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Given the escalating apprehensions regarding climate change and environmental risks, the construction industry is confronted with the crucial task of guaranteeing the enduring structural robustness of buildings. Building Information Modeling (BIM) has emerged as an innovative tool to tackle these challenges effectively and enhance the performance of building structures processes by developing intelligent and sustainable structures. A comprehensive methodology was utilized to assess the relationships between the BIM factors and their impacts on smart and sustainable structure development by conducting a literature overview, quantitative analysis, exploratory factorial analysis (EFA), structural equation modeling (SEM), and predictive relevance findings. The findings show positive correlations between the implementation of BIM and the elements integral to smart and sustainable structure development. This study investigates the effects of BIM-driven environmental risk assessment, BIM-enabled energy efficiency, environmental performance, climate change adaptation strategies with BIM, and real-time monitoring and maintenance on the effectiveness of smart and sustainable structures development. The BIM-driven environmental risk assessment significantly impacts the sustainable and smart structures development with B = 0.360, followed by the real-time monitoring and maintenance with BIM with 0.316. This study provides the contemporary knowledge base by providing insights into BIM's transformative abilities in shifting sustainable and smart construction practices. The outcomes offer widespread insights to enterprise specialists interested in enhancing task effects and organizing sustainable and environmentally aware built surroundings. The growing popularity of BIM has implications for the future growth of the construction industry in phrases of ecologically smart and sustainable structure development.

Implementing Internet of things (IoT) technology in the context of intelligent buildings and infrastructure development has garnered significant attention within the construction sector. Nonetheless, the implementation of IoT could be improved by assessing various barriers. The purpose of this study was to examine the obstacles related to the adaptation of IoT techniques within the construction sector, as well as the effects on the advancement of intelligent building and infrastructure systems. The study employed a mixed-method approach involving exploratory factor analysis (EFA) and structural equation modeling (SEM) to determine six types of barriers: knowledge, technical, standardization, creativity, complexity, and economics. The study revealed that the implementation of IoT for developing smart construction and infrastructure in the construction sector was significantly influenced by all six constructs. The results of this study offer significant ramifications for the field. The study underscores the necessity for heightened consciousness and instruction regarding the advantages of implementing IoT. The study posits that the technical barriers, including interoperability, modernization of legacy infrastructure, and coordination and collaboration difficulties, require attention from the industry. The study highlights the significance of establishing industry-wide standards and protocols for implementing IoT and regulatory and legal frameworks. Finally, the study underscores the necessity for augmented funding and financing options for IoT endeavors. Subsequent study endeavors may expand upon the present findings by delving into the barriers encountered by alternative sectors and nations and assessing the efficacy of the suggested measures in this investigation.

In recent times, there has been a notable increase in the focus on the use of Building Information Modelling (BIM) within the Architecture, Engineering, and Construction (AEC) industry. This study aims to fill a notable void in the current body of literature by examining the connections between the implementation of BIM and the factors that influence it. Additionally, it investigates the resulting effects on collaboration, continuous improvement, data management, gradual adoption, standardisation, and the various dimensions of society, economy, politics, and technology. This study examines the impact of BIM adoption within the AEC sector, focusing on its external environment by using a Political, Economic, Social, and Technological (PEST) approach. Using a quantitative approach, data was gathered by means of a survey questionnaire that was delivered to a sample of 216 professionals in the AEC business, who were chosen using purposive selection. The results suggest that the deployment of BIM cooperation, continuous improvement, effective data management, gradual acceptance, and standardisation, leading to positive outcomes in several areas such as social, economic, political, and technical. These findings have significant consequences for professionals working in the field.

The growing demand for sustainable and energy-efficient buildings, particularly in the context of tall structures, has prompted increased attention to innovative solutions. Despite advancements in Building Information Modelling (BIM) technology, there exists a critical gap in understanding its comprehensive application for achieving net-zero energy consumption in tall buildings, particularly in the Malaysian construction industry. This research addresses this gap by presenting a novel strategy that integrates BIM technology with energy analysis tools for net-zero tall buildings in Malaysia. The aim of the study is to contribute valuable insights to the construction industry, policymakers, and researchers by conducting empirical research, utilizing case studies, validating the proposed framework, advancing sustainable design practices, and supporting the transition towards net-zero energy tall buildings in Malaysia. The methodology involves a three-phase approach, including qualitative analysis, a pilot survey, and a main questionnaire. Exploratory factor analysis (EFA) validates the categorization derived from qualitative interviews, while Partial Least Squares Structural Equation Modelling (PLS-SEM) assesses the convergent and discriminant validity of the measurement model. Hypotheses testing using bootstrapping establishes the significance of correlations between BIM deployment and key factors such as early design integration, enhanced energy efficiency, optimized system integration, predictive performance analysis, and validation of sustainable design. The research findings support the positive associations between BIM deployment and the mentioned factors, providing statistical significance through T-statistics and p-values. The implications of this research extend beyond the Malaysian context, offering valuable insights for architects, engineers, and stakeholders involved in designing and managing sustainable tall buildings. By addressing the identified gaps and leveraging BIM technology effectively, stakeholders can contribute to the construction of net-zero energy structures, aligning with global efforts towards sustainable and energy-efficient building practices.

In recent years, CAD/CAM technology has allowed indirect ceramic restorations to become a part of everyday chairside clinical practice. Therefore, the impact of different cavity-preparation designs on the fracture resistance of CAD/CAM fabricated ceramics was assessed in this study. Three designs of cuspal covering (none, palatal, and entire) and two widths of the occlusal isthmus (75% and 100% of the intercuspal distance) were used for the preparation of inlays and onlays to form six groups (n = 10/group). Moreover, thermomechanical cyclic loading was applied to every tooth under a chewing simulator. A universal testing machine was used to measure each group’s fracture resistance. The tested specimens were inspected for any signs of fractures and cracks to categorize failure patterns. Thereby, the values of fracture strength showed that there were statistically nonsignificant differences between the tested groups (p < 0.05). However, a significant difference (p = 0.01) was found between group 1 (inlays) (1950 ± 405) and group 6 (onlays) (3900 ± 770). Type III or type IV fracture modes were seen in the majority of the specimens. In conclusion, inlays and onlays made of zirconia using CAD/CAM technology were deemed reliable for restoring premolars, irrespective of the cavity-preparation design, except for inlays with a 75% intercuspal distance.

Project failure is a persistent challenge in the construction industry, rendering it one of the most demanding sectors. Many obstacles, including safety concerns, quality management issues, environmental preservation challenges, economic sustainability, privacy constraints, and legal regulations, weigh heavily on construction projects. However, a beacon of hope emerges in AI-powered drones capable of surmounting these challenges and paving the path to resounding project success. This study employed diverse methodologies, engaging subject-matter experts through interviews and conducting pilot and primary surveys. Our analytical arsenal featured Exploratory Factor Analysis (EFA) for the pilot survey and Structural Equation Modelling (SEM) for the primary survey. Our research revolves around a singular mission: elevating building project success by dismantling the barriers that have impeded the widespread adoption of AI-driven drones in construction. The study’s verdict is clear: privacy and legal constraints, coupled with economic and sustainability challenges, alongside human resource management dilemmas, constitute the formidable triumvirate obstructing the ubiquitous embrace of drones in construction. Yet, the impact of breaching these barriers reverberates far beyond overcoming these hurdles. It cascades into public health and safety, environmental conservation, quality management, and economic sustainability, culminating in an amalgam of enhanced Building Project Success. The implications of our findings are profound for the construction industry. They beckon the sector to confront and surmount the legal and regulatory barriers to adopting AI-based drones. A clarion call to invest in human resources to empower technology integration resounds. And, perhaps most importantly, it beckons the industry to embrace the profound economic and sustainability advantages of embracing these cutting-edge technologies. Furthermore, our study underscores that adopting AI-powered drones in construction is not merely about project success; it catalyzes fostering public health, safeguarding the environment, ensuring top-tier quality management, and fortifying economic sustainability. These interwoven facets illuminate the broader canvas of drone technology’s transformative role in construction.

BACKGROUND: Thrombosis and acute respiratory failure are among the leading causes of mortality in COVID-19 patients. The von Willebrand factor (VWF) is one of the main components in the blood coagulation system. It has been hypothesized that the increased VWF level results from vascular damage because VWF is stored in endothelial cells. Infection of endothelial cells with SARS-CoV-2 can stimulate the release of VWF. This study aimed to determine the level of VWF activity among the Saudi population affected by COVID-19 and investigate the correlation between VWF level and D-dimer level. MATERIALS AND METHODS: This is an analytical, retrospective, observational study conducted in a single-center tertiary hospital at King Fahad Military Medical Complex (KFMMC). A study sample of 80 hospitalized patients (aged ≥18 years) diagnosed with COVID-19 confirmed by nasopharyngeal SARS-COV was randomly included in this study. Frozen blood samples were used to measure VWF antigen (Ag) level and activity for all patients. Historical data on hemostasis markers such as platelets (PLTS), fibrinogen, and D-dimer were obtained retrospectively, as well as demographic and clinical data. RESULTS: Data of 80 patients were analyzed to assess VWF Ag level and activity in correlation to D-dimer level. The mean age of the patients was 58.3 (standard deviation 16.18), with nearly two-thirds being females (62.6%). The most common comorbidities were arterial hypertension (67.5%), diabetes (56.3%), and dyslipidemia (22.5%). Only 10% of patients were obese. The mean values of were 3.25 for D-dimer, 3.55 for fibrinogen, 226.4 for PLTS, 9.88 for white blood cell, 237.04 for VWF Ag, 253.21 for VWF activity, and 70.45 for C-reactive protein. Pearson's correlation coefficient revealed that the correlation between D-dimer and VWF Ag and D-dimer and VWF activity was statistically insignificant (P > 0.05). Only six patients had overt thrombosis, but this has no significant correlation with VWF Ag, activity, D-dimer, or platelet count. VWF Ag and activity were higher in intensive care unit (ICU) than non-ICU patients. However, it is not significant statistically. VWF Ag and activity were significantly higher in deceased patients than in survivors. CONCLUSIONS: The results of this study showed that there was no significant correlation between VWF Ag and activity with D-dimer among Saudi patients with confirmed COVID-19.

The potential of Industry 4.0 digitization practices to improve sustainability and enhance overall project performance has garnered significant attention in the construction industry. Nonetheless, there is a necessity for empirical investigations that delve into the particular factors and constructs that contribute to this achievement. This research aims to address the existing gap in the literature by examining the favorable consequences of Industry 4.0 digitalization techniques in the context of sustainable construction management. The research utilized a mixed-methods methodology, integrating exploratory factor analysis (EFA) and structural equation modeling (SEM), to examine survey data obtained from the construction sector in China. The survey questionnaire comprised constructs that pertained to sustainability, technology, design, functional aspects, resource management, and managerial efficiency. The concept of sustainability has been identified as the most significant factor in shaping sustainable construction practices. The findings presented herein contribute to the theoretical comprehension of the determinants that impact the execution of Industry 4.0 digitalization methodologies within the construction sector. The interrelated constructs that have been identified provide valuable insights for practitioners and policymakers seeking to utilize Industry 4.0 practices to achieve sustainability, enhance technology adoption, optimize design processes, streamline functional aspects, improve resource utilization, and increase managerial efficiency. Implementing these strategies can enhance project success and ensure long-term sustainability in the construction industry. This research adds to the expanding pool of information regarding the factors that lead to success in Industry 4.0 digitization practices within sustainable construction management.

Construction is dangerous, making safety management essential. Robotics process automation (RPA) can improve construction project risk management. RPA is hindered by several factors. This study examined the primary technical, economic, legal, privacy, and resource obstacles to RPA adoption for tall building safety management. The pilot survey comprised 161 Malaysian tall building specialists, while the full questionnaire poll included 231 experts. EFA and SEM analyzed the data. Technology, economics, legislation, privacy, and resources prevented RPA from managing tall building safety. Theoretical and empirical breakthroughs in construction safety management and RPA deployment prompted this inquiry. This study illuminates the main obstacles to employing RPA for tall building safety management. The results show where to spend time and money to eliminate the obstacles. The study’s management implications may benefit construction safety managers, project managers, and company owners. The findings may help the building industry plan RPA safety management in tall projects and overcome hurdles. This study contributes to construction safety management and RPA deployment theory by identifying and analyzing the main barriers to using RPA for safety management in high-rise buildings. This research can help solve the problems preventing RPA from being used in construction project safety management.