, clay, BD, MC, pH, EC, CEC, percent base saturation (PBS) and basic cations increased with soil depth while decreasing sand, silt, TP, OM and AP. The basic cations ( Ca, Mg, K), PBS and AP decreased in the soil of the 25-year old Eucalyptus globulus plantation compared to cropland by 38%, 36%, 43 %, 45% and 47% and grazing land by 56%, 60%, 76 %, 60% and 56%, respectively. Therefore, appropriate and effective land use management principles should be implemented in the study area.

The leaves of Nicotiana glauca (Solanaceae) plant, are known for its major cause of health concern. This study investigated the antioxidant activity and polyphenols composition of aerial parts of N.glauca collected from its wild habitat in Jordan, using Methanol-Conventional (MC) and deep eutectic solvents (DESs) extraction methods in addition to nicotine content determination using UHPLC. The results have shown that the MC extract contains fewer total phenols and flavonoid content than the DES extract at ratio of 90% (0.1194 ±0.009 and 0.311± 0.020 mg/mL equivalent to gallic acid) and (0.01084±0.005 and 0.928 ± 0.09 mg/mL equivalent to rutin), respectively. Moreover, the study showed that the MC extract contains 635.07 ppm nicotine compared to the DES extraction method, which contains 1194.91 ppm. Both the MC and the DES extracts exhibited weak antioxidant activities with the highest was 33%inhibition equivalent to ascorbic acid was found for DES at (90%) ratio. The UHPLC-MS/MS analysis revealed the presence of variations in the detected compounds between the two extraction methods used. This study found that en-vironmentally friendly DES extraction of N. glauca produced higher phenol and flavonoid content than MC method, highlighting green chemistry methods' superior efficiency and environmental benefits for extracting valuable phytoconstituents.

This research explores and analyzes the challenges and opportunities due to globalization's impact on sustainable strategic management. The research uses a mixed-method design, combining primary and secondary data collection methods. Secondary data is sourced from various credible publications and analyzed through an extensive literature review. A case study approach is adopted, involving semi-structured interviews with six experienced managers from Tazweed Venture Capital in Jordan. The study employs a qualitative, descriptive, and analytical approach to develop a conceptual framework by exploring managers' experiences and perspectives on Globalization and its impact on Sustainable Strategic Management. The findings identify challenges of environmental degradation, economic inequality, transportation and logistics pressures, and compliance challenges for sustainability. While implementing sustainable practices incurs upfront costs, accessing renewable energy markets and financial support presents opportunities. Tazweed successfully implements sustainable strategic management, emphasizing stakeholder engagement and collaboration across departments. This research offers valuable insights and guidance for companies navigating globalization's impact on sustainability strategic management.

Objective: Regeneration of bone defects remains a challenge for maxillofacial and reparative surgeons. The purpose of this histological study was to assess the osteogenic potential of octacalcium phosphate (OCP) and bone matrix gelatin (BMG) alone and in combination in artificially created mandibular bone defects in rats. The quality of the newly formed bone was also evaluated. Methods: Thirty-six male Sprague Dawley rats (6-8 weeks old with 120-150 g weight) were randomly divided into four groups. Defects (3 mm in diameter and 2 mm in depth) were created in the mandible of rats and filled with 6 mg of OCP, BMG or a combination of both (1/4 ratio), respectively. Defects were left unfilled in the control group. To assess osteoinduction and bone regeneration and determine the quality of the newly formed bone, tissue specimens were harvested at seven, 14, and 21 days post-implantation. The specimens were processed, stained with hematoxylin and eosin (H&E) and histologically analyzed under light microscopy. Results: In the experimental groups, new bone formation was initiated at the margins of defects from seventh day after implantation. At the end of the study period, the amount of the newly formed bone increased and the bone was relatively mature. Osteoinduction and new bone formation were greater in OCP/BMG group. In the control group, slight amount of new bone had been formed at the defect margins (next to host bone) on day 21. Conclusion: Combination of OCP/BMG may serve as an optimal biomaterial for treatment of mandibular bone defects.

This study aims to explore the E-marketing orientations and relationship management constructs in Jordanian startup enterprises to examine their influence on brand visibility and loyalty in the context of the digital market . The sample consists of 161 managers in startup companies, and structural equation modeling is used to study the relationships between the constructs of e-marketing orientation, capabilities, E-relationship management, brand visibility, and loyalty. The results illustrate that the realization of e-marketing orientation is directly achieved by capabilities and visibility, thereby stressing the importance of a formulated digital market approach and that the realization of effective e-relationship management directly expression by e-marketing capabilities, demonstrating the significance of the digital market concept’s approach. The results further demonstrate that e-marketing capabilities and visibility serve as mediators between the realization of e-marketing orientations and loyalty, Two explanations may be drawn, one from the R resource-Based View theory, and another derived from R elationship M arketing T heory Thus, the study has theoretical implications in terms of R esource-Based V iew and R elationship M arketing T heory. The study offers essential managerial insights for practitioners into the entrepreneurship domain concerned with the necessity of e-marketing capabilities and E-RM attitudes at a customer-centered approach and the strategic application of digital channels to enhance visibility in the intense competition context. Therefore, the empirical results have contributions as essential insights for both stakeholders and account for practical, theoretical, and managerial perspectives in the entrepreneurship domain.

Hepatocellular carcinoma (HCC) is the third most common cause of cancer-related deaths. Classically, liver transplantation (LT) can be curable for HCC tumors within the Milan criteria. Bridging strategies to reduce the dropouts from LT waiting lists or/and to downstage patients who are beyond Milan criteria are widely utilized. We conducted a literature-based review to evaluate the role of systemic therapies as a bridging treatment to liver transplantation (LT) in HCC patients. Tyrosine Kinase Inhibitors (TKIs) can be used as a bridging systemic therapy to LT in patients with contraindication to locoregional liver-directed therapies. Immune Checkpoint Inhibitors (ICIs) treatment can be utilized either as a monotherapy or as a combination therapy with Bevacizumab or TKIs prior to LT. Acute rejection post liver transplantation is a concern in the context of ICIs treatment. Thus, a safe ICI washout period before LT and cautious post-LT immunosuppression strategies are required to reduce post-LT rejections and to optimize clinical outcomes. Nevertheless, prospective clinical trials are needed to establish definitive conclusions about the utility of systemic therapy as a bridging modality prior to LT in HCC patients.

Road congestion in Amman city increased yearly, due to the increase in private car ownership and traffic volumes. This study aims to (a) assess the social and economic impacts of the toll road in Amman, Jordan through a survey questionnaire using statistical software (SPSS), (b) identify the optimal price at selected road using micro-simulation (VISUM). Traffic, geometric and cost data of toll technique of two sections on the Airport Highway (From Ministry of Foreign Affairs to Madaba Interchange.; and From Madaba Interchange to Queen Alia International Airport (QAIA) interchange) were used for simulation purpose. The toll road (across 7 distinct scenarios at various price) were assessed for an optimal revenue. The survey questionnaire was made based on all scenarios including AM peak hour. The operation cost for toll road was determined based on greater Amman Municipality (GAM). The optimal scenario was measured based on the value ¬¬of revenue (JD), and type of payment. The results indicate that users found the most charging method to be based on traveled distance (54.02%) and the optimal value of the toll to be equal 0.25 JD (34.08%). In Addition, the total cost of Manual Toll Collection method (MTC) in 2025 is 126,935JD and the revenue is 1122.6 JD so this indicates to positive result. Eventually, the result of applying road pricing on the airport road in 2025 indicate to be effective and economically feasible only by using Manual Method.

Direct-acting antivirals (DAAs) revolutionized therapeutics of chronic hepatitis C. The emergence and transmission of HCV variants with resistance-associated substitutions (RASs) can undermine HCV treatment. This study aimed to assess the prevalence and temporal trends of RASs in HCV with a particular focus on the clinically-relevant RASs (cr-RASs). Near-complete HCV GenBank sequences archived in the Los Alamos HCV Database were analyzed. The study period was divided into two phases; before 2011 and 2011 onwards. Identification of RASs across three DAA classes; NS3, NS5A, and NS5B inhibitors was based on the 2020 EASL guidelines. The AASLD-IDSA recommendations were used to identify cr-RASs for three HCV genotypes/subtypes (1a, 1b, and 3) for four DAA regimens; ledipasvir/sofosbuvir; elbasvir/grazoprevir; sofosbuvir/velpatasvir; and glecaprevir/pibrentasvir. The final HCV dataset comprised 3443 sequences and the prevalences of RASs were 50.4%, 60.2%, and 25.3% in NS3, NS5A, and NS5B, respectively. In subtype 1a, resistance to ledipasvir/sofosbuvir was 32.8%, while resistance to elbasvir/grazoprevir was 33.0%. For genotype 3, resistance to sofosbuvir/velpatasvir and glecaprevir/pibrentasvir was 4.2% and 24.9%, respectively. Significant increase in cr-RASs was observed across the two study phases as follows: for ledipasvir/sofosbuvir in subtype 1a, cr-RASs increased from 30.2% to 35.8% (p=0.019); for elbasvir/grazoprevir in subtype 1a, cr-RASs increased from 30.4% to 36.1% (p=0.018); In subtype 1b, neither ledipasvir/sofosbuvir nor elbasvir/grazoprevir showed any cr-RASs in the first phase, but both were present at a prevalence of 6.5% in the second phase (p&lt;0.001); for sofosbuvir/velpatasvir in genotype 3, cr-RASs increased from 0.9% to 5.2% (p=0.006); and for glecaprevir/pibrentasvir, cr-RASs increased from 12.0% to 29.1% (p&lt;0.001). Rising prevalence of HCV RASs and cr-RASs was discernible. This highlights the necessity for ongoing surveillance and adaptation of novel therapeutics to manage resistance effectively. Updating of the clinical guidelines and treatment regimens are recommended to counteract the evolving resistance to DAAs.

This study finds that in northern Jordan, breeder indicators present challenges to the sustainability and growth of sheep and goat farming, while economic indicators suggest a combination of financial stability alongside hurdles related to profitability and resource ownership. Breeder age plays a role in the management of livestock herds, due to factors such as experience, resources, or adherence to traditional practices. Experience significantly affects breeders' decisions on male insemination replacements, likely due to skill. Crop cultivation influences breeders' returns by reducing feeding costs, while strategic lamb sales management boosts individual animal profitability. Winter raises animal mortality due to cold stress. Other animals in herds increase kid mortality by spreading diseases. Breeder experience significantly affects lamb survival, stressing its role in care. Increasing sheep proportion enhances lamb production and reduces lamb mortality while managing rams and selling lambs positively affects herd health and productivity. A larger goat herd proportion positively correlates with kids sold but inversely with breeding males and overall kids, implying trade-offs affecting herd productivity and mortality rates. Sheep herds (92.5%) show slightly better reproductive success than goats (90.6%), implying superior long-term viability. Flock excels in birth, survival, and sales, but low sheep and lamb%. Improvement is needed for sustainability, and the potential is high. Goat breeding shines in birth, sales, and overall success, but needs attention to kid survival and other sustainability issues. In conclusion, despite challenges, there are promising opportunities to enhance sheep and goat farming in Jordan. Effective management, informed by breeders' experience and economics, is crucial. Empowering small-scale herders and implementing targeted interventions like winter mortality solutions and selective breeding is vital for sustainable growth.

The WTO is here to stay. Institutions are never perfect. The way the WTO, as an institution, runs its business may not be perfect either. Arab countries are attempting to broaden their engagement in the multilateral trading system in a manner that has many implications. This engagement includes accession to the WTO, participation in WTO dispute resolution mechanism, and representations at the WTO.

Water scarcity is a significant challenge facing Jordan today. It is a challenge in all areas that use water, and it has become certain that water is the critical factor in the population/resources equation. The water resources in Jordan have become limited with the noticeable increase in the population, mostly resulting from forced migrations in neighboring countries because of the wars and until our time. The rising natural population growth rate, along with the massive influx of refugees, has turned into a state of disproportion between the daily consumption of the population and the amount of water available. That Jordan shares most of its surface water resources with neighboring countries has exacerbated the situation. The current use of water already exceeds its renewable supply. Excessive withdrawal from aquifers, which leads to a lowering of the water table and deterioration in water quality, covered the deficit. This paper focuses on assessing the water situation in Jordan, mainly evaluating this problem and the solution being considered, the true basis for a sustainable water solution requires awareness by the population, and several governmental and non-governmental organizations are actively involved in educating residents about water shortages. The most important and 'actionable' elements of comprehensive water solutions are discussed in this paper, and these elements exist, develop extra water supplies, water harvesting, water desalination, proper wastewater reuse in the agricultural sector, and reduce the demand for drinking water. This research provides specific recommendations to address the shortage of water resources in the Kingdom and highlights the importance of water conservation and optimal use.

We have shown in previous work that the equivalence of the Heisenberg and Schrödinger pictures of quantum mechanics requires the use of the Born and Jordan quantization rules. In the present work we give further evidence that the Born--Jordan rule is the correct quantization scheme for quantum mechanics. For this purpose we use correct short-time approximations to the action functional, initially due to Makri and Miller, and show that these lead to the desired quantization of the classical Hamiltonian.

Non-Vitamin K Oral Anticoagulants (NOACs) have revolutionized anticoagulant therapy, offering improved safety and efficacy over traditional agents like warfarin. This review comprehensively examines the dual roles of NOACs—Apixaban, Rivaroxaban, Edoxaban, and Dabigatran—not only as anticoagulants but also as modulators of inflammation via Protease-Activated Receptor (PAR) signaling. We highlight the unique pharmacotherapeutic properties of each NOAC, supported by key clinical trials demonstrating their effectiveness in preventing thromboembolic events. Beyond their established anticoagulant roles, emerging research suggests that NOACs influence inflammation through PAR signaling pathways, implicating factors such as FXa and Thrombin in the modulation of inflammatory responses. This review synthesizes current evidence on the anti-inflammatory potential of NOACs, exploring their impact on inflammatory markers and conditions like atherosclerosis and diabetes. By delineating the mechanisms by which NOACs mediate anti-inflammatory effects, this work aims to expand their therapeutic utility, offering new perspectives for managing inflammatory diseases. Our findings underscore the broader clinical implications of NOACs, advocating for their consideration in therapeutic strategies aimed at addressing inflammation-related pathologies. This comprehensive synthesis not only enhances understanding of NOACs' multifaceted roles but also paves the way for future research and clinical applications in inflammation and cardiovascular health

The vastness of chemical-space constrains traditional drug-discovery methods to the organic laws that are guiding the chemistry involved in filtering through candidates. Leveraging computing with machine-learning to intelligently generate compounds that meet a wide range of objectives can bring significant gains in time and effort needed to filter through a broad range of candidates. This paper details how the use of Generative-Adversarial-Networks, novel machine learning techniques to format the training dataset and the use of quantum computing offer new ways to expedite drug-discovery.

Arabic was the language of philosophy, logic, Islamic sciences and rhetorical linguistic sciences. It was used in the writing of all sciences generally and became the language of world culture. Although the other languages of the Islamic world had a little share, but all peoples of Islamic countries; Arabs and non-Arabs, Muslims and non-Muslims attributed to that movement appreciated. Hence, Arab sciences flourished in their bright ages. Arabic language was a cultural container of the ancient Greek and Latin intellectual heritage. As the ancient Greek and Latin sciences and literatures were translated into Arabic in the bright ages of Islam. Arab language was a strong bond for them, as a common human heritage for the centuries to save it from being lost, as Muslims used it to develop their sciences and arts, as Muslims in the East used the Western sciences and literatures in the modern age, because they are not Eastern or Western, but the common efforts of all humanity. Arabic language opened for the dictionaries ​​and other tongues of cross-fertilization, civil friction and simulation. Arabic had become the language of sciences: mathematics, astronomy, engineering, logic, philosophy, mysticism, agriculture, industry and economics by the continuous efforts of scientists in their scientific research, invention, experimentation, knowledge collection and classification in various fields, where orientalists recognized the Arab leadership. That scientific and literary civilization moved to Europe through Italy, Andalusia, Crusades and the Ottoman Caliphate. Europeans learned Arabic language, literature and sciences in the centers of Toledo, Fez and cities of Maghreb.

Background: Corticosteroids (CS) are crucial for managing various medical conditions, but long-term use is associated with significant risks. Balancing the therapeutic benefits and potential hazards requires careful prescription and monitoring. This study explores Jordanian physicians' knowledge, experiences, and concerns regarding CS prescriptions. Methods: This was a cross-sectional study conducted between March and August 2023, using an online link distributed using social media platforms. Results: A total of 171 physicians enrolled in the study were predominantly male, with a median age of 31 years. Two-thirds worked in central Jordan, and one-third were general practitioners. The majority (86.5%) had experience both in topical (83.1%) and injectable (81.1%) dosage forms. Physicians demonstrated high knowledge (median score 11/11) and major concerns (median fear score 3.5/5) about CS. Major worries included the risk of osteoporosis (73.7%) and hyperglycemia (66.7%). Sociodemographic factors did not significantly impact their knowledge or fears. Conclusion: Our study showed that physicians have a high knowledge level about CSs but have major concerns about CS side effects, particularly osteoporosis and hyperglycemia. These findings highlight the need for targeted interventions to address these fears, enhancing physician confidence and improving patient management outcomes.

1) Background: carbapenem-resistant Acinetobacter baumannii (CRAB) is an opportunistic Gram-negative pathogen that has a significant role in healthcare-associated infections. Unlike several studies on the antibiotic-resistant epidemiology of A. baumanni, virulence molecular epidemiology was less studied. This study aimed to investigate CRAB virulence genes and their ability to form biofilms, and to correlate their biofilm formation ability with both; biofilm-encoding virulence genes and carbapenemase-encoding resistance genes. 2) Methods: 107 CRAB clinical isolates were collected from two hospitals in Jordan between 2018 and 2019 and were screened for virulence genes using PCR. In addition, biofilm formation ability was assessed using the microtiter plate method. 3) Results: the frequencies of the bap, OmpA, surA, PLD, paaE, basD, and traT virulence genes were 99.10%, 98.20%, 98.20%, 95.50%, 89.10%, 86.40%, and 8.20%, respectively. Overall, 86.4% of the tested isolates were biofilm formers with varying degrees; weak (28.2%), moderate (36.4%) and strong (21.8%). A significant relationship was found between the carbapenemase-encoding gene (OXA-23 gene) and biofilm production. 4) Conclusion: to the best of our knowledge, this is the first study in Jordan that inspected CRAB virulence genes and highlighted the importance of improving infection control measures to avoid CRAB outbreaks.

In this paper, the effect of multi-pass friction stir processing on the mechanical properties of AZ91 alloy has been studied. For the numerical investigation, this process has been simulated with the three-dimensional numerical modeling based on the ABAQUS/Explicit. This simulation involves the Johnson-Cook models for defining the material behavior during this intense plastic deformation and investigating the fracture criterion. The tool plunging and stirring phases in the two-pass process has been simulated. To prevent too much distortion of elements during modeling, the Arbitrary Lagrangian-Eulerian technique for automatically re-meshing of distorted elements has been used. The model was calibrated using the experimental results from the previous works. This model can predict the transient temperature distribution and residual stress field during FSP on AZ91. The results show that the maximum temperature in the advancing-side region is more than that in the retreating-side region. In addition, numerical results show that at the end position of the process, the tool during the lift-up leaves the keyhole region in the compressive stress state. The experimental results investigated the effect of multi-pass FSP on the microstructure, microhardness, tensile and creep properties of AZ91 magnesium alloy. The FSP is performed by applying 50% overlapping. The tensile, and creep tests are conducted at several temperatures from 25 to 210 °C. The optical microscopy and scanning electron micrograph (SEM) were used to study the microstructure of the samples after performing multi-pass friction stir processing. The experimental results indicate that on average, the tensile strength, microhardness, and creep strength of the processed samples increased by about 29, 23, and 38 %, respectively compared to the unprocessed ones.

For many disciplines of science, all conceivable collisional cross sections and reactions must be precisely known. Although the recent decades were a trial of large-scale research to give these data, many essential atomic and molecular cross section data still missing, and the reliability of the existing cross sections has to be validated. In this paper, we present electron stripping, electron capture, and system breakdown cross sections in carbon (C5+) ions and lithium (Li2+) ions collisions with atomic hydrogen based on the Monte Carlo models of classical and quasi-classical trajectories. According to our expectation, the QCTMC results show higher results in comparison to standard CTMC data, emphasizing the role of Heisenberg correction constraint, especially in the low energy regime. On the Other hand, at high energy, the Heisenberg correction term has less influence as a projectile momentum increase. We present the total cross sections of electron stripping, electron capture, and system breakdown in C5+ ions and Li2+ ions collisions with atomic hydrogen in the impact energy range from 10 keV to 160 keV, which is of interest in astrophysical plasmas, atmospheric sciences, plasma laboratories, and fusion research.

Background: Previous investigations have found a correlation between abnormal curvatures and a variety of patient complaints such as cervical pain and disability. However, no study has shown that loss of the cervical curve is a direct result of exposure to a motor vehicle collision (MVC). This investigation presents a retrospective consecutive case series of patients with both a pre-injury cervical lateral radiograph (CLR) and a post-injury CLR after exposure to a MVC. Computer analysis of digitized vertebral body corners on CLRs was performed to investigate the possible alterations in the geometric alignment of the sagittal cervical curve. Methods: Three spine clinic records were reviewed, over a 2-year period, looking for patients where both an initial lateral cervical x-ray and an examination were performed prior to the patient being exposed to a MVC; afterwards an additional exam and radiographic analysis were required. A total of 41 patients met the inclusion criteria. Examination records of pain intensity on numerical pain rating scores (NPRS) and neck disability index (NDI), if available, were analyzed. The CLRs were digitized and modeled in the sagittal plane using curve fitting and the least squares error approach. Radiographic variables included total cervical curve (ARA C2-C7), Chamberlain’s line to horizontal (skull flexion), horizontal translation of C2 relative to C7, segmental translations (retrolisthesis and anterolisthesis), and circular modelling radii. Results: There were 15 males and 26 females with an age range of 8-65 years. Most participants were drivers (28) involved in rear end impacts (30). The pre-injury NPRS was 2.7 while the post injury was 5.0; p &lt; 0.001. The NDI was available on 24 /41 (58.5%) patients and was found to increase following exposure to the MVC: 15.7% to 32.8%, p &lt; 0.001. An altered cervical curvature was identified following exposure to MVC, characterized by an increase in radius of curvature and an approximate 8° reduction of lordosis from C2-C7; p &lt; 0.001. The mid cervical spine (C3-C5) showed the greatest curve reduction with localized mild kyphosis at these levels on average. Several participants developed segmental translations that approached the instability value of translation &gt; 3.5mm. Conclusions: Abnormalities of cervical lordosis occurred following exposure to a MVC. The average loss of cervical curvature was 8° from C2-C7, with mild flexion of the mid cervical segments. Snap through type or dynamic buckling during the MVC may explain our findings. The primary contribution of this study to the motor vehicle collision literature is that altered cervical lordosis may result from MVC exposures and the consequences of an altered cervical alignment, in turn, may lead to future pain, disability and decreased health-related quality of life.

The purpose of this study was to examine the problem of violent extremism among young people. Additionally, a youth violent extremism scale (YVES) was developed that takes into account the differences between and within Arab cultures. The goal was to produce a scale that could be used and tested within an Arab country or between Arab countries. The scale was developed in three stages: generation, refinement, and validation. A literature review and nomological network were utilized to show the scale's dimensions, correlations to those dimensions, and other relevant variables (such as the LSC, LSE, and criminality scale). A sample of 6726 young students from fifteen Arab countries and the authorities involved were selected. Findings showed that six factors were obtained through principal component factor analysis using Varimax and Kaiser normalization (29 items). A significant positive association was found (r=.651, p = 0.000), supporting the scale's validity. Using Cronbach's alpha, the scale reliability was strong and assessed at 0.98. The scale's construct validity was estimated by assessing the correlation between the Youth Violent Extremism scale and low self-control. A significant positive correlation (r=.651, p = 0.000) indicates the scale's validity. Findings showed significant differences between males and females in youth violent extremism (F = 13.678, α ≤0.000). Descriptive results showed, however, that females have a slightly higher mean of violent extremism than males (M =85.2 vs. 87.6), with a close variation (26 vs. 27) for males and females, respectively. In this study, a measurement tool was provided that can be used as a knowledge base for security strategies. The scale can be applied to identify legal, social, and educational policies and applications of violent extremism. Future research is needed to test the scale on different professions like teachers, police officers, and parents. Also, a need to test the scale on different age groups, settings, and cultures. A need for atheoretical and empirical framework for understanding and preventing youth violent extremism through promoting a more cohesive and resilient youth society.

In this paper, the effect of preheating on the mechanical properties and micro structure of similar friction stir welded AA6061 aluminum alloys sheets was investigated. Aluminum alloy 6061 sheets with a thickness of 5 mm and threaded cylindrical pins were used. Rotation and traverse speeds were 1200 rpm and 75 mm/min, respectively. The results of tensile tests performed on the welded samples showed that compared to the non-preheated samples, preheating had increased the strength and elongation of the joints by 58% and 46%, respectively. In the present study, during the welding process preheating cause emerged heat with lower slope from stir zone. This phenomenon may result in Increase the deformation resistance of material and consequently decrease of grain size. This grain refinement can improve the mechanical properties of welds. Accordingly, hardness and strength of the material will be increased.

Abstract Purpose: In this study, the Pre-implantation embryonic sex ratio in 125 couples who had three or more female children and underwent pre-implantation genetic diagnosis (PGD) for non-medical reason was included. Besides, we have aimed to find out whether these couples had more chances of getting a girl child once again. Methods: 125 couples who had three or more female offspring and those who underwent PGD for non-medical sex selection (XY) between 2015 and 2019 were included. Nuclear DNA was analyzed by Fluorescent in situ Hybridization (FISH). 2-chromosome (X, Y), 3-chromosome (21, X, Y), 5-chromosome (13, 18, 21, X, Y) probes were used for FISH. The standard protocol was followed for sperm processing and embryo culture for IVF and PGD. Result: Independent sample t-test showed that there is no significant difference between equal and unequal embryonic groups in patients’ age, husbands’ age, sperm count, sperm motility, total male embryos, total female embryos, normal male embryos, and normal female embryos. For patients with positive pregnancy outcome, 84.6% had unequal embryonic ratio while 15.4% had equal embryonic ratio. Similarly, patients those who were treated by short protocol had 85% of unequal embryonic ratio and 15% had equal ratio. Conclusion: Greater variability in the female to male embryos was found in these couples, confirms the fact that couples previously having girl offspring may predominantly not produce embryo of the same sex every time.

As Arab countries are beginning to recover from the socioeconomic impacts of the COVID-19 pandemic, conservation programs are restarting. Noticeably, traditional conservation efforts have not helped improve the poor living conditions in most historic urban centers of Arab cities due to many reasons such as a lack of funds, urban management policies, and the narrow scope of conservation projects. In 2016, the UN urban agenda recognized tangible and intangible heritage as the basis for sustainable, vibrant, urban economies. These efforts reflect the new shift in conservation activities to tangible and intangible heritage and consider urban heritage a tourist product rather than antiquity. This approach grants urban vitality and sustainability for heritage areas. Thus, this study investigates the existing trends and forthcoming changes in conservation and their implication for the deteriorated historic urban city centers of the Arab world. International urban heritage conservation trends were highlighted, objectives and bases of successful urban conservation trends were reviewed, and an assessment framework was developed. Two case studies of historic centers in two Arab cities, Jeddah, and Aman, were empirically assessed using the developed framework. The findings highlight the most common urban problems of the historic centers in terms of urban management policies and trends. In addition, the impact of urban management policies on historic urban areas' sustainability, vitality, and quality was revealed. The paper ends with recommendations for conservation authorities to define a proposed framework to embed the conservation within the urban development plans for deteriorated historic urban centers. The paper's findings and recommendations can contribute to the required knowledge related to urban heritage conservation for practitioners and decision-makers.

Opium smoking for long hours and over many years is common in Iran, and the Covid-19 pan-demic and false beliefs about the protective effects of that opium against COVID-19 infection has caused the increasing of opium smoking during the pandemic. The aim of this study was to in-vestigate the relationship between non-ergonomic positions of traditional opium smoking in Iran with the occurrence of neck pain and disability, forward head posture and hyperkyphosis. In this cross-sectional and correlation study 120 people who smoke opium were selected based on the inclusion criteria and were interviewed about their addiction profile and evaluated for the pres-ence of pain and disability in the neck by Maudsley Addiction Profile, Leeds Dependence Ques-tionnaire, the Visual Analog Scale and Neck Disability Index. Also, they were evaluated about forward head posture (FHP) through side view photography and hyperkyphosis (HK) through flexible ruler. Data were analyzed by correlation coefficient tests and stepwise linear regression. There was a significant relation between homelessness, the duration of lifetime opium smoking (months), the duration of daily opium smoking (minutes) and drug dependence severity with the severity of neck pain, neck disability, forward head posture and hyperkyphosis. Homelessness is the strongest predictive variable of the possibility of neck pain and disability, FHP and HK, fol-lowed by ‘‘the number of months of opium smoking’’ and ‘‘the number of minutes of opium smoking in one day’’ respectively. Increasing the duration of sitting in non-ergonomic positions can lead to neck pain and disability, FHP and HK due to their non-neutral posture in opium smokers.

Bacterial infections occur when wound healing fails to reach the final stage of healing, usually hindered by the presence of different pathogens. Different topical antimicrobial agents are used to inhibit bacterial growth due to antibiotic failure in reaching the infected site accompanied very often by an increased drug resistance and other side effects. In this review, we focus on antimicrobial peptides (AMPs), especially those with a high potential of efficacy against multidrug-resistant and biofilm-forming bacteria and fungi present in wound infections. Currently, different AMPs undergo preclinical and clinical phase to combat infection-related diseases. AMP dendrimers (AMPDs) have been mentioned as potent microbial agents. Various AMP delivery strategies, such as polymers, scaffolds, films and wound dressings, organic and inorganic nanoparticles, to combat infection and modulate the healing rate have been discussed as well. New technologies such as CRISPR-Cas are taken into consideration as potential future tools for AMP delivery in skin therapy.

Opioid use disorder has increased in the world in recent years and Iran ranks first in terms of opium smoking in the world. In fact, opium smoking by traditional methods, in addition to dependence on morphine, is a behavioral addiction in Iran. The body position during opium smoking is usually non-standard and non-ergonomic. Over time, changes in muscle tissue, tendons and ligaments, and the connective tissue go from elasticity to neuromuscular plasticity. This study aims to compare sway back posture and musculoskeletal problems between opium smokers and non-drug users. In this comparative and cross-sectional study, 80 opium smokers were compared with 74 non-drug users in terms of sway angle (sway back posture), and musculoskeletal complaints (NORDIC questionnaire) and the association of possible risk factors was investigated. Data were analyzed by Kolmogorov-Smirnov, Correlation Coefficient and paired-t tests using SPSS version 23. There were significant differences between two groups in terms of sway back posture (P=0.007), and neck (<0.001), upper back (<0.001) and lower back (0.006) musculoskeletal complaints. Homelessness, the lifetime duration of opium smoking (in months), and the duration of daily opium smoking (in minutes) had significant correlation with sway back posture and musculoskeletal complaints. Homelessness was the strongest predictor and had strongest correlation. Overall, an increase in the duration of sitting in non-ergonomic positions could lead to increase in sway angle and sway back posture and increase in musculoskeletal complaints of neck, upper back and lower back due to the non-neutral posture of opium smoking. It seems that plasticity and structural and functional adaptations of the posture occurs due to opium smoking and further studies are recommended.

Abstract: The need to rapidly reduce GHG has accelerated the adoption of circular models of production. However, this has proved to be a challenging task for SMEs, who lack the financial, organizational and informational capabilities to implement circular business models. In this context, calculating the carbon footprint (CF) of their products could provide the basis for assessing the different circular economy (CE) practices. The aim of this study is to present a CF calculation tool that can be used to calculate the CF of SMEs. The design of the tool was based on the Life Cycle Assessment (LCA) methodology, taking into account the various barriers that SMEs face in adopting CE practices. The tool was tested in a small cheese factory in northern Greece. The pro-duction process was mapped, a GHG inventory was created and the total emissions related to the production of a specific product was estimated. The final aim is to test this tool at a large scale.

This study investigates the valorization potential of yellowfin tuna tails for the production of high-value commercial products. Muscle and skins were firstly mechanically separated by using a specifically designed device. The muscle was then used as a nitrogen source for the growth of the proteolytic enzymes-producer Bacillus subtilis, whereas the skins were employed for gelatin extrac-tion. The proteases from Bacillus subtilis were partially purified and used to produce antioxidant peptides from gelatin obtained. The gelatin obtained formed a gel upon cooling, with gelling and melting temperatures at 16 ºC and 22 ºC, respectively, and Bloom Strength of ≈ 160. RSM was used to determine the optimal hydrolysis conditions to obtain the highest antioxidant activity (35.96%, measured as DPPH radical scavenging activity), which were 50°C / 6.5 IU of enzyme. The findings emphasize the importance of an integrated approach to maximize the value of tuna by-products, promoting sustainability in the frame of circular bioeconomy. Overall, these results contribute to the efficient utilization of tuna by-products, waste reduction, and enhance economic viability of the tuna industry.

Duct-dependent lesions are classically divided into duct dependent pulmonary circulation which involves severe right sided obstructive lesions such as pulmonary atresia or critical stenosis, and duct dependent systemic circulation which is characterized by malformation of the left side of the heart, and whose severest spectrum is hypoplastic left heart syndrome. Dextro-transposition of the great arteries remains in gray zone between being included in some old classifications as a duct dependent pulmonary circulation lesion or a new category of duct-dependent or independent mixing lesion. We hypothesize that re-classifying duct dependent congenital defects into duct dependent perfusion and oxygenation offers a model to fit D-TGA into the same category of right sided obstructive lesions and reflects the clinical spectrum in a more comprehensive way.

One of the most important pieces of equipment used in labs in culturing populations of fruit flies (Drosophila sp.) is that of the “CO₂ gas plate”, which is used to anesthesize individuals during “fly-pushing”. This piece of equipment consists of a box with a porous top into which carbon-dioxide is pumped. Flies placed on its surface are left immobilized, permitting the sorting, categorizing and/or counting of flies during population culturing and experimental assays. Unfortunately, commercially available gas plates are typically expensive. Here, we describe a new design for a gas plate that can be easily produced using a 3D printer and a laser cutter, which we are making freely available to the fly community.

Despite marked advancements, life expectancy (LE) growth in Saudi Arabia and the United Arab Emirates (UAE) has remained stagnant compared to other developed nations. This study aims to investigate the significant correlation between macroeconomic (ME), sociodemographic (SD), and health status-resources (HSR) factors and LE to formulate an explanatory model for Saudi Arabia and the UAE – a previously unexplored area. Utilizing an ecological, retrospective, time-series study design, we delved into secondary data on SD, ME, HSR, and LE of the UAE population spanning three decades (1980-2020). We employed the partial least squares-structural equation modeling for statistical analysis. Our analysis revealed significant direct impacts of HSR on LE for Saudi Arabia (Beta=0.958, p<0.001) and the UAE (Beta=0.716, p<0.001). Furthermore, we discerned a notable indirect influence of ME on LE, mediated through SD and HSR for Saudi Arabia (Beta=0.507, p<0.001) and UAE (Beta=0.509, p<0.001), along with a considerable indirect effect of SD on LE through HSR (Saudi Arabia: Beta=0.529, p<0.001; UAE: Beta=0.711, p<0.001). This study underscores the mediating role of a nexus of ME-SD-HSR factors on LE in Saudi Arabia and the UAE. Consequently, these findings signal an imperative need for holistically policy interventions addressing ME, SD, and HSR factors, aiming to alter health behaviors and improve LE projections for Saudi Arabia and the UAE in the long run.

The construction industry, a major player in economic development, is facing increased pressure to address sustainability concerns amidst rapid population growth and urbanization. With global projections indicating a significant rise in building demand by 2050 , sustainability emerges as a crucial focus area and paradigm shift to enhance environmental friendliness, improved quality, and project outcomes. The UAE, renowned for its vibrant construction industry, offers a unique context for examining the integration of sustainable practices. The growing use of sustainable construction practices is growing in the U.A.E., where the built environment plays a key role in economic growth and environmental stewardship. The United Arab Emirates (UAE) aims to foster long-term sustainability while enhancing the standard of living for current as well as future generations by integrating social, environmental, and economic aspects within construction projects, while also reevaluating conventional sustainable development frameworks and embracing a Triple -Bottom Line approach. Through an exploration of the significance of sustainable construction materials, this researcher underscores the multifaceted benefits of locally sourced, recyclable, and renewable materials in reducing environmental impacts, fostering economic and social well-being, and improving overall project performance, and project management practices. The construction sector's role in economic development and its substantial environmental impact are discussed in, alignment with sustainable construction materials, sustainable construction practices, and the need to enhance environmental sustainability; and create healthier built environments. In the realm of sustainable construction materials, project management knowledge areas encompass a range of factors. These include the properties of materials sourced regionally;, the incorporation of recycled content;, considerations for indoor air quality, energy, and water efficiency parameters;, and how these properties relate to project scope, scheduling constraints, and challenges. Additionally, the availability of resources and competency levels, quality control standards, specifications, communication strategies, and stakeholder involvement play crucial roles. It is important to assess both the positive and negative risks associated with these elements across construction projects.

The increasing cancer burden is a major health concern in Arab countries with variations in cancer profiles. Given the limited oncology research output and scarce data on cancer trial participation in the Arab region, this study explored the therapeutic cancer trial landscape in Arab countries over the past 20 years. A bibliometric analysis of the PubMed database was conducted on primary publications of therapeutic trials with a participating Arab center. Arab countries participated in 320 published cancer-related therapeutic trials (2000‒2021). There was a consistent increase in the number of trials, sample size, multiregional site participation, and number of randomized trials. However, most trials were small, did not receive external funding, and included a single Arab site. Compared with Arab-only trials, trials with joint non-Arab sites were larger (p = .003) and more likely to be externally funded (p < .001). Citation numbers and journal impact factors were higher in trial publications with joint non-Arab authorship than those without (p < .001, for both). Despite improving conduct and publication records of oncology trials with Arab centers, cancer trial participation remains limited in Arab countries. Concerted efforts are required to encourage sponsorship and international collaboration in this region.

Aims/Hypothesis): Type 1 diabetes is an immune-mediated disease with destruction of the pancreatic β-cells, a process that is conditioned by multiple genes and other factors. HLA counts as the major susceptibility gene. Significant variations in HLA genetic susceptibility to type 1 diabetes between Caucasians, African and Asian and other ethnic groups may have led to the variation in incidence of type 1 diabetes globally. Type 1 diabetes is characterized upon HLA identification. In this chapter we discuss global variations in genetic susceptibility of HLA with regard to type 1 diabetes globally with a particular attention to Arab population. Methods): Haplotype configuration of HLA class I A, B, C and Class II –DR/DQ/DP were studied in Caucasians, African and Asian and in Arab population to see if that is responsible for the exponential rise in the rate of type 1 diabetes. Results): Although Arabs have one of the highest global incidence and prevalence rates of type 1 diabetes, unfortunately, there is a dearth amount of information regarding HLA genetic susceptibility to type 1 diabetes in the Arab world. HLA haplotype configurations contribute to its risk value. However, out of an insufficient present study there are examples of misjudgment of HLA risk according to HLA alleles rather than haplotypes. Conclusion): To date HLA outlooks for the characterization of type 1 diabetes. There is an ethnicity difference in HLA characteristics which is responsible for variation in type 1 diabetes. Although Arab population have contributed heavily in the rise of burden of type 1 diabetes, however, there is significantly a dearth amount of studies on HLA in Arab population. Obviously, any future prediction, prevention or cure of the disease will be based on the HLA genetics. There is a dire need for a systematic screening of HLA for Arab population with type 1 diabetes, identification of Arab HLA-risk values and identify those who are prone to get the disease.

This article introduces a novel nature-inspired metaheuristic algorithm called Frilled Lizard Optimization (FLO), which emulates the hunting behavior of frilled lizards in their natural habitat. FLO draws in-spiration from the sit-and-wait strategy observed in frilled lizards during hunting. The underlying theory of FLO is presented and mathematically formulated in two phases: (i) an exploration phase, simulating the frilled lizard's attack towards prey, and (ii) an exploitation phase, simulating the lizard's retreat to the top of the tree after feeding. To assess FLO's efficacy in solving optimization problems, the algorithm's performance is evaluated across fifty-two standard benchmark functions, encompassing unimodal, high-dimensional multimodal, fixed-dimensional multimodal, and the CEC 2017 test suite. Comparative analyses with twelve existing metaheuristic algorithms are conducted. The simulation results reveal that FLO, distinguished by its adeptness in exploration, exploitation, and balancing them during search process, outperforms competing algorithms. Additionally, FLO is implemented on twenty-two constrained optimization problems from the CEC 2011 test suite and four engineering design problems, demonstrating its effectiveness in addressing real-world optimization applications.

Preterm delivery can be precipitated by infection, and preterm infants are at heightened risk of postnatal infection. Little is known about the ontogeny of inflammatory biomarkers in extremely preterm infants. We hypothesized that suspected prenatal infection (chorioamnionitis or spontaneous preterm labor) and clinically diagnosed postnatal infection would be associated with unique biomarker signatures, and those patterns would be influenced by the degree of prematurity. Venous blood was collected daily for the first week and weekly for up to 14 additional weeks from 142 neonates born at 22-32 weeks gestation. A custom array was utilized to measure monocyte chemoattractant protein-1 (MCP-1) and interleukin-6 (IL-6). C-reactive protein (CRP) levels were obtained from the electronic medical record. 90 infants had suspected prenatal infection and 63 were diagnosed with postnatal infection. Independent of gestational age at delivery, MCP-1 was significantly increased (P &lt; 0.001) in association with maternal preeclampsia, but MCP-1 was decreased (P&lt;0.01) and CRP was increased (P&lt;0.05) in the presence of chorioamnionitis. IL-6 and CRP were both increased in infants diagnosed with postnatal infection with peak levels observed on days 2 and 3, respectively. In conclusion, suspected prenatal and postnatal infections and non-infectious complications of pregnancy are associated with unique biomarker profiles, independent of gestational age. In those clinically diagnosed with a postnatal infection in the absence of antenatal infection concerns, IL-6 increases before CRP, emphasizing a potential role for expanded biomarker screening if antibiotics are initially avoided in infants born exclusively for maternal indications.

Improving the acquisition and retention of a new motor skill is of great importance. The present study (i) investigated the effects of difficulty manipulation strategies (gradual difficulty), combined with different modalities of feedback (FB) frequency on performance accuracy and consistency when learning a novel fine motor coordination task, and (ii) examined relationships between novel fine motor task performance and executive function (EF), working memory (WM), and perceived difficulty (PD). Thirty-six, right-handed, novice physical education students volunteered to participate in this study. Participants were divided into three progressive difficulty groups (PDG), 100% visual FB (FB1), 50% FB (FB2), and 33% FB (FB3). Progressive difficulty was increased by the manipulation of the distance to the target; 2 m, 2.37 m, and 3.56 m. Three FB modalities were investigated (i.e.: 100% visual FB (100% FB), 50% reduced feedback condition (50% RFB), and 33% reduced feedback conditions (33% RFB)). Performance assessments were conducted following familiarization, acquisition, and retention learning phases. Two stress-conditions of dart throws were investigated (i.e.: free condition (FC) and time pressure condition (TPC)). After the learning intervention, data showed that, under the free condition, the 100% FB group had a significant improvement in accuracy during all learning phases. Under time pressure condition, for the 50% RFB and the 33% RFB group, the measured variable (accuracy and consistency) showed a significant linear improvement in performance. The association between the percentage of RFB frequencies and the task difficulty (50% group) may be a more appropriate and manageable cognitive load compared to the 33% RFB and the 100% FB group. The present findings could have practical implications for practitioners because, while strategies are clearly necessary for improving learning, the efficacy of the process appears to be essentially based on the characteristics of the learners.

Keywords: Barriers; Facilitators; Sepsis; Sepsis Six Guidelines; Nurses.

In this work, we show that a late fusion approach to multi-modality in sign language recognition improves the overall ability of the model in comparison to the singular approaches of Computer Vision (88.14%) and Leap Motion data classification (72.73%). With a large synchronous dataset of 18 BSL gestures collected from multiple subjects, two deep neural networks are benchmarked and compared to derive a best topology for each. The Vision model is implemented by a CNN and optimised MLP and the Leap Motion model is implemented by an evolutionary optimised deep MLP topology search. Next, the two best networks are fused for synchronised processing which results in a better overall result (94.44%) since complementary features are learnt in addition to the original task. The hypothesis is further supported by application of the three models to a set of completely unseen data where a multi-modality approach achieves the best results relative to the single sensor method. When transfer learning with the weights trained via BSL, all three models outperform standard random weight distribution when classifying ASL, and the best model overall for ASL classification was the transfer learning multi-modality approach which scored 82.55% accuracy.

The outbreak of coronavirus 2 (SARS-CoV-2) has already taken on pandemic proportions and has affected more than 100 countries in recent weeks. It is imperative that global healthcare systems are prepared. Containment initiatives in Jordan, on the other hand, have decreased new cases by over 63%. The Jordanian national health system has been very pleased with its ability to adequately meet the needs of the patients diagnosed with SARS-CoV-2 pneumonia, and includes intensive care. From 2 March to 14 April 2020, between 4% and 8% of active infected patients in Jordan registered daily in intensive care. The percentage is very low.

Introduction: intraocular pressure (IOP) measurement is an essential part glaucoma’s diagnosis and follow-up. Goldmann applanation tonometry (GAT) is the gold standard for IOP measurement but it’s affected by many factors like central corneal thickness (CCT). Racial differences in CCT are reported but the Syrian population was never studied. Research design and methods: 57 subjects with 114 eyes visiting Damascus hospital were examined and 100 eyes were included. IOP was measured using GAT and CCT was measured using OCULUS Pentacam AXL Corneal Topography, demographic data and history of ocular surgery, systemic co-morbidities and history of medications were collected. IOP values were corrected for CCT. Results: 56% were males, the mean age was 48.1. 24% of subjects had hypertension. Males had higher CCT with 557.23± 25.33 compared with 531.34 ± 41.88 for females. There was a moderately positive correlation between CCT and IOP (r=0.232, p-0.02), CCT and IOP values were linearly correlated (ANOVA, p=0.02). Conclusions: This study showed that the correlation between CCT and IOP is present in the Syrian population. Males had a slightly thicker corneas than females and CCT didn’t significantly change with age.

Polarimetric Synthetic Aperture Radar (PolSAR) images encompass valuable information that can facilitate extensive land cover interpretation and generate diverse output products. Extracting meaningful features from PolSAR data poses challenges distinct from those encountered in optical imagery. Deep Learning (DL) methods offer effective solutions for overcoming these challenges in PolSAR feature extraction. Convolutional Neural Networks (CNNs) play a crucial role in capturing PolSAR image characteristics by leveraging kernel capabilities to consider local information and the complex-valued nature of PolSAR data. In this study, a novel three-branch fusion of complex-valued CNN named Shallow to Deep Feature Fusion Network (SDF2Net) is proposed for PolSAR image classification. To validate the performance of the proposed method, classification results are compared against multiple state-of-the-art approaches using the Airborne Synthetic Aperture Radar (AIRSAR) datasets of Flevoland, San Francisco, and ESAR Oberpfaffenhofen dataset. The results indicate that the proposed approach demonstrates improvements in OA, with 1.3% and 0.8% enhancement for the AIRSAR datasets and 0.5% improvement for the ESAR dataset. The analyses conducted on the Flevoland data underscore the effectiveness of the SDF2Net model, revealing a promising OA of 96.01% even with only 1% sampling ratio.

Routing quantum information among different nodes in a network is a fundamental prerequisite for a quantum internet. While single-qubit routing has been largely addressed, many-qubit routing protocols have not been intensively investigated so far. Building on the many-excitation transfer protocol in Ref. , we apply the perturbative transfer scheme to a two-excitation routing protocol on a network where multiple two-receivers block are coupled to a linear chain. We address both the case of switchable and permanent couplings between the receivers and the chain. We find that the protocol allows for efficient two-excitation routing on a fermionic network, although for a spin-12 network only a limited region of the network is suitable for high-quality routing.

Problem:Palestinian demographic landscape is undergoing an increase in the elderly population like many regions across the world. The elderly Palestinians face a unique challenges and problems of limited access to traditional care due to restricted movement, checkpoints, and also for limited healthcare resources. Therefore, the need arose to develop a sensitive and adaptable smart health monitoring system for Palestinian elderly to provide accurate and timely health data to improve well-being and prevent complications. Method: The proposed system (SHMS) leverages the Internet of Things (IoT) with appropriate sensors to track vital signs like heart rate, blood oximeter, body temperature and signal from a patient heart. Advanced algorithms analyze the data, generating alerts for potential health risks, triggering timely interventions, and enabling remote consultations. Results: This system has the potential to contributes to SDG 3 to significantly improve the health and well-being of elderly Palestinians by providing an accurate, low-power, and low-cost system for remote health monitoring. The system, being wearable, reads vital signs in real-time, overcoming geographical barriers and facilitating remote monitoring, especially in areas with limited healthcare centers and suffered from barriers along the way. The Doctor can suggest the patient’s prescription needed based on the momentary condition of the elderly and on previous readings of the sensors, if necessary. Which will also be notified via messages. Moreover, the doctor can take immediate intervention in case of an emergency. By implementing the system, it will be unnecessary for more than 50\% of the elderly to visit health care, thus reducing the cost to 50\%.}

Jordan is classified as a low- to-middle-income, in which the primary energy sources are imported crude oil and natural gas. The energy expenses represent a high percentage of the country's GDP. Meanwhile, due to its geographical location and its climate, Jordan ranks very high among the world countries with respect to solar energy exploitation potential. Therefore, solar energy is a key resource that can be utilized to significantly improve both the country’s economy and energy security. It has to be highlighted that Jordan focus on a network dedicated to solar energy and it has to be mentioned the Erasmus Plus INNOMED Project based on virtual classrooms, which aims to promote innovative technologies and applications of solar energy in MENA Countries. This paper presents an overview of the solar energy resources in Jordan that includes: the current situation, the potential, and future expectations.

Plants have acquired sets of highly regulated and complex signaling pathways to respond to unfavorable environmental conditions during evolution. Calcium signaling, as a vital mechanism, enables plants to respond to external stimuli, including abiotic and biotic stresses, and coordinate the basic processes of the growth and development. In the present study, the calcium sensor families, including CBL and CIPK, were investigated in the halophyte plant, Aeluropus littoralis, with a comprehensive analysis. Here, six AlCBL genes, and twenty AlCIPK genes were presented. The analysis of the gene structure and conserved motifs, as well as physicochemical properties, showed that these genes are highly conserved during evolution. The expression levels of AlCBL genes and AlCIPK genes were evaluated under salt stress in leaf and root tissue. Based on the real-time RT-PCR results, AlCIPK gene family had a higher variation in mRNA abundance compared to the AlCBL gene family. The AlCIPKs were found to have a higher abundance in leaves than in roots. The results suggest that the interaction pattern of AlCBL genes with AlCIPK is tissue-specific, and different interactions can be expected in leaves and roots. Based on these patterns AlCIPK3.1 - AlCBL4.1 and AlCIPK1.2 - AlCBL4.4 can interact in root tissue, while the AlCBL10 has the potential to interact with the AlCIPK5, AlCIPK26 and AlCIPK12.3 in the leaf tissue. These findings provide valuable information on the structure and function of calcium sensor families in Aeluropus littoralis a halophyte plant, for future research on the biological function of CBLs and CIPKs on salt stress resistance.

The incidence of Type 1 Diabetes (T1D) in the Arab world, particularly, oil and gas rich Gulf Cooperative Council (GCC) countries has more than doubled in the last twenty years. Therefore, there is a dire need for careful systematic familial cohort studies, especially in high-risk populations. Several immunogenetic factors affect the pathogenesis of the disease. Genes in the human leukocyte antigen (HLA) account for the major genetic susceptibility to the disease. The triggering agents initiate disease onset by destruction of pancreatic β-cells. The autoantibodies against glutamic acid decarboxylase (GADA), insulinoma antigen-2 (IA-2A), insulin (IAA), and zinc transporter-8 (ZnT-8A) comprise the most reliable biomarkers for T1D in both children and adults. Although three of the GCC countries, namely Kuwait, Saudi Arabia and Qatar are among the top 10 countries with high incidence rate of T1D, no proper diagnostic and prediction tools were applied in the region. Understanding the disease sequelae in a homogenous gene pool with high consanguinity in the GCC could help solve the challenges in understanding pathogenesis, as well as hasten the prevention of T1D. Arab states must incorporate T1D predictive and intervention policies on a war-footing basis to minimize the burden of this serious disease.

Appropriate diagnostic testing to identify persons infected with SARS-COV-2 is a vital part of a health system’s ability to control the global pandemic of COVID-19 disease. The primary purpose of this review is to provide an overview of the mass testing strategy implemented throughout the UAE and the overall impact it has made on containing and controlling the spread of the disease. This study describes the mass testing strategy and capacity of the UAE during the pandemic of the new coronavirus SARS-COV-2. The UAE has conducted 15 million polymerase chain reaction (PCR) tests to SARS-COV-2, as of 15 November 2020. The number of tests per day varied from 10,000 by the end of March to 120,000 tests per day in November 2020. The mass testing initiative across the entire UAE forms an integral part of a bigger strategy focusing on testing, tracing contacts and isolating positive cases.

Soil salinity, whether natural or human induced, is a major geo-hazard in arid and semi-arid landscapes. In agricultural lands, it negatively affects plant growth, crop yields, whereas in semi-arid and arid non-agricultural areas it affects urban structures due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation Accurately mapping soil salinity through remote sensing techniques has been an active area of research in the past few decades particularly for agricultural lands. Most of this research has focused on the utilization and development of salinity indices for properly mapping and identifying saline agricultural soils. This research study develops a soil salinity index and model using Landsat 8 OLI image data from the near infra-red and shortwave infra-red spectral information with emphasis on soil salinity mapping and assessment in non-agricultural desert arid and semi-arid surfaces. The developed index when integrated into a semi-empirical model outperformed in its soil salinity mapping overall accuracy (60%) in comparison to other salinity indices (~50%). The newly developed index further outperformed other indices in its accuracy in mapping and identifying high saline soils (67%) and excessively high saline soils (90%).

Effective solar forecasting has become a critical topic in the scholarly literature in recent years due to the rapid growth of photovoltaic energy production worldwide and the inherent variability of this source of energy. Due to the technological and econonomic limitations of energy storage solutions, using other, mosty conventional, sources to cover energy shortfalls and at the same time utilising solar surpluses production becomes necessary. The need to optimize energy systems, ensuring power continuity, and balancing energy supply and demand has led to the development of various forecasting methods and approaches based on meteorological data or photovoltaic plant characteristics. This article presents the results of a meta-review of the solar forecasting literature, including the current state of knowledge and methodological discussion. It presents a comprehensive set of forecasting methods, evaluates current classifications, and proposes a new synthetic typology. The article emphasizes the increasing role of artificial intelligence (AI) and machine learning (ML) techniques in improving forecast accuracy, alongside traditional statistical and physical models. It explores the challenges of hybrid and ensemble models, which combine multiple forecasting approaches to enhance performance. The paper addresses the emerging trends in solar forecasting research, such as the integration of big data and advanced computational tools. Additionally, from a methodological perspective, the article outlines a rigorous approach to the meta-review research procedure, addresses the scientific challenges associated with conducting bibliometric research, and highlights best practices and principles. This includes defining research questions, selecting eligibility criteria, literature search, data extraction, synthesis, and assessing bias and quality. The article contributes to the solar forecasting field by providing up-to-date knowledge, along with insights on the emerging trends, future research directions, and anticipating implications for the theory and practicce.

Heat-treated aluminum-silicon (Al-Si)-based alloys have dominated the cast lightweight alloy industry for several decades. However, in the last decade, Al-Ce-based alloys have shown promise in replacing Al-Si alloys due to their ability to remove the need for costly heat treatments. Since the properties of Al-Ce alloys depend on the as-cast microstructure, it is important to characterize the solidification kinetics of these alloys. Therefore, this study focused on characterizing the solidification of a near eutectic Al-Ce alloy with additions of Ni and Mn. The alloy was cast in a wedge mold configuration, resulting in cooling rates between 0.18 and 14.27 °C/s. SEM coupled with EDS and DSC techniques characterized the evolution rate of solid phases. The SEM/EDS data revealed that an Al10CeMn2 phase is present at higher cooling rates. At lower cooling rates, near the center of the casting, a proeutectic Al23Ce4Ni6 phase was more present. It was observed that up to 2.6 at. % of Mn was dissolved in this proeutectic Al23Ce4Ni6 phase, thereby removing a large portion of the available Mn for forming the Al10CeMn2 phase. DSC analysis showed differences in the samples' liquidus temperatures which is indicative of compositional variations. Inductively coupled plasma atomic emission spectroscopy (ICP-OES) and Scheil solidification simulations correlated the compositional differences to phase formation, which agreed with the SEM and DSC results. This experimentation provides insight into novel Al-Ce-Ni-Mn alloys and where their potential lies in industrial applications.

The electronic transport stability in nanodevices composed by metal/trans-polyacetylene /metal with different long length has contributed greatly for performance, homogeneity, stability, organization of the chains, reproducibility and higher conductivity. In this paper, we present an analytical study of the electronic transport characteristics from dimerized trans-polyacetylene (trans-PA) molecules containing an odd-even number of sites coupled to metal leads (left and right) in T-shaped geometry using the extended Su-Schrieffer-Heeger (SSH) model based on tight-binding Hamiltonian with the Non-Equilibrium Green´s Function (NEGF) via Heisenberg´s equation of motion and the Keldysh´s formalism. Due to the complexity of the T-shaped odd-even chain, our proposal was to test the effects on the finite-length network for three, four, five sites and furthermore foresee for 17-sites. We show how to tune dimerization strength () coupling to the parameters and T-shaped geometry of the device to which it affects the overlap integral localized at the three endpoints of the T-shaped system, making both the odd and even chains to undergo a metal-insulator transition in their electronic behavior. The results reached through control parity of the chain plane of the parameters governing () the electronic and experimental tunneling allow a better understanding of the subject.

The impact of scientific articles is often measured using metrics such as the Journal Impact Factor (JIF) and CiteScore, which rely on citation counts and publication volume. In this study, we aimed to identify the predictors of article impact in the leading solid organ transplantation journals from 2019 to 2020. Article impact was determined using its citation count in 2021 compared to the JIF. Statistical analysis was performed using IBM SPSS Statistics to identify significant predictors of positive impact on the JIF. A total of 2,461 articles and reviews were included, with variations observed among the top transplantation journals. Factors such as the number of authors, open access publishing, and authors from top affiliations were found to significantly influence the impact of articles. Articles discussing kidney transplantation and COVID-19 were associated with a positive impact on the JIF, while those discussing lung transplantation had a negative impact. The findings suggest that collaborative research with more authors and involvement of top institutions enhances impact. Open access publishing also correlated with increased citations and a positive impact on the JIF. Further research incorporating a broader range of journals and years would provide a more comprehensive understanding of factors influencing article impact.

The exceptional Jordan algebra is the algebra of $3 \times 3$ Hermitian matrices with octonionic entries. It is the only one from Jordan’s algebraic formulation of quantum mechanics which is not equivalent to the conventional formulation of quantum theory. It has often been suggested that this exceptional algebra could explain physical phenomena not currently explained by the conventional approach, such as values of the fundamental constants of the standard model of particle physics, and their relation to gravitation. We show that this is indeed the case; and this also unravels the connection between general relativity and the weak force. The exceptional Jordan algebra also predicts a new U(1) gravitational interaction which modifies general relativity, and which provides a theoretical basis for understanding the Modified Newtonian Dynamics (MOND).

The microbial contamination in food packaging have been a major concern that paved the way for the search for natural based new anti-microbial agents, such as modified α-mangostin. In the present work, twelve synthetic analogs were obtained via semi-synthetic modification of α-mangostin by Ritter reaction, reduction by palladium-carbon (Pd-C), alkylation, and acetylation. The evaluation of the anti-microbial potential of the synthetic analogs showed higher therapeutic value than the parent molecule. The anti-microbial studies proved that I E showed higher antibacterial activity whereas I I showed most significant antifungal activity. Due to their microbial properties, modified α-mangostin can be utilized as active anti-microbial agents in food packaging.

Phosphorus is essential and non-substitutable chemical element required for the cellular processes of all living organisms. The main source of phosphorus in the biosphere is phosphate rock. With more than 700 Mt P2O5, Estonia holds the largest sedimentary phosphate rock deposits in European Union. Estonian phosphate rock is principally sandstone that holds abundant remains of phosphatic brachiopod shells and compared to other sedimentary rocks, is particularly outstanding by its remarkably low content of hazardous heavy metals such as Cd and saturated by valuable elements present in the rock such as rear earth elements (REEs).

The Center for Disease Control and Prevention and the World Health Organization issued a practical approach and Global Action Plan to control the threatening emerging antibacterial resistance. One of the main basis of this plan is the Antimicrobial Stewardship Program (ASPs). This study aimed to evaluate community pharmacists’ awareness and perception towards antimicrobial resistance and ASPs in Jordan. Thus, a qualitative study was conducted through in-depth interviews with twenty community pharmacists. Convienience sampling was used in the study. Qualitative analysis of the data yielded four themes and eleven sub-themes. All the respondents showed good understanding about the causes of antimicrobial resistance. The most important causes reported by them was the non-restricted prescription of antimicrobials. Most of the pharmacists believed that they are competent to provide ASPs, however, they believed that there are several barriers against the implementation of ASPs in community pharmacies in Jordan. Barriers demonstrated by the pharmacists, including organizational obstacles, resources obstacles, and personal obstacles. As a conclusion, this study revealed several barriers against the implementation of ASPs in community pharmacies in Jordan. Incorporating ASPs in the community pharmacy settings requires proper pharmacist training, several academic disciplines team efforts, and good pharmacy practice of antimicrobial guidelines.

This paper highlights the impact of financial inclusion on individuals’ borrowing and saving decisions in the United States and the United Arab Emirates. It does so, using data from the 2014 Global Financial Inclusion database, and an empirical strategy consisting of first testing the significance of the joint bivariate model over its binary conterparts using the Lagrange multiplier test, followed by a contrast between the fully-parametric and semi-parametric specifications of the saving and borrowing equations. Based on model performance measures, the semi-parametric bivariate probit specification is identified as a better framework for describing the two processes of saving and borrowing, with a correlation coefficient of 12.3%. Although no significant difference exists between UAE and US residents in borrowing behavior, we find that US residents are 31.4% more likely to save than their UAE counterparts. In addition, and in line with the Permanent Income Hypothesis, the results reveal the absence of an income based saving or borrowing gradient in the two countries. Conversely, we found the prevalence of a gender based saving (12.4%) and borrowing (13.8%) inequality in favor of the male gender. Furthermore, access to a bank account and a debit card, companies policy of direct wage and salary transfer, and government transfer programs with direct deposit options are all financial inclusion strategies that are found to significantly raise the likelihood of saving and borrowing. As such, companies with payroll practices based on cash or physical paycheck issuing, especially in the US, should revise such policy to create more financial inclusion, and thereby more saving potential which in turn would contribute to further borrowing, investment and growth of the national economy.

ANGPTL3 is an important regulator of lipid metabolism. Its inhibition in people with hypercholesteremia reduces plasma lipid levels dramatically. Genome-wide association studies have associated ANGPTL3 variants with lipid traits. Irisin, an exercise modulated protein, has been associated with lipid metabolism. Intracellular accumulation of lipids impairs insulin action and contributes to metabolic disorders. In this study, we evaluate the impact of ANGPTL3 variants on levels of irisin and markers associated with lipid metabolism and insulin resistance. ANGPTL3 rs1748197 and rs12130333 variants were genotyped in a cohort of 278 Arab individuals from Kuwait. Levels of irisin and other metabolic markers were measured by ELISA. Significance of association signals was assessed using Bonferroni-corrected P-values and empirical P-values. The study variants were significantly associated with low levels of c-peptide and irisin. Levels of c-peptide and irisin were mediated by interaction between carrier genotypes (GA+AA) at rs1748197 and measures of IL13 and TG, respectively. While levels of c-peptide and IL13 were directly correlated in individuals with reference genotype, they were inversely correlated in individuals with carrier genotype. Irisin correlated positively with TG which is strong in individuals with carrier genotypes. These observations illustrate ANGPTL3 as a potential link connecting lipid metabolism, insulin resistance and cardioprotection.

The Impact of Event Scale-Revised (IES-R) is the most popular measure of post-traumatic stress disorder (PTSD), which has been recently validated in Arabic. This instrumental study aimed to determine optimal cutoff scores of the IES-R and its subscales in Arab samples of psychiatric patients (N = 168, 70.8% females) and healthy adults (N = 992, 62.7% females) from Saudi Arabia during the COVID-19 pandemic as an ongoing collective traumatic event. Based on a cutoff score of 14 of the Depression Anxiety Stress Scale 8-items (DASS-8), receiver operator curve (ROC) analysis revealed two optimal points of 39.5 and 30.5 for the IES-R in the samples (area under the curve (AUC) = 0.86 &amp; 0.91, p values = 0.001, 95% CI: 0.80-0.92 &amp; 0.87 to 0.94, sensitivity = 0.85 &amp; 0.87, specificity = 0.73 &amp; 0.83, Youden index = 0.58 &amp; 0.70, respectively). Different cutoffs were detected for the six subscales of the IES-R, with numbing and avoidance expressing the lowest predictivity for distress. Meanwhile, hyperarousal followed by the irritability expressed stronger predictive capacity for distress than all subscales in both samples. In path analysis, pandemic-related irritability resulted from direct and indirect effects of key PTSD symptoms (intrusion, hyperarousal, and numbing). Irritability contributed to traumatic symptoms of sleep disturbance in both samples while the opposite was not true. The findings suggest usefulness of the IES-R at a score of 30.5 for detecting adults prone to trauma related distress, with higher scores needed for screening in psychiatric patients. Various PTSD symptoms may induce dysphoric mood, which represents a considerable burden that may induce circadian misalignment and more noxious psychiatric problems/ co-morbidities (sleep disturbance) in both healthy and diseased groups.

Creating environmentally sustainable oral healthcare culture requires embedding contents in dental curriculum. This study aimed to explore the current knowledge and drivers among dental students and educators regarding environmentally sustainable dentistry (ESD) in the United Arab Emirates (UAE) and identify barriers and enablers to embrace it. A cross-sectional survey using online questionnaire was carried out in undergraduate dental educational institutes. Data analysis included descriptive statistics and thematic analysis. Most students and educators were not aware of ESD content in their curriculum. However, the majority of educators were familiar with ESD concept, while students were mostly unfamiliar. Nonetheless, students largely agreed on its im-portance and their interest in learning it, as they view it relevant to their future practice. Educators agreed that the dental profession has a responsibility to be environmentally friendly and expressed desire in introducing ESD content into the curricula. Several barriers were reported such as lack of knowledge, curriculum space, educational resources, and time. Meanwhile, enablers included providing training and resources. There is no explicit presence of ESD content in the dental curricula. Regardless of the lack of in-depth knowledge among educators and more so with students, they both have positive views toward incorporating ESD into dental curricula.

The coronavirus (COVID-19) pandemic limitations may negatively affect children and youth in terms of health behaviors, and it might be especially challenging for children who are diagnosed with neurodevelopmental disorders such as children and youth diagnosed with Autism Spectrum Disorder (ASD). The present study assessed alterations in physical activity, screen time, and sleep duration of ASD children and the prevalence of meeting the 24-hour movement guidelines during the COVID-19 outbreak. Forty-six Arab Israeli mothers of children with ASD were surveyed by an online cross-sectional survey. As reported by the mothers, the results show a significant decrease in physical activity, a significant increase in screen time, and a significant increase in sleep duration during the COVID-19 pandemic. Moreover, the proportion of the sample who gained the physical activity and screen time recommendations lessened while the percentage of children who met the sleep duration guidelines increased. The prevalence of ASD children who achieved the overall 24-hour movement guidelines was very small during the COVID-19 outbreak. The outcomes extend the body of knowledge regarding the negative effects of the COVID-19 pandemic on children diagnosed with neurodevelopmental disorders and highlight the need for instant healthcare and interventions and programs for children with ASD.

Background: Health Care Workers (HCWs) are at increased risk of acquiring and transmitting COVID-19 infection. Also, they present role models for communities with regards to attitudes towards COVID-19 vaccination. Hence, hesitancy of HCWs towards vaccination can crucially affect the efforts aiming to contain the pandemic. Previously published studies paid little attention to HCWs in Arab countries, which has a population of over 440 million. Objectives: to assess the rates of COVID-19 vaccine hesitancy in Arabic-speaking HCWs residing in and outside the Arab countries, and their perceived barriers towards vaccination. Methods: a cross-sectional study based on an online survey was conducted from 14-Jan 2021 to 29-Jan 2021, targeting Arabic-speaking HCWs from all around the world. Results: the survey recruited 5,708 eligible participants (55.6% males, 44.4% females, age 30.6±10 years) from 21 Arab countries (87.5%) and 54 other countries (12.5%). Our analysis shows a significant rate of vaccine hesitancy among Arabic-speaking HCWs residing in and outside Arab countries (25.8% and 32.8%, respectively). The highest rates of hesitancy were among participants from the west region of the Arab world (Egypt, Morocco, Tunisia, and Algeria). The most cited reasons for hesitancy were concerns about side effects and distrust in vaccine expedited production and healthcare policies. Factors associated with higher hesitancy included age of 30-59, previous or current suspected or confirmed COVID-19, female gender, not knowing the vaccine type authorized in the participant’s country, and not regularly receiving the influenza vaccine. Conclusion: this is the first large-scale, multinational, post-vaccine-availability study on COVID-19 vaccine hesitancy among HCWs. It reveals high rates of hesitancy among Arab-speaking HCWs. Unless addressed properly, this hesitancy can impede the efforts for achieving widespread vaccination and collective immunity.