Hadhramout University

Building Information Modeling (BIM) is considered a crucial technological innovation that should be embraced. While BIM adoption has progressed among large firms, its implementation within Small Medium Enterprises (SMEs) remains limited, particularly in developing countries where SMEs dominate the construction sector. Construction SMEs face unique constraints, including limited financial resources, fragmented project teams, restricted technical capacity, and lower organizational readiness, making BIM adoption both critical and challenging. The aim of this research is to investigate the challenges and key success factors for BIM implementation from Malaysian SMEs. A survey was distributed to 590 construction firms, resulting in 268 usable responses. The results showed that only 13% of respondents reported using BIM in their building projects, with the majority (76%) citing complicated legal framework, lack of standardized BIM processes, absence of affordable training, low levels of trust and fragmented team. For effective Implementation of BIM, the top critical success factors included early involvement and participation of project teams, availability of information and technology, and early selection of appropriate BIM tools. The outcomes provide targeted insights for SMEs and policymakers by offering empirically validated guidance to support BIM adoption in sustainable building projects. While the study is based on Malaysian context, the results are relevant to other developing nations with SME-dominated industry facing similar institutional and technological conditions. The findings provide targeted insights for SMEs, policymakers, and industry stakeholders by offering empirically validated guidance to support BIM adoption in sustainable building projects.

Abstract Pennahia aneus is a commercially important demersal sciaenid fish found in the Indo-Pacific region, yet its population structure in Malaysia remains insufficiently documented. This study aimed to differentiate four populations of P. aneus in Peninsular Malaysia and Borneo using morphometric multivariate analyses. A total of 423 samples were obtained from 22 landing sites across the South China Sea, Celebes Sea, Sulu Sea, and Strait of Malacca. Eleven morphometric characteristics were measured and used for the analyses. Principal component analysis (PCA) revealed minimal variability in body shape and size due to significant overlap among groups. Hierarchical cluster analysis (CA) identified two distinct morphological groups: the South China Sea population and the Strait of Malacca-Celebes-Sulu Sea population. This classification was reinforced by discriminant function analysis (DFA) and uniform manifold approximation projection (UMAP). The most distinctive morphometric traits for differentiating P. aneus populations were eye depth (ED), snout length (SnL), caudal peduncle depth (CPD), and head length (HL). The classification accuracy for these populations was 71.65%. This study provides the first comprehensive insight into the structured population of P. aneus in Malaysia, offering valuable information for conservation and sustainable resource management. However, molecular validation is necessary to refine the population structure further and strengthen effective management strategies.

Lightweight concrete effectively maintains structural integrity while subtly reducing the load imposed by traditional dead load limits. The current study aims to investigate the synergistic effects that can result from combining silica fume and aluminum powder in lightweight concrete. Silica fume was added to replace OPC because it has a lower density, significantly reducing the overall density of the concrete. An experimental design approach was used to examine the combined effects of aluminum powder and silica fume. In concrete, silica fume was incorporated at varying proportions to replace cement: 0%, 5%, 10%, 15%, and 20%. As an aerating agent, aluminum powder was added at different proportions, including 0%, 0.1%, 0.2%, 0.5%, and 0.7%. A series of experiments was conducted to assess the fresh, mechanical, and durability characteristics of the concrete, all of which are critical for lightweight concrete. It was observed that adding aluminum powder reduces strength, while silica fume improves it. Specifically, 20% replacement of OPC with silica fume increased compressive strength, split tensile strength, flexural strength, and modulus of elasticity by 7.64%, 5.68%, 4.40%, and 3.30%, respectively. It was also found that adding aluminum powder and silica fume decreases the dry density of the concrete. Models were developed using response surface methodology, and mathematical equations were created to predict response outcomes. All responses were optimized through multi-response optimization, and experimental validation was performed to confirm the optimized results.

BackgroundInfant health is profoundly influenced by socioeconomic factors, parental lifestyle, and prenatal care. Understanding the critical role of all these factors can guide targeted public health interventions to reduce infant morbidity and mortality.AimsTo investigate the impact or association of various maternal and paternal factors, including periconceptional care, pregnancy-related health conditions, antenatal care, smoking, radiation, nutrition, SARS-CoV-2 infection, and COVID-19 vaccination, on infant health in Egypt, Palestine, Yemen, and Jordan.MethodsA cross-sectional study was conducted among 445 mothers from August 2024 to October 2024 using a pretested and well-structured questionnaire. A well-trained physician conducted a face-to-face interview to collect data. Statistical analysis was performed to identify significant associations.ResultsThe mean ±SD maternal age was 27.72 ± 6.4 years, and the paternal age was 32.35 ± 7.25 years. Most mothers were Palestinian (34.8%) and Egyptian (26.7%), with 62.7% residing in urban areas. Key findings revealed that smoking (P = 0.042), inadequate intake of folic acid during pregnancy (P = 0.003), and non-prescription drug use (P = 0.008) were significantly associated with infant diseases. High income levels (P < 0.05) and routine prenatal visits (P = 0.03) showed significant associations with healthy infants. Chronic parental illnesses, being unaware of pregnancy for a longer time, hyperemesis gravidarum, and maternal COVID-19 during pregnancy were all important factors that were linked to a higher incidence of infant diseases (P = 0.05).ConclusionThis study highlights the importance of socioeconomic factors, healthy parental lifestyle, and prenatal care in improving infant health outcomes. Public health initiatives should focus on promoting awareness of maternal health, early medical intervention, and socioeconomic support to enhance maternal and infant well-being. To explore the long-term impacts of these factors and develop targeted strategies for vulnerable populations, further research is necessary.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12889-025-23462-0.

Epidermal Growth Factor Receptor (EGFR) plays a critical role in the development of several cancers. Thus, modulation/inhibition of EGFR activity is an appealing target of developing novel cancer therapeutics. With the advent of modern machine learning technologies, it is now possible to simulate interactions with high precision between EGFR and small molecules to predict inhibitory/ modulatory activity at an unprecedented scale. In this work, we propose a novel machine-learning method to fast and precise classification of small compounds that are active, intermediate or inactive in inhibiting/modulating EGFR activity. We developed DeepEGFR, a novel multi-class graph neural network (GNN) model, to classify compounds into Active, Inactive, and Intermediate functional categories. DeepEGFR leverages complementary molecular representations, combining SMILES strings and molecular fingerprint matrices (Klekota-Roth and PubChem) to capture both structural and property-based features of compounds. The model constructs an advanced molecular graph representing atom type, formal charge, bond type, and bond order, through nodes and edges. DeepEGFR achieved superior performance compared to baseline machine learning algorithms (e.g., SVM, Random Forest, ANN), with approximately 94% F1-scores across training and test datasets for all activity classes. To ensure interpretability, the top 20 features identified by DeepEGFR were validated against the five key characteristics of FDA-approved EGFR inhibitors (Afatinib, Gefitinib, Osimertinib, Dacomitinib, Erlotinib), confirming the biological relevance of the features. Moreover, DeepEGFR successfully identified 300 underexplored EGFR-targeting compounds, demonstrating its potential to accelerate the discovery of therapeutic agents. These results highlight the effectiveness of graph neural networks in advancing molecular activity classification, setting a potential new benchmark for EGFR inhibitor prediction. These findings demonstrate the DeepEGFR’s ability to highlight the promising EGFR inhibitors, that have received limited prior investigation, thereby supporting its role in facilitating the rational development of targeted therapies for precision oncology.Supplementary InformationThe online version contains supplementary material available at 10.1038/s41598-025-22126-8.

Perioperative bleeding is a significant concern in hepatic surgeries, leading to increased morbidity, blood transfusions, and associated risks. Tranexamic acid (TXA) is effective in reducing blood loss in various surgical procedures, but its efficacy in liver surgeries remains uncertain. PubMed, CENTRAL, Web of Science, Embase, and Scopus were systematically searched without any automated filters through 20th October 2024. Continuous data were reported in mean difference (MD) with 95% confidence interval (95% CI), and dichotomous data were reported in odds ratio (OR) with 95% CI. STATA Corp M17 was used to analyze our outcomes. Six RCTs were analyzed, including 1,618 patients undergoing liver surgeries (resections or transplants). TXA did not significantly reduce the need for postoperative blood transfusion (OR 0.72; 95% CI [0.35-1.47], p = 0.37; I2 = 52.9%). TXA also showed no significant effect on intraoperative RBC units (MD - 1.31; 95% CI [-3.41 to 0.78], p = 0.22; I2 = 72.14%). No increased risk of thrombotic events (OR 1.68; 95% CI [0.98-2.88], p = 0.06; I2 = 0%) or mortality (OR 1.05; 95% CI [0.57-1.91], p = 0.88; I2 = 0%) was observed. TXA did not significantly reduce blood loss or hospital stay duration. TXA demonstrates no significant benefit in reducing perioperative bleeding or transfusion requirements in hepatic surgeries. It might be safe, with no increased thrombotic risk, but its clinical utility in this surgical context remains questionable. Further large-scale RCTs are needed to clarify its role in liver surgeries.

Software refactoring is a crucial practice in modern software development methodologies, such as Agile and DevOps, as it enables teams to iteratively improve and evolve their codebases while minimizing the risk of introducing bugs or regressions. It fosters a culture of continuous improvement and code hygiene, ultimately leading to more robust, maintainable, and scalable software systems. However, research examining the impact of refactoring on code effectiveness is scarce. This study, therefore, seeks to investigate the impact of refactoring methods on the code’s effectiveness. The study was carried out in four distinct phases: refactoring methods selection, case study selection, software metric selection for evaluating the effectiveness of the code, and refactoring methods implementation. The five most prevalent refactoring methods (Extract Subclass, Extract Class, Introduce Parameter Object, Extract Method, and Move Method) were chosen and implemented in the jHotDraw case study. The refactoring methods were implemented 86 times across five experiments in the jHotDraw case study. The results indicate that Extract Subclass, Extract Class, and Introduce Parameter Object have a significant positive impact on code effectiveness, while Extract Method and Move Method do not affect code effectiveness. Practitioners and software designers can utilize this knowledge to make informed assessments regarding refactoring methods and produce software systems that are more reliable and effective.

Abstract Disclosure: M. Kakakhel: None. S. Cheema: None. R. Haider: None. M. Filal: None. A. Ullah: None. M.U. Hussain: None. M.A. Sadiq: None. T. Asghar: None. F. Arshad: None. N.K. Binashikhbubkr: None. H. Jawad: None. A. Abdullah: None. M. Qadri: None. A. Qadeer: None. M. Khawar: None. H. Ahmad: None. F. Ahmed: None. R. Alcaraz: None. Background: Hypertension is a major global health issue, affecting nearly half of U.S. adults. It is a leading risk factor for cardiovascular diseases like stroke, heart attack, and heart failure. Additionally, it is often linked to endocrine disorders, which can result in secondary hypertension. Endocrine disorders contributed to a concerning 2,383,332 deaths in the United States between 1999 and 2020, with many of these individuals having underlying hypertension. Methods: Death certificate data for adults aged 25 and older were obtained from the CDC-WONDER database. Crude mortality rates (CMR) and age-adjusted mortality rates (AAMRs) per 100,000 individuals were computed. Temporal trends were analyzed by calculating the annual percent change (APC) and the average annual percent change (AAPC) in the rates using Joinpoint regression analysis. Results: The age-adjusted mortality rate (AAMR) rose sharply from 10.7 (95% CI:10.6-10.9) in 1999 to 24.9 (95% CI: 9.5 to 56.7) in 2001, then continued to increase steadily to 36.5 (95% CI: 0.6 to 2.1) by 2018. From 2018 onwards, the rate spiked significantly, reaching 51.7 (95% CI: 9.3 to 23.5) in 2020, which coincided with the COVID-19 pandemic. Men had higher overall AAMR i.e. 36.6 as compared to women 28.4 during the span of this study. Stratifying by race, Non-Hispanic Blacks or African Americans had the highest overall age-adjusted mortality rate at 64.4 vs non-Hispanic whites, who had the lowest rate at 27.6. Southern states exhibited the highest mortality rates among the census region followed by the Western, Midwestern, and Northeastern regions. In contrast, the Annual Mortality Rates (AAMRs) displayed similar patterns across all regions. Regarding age, people aged 85 and above had the highest mortality rate among all the age groups while ages 25-34 had the lowest. Conclusion: Endocrine disorders associated with underlying hypertension showed an increasing trend throughout the study period, peaking during the COVID-19 pandemic. These findings account for immediate targeted interventions directed at the most vulnerable demographic and geographical groups Presentation: Monday, July 14, 2025

The asymmetric unit of the title compound, C3H4N4O2, contains two coplanar mol-ecules (A and B) completely located on mirror planes. In the crystal, N-H⋯O, N-H⋯N, C-H⋯O and C-H⋯N hydrogen bonds link the mol-ecules into sheets parallel to (010). There are neither significant π-π nor C-H⋯π(ring) inter-actions. Hirshfeld surface analysis indicates that the most important contributions to the crystal packings of mol-ecules A and B are from H⋯O/O⋯H (32.4% for A, 30.1% for B), H⋯N/N⋯H (28.2%, 31.5%) and H⋯H (12.3%, 8.0%) inter-actions.

Rationale:Acquired methemoglobinemia, a rare condition, occurs due to the presence of elevated methemoglobin levels in the blood, leading to tissue hypoxia. Dapsone, commonly used in dermatological conditions, can induce methemoglobinemia. This study is important as acquired methemoglobinemia, especially induced by dapsone, is a rare but life-threatening condition. The aim of this case report is to highlight its clinical presentation and the importance of prompt diagnosis and treatment.Patient concerns:A previously healthy 16-year-old female presented with acute cyanosis, dyspnea, palpitations, and headache 1 day after initiating dapsone 200 mg for acne. On examination, she was hemodynamically stable but had central and peripheral cyanosis. Oxygen saturation was 83% despite supplemental oxygen. Cardiopulmonary and neurological examinations were unremarkable.Diagnoses:Laboratory tests, including complete blood count, renal function tests, liver function tests, and electrocardiography, were within normal limits. However, arterial blood gas analysis revealed a methemoglobin level of 17%, confirming dapsone-induced methemoglobinemia.Interventions:The offending agent was discontinued, and supportive oxygen therapy was initiated.Outcomes:Within 6 hours, the methemoglobin level decreased to 3%, with complete resolution of symptoms. The patient was discharged home with advice to avoid dapsone in the future.Lessons:This case focused on the importance of methemoglobinemia in a differential diagnosis for a patient with a history of drug use, including dapsone, who exhibits symptoms and cyanosis suggestive of tissue hypoxia. In such a patient, prompt care and appropriate action will have a favorable prognosis.