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To address road accident losses, there is a need to prioritize safety factors, especially in high-risk locations on the road network, toward assuring a sustainable transport system. This paper proposes an approach for quantitative risk assessments of safety factors in hazardous road locations and involves the integration of the Fuzzy logic model, the Analytic Hierarchy Process (FAHP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This new innovative method offers a way to prioritize and select safety factors associated with hazardous locations using a hierarchical structure. To demonstrate the applicability of this method, a case study was conducted in Egypt. The assessment process involved active participation by professionals through multiple expert meetings. This collaborative approach ensures that the assessment incorporates valuable real-world knowledge and experiences. It analyzed road safety hazardous conditions across various sections, including intersections, non-intersection sections, narrow bridge sections, and curve sections. The application of FAHP-TOPSIS enables the determination of weights for safety factors within each section, facilitating the evaluation of safety indices between them and ranking the safety hazard sections. The achieved analysis revealed that the hazard safety factor index is comparatively higher in curved sections compared to other types of sections. Light utility poles and road barriers significantly affected the hazard index. By utilizing this approach, governments may make informed decisions regarding the allocation of resources and the implementation of safety measures at hazardous road locations.

Construction projects face many risks that can impact cost, schedule, and quality. To prioritize the most critical risks, a multi-criteria decision analysis method like the analytic hierarchy process (AHP) is useful. AHP provides a structured framework to evaluate risks across different criteria and determine their overall priority. This enables focusing risk management efforts on the highest impact risks to cost, time, and quality. Construction projects in Egypt face many risks that can impact cost, schedule, and quality. This research applied a multi-criteria decision analysis method called the analytic hierarchy process (AHP) to identify and prioritize high-impact risks for construction projects in Egypt. The study considered criteria such as cost, time, and quality when evaluating risk factors. Statistical modeling illustrated the process of investigating and identifying the risk factor with the most significant potential impact. The findings indicate that the lack of clear delegation of responsibilities for professionals to allocate activities is the most critical risk factor for construction projects in Egypt. And, effective risk management should focus on mitigating this risk to avoid negative impacts to project performance.

Traditional Pavement Condition Index (PCI) assessments are highly resource-intensive, demanding substantial time and labor while generating significant carbon emissions through extensive field operations. To address these sustainability challenges, this research presents an innovative methodology utilizing Gene Expression Programming (GEP) to determine PCI values based on International Roughness Index (IRI) measurements from Iraqi road networks, offering an environmentally conscious and resource-efficient approach to pavement management. The study incorporated 401 samples of IRI and PCI data through comprehensive visual inspection procedures. The developed GEP model exhibited exceptional predictive performance, with coefficient of determination (R2) values achieving 0.821 for training, 0.858 for validation, and 0.8233 overall, successfully accounting for approximately 82–85% of PCI variance. Prediction accuracy remained robust with Mean Absolute Error (MAE) values of 12–13 units and Root Mean Square Error (RMSE) values of 11.209 and 11.00 for training and validation sets, respectively. The lower validation RMSE suggests effective generalization without overfitting. Strong correlations between predicted and measured values exceeded 0.90, with acceptable relative absolute error values ranging from 0.403 to 0.387, confirming model effectiveness. Comparative analysis reveals GEP outperforms alternative regression methods in generalization capacity, particularly in real-world applications. This sustainable methodology represents a cost-effective alternative to conventional PCI evaluation, significantly reducing environmental impact through decreased field operations, lower fuel consumption, and minimized traffic disruption. By streamlining pavement management while maintaining assessment reliability and accuracy, this approach supports environmentally responsible transportation systems and aligns contemporary sustainability goals in infrastructure management.

Canal rehabilitation improves water management and agricultural productivity but requires balancing immediate benefits with long-term sustainability risks. Unlike previous studies that focused mainly on water seepage and groundwater effects, this research takes a comprehensive approach by integrating environmental, social, and economic factors to create strategic guidelines for sustainable canal projects. This holistic method ensures that water infrastructure improvements optimize performance while maintaining ecological balance, supporting communities, and addressing water security challenges amid climate change and increasing demand. This research introduces a novel approach for conducting quantitative risk assessments of concrete-lined canals by combining Fuzzy logic, the Analytic Hierarchy Process (FAHP), and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS). This integrated framework allows for the effective identification and prioritization of key risk factors associated with concrete canal lining projects. To validate the methodology, the study applied it to a case study in Egypt. Risk factors were categorized and analyzed across three primary domains: environmental, economic, and social. Using the FAHP-TOPSIS approach, the study assigned weighted values to individual risk factors within each domain, enabling a comparative evaluation of risk indices and a systematic ranking of environmental, economic, and social considerations. The findings revealed that environmental risk domain had higher index values compared to economic and social domain. Notably, groundwater depletion emerged as a critical factor with a significant impact on the overall risk index. The research employs bow-tie analysis to thoroughly investigate the five most critical risk factors.

Seismic pounding occurs when adjacent buildings lack adequate spacing, exacerbated by Alignment eccentricity and horizontal irregularities of adjacent buildings. The seismic lateral oscillation of adjacent irregular buildings promotes a torsional response under earthquake excitation, moreover, the gap distances recommended in the regulations to prevent collisions are generally insufficient due to the pounding behavior complicated by irregularity of adjacent buildings. Hence, this research aims to evaluate the eccentric pounding effects on seismic response demands for adjacent irregular buildings with transverse alignment eccentricity. The displacement, inter-story drift, story shear force, and torsional rotation responses are investigated and compared for different levels of irregularity. Results findings reveal that increasing alignment eccentricity of adjacent buildings leads to greater lateral displacements in the rebound direction, reduced displacements in the impact direction, and increased torsional rotation of the buildings, consequently, promote eccentric pounding, higher eccentricity leads to greater horizontal floor displacements and twisting motions, which increases the chances of adjacent floors colliding.

Background This study aimed to investigate the possible association of LPCAT1- rs8352 genetic variant (single nucleotide change C to G) with the onset and severity of pediatric asthma. Additionally, the study examined the influence of LPCAT1- rs8352 genotypes on asthma-related biomarkers including blood eosinophils count (BEC), eosinophil cationic protein (ECP), high-sensitivity C-reactive protein (hs-CRP), and immunoglobulin E (IgE) and on lung function [forced expiratory volume in one second (FEV1) and the forced vital capacity (FVC)]. Patients and methods The study included ninety-six participant grouped into two groups: G1 (46 asthmatics) and G2 (50 healthy controls). ECP, hs-CRP, and total IgE serum levels were measured using their corresponding ELISA kits. Neonatal blood DNA was extracted using the Gene JET™ Whole Blood Genomic DNA Purification Mini Kit. Genotyping was performed by RT-PCR. Results A significantly higher proportion of individuals in G1 had the LPCAT1-rs8352 CC and GC genotypes compared to G2 ( p  < 0.001). Individuals with the CC genotype exhibited significantly more severe asthma, along with elevated levels of BEC, ECP, hs-CRP, and total IgE. Those with the GC genotype demonstrated a similar, though less severe, pattern, followed by individuals with the GG genotype. The FEV1 and FVC values showed the opposite trend, with individuals having the GG genotype exhibiting the highest lung function values. Conclusion The LPCAT1 -rs8352 allele C is associated with pediatric asthma onset and severity. Further research on the LPCAT1 genetic variants may provide a deeper understanding of pediatric bronchial asthma mechanisms and lead to improved management strategies.

In recent years, lightweight concrete has become very popular in the construction industry. And, its usage can lead to reduced costs and time. Therefore, different types of concrete (lightweight (LC), heavyweight (HC), and ordinary concrete (OC)) have been investigated to comprehend their response to earthquake load. Also, the comparison between their responses has been considered for getting the best response for various materials in construction work. The results prove that building models with LC are more resistant to earthquakes than the other types due to the reduction in the weight of buildings. Consequently, it has a role in resisting seismic forces. Furthermore, the combination of different concrete in the structural elements is another important criterion to be considered in thesis. The findings demonstrate that the responses in models for OCC-LCR (ordinary concrete for the column and light concrete for the roof) and LCC-OCR (light concrete column and ordinary concrete roof) have fewer values than the other types.

Background. Nonalcoholic fatty liver disease (NAFLD) is the commonest etiology of chronic hepatic problems in children with obesity. This study aimed to assess whether urinary C-peptide creatinine ratio (UCPCR) might be a potential indicator of NAFLD in obese children. Methods. The study included 240 children with simple obesity. Hepatic ultrasonic examination, anthropometric and laboratory measurements including fasting plasma glucose, fasting insulin, fasting C peptide, liver, renal profile, lipid profile, and UCPCR were obtained in all cases. According to the results of the hepatic ultrasonography, cases were classified into two categories, those with NAFLD (n=98) and without NAFLD (n= 142). Results. In cases with NAFLD, UCPCR was significantly higher than those without NAFLD (P &lt; 0.001). A significant positive correlation between UCPCR and waist circumference (WC SDS), triglyceride, fasting C-peptide, HOMA-IR and alanine aminotransferase (ALT) was found (P &lt; 0.001 for each). Adjusting for other variables, UCPCR was the most significant predictor of NAFLD in children with obesity with higher odds ratio (OR = 3.26) than fasting C peptide (OR = 2.87), triglyceride (OR = 1.89), ALT (OR = 2.20), WC SDS (OR = 1.32) and age (OR=1.27) . UCPCR cut-off value of 0.755 nmol/mmol was able to discriminate cases with NAFLD from those without NAFLD with a sensitivity of 95%, a specificity of 87%. Conclusions. We concluded that UCPCR is a useful, practical and non-invasive predictor of NAFLD in children with obesity with high sensitivity and specificity.

Adherence to either continuous positive airway pressure (CPAP) or bilevel positive airway pressure (BiPAP) therapy in patients with obstructive sleep apnea syndrome (OSAS) represents a real challenge to sleep medicine physicians. Many risk factors/predictors for nonadherence exist, and usually, it is multifactorial. Long-term nonadherence with CPAP therapy has been associated with the use of CPAP for <4 hours/night during early treatment, moderate to severe obstructive sleep apnea (OSA), poor self-efficacy, and unsupportive bed partner. The American Academy of Sleep Medicine (AASM) recommends follow-up of patients with OSA within the first two weeks of CPAP use to optimize adherence. Measures to improve adherence to positive airway pressure (PAP) therapy go through an integrated approach that involves behavioral therapy and prompt management of side effects. Pharmacologic therapy in the form of a sedative-hypnotic sleep aid has a minor role in managing nonadherence to CPAP based on the greater risk of side effects. This article will briefly discuss the risk factors and management of nonadherence to PAP therapy in patients with OSAS.

Delays are a common problem in the global construction industry, affecting the development of the road construction industry, particularly in developing countries. Where, the construction industry faces a lot of risk factors that can contribute to project delays, particularly during COVID-19. The road projects risk management framework was used to identify potential risk categories that could impede the success of road construction in Egypt. On the other hand, road construction in Egypt faces numerous challenges with increasing unexpected parameters throughout the project life cycle. In other words, unanticipated risk factors have a significant impact on the success of project execution. As a result, the study’s primary goals are to investigate the majority of the risk factors that cause road construction delays in Egypt. The impact of numerous risk factors has changed the delays in road projects as the COVID-19 pandemic spread across the world. As a result, the study incorporates previously unstudied factors. As well, the research has sought to investigate the new severity of risk factors during coronavirus infection. Moreover, risk breakdown structures have classified the risk factors into several categories. They include consultant risk, design risk, equipment risk, material risk, owner risk, contract risk, contractor risk, labor risk, external risk [coronavirus effects and others] and operational risk. The strategy employed in the paper is to incorporate the DEMATEL technique and risk analysis into the statistical model. Whereas the risk analysis prioritizes risk based on the evaluation of each specific project risk. Additionally, this approach has been able to create connections between risks, which may make it easier to understand the likelihood and severity of project risk than if the risks were just considered isolated events. Furthermore, the pilot survey is divided into two stages, the first of which is based on risk analysis to identify the most significant risks. As a result, the identification of the high-risk for each category has been researched. The second survey was issued to risk management by evaluating the importance of risk factors and creating causal relationships among components using the decision-making trial and evaluation laboratory (DEMATEL) approach. Finally, it is noticed that operational risk and external risk caused by the effects of the coronavirus have the greatest impact on the delay of road projects.