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This study aims to highlight the challenges that undergraduates face when traveling a significant distance from home to study. These challenges are psychological, financial, and nutritional. The study was descriptive and based on a survey conducted to investigate the challenges faced by university students while studying away from their hometown. A questionnaire was used to collect data from 214 undergraduates between February and April 2021. The collected data were analyzed using the computer program SPSS version 24. Pearson's Chi-square and Fisher's exact tests were applied to observe associations between qualitative variables. A total of 214 undergraduates participated in the study, with a median age of 22 years. The study found significant relationships between weight change and housing (P < 0.001), weight change and distance (P < 0.001), level of homesickness and housing (P < 0.001), level of homesickness and college distance (P < 0.001), and financial status with housing (P = 0.025). The study revealed that a significant number of undergraduate participants face psychological, financial, and nutritional challenges. These challenges include psychosocial issues, such as homesickness financial difficulties, such as money issues, and nutritional concerns, such as weight changes.

Abstract Cloud computing is an environment where everything is provided as a service based on demand. It follows pay as per the used model in which the service consumer needs to pay for what they have consumed. Due to the increased dependence on digitalization, the number of consumers and providers tends to grow tremendously. The consumer who needs the service from the provider is not sure about the specified service outcome, and it is too hard for them to monitor and manage the service. Hence, a trusted third party called a trusted cloud broker (TCB) is introduced for managing the services. The service level agreements (SLA) management and reputation estimation framework is proposed, which includes three phases such as (i) SLA establishment between the three parties, (ii) violation detection by comparing the observed value of the TCB and (iii) the reputation and penalty estimation of the service. The novel TCB is created to monitor the deployed services, ensuring the achievement of SLA. The TCB observes the values and estimates the reputation value for each service. It is compared with the provider log‐based reputation value and found that the proposed model provides a more precise reputation value for the service providers.

Background Sickle cell disease (SCD) is associated with oxidative stress due to an imbalance between production and elimination of the reactive oxygen species. It has been reported that SCD patients are at risk of multiple micronutrients' deficiencies, including several trace elements involved in the antioxidation mechanisms. We aimed to assess the status of these micronutrients in SCD patients. Methods This study was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) guidelines. The databases of MedLine, Embase, and PsycInfo were used for the systematic search from time the databases existed until April 2021. A total of 36 studies fulfilled the eligibility criteria. We calculated the pooled standardized mean difference (SMD) of serum zinc, magnesium, or copper levels among patients with SCD and their healthy controls. Results SCD patients had significantly lower zinc (SMD = −1.27 [95% CI: 1.67−0.87, p 0.001]) and magnesium levels (SMD = −0.53 [95% CI: 1.0−0.06, p 0.026] than their controls. Copper level was found to be significantly higher in SCD patients, with SMD = 0.68 (95% CI: 0.05−1.32, p 0.004). Conclusion This review showed that SCD patients may potentially prompt to have lower zinc and magnesium levels and higher copper levels compared with those without the disease. Future research need to be directed to investigate clinical outcome of nutritional difficiencies in patients with SCD, as well as the possibility of implementing nutritional supplement programs which may help minimizing the harmful effects of the disease on human body.

Background: This study shows how multiple ethical criteria evaluations result in patient screening and ranking. Furthermore, as Omicron outbreaks increase, hospital emergency departments will become overburdened with critically ill patients. It is a one-of-a-kind global triage algorithm for infectious decreases of COVID-19 and Omicron. The algorithm is qualitative and quantitative, and adaptable to various bio-ethical and social factors. The measurement of the evaluation process eliminates any inconsistencies, which is an advantage of a decision-making algorithm. The proposed algorithm is unique because there are no similar algorithms in the literature that provide triage guidelines based on social ethics, bioethics, and human dignity. Objective: It's simple to evaluate a patient's potential benefits when ethical triage judgments are structured and transparent. Furthermore, decisions made primarily based on economic considerations in stressful situations overlook the socioeconomic realities of the underprivileged. This triage algorithm eliminates the need for ad hoc triage evaluations and facilitates criteria for inclusion, such as human dignity. It also takes into account patient comorbidities and social, ethical issues. Method: Healthcare professionals use predefined ethical criteria to assign relative rankings among patients based on treatment response and social circumstances. It is a Delphi method for evaluating patient illnesses with the help of medical professionals. For example, the admission to the intensive care unit and providing a ventilator depend entirely on hierarchical multidimensional triage scoring results. This algorithm can evaluate triage scores quickly. It is robust, accurate, and quick in assessment, evaluation, and reevaluation during an emergency. A team of three experts can implement this algorithm. Result: The Consistency Scores (CR) show how well clinical and non-clinical ethical criteria may be used to make triage judgments. As a result, all specialists have reported allogeneic reactions in the triage assessment. Furthermore, this system enables decision-makers to identify cognitive biases that may influence their decisions. A Group Consciousness Ratio (GCR) of over 85% indicates that the decision-making process is transparent. Patients with a high level of social dependency, a reasonable probability of recovery, a favorable weighted average comorbidity score, and those who are less fortunate are all considered in the overall triage decision. Conclusions: This algorithm differentiates patients who need ICU (Incentive Care Unit) care and do not immediately require critical resources. As a result, patients queue up on a waiting list when the ICU demand spikes due to the increased incidence of COVID-19 infection or its variants. This situation presents a dilemma for the triage policy. Therefore, a national emergency policy requires monetary and technical assistance to expand healthcare facilities. However, the clarity of this triage policymaking is at odds with decision-makers interested in manipulating results. It is challenging to deal with consistency issues in the Delphi process in group decision-making without professional moderators and valid evaluation metrics. Therefore, transparency, consistency, and strong judgment are essential elements of the presented algorithm. Doi: 10.28991/esj-2022-SPER-07 Full Text: PDF

BACKGROUND: Thalassemia syndromes and structural hemoglobin variants generate blood crisis of variable clinical symptoms, ranging from mild-to-moderate hematological disorder to severe, lifelong, transfusion-dependent anemia. The aim of current study was to uncover the prevalence of thalassemia and other hemoglobinopathies in the Erbil governorate, Kurdistan region of Iraq. MATERIALS AND METHODS: The available data of thalassemia major, thalassemia intermedia, sickle cell disease, sickle cell trait, and HbH and HbE until the end of 2020 were collected retrospectively from Erbil Thalassemia Center in Erbil governorate, Kurdistan region of Iraq and analyzed by using Microsoft Excel (Version 2016). RESULTS: An increase in the prevalence of thalassemia syndromes from 30.8/100,000 in 2015 to 37.3/100,000 individuals in the population in 2020 was revealed. The prevalence of all hemoglobinopathies combined increased from 31.9/100,000 to 42.7/100,000 individuals of the population. Thalassemia major was the predominant condition among the hemoglobinopathies with 758 (78.71%) cases out of 963 cases at the end of 2020. CONCLUSION: This rise might be attributed to a large number of consanguineous marriages, the lack of effective prevention programs, and poor legislation. There is an emergent requirement for a preventive program, entailing identification of carriers, genetic counseling, guidelines to differentiate between other microcytic anemias with thalassemia traits, antenatal diagnosis, public education, and sustained legislation.

The concept of smart sustainable cities—as a favorable response to different challenges faced in urban areas—is rapidly gaining momentum and worldwide attention. This trend has driven the exploration of various technologies to improve the utilization of limited resources and idling capacities (i.e., underutilized physical assets such as buildings or facilities). In fact, a new business model has been introduced recently to smart cities, known as “shared economy”. The shared economy is a socioeconomic system that enables intermediary exchanges of goods and services between people and/or organizations, which boosts productivity and leverages underutilized resources to maximum potential. However, one of the inherent issues hindering the wide adoption of shared economy systems is the lack of trust between the providers and users of such systems. To this end, this study focuses on long-term shared properties/buildings and proposes an intelligent, IoT-enabled device and dynamic pricing model to address the issue of information asymmetry. First, 10 indicators were identified to assess the condition of the shared property. Next, multiple sensors were used, calibrated, and integrated into an IoT-enabled sensing device where the collected data was combined using intelligent sensor fusion technologies in a real-time manner. Third, a survey was developed and distributed to examine the significance of the 10 indicators, and an innovative reliability index was created accordingly to reflect the overall condition of the shared property. Fourth, a dynamic pricing model was developed to reward condition-conscious property users and penalize condition-unconscious ones. To ensure applicability and robustness of the proposed device and model, a pilot project was implemented in a smart long-term rental property in Newark, NJ, United States. Ultimately, this research provided insights on how to improve the operational efficiency of shared economy systems by offering (1) the providers of shared properties visibility over the condition of their properties through real-time assessment of the user reliability, and (2) the users of shared properties assured safety and monetary incentives to maintain the shared environment in a good condition.

الملخص: أهداف البحث: تقيم هذه الدراسة في المقام الأول أنماط استخدام وسائل التواصل الإجتماعي بين ممارسو طب الأسنان العامون والمتخصصون في المملكة العربية السعودية. والهدف الثاني من هذه الدراسة هو تقييم تفضيلات وسائل التواصل الاجتماعي من المجموعة المختارة للترويج لممارساتهم ومدى الإحتراف المهني لديهم أثناء استخدام وسائل التواصل الاجتماعي. طرق البحث: تم تطوير استبانة اليكترونية وتوزيعها على أطباء الأسنان والمتخصصين المسجلين في المملكة العربية السعودية من خلال منصة الجمعية السعودية لطب الأسنان. وتتألف الاستبانة من أسئلة مغلقة مع اختيار إجابات محددة مسبقا وتشمل التركيبة السكانية، وأغراض استخدام شبكات التواصل الاجتماعي، والطرق التي قد تؤثر بها شبكات التواصل الاجتماعي على الاحتراف المهني. النتائج: استجاب ٢٣٨ من ممارسي طب الأسنان العامين واختصاصي طب الأسنان من مختلف الأعمار. وأظهرت البيانات أن ٤١٪ من المستجيبين يستخدمون وسائل التواصل الاجتماعي بالتساوي للأغراض الشخصية، والمهنية، والأعمال. وكان برنامج الإنستجرام هو الأكثر استخداما على منصة وسائل التواصل الاجتماعي للإعلان حيث يعتبر من أقوى وسائل الإعلام بين المستجيبين. نادرا ما نشر ٤٣٪ من المشاركين الحالات المرضية على وسائل التواصل الاجتماعي. ومع ذلك، لوحظ تباين كبير بين التخصصات. الاستنتاجات: الاستخدام غير الملائم لوسائل التواصل الاجتماعي يمكن أن يؤدي إلى قضايا أخلاقية تتعلق بخصوصية المرضى وحماية البيانات التي قد تؤثر سلبا على مهنة طب الأسنان. لذلك، يجب وضع ارشادات وسياسات يمكن أن تنظم استخدام وسائل التواصل الاجتماعي لتبادل البيانات السريرية من قبل المتخصصين في طب الأسنان. Abstract: Objective: This study primarily assesses the social media use patterns of general dental practitioners and specialists in KSA. To fulfil its secondary objective, the study evaluates the social media preferences of the selected cohort for promoting their practice, and their extent of professionalism while using social media. Method: An electronic questionnaire was developed and administered to all registered dentists and specialists in KSA through the Saudi Dental Association platform. The questionnaire comprised closed-ended items with a choice of predefined answers that covered demographics, reasons for using social media, and the ways in which social networking might affect professionalism. Results: A total of 238 general dental practitioners and specialists from various age groups answered the questionnaire. The data revealed that 41% of the respondents used social media equally for personal, professional, and business purposes. Instagram was the most commonly used social media platform for dental practice promotion, and also regarded as the most powerful platform by all respondents (p = 0.0009). Thirty-four percent of the respondents rarely posted their own clinical cases on social media. However, a significant difference was observed amongst the specialities (p = 0.01). Conclusion: Inappropriate use of social media can cause ethical issues regarding patient confidentiality and data protection that may lead to negative perceptions of dental professionalism. Therefore, guidelines and policies should be established to regulate dental practitioners’ use of social media for sharing clinical data.

The purpose of this study was to investigate the relation between selected demographic and clinical characteristics and quality of life (QOL) scores in patients with end-stage renal disease who receive dialysis. We conducted the study at one hemodialysis (HD) unit in Bahrain from May 2018 to July 2018. We used standard QOL Index (QOLI) score instrument in Arabic form. This study included 100 patients (66 men and 34 women), aged 22 to 80 years on treatment with maintenance HD for four to 190 months. Inclusion criteria were as follows: those aged >18 years with no severe morbidities or psychological diseases and were on dialysis for at least three months. The following QOL scores were recorded: the health and functioning domain (64.8 ± 15.3), the social and economic domain (65.6 ± 14.1), the psychological/spiritual domain (74.9 ± 14.3), and the family subscale domain (75.9 ± 14.5). Male patients had reduced QOL though not statistically significant and younger patients had better QOL scores. The QOL scores revealed a decreasing trend with decreasing level of education, and they were higher among those who were not working and stayed at home. In addition, the family subclass scores were significantly higher among the married patients. Correlations between the demographic characteristics and QOL scores showed that there was a significant negative correlation between family domain and educational level and marital status, while there was a significant positive correlation between residence and psychological domain. Age, gender, marital status, residence, ethnicity, education level, employment status, income, and duration on HD nonsignificantly affected one or more domains of QOLI scores in such patients. Adequate management of these factors could influence patient outcomes.

Context: Falls cause significant morbidity and mortality, constituting 38.9% of trauma visits to the emergency department (ED) in Lebanon. Elderly have increased risk of falls due to co-morbidities. Injury-related deaths are most common in developing countries, and few studies have examined falls internationally. Aims: Describe characteristics, injury patterns, and outcomes of elderly treated for fall injuries at a tertiary care center in Lebanon. Settings and Design: Retrospective observational chart review of elderly presenting after a fall to the ED. Subjects and Methods: Retrospective observational study of elderly (≥65 years) patients who presented to the ED at a tertiary care center in Lebanon with the chief complaint of “fall” over a 6-year period. Statistical Analysis Used: Descriptive analysis. Results: Two hundred and thirty-five patients were included; mean age was 78.1 (±7.2) years with female predominance (60.5%). Falls occurred at home (99.2%) and from ground level (96.4%). Patients presented by private transport (85.8%). The initial impact was to the head in 31.2% of patients with 47.8% on antiplatelet/anticoagulation therapy. Imaging includes extremity X-ray (46.6%) and head/cervical spine computed tomography (39.5%). Dispositions included home (58.9%), regular floor (23.3%), operating room (7.9%), and intensive care unit (5.9%). Pelvic/hip repair was the most common surgical procedure. Most injuries were nonlife-threatening. Overall mortality was 2%. Conclusions: Falls have a high impact on the elderly population in Lebanon, with most occurring at home, resulting in pelvic/hip injuries and a mortality of 2%. There is a need to implement multifaceted fall prevention programs to mitigate such injuries and improve patient safety and outcomes.

There has been a renewed interest in accurately forecasting the price of crude oil and its fluctuations. That said, this paper aims to study whether the price of crude oil in the United States (US) could be predicted using the stock prices of the top information technology companies. To this end, time-series data was collected and pre-processed as needed, and three architectures of computational neural networks were tested: deep neural networks, long-short term memory (LSTM) neural networks, and a combination of convolutional and LSTM neural networks. The findings suggest that LSTM networks are the best architectures to predict the crude oil price. The outcomes of this paper could potentially help in making the oil price prediction mechanism a more tractable task and in assisting decision-makers to improve macroeconomic policies, generate enhanced macroeconomic projections, and better assess macroeconomic risks.

Project bundling has been introduced as an innovative approach that groups several infrastructure projects into a single contract. Project bundling has numerous benefits such as expediting project delivery, capitalizing on economies of scale, and reducing the overall contract cost. However, agencies implementing project bundling also face some challenges, one of which is assessing the feasibility of a certain project delivery method (PDM) of interest. While different PDMs could be used for bundled projects, design-build (DB) has attracted particular interest from project owners as an alternative, innovative PDM due to its numerous benefits related to project performance. While previous research efforts examined different aspects of project bundling in terms of its decision-making factors, opportunities, and challenges, no previous research effort was devoted to studying the feasibility or applicability of the DB delivery method for bundled projects. To that extent, and to fill this gap, this paper develops a scoring framework that assesses the feasibility of the DB delivery for bundled projects. First, a questionnaire survey was distributed to industry experts to quantify the importance of 25 project bundling objectives. Second, principal component analysis (PCA) was implemented to calculate a weight for each project bundling objective. Third, a score for each project bundling objective was calculated and the DB feasibility tiers were identified using a series of statistical tests. Finally, a user-friendly feasibility scoring framework was developed to assign a feasibility score for the DB delivery method based on the user's inputs related to the bundled project of interest. The results showed that the key project bundling objectives that mostly increase the feasibility score of the DB delivery method for bundled projects are (1) Having specific scheduling, sequencing, staging, and phasing; (2) Meeting tight milestones or deadlines (timely completion of individual phases); and (3) Completing the overall project on schedule. Ultimately, this research adds to the body of knowledge by equipping agencies and project owners with a decision-support system that helps them make the go/no-go decision for the DB delivery method for their bundled projects. By making the right PDM decision, project owners can enhance their bundling practices (especially in relation to the PDM selection), reduce the associated risks and challenges, improve the overall schedule of the bundled program, and keep the cost within the identified budgets. [ABSTRACT FROM AUTHOR]

Amid escalating global challenges such as population growth, pollution, and climate change, access to safe and clean water has emerged as a critical issue. It is estimated that there are 4 billion cases of water-related diseases worldwide that cause 3.4 million deaths every year. This underscores the urgent need for efficient water quality monitoring and assessment. Traditional assessment techniques include laboratory-based methods that are manual, costly, time-consuming, and risky. Although some studies leveraged Internet of Things (IoT)-based systems to examine water quality, they only relied on a limited number of water quality parameters (and thus do not offer a comprehensive and accurate water quality assessment), mainly due to the technical difficulties to integrate multiple sensors to a single device. In fact, due to the issues of multimodality, heterogeneity, and complexity of data, the interoperability among sensors with various measurements, sampling rates, and technical requirements makes it very challenging to seamlessly integrate multiple sensors into one device. This study overcame these technical challenges by leveraging multisensor data fusion capabilities to develop an intelligent cloud-based IoT multimodal edge sensing device to provide an automated, real-time, and comprehensive assessment process of water quality. First, a total of nine water quality parameters were identified and considered. Second, the sensing device was designed and developed using an ESP32 embedded system, which is a low-cost, low-power system on a chip (SoC) microcontroller integrated with Wi-Fi and dual-mode Bluetooth connectivity by fusing data from six different sensors that measure the nine identified water parameters on the edge. Third, the overall water quality was evaluated using the National Sanitation Foundation Water Quality Index (NSFWQI). Fourth, a cloud-based server was created to publish the data instantly, and a graphical user interface (GUI) was developed to provide easy-to-understand real-time visualization and information of the water quality. The real-world applicability and practicality of the developed IoT-enabled sensing device was tested and verified in a pilot project (i.e., a case study) of a building located in Newark, New Jersey, for a duration of 6 months. This paper adds to the body of knowledge by being the first research developing a single IoT-enabled device that is capable of reporting NSFWQI in real-time based on 9 water quality indicators encompassing both physical [temperature, total dissolved solids (TDS), turbidity, and pH] and chemical [potassium, phosphorus, nitrogen, dissolved oxygen (DO), and 5-day biochemical oxygen demand (BOD5)] parameters. Thus, this study serves as a multifaceted improvement across different dimensions, fostering healthier, more efficient, and technologically advanced environments. [ABSTRACT FROM AUTHOR]

Project bundling is an innovative project-delivery approach that bundles and groups different infrastructure projects into a single contract. Project bundling provides numerous opportunities and benefits for agencies and states while maintaining, rehabilitating, and repairing their infrastructure assets. Although previous research provided insights on some aspects of project bundling, none have identified the success factors needed to enhance the performance of bundled projects after the project bundling decision has been made. This study aims to fill this gap through identifying, studying, and prioritizing the success factors needed to efficiently bundle several infrastructure projects together. First, a survey was developed and distributed to numerous experts to examine the likelihood of occurrence and relative impact of 25 success factors. Second, the reliability of the survey and its results were assessed and validated using internal and external reliability assessment measures. Third, various statistical analysis tests were performed to examine the alignment between the perspectives of different project stakeholders in relation to the various project-bundling success factors. Fourth, the criticality of the different project-bundling success factors was quantified. Fifth, the success factors were ranked and prioritized to identify the key and most critical factors. The results showed that the most critical project-bundling success factors are (1) having well-defined design features; (2) having a complete project design prior to construction; (3) requiring prior knowledge or experience with similar project size and scope (by the contractor and the design agency); (4) having clear design control requirements; and (5) maintaining constant coordination and communication between all project stakeholders. This study adds to the body of knowledge by quantifying and studying the criticality of different success factors needed to enhance the performance of bundled projects. This study also provides decision-makers with the required knowledge and guidance on the key success factors that influence project-bundling performance. [ABSTRACT FROM AUTHOR]

Construction firms face considerable challenges in relation to finding cost-effective formwork solutions to meet increased construction demands. Project stakeholders have relied on self-consolidating concrete (SCC) to speed up the construction time because SCC is highly fluid and has numerous advantages compared to traditional concrete. To withstand SCC's high fluidity, formwork systems should be robust. Although previous research has experimentally examined various characteristics of SCC, few research studies have used machine-learning algorithms to estimate or predict the lateral pressure exerted by SCC on formwork systems. Hence, this study addressed this knowledge gap by proposing a machine-learning approach to predict the lateral pressure of SCC on vertical formwork systems. First, laboratory tests were performed to collect data on lateral pressure measurements, material factors, placement conditions, and formwork characteristics affecting the SCC lateral pressure on formwork systems. Second, four supervised machine-learning algorithms were considered in this study: k-nearest neighbor (KNN), artificial neural network (ANN), decision tree (DT), and random forest (RF). Third, the hyperparameters of the machine-learning algorithms were tuned, and their performance metrics were compared. Fourth, the most accurate predictive machine-learning model was verified on an unseen testing set. The results showed that the RF machine-learning algorithm was the best model for predicting the lateral pressure of SCC on formwork systems, with a mean percentage error of 0.8%, a mean absolute percentage error of 4.29%, and a coefficient of determination R2 of 0.9548. This study adds to the construction engineering and management body of knowledge by developing a machine-learning predictive model that can be used to accurately assess the lateral pressure exerted by SCC on formwork, which helps to ensure safe design of formwork systems and economic construction operations in formwork-related activities. [ABSTRACT FROM AUTHOR]

The construction industry has witnessed unprecedented disruptions in the supply chain (SC) over the past four years due to the consecutive impacts of the 2018 steel and aluminum tariffs, the COVID-19 pandemic, and the Russian–Ukrainian war. SC disruptions have been linked to price escalations, the management of which varies across different construction contracts. Thus, there is a timely need to understand the contractual implications of price escalation clauses. This article fulfills this research requirement by following an interdependent research methodology. First, the authors analyzed and compared price escalation provisions under various US-based, international, and UK-based standard design–bid–build contracts. Second, the authors examined legal cases that have arisen due to disputes over price escalation-related matters. Third, based on the contractual and legal analysis, the authors formulated and proposed a set of contractual considerations that can be used to plan and manage the contractual implications arising from triggering price escalation clauses. The findings indicate substantial variability in contractual provisions addressing price escalation. A predominant approach entails specifying a fixed contract price, often with a general exception permitting adjustments related to legislative changes. Certain standard contracts afford flexibility through the incorporation of supplementary clauses or amendments during the contract formation stage to counteract escalation risks. Further, insights from the legal review show that judicial relief from contractual obligations is typically granted solely in instances of unforeseen and severe economic conditions. This research makes a significant academic contribution by advancing the understanding of contractual obligations concerning price escalation, especially in the context of ongoing market disruptions. Ultimately, the findings of this study will impact the construction industry by promoting more balanced contractual practices regarding price escalations in construction projects. [ABSTRACT FROM AUTHOR]