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Background: While improved student engagement has been highlighted as an essential goal and a major outcome of Problem and Project-Based learning (PBL), little empirical evidence has been provided regarding types and forms of student engagement. Material and method: The study explored forms of student engagement in PBL settings, drawing on empirical data of observations and group interviews with 23 project teams (116 students) in four different PBL undergraduate civil engineering courses at Qatar University. Results: The study identified four patterns of student engagement in a PBL setting. Participants reported significant indicators of the first two patterns - engagement as autonomy and as connection. Regarding the other two indicators, namely relational and emotional engagement, they reported positive yet slightly fewer indicators. Three factors were identified that influenced student engagement in a project teams, namely PBL types and its appropriateness to the nature of the course, students' prior experiences with PBL, and team dynamics. Conclusions: These results facilitate the establishment of an institutional framework supporting a progressive approach to embracing PBL. In this framework PBL implementation begins with diverse practices at the course level and has systemic change as its ultimate goal. This framework particularly aims to support an institutionalized approach to transition to PBL in a socio-cultural context (e.g., a non-western context) where instructors are as the primary and authoritative source of knowledge. The overall outcome of the study supports management of change from a lecture-based mode to PBL in a non-western context.

This study examined engineering students' initial readiness to transition to emergency online learning in response to COVID-19 in Qatar. A theoretical framework is proposed for understanding the factors influencing students' readiness for change. Sequential explanatory mixed-method research was conducted, with 140 participants completing an online survey, of which 68 also contributed written reflections and 8 participated in semi-structured interviews. Exploratory factor analysis displayed a four-factor structure, including initial preparedness and motivation for online learning, self-efficacy beliefs about online learning, self-directed learning online, and support. The qualitative outcomes supported the four factors and provided further insight into their varied and nuanced manifestation. In accounting for the perceived impact of the factors on readiness, significant differences were identified regarding pedagogical mode, with students enrolled in PBL courses reporting higher readiness than those from non-PBL courses. The practical implications for preparing students for future emergency online learning are discussed.

Background: This study investigated the development of engineering students' approaches to learning and views on collaboration in a PBL environment. Material and methods: An explanatory mixed research approach was employed with participants from four PBL-implementing engineering courses in Qatar and China. 197 students responded to two surveys, and 168 students participated in group interviews. Results: While the study reveals increased adoption of deep approaches to learning on team projects, little influence on surface approaches to learning was found. The study also provides evidence supporting the positive relationship between students' adoption of deep learning approaches and their acknowledgement of values of collaboration in teamwork. Conclusions: This study suggests that while PBL characteristics may support deep learning, certain factors may underpin surface learning, including a feeling of insecurity during first experiences with it, lack of skills, and assessment methods that favor surface learning. Further efforts on engaging students with PBL may benefit both deep learning and team effectiveness.

Background: Few studies have reported how students enact learner agency in a team setting or examined what elements of team settings students perceive as more supportive of their learning in problem- and project-based learning (PBL) processes. Purpose: This study explores how engineering students perceive their enactment of learner agency, particularly which aspects of the PBL process they find most important. Method: Thirty-nine students from two PBL civil engineering courses in Qatar participated in the study. Q methodology was chosen for both qualitative and quantitative data collection and analysis. A 40-item Q set based on a theoretical model of learner agency was used. Results: Eight significantly different student viewpoints emerged from the Q methodological factor analysis, indicating a range of individual perceptions of learner agency. Intrapersonal dimensions were highlighted by three of the eight viewpoints, behavioral dimensions were underlined by seven viewpoints, and environmental dimensions were valued by all viewpoints. Conclusion: While the results reveal a wide range of individual experiences with learner agency across the three dimensions, students addressed self-directed learning aspects both actively and passively, suggesting that many participants still value instructors' roles of providing direct instruction and authorized knowledge in PBL. The results highlight the need for more awareness of learner agency and more opportunities for students to enact learner agency by increasing PBL knowledge, skills, and efficacy. Q methodology can contribute to engineering education research by providing new theoretical and empirical insights into learners' subjective understanding of agency in a PBL setting as a complex system.

This qualitative longitudinal study explored three engineering instructors' professional agency in implementing project-based learning (PBL), including multiple sets of data (18 interviews, observations, and written reflections spanning three semesters). The results show that the instructors' care for students, interest in pedagogical innovation, and efforts in professional learning supported their confidence in stance, sense of agency, and competence in PBL practice. The efficacy and strong beliefs of the instructors further supported their agency-in-action regarding how they acted to influence their teaching by negotiating both its content and conditions. The study also revealed how individual resources and social conditions frame the enactment of professional agency and how the instructors developed agency and strategies to overcome challenging issues at work. Although they developed different types of agency, they demonstrated the same attitude towards resilience and negotiation for autonomy as well as the same engagement in self-empowerment and transforming their agentic competence into educational leadership.

Digital transformation (DT) is revolutionizing building facility management (FM) by streamlining operations, maximizing resources, and increasing performance. FM firms prioritize DT to stay competitive as speed and efficiency become more crucial in the corporate context. Traditional FM methods like manual record-keeping and reactive maintenance cannot meet recent corporate needs. Modern technologies such as IoT, AI, digital twins, and data analytics enable real-time building asset monitoring and optimization. This paper evaluates the digital transformation readiness level index of building facility management (DTRLIBFM), which includes critical success factors for DT development, using structural equation modeling (SEM). DTRLIBFM model determines the importance of key factors that contribute to the success of digital transformation initiatives, specifically focusing on the DT readiness level index of building facility management. Expert interviews and an intensive literature review were employed to identify the critical success factors for the DTRLIFMB. The Delphi technique was employed to validate these factors with 13 highly experienced professionals, and they were subsequently appraised for significance through an online questionnaire that was circulated to industry experts. To quantitatively evaluate the interconnectedness of different elements of DTRLIFMB and establish the impact of each construct on the overall digital transformation, data from 220 participants from around the world were analyzed using (SEM). The evaluation included reliability, validity, hypothesis testing, multivariate normality, and goodness-of-fit indexes. The DTRLIBFM model, with 20 indicators in three constructs, explains how DT readiness affects a building's digitalization importance level. The research provides governments, organizations, contractors, consultants, suppliers, subcontractors, and facility managers with a current DT index and DT roadmap for building facility management. [ABSTRACT FROM AUTHOR]

Construction projects play a vital role in the global economy. However, the construction industry still lags in the adoption of digital technologies which have the potential to alleviate inefficiencies. There is also a lack of construction professionals with skills to implement digital technologies, and the industry is plagued by inadequate research and development (R&D) and low productivity. This paper applies the Digital Transformation Readiness Level Index in Building Construction (DTRLIIBC) to investigate digital transformation in the construction industry, and specifically in the construction phase, by identifying technologies, alternatives, policy incentives to ensure best practices, and infrastructure needed to smoothly implement digital technologies. A survey was distributed to executive managers, department managers, project managers, senior engineers, and supervisors in the construction industry. Interviews were also conducted with 13 experts with more than 20 years of experience, using the Delphi method to ensure the validity and reliability of the factors identified as significant based on their experience and perspectives. This study thus assessed potential factors related to digital transformation, along with identifying factors enabling the use of the DTRLIIBC itself. Structural Equation Modeling (SEM) was employed to identify causal relationships among the variables while minimizing measurement errors, as SEM was considered a multiple regression analysis to improve the efficiency of the model. To ascertain the model's robustness and stability, a comprehensive evaluation was conducted that included tests for multivariate normality conformance, validity and reliability assessments, and accuracy evaluations to improve overall performance in the construction industry. The benefit of implementing SEM is its ability to provide a clear decision-making alternative as well as a potential vision for construction industry firms to improve efficiency and productivity in construction projects. [ABSTRACT FROM AUTHOR]

This study presents the development of a comprehensive model for evaluating the level of readiness of buildings for digital transformation during the pre-construction phase. The proposed model utilizes structural equation modeling (SEM) and includes a full list of key factors for achieving success. This tool is designed to support industry stakeholders in assessing operational efficiency in terms of digital transformation readiness in the pre-construction phase (DTRPC) and analyze the effectiveness and limitations of DTRPC across various management levels. Key success factors were identified through interviews with experts and a review of the relevant literature. These variables were then validated through two rounds of the 8 Delphi technique, which included the input of 13 highly qualified experts. Finally, an online questionnaire was disseminated to industry professionals, who assessed the factors' relative levels of significance. Questionnaire responses were collected from a sample of 300 individuals from different professional fields. SEM was then used to quantitatively analyze the relationships between the various components of the DTRPC success factors. The goal was to determine the impact of each construct on the overall level of readiness. The model underwent a thorough evaluation to determine its strength and stability across several parameters, including accuracy, conformity to multivariate normalcy, and reliability and validity. A hypothesis analysis was also conducted. The collected data were used to develop the proposed DTRPC model, consisting of 30 essential performance indicators grouped into four categories. The use of SEM uncovered a significant correlation between the operational indicators of these critical factors and the construct groups, as well as the influence of effective DTRPC constructs on overall project performance. This research expands the current knowledge by identifying important indications for evaluating the success of the DTRPC model and using them to create a comprehensive global SEM that can be used as a tool for measuring readiness at the pre-construction stage. This has the potential to provide essential assistance to organizations, project managers, and policymakers in making informed decisions. [ABSTRACT FROM AUTHOR]

The construction project information for FM team control and maintenance is vital. However, current practices indicate significant data drops during the handover stage, leading to rework during FM systems integration of inaccurate, delivered information. Although challenges in BIM implementation are well studied, there is a current lack of best practices from FM industry experts highlighting challenges with a specific focus on the areas of the data drop. Therefore, the aim is to develop a framework that can reduce data loss and improve data management. The objectives include robust literature review on challenges of information loss during handover phase, management and frameworks; Adopting case study and workshops to identify information loss challenges, framework development and validation with industry experts. This paper adopted a grounded theory approach to explore literature and conducted case studies, including a series of semistructured interviews and a workshop with FM industry experts. The findings show the areas and causes of information loss and how to manage them through the developed information loss management framework (ILMF). Practical Applications: With the start of any type of project, planning and establishing rules from the beginning facilitates the smooth transition between different phases. Similarly, in construction projects, this research provides guidelines on how facility managers can manage information loss when exchanged through projects' stages. Furthermore, with the continuing advancements in the construction world, the facility management should be equipped with management and leadership guidelines as presented in the proposed framework to reduce data loss during handover. However, there are cost and contractual issues that prohibit any involvement of the facility manager in early project stages. The results of this study provide an identification of professional practices do's and do not's that facilitate the management and development of projects with the support of the latest technologies in the market. Ultimately, developing a guide that adapts international standards. The study's contribution to knowledge includes the development of a new information loss management framework that adopts BIM and ISO standards after exploring the existing data management frameworks in the literature that lack data loss management as a focus. The framework works as a guide for various stakeholders such as designers, contractors with a focus on FM to facilitates data coordination and management to reduce information loss, its creation and validation were conducted in collaboration with industry experts. Furthermore, its novelty lies in integrating FM role, information management, information loss, address project life cycle, and adopts the ISO 19650 series. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid conceptual and performance assessment integrated dispute risk system that enables construction professionals to evaluate, track, and manage construction disputes. It establishes a correlation between dispute-contributing factors and their respective preconstruction stages, facilitating early dispute detection and mitigation before the construction phase. This method can be applied to gauge the effectiveness of the preconstruction phase in relation to its influence on the emergence of disputes. Through an extensive literature review, expert interviews, and the Delphi technique, 48 key risk factors were identified and categorized into four groups. Eighteen experts were selected using purposive sampling, and their survey responses were checked for normality and reliability using the Shapiro–Wilk test and Cronbach's alpha. The Delphi method was employed to reach a consensus among the panelists after two rounds of evaluation, using the nonparametric statistical parameters, such as Kendall's coefficient of concordance and chi-squared. Subsequently, the interrater agreement (IRA) was measured, and the dispute factors were ranked. Based on the ranking results, a novel integrated hybrid system was formulated that synergistically combines a hybrid conceptual and performance assessment framework with a fuzzy logic–structural equation model (SEM). The proposed hybrid system includes two key components: a unique conceptual and performance assessment framework and a hybrid model that combines fuzzy logic and SEM. This combined approach captures uncertainty and ambiguity in assessing dispute risks related to probability and severity, providing a more precise evaluation of disputes in construction projects. Additionally, the introduction of new dispute categories specifically targeting the preconstruction phase proactively deals with potential disputes before the construction begins. This advanced integrated hybrid system can be an effective preconstruction assessment tool for evaluating and managing various dispute factors, enabling project managers to proactively assess, manage, and mitigate construction disputes between project parties. [ABSTRACT FROM AUTHOR]

Smart buildings and cities are rapidly emerging as solutions to address the challenges of efficiency, urbanisation, and sustainability in the sector. The study proposes deploying data-driven digital twins for smart buildings by utilising the available building's technology and IT infrastructure to complement and augment existing functions. The digital twin will consist of a core data-driven energy model and a 2D visual representation of the building's systems, with the potential for future evolution into a 3D model. This study aims to present a preliminary investigation into the idea of data-driven digital twins in building management towards enhancing the operations of smart buildings and empowering the concept of smart cities. It is demonstrated on a building on the campus of Qatar University. With an emphasis on the air conditioning systems of the building, considering their substantial contribution to overall energy consumption, the study maintains an open approach to also encompass other energy systems within the buildings, and presents a comparative evaluation between simulation-based and data-driven modelling on the case study, as well as an exploration of various machine learning algorithms that can be used. Furthermore, exploring essential smart applications of the building's data-driven digital twin. Practical Application: The study provides a comprehensive exploration of the practical aspects of deploying data-driven digital twins for smart buildings, addressing challenges related to data collection, model development, integration with building infrastructure, and potential limitations. The paper aims to advance the field of facility management and promote smart and sustainable practices in building operations. By contributing to the existing knowledge in facility services and management, our study offers practical guidance towards optimising building performance, reducing energy consumption, and fostering sustainable urban development. [ABSTRACT FROM AUTHOR]

This study explores engineering students' enactment of collective agency and perceptions of professional identity. Empirical data were drawn from observation and group interviews with 30 engineering students in a civil engineering course using a problem and project-based learning (PBL) approach. Using the technique of quantifying qualitative data, the study identified patterns of agency manifestation in seven domains within project work: (1) motivation, (2) goal setting, (3) planning, (4) project progression, (5) self-reflection and evaluation, (6) team dynamics, and (7) external support and resources. The study identified a significant correlation between the engineering students' collective agency in these seven aspects of their learning process and their project team outcomes based on group-based project grades. Although students reported many reasons for choosing to study engineering, the majority of the students were found to have a general uncertainty regarding their sense of professional identity, suggesting more activities to support the building of professional competences, such as PBL, should be provided at an earlier stage of engineering curricula.

The rapid advancement of digital technology has enabled digital transformation across various sectors, including construction. The construction industry has long been associated with conventional, labor-intensive practices that can adversely influence the entire construction process. However, this culture is changing as key players in the sector are progressively identifying and embracing the vast opportunities and associated benefits of using digital tools and technologies to improve the performance and outcomes of the overall project lifecycle. To this end, this study uses the Delphi technique to identify 70 factors that contribute to the digital transformation of the construction industry, categorizing them into five groups: management, design, technology, policy, and infrastructure. Delphi analysis is used to examine the critical success factors for digital transformation identified in the literature and rate their importance during the preconstruction, construction, and facility management phases. Furthermore, this research results in the introduction of the Digital Transformation Level of Readiness Framework (DTRLF) to help facility management firms, clients, organizations, contractors, and designers comprehend the implementation of digital transformation within their respective domains and support decision-makers in establishing action to adapt related technologies in their respected project phases. [ABSTRACT FROM AUTHOR]

This paper presents the development of a comprehensive campus facility management performance assessment model (CFMPM). The model employs structural equation modeling (SEM) and incorporates a thorough list of crucial success factors. The CFMPM tool is intended for use by industry shareholders to evaluate the operational effectiveness of campus facility management (CFM) and analyze the proficiency and constraints of CFM organization across diverse managerial tiers. Key CFM success factors were collected using interviews with experts and relevant literature, validated using two rounds of the Delphi technique with 14 highly qualified experts, and disseminated via an online questionnaire to industry experts who rated them according to their significance. Data were obtained from 402 participants hailing from diverse regions. Then, SEM was used to perform a quantitative analysis of the interconnectedness between the various aspects of CFM performance, with the aim of ascertaining the influence of each construct on overall performance. The model was rigorously assessed for its robustness across several parameters, including goodness-of-fit measurements, multivariate normality tests, and reliability and validity tests, in addition to hypothesis analysis. The gathered data were used to construct a CFMPM comprising 45 key performance indicators of successful CFM grouped into seven different constructs. The application of SEM revealed a noteworthy correlation between the operational indicators of proficient CFM and the construct groups, in addition to the impact of efficacious CFM constructs on CFM performance overall. This research enhances the existing knowledge base by identifying vital indicators for the evaluation of CFM effectiveness and utilizing them to formulate an inclusive global SEM capable of serving as a tool for gauging the efficiency of CFM. This could lend valuable support for organizations, facility managers, and policy makers when making well-informed decisions. [ABSTRACT FROM AUTHOR]

Organizational resilience indicates the capacity of an organization or a system to return to its steady condition, or exceed it, after going through a disruptive event that disrupts its steady condition. Qatar's oil and gas sector has shown remarkable resilience during the COVID-19 pandemic due to its preparedness and readiness to deal with such a disruption. As a lesson learned from the recent COVID-19 pandemic, local governmental institutions need to support national preparedness and resilience to handle emergencies and unpredictable crises by learning from the successful model of Qatar's oil and gas sector. This study presents the key Resilience Engineering Indicators (REIs) that make this sector resilient and validates the six Resilience Engineering indexes or dimensions adopted, which include top management commitment, speaking up culture, learning, awareness, being prepared, and flexibility. The study evaluated the performance of these REIs using a 5-point Likert Scale survey questionnaire based on the relevance to resilience dimensions. The results show ten REIs contributing to the organization's resilience and the top four most important Resilience Dimensions (RDs). Moreover, this is the first study to evaluate and assess the organizational resilience level in Qatar's oil and gas sector. This study's results can be integrated into different organizations' strategies to improve the efforts to enhance the national response to disturbances in governance. [ABSTRACT FROM AUTHOR]

Public spaces play a significant role in improving social, recreational and cultural activities that are inclusive. However, smart public spaces are required to save time and costs, and to provide comfort to the public, ultimately enhancing livability. There are various user requirements and demands to respond to. This research aims to adopt intelligent technologies applied in public spaces to facilitate livability through urban facility management (UFM) involvement in improving livability. The establishment of intelligent systems in the architecture industry goes hand in hand with the growing advancement of science and technology in several aspects of human life. A fundamental key to the success of smart cities is the high quality of livability offered to their residents and visitors. The UFM can enable livability by providing data centers, access controls, integrated security systems, monitoring, smart waste, energy and water management in public spaces. This study focused on five elements of livability, including accessibility, functional infrastructure, interaction and social cohesion, amenity and participation, quality of life through safety and security and privacy. The research methodology adopts the activity theory (AT) as its underpinning theory for the qualitative data collection process (interviews and a workshop) from industry experts in two prominent smart cities in Qatar, Lusail and Msheireb, along with a literature review. This study's results provide information on existing smart city and public space features, infrastructures and their impact on livability. The findings of this study support the development of the smart livable public spaces (SLiPS) framework. The framework is a baseline for improving livability in smart cities, which allows future updates based on existing ICT infrastructure, enabling new functions and the availability of novel technology applied by UFM. The outcome of livability leads to the achievement of smart city goals. [ABSTRACT FROM AUTHOR]

Fast-track construction has recently become the prevailing construction approach globally. It enables owners and developers to make rapid returns on investment through shortened construction periods. This strategy has many effects on the industry; therefore, four groups of factors were studied in this project: (1) financial, (2) logistics and finance, (3) management, and (4) legal. A 22-question survey was distributed to 155 professionals in the construction industry, who evaluated the impact of the stated factors on a 5-point scale. The results revealed a high level of consistency determined through Cronbach's alpha, and a positive correlation was found by Spearman's rank coefficient. The Relative Importance Index was used to rank the factors based the evaluation by the professionals, resulting in the following impact ranking: (1) poor communication among design and construction teams, (2) large amounts of rework, (3) low quality of work by the contractor, (4) design errors, (5) late or insufficient payment according to terms agreed with the client, and (6) unavailability of materials in the market. By providing a quantitative RII model to evaluate fast-track project management performance with the use of corresponding performance indicators, this study will benefit industry practitioners and researchers as it identifies the most significant factors that impact fast-tract project management performance. [ABSTRACT FROM AUTHOR]

This paper presents a study on the effects of graphene nanoplatelets (GNPs) on the mechanical behavior of 3D-printed burnt clay, the most sustainable and green construction material, under constant printing parameters. Mixes with different nanofilament contents—0.1%, 0.2%, and 0.3% by clay weight—were printed and tested under compression and bending loadings. The results obtained on the printed samples were compared with those fabricated using the molding method. The samples' microstructures were then analyzed using a scanning electron microscope (SEM). Energy dispersive X-ray (EDX) analysis was employed to obtain the elemental distributions. The testing results were then statistically analyzed using a t-statistical method to investigate the impact of using GNPs on the properties of 3D-printed clay. Strength test results showed that mixes containing a low GNP content, i.e., 0.1 wt.%, attained higher compressive and flexural strengths than those containing higher contents, i.e., 0.2 and 0.3wt.%. The results additionally highlighted that the efficiency of GNPs was better observed in the printed samples rather than the molded ones, indicating that the printing process contributed to a better and more uniform dispersion of GNPs in the clay matrix. The t-statistical analysis confirmed that a significant improvement in compressive strength could be obtained using a GNP content of 0.1 wt.%, regardless of the fabrication method. On the other hand, significant flexural strength improvements were observed in the printed samples at all GNP dosages. Micrographs of GNP-modified clay supported the strength results obtained in this study. In summary, this research work signified the importance of using nanofilaments in 3D printing applications in order to achieve the desired elements' mechanical properties. [ABSTRACT FROM AUTHOR]

An effective facility management process is crucial to overall firm performance and is becoming a core competency for organizations seeking to gain a competitive advantage. The recent literature on facility management reveals that poor facility management is a major cause of management inefficiency, leading directly to budget overruns, maintenance delays, repetition of work, variations, noncompliance incidents, unnecessary risk, and dissatisfied customers. Therefore, facility management firms should pay close attention to the most critical success factors in order to effectively manage and measure performance. This paper presents a multidimensional campus facility management performance framework (CFMPF) that addresses both operational and systematic factors. Facility management companies, owners, contractors, and consultants can use this framework to identify systemic weaknesses using key indicators to specifically assess the effectiveness and success of facility management. The significance of 45 key facility management success factors across seven categories was determined via a literature review, expert interviews, and the Delphi method. The seven process groups are: Campus Facility Work Force Management, Campus Facility Communication Management, Campus Facility Systems Management, Campus Facility Organizational Management, Campus Facility Financial Management, Campus Sustainability & Environment Management, and Campus Facility Assets Management. To verify the overall agreement via the Delphi rounds, the score percentage and standard deviation to mean ratio were examined. Mean value and interrater agreement (IRA) analyses were conducted to evaluate the correlation between the factors and facility performance. This research adds to the body of knowledge by presenting a systematic operational framework for campus facility management that identifies the underlying factors influencing performance and fills the gaps left by previous studies. [ABSTRACT FROM AUTHOR]

Rosenbergiella bacteria have been previously isolated predominantly from floral nectar and identified in metagenomic screenings as associated with bees. Here, we isolated three Rosenbergiella strains from the robust Australian stingless bee Tetragonula carbonaria sharing over 99.4% sequence similarity with Rosenbergiella strains isolated from floral nectar. The three Rosenbergiella strains (D21B, D08K, D15G) from T. carbonaria exhibited near-identical 16S rDNA. The genome of strain D21B was sequenced; its draft genome contains 3,294,717 bp, with a GC content of 47.38%. Genome annotation revealed 3236 protein-coding genes. The genome of D21B differs sufficiently from the closest related strain, Rosenbergiella epipactidis 2.1A, to constitute a new species. In contrast to R. epipactidis 2.1A, strain D21B produces the volatile 2-phenylethanol. The D21B genome contains a polyketide/non-ribosomal peptide gene cluster not present in any other Rosenbergiella draft genomes. Moreover, the Rosenbergiella strains isolated from T. carbonaria grew in a minimal medium without thiamine, but R. epipactidis 2.1A was thiamine-dependent. Strain D21B was named R. meliponini D21B, reflecting its origin from stingless bees. Rosenbergiella strains may contribute to the fitness of T. carbonaria. [ABSTRACT FROM AUTHOR]

Epstein-Barr virus (EBV) is a ubiquitous virus that infects more than 90% of the world's population. It is a tumorigenic herpes virus that causes infectious mononucleosis (IM) and has been linked to the development of several malignant tumours such as Burkitt`s lymphoma, Hodgkin`s lymphoma, Nasopharyngeal carcinoma and Gastric carcinoma. This study was designed to detect EBV DNA and to identify the EBV genotypes and phylogeny among cancer patients' group (Case) and healthy individuals' group (Control) in Sana'a city, Yemen. One hundred subjects were enrolled in the study. Fifty individuals were clinically diagnosed to have cancer. The remaining 50 individuals were healthy controls. Serum IgM antibody against EBV viral capsid antigen (VCA) were tested by an enzyme-linked immunosorbent assay (ELISA).EBVDNA detection was done using conventional polymerase chain reaction while genotyping and sub-genotyping were performed by Nested polymerase chain reaction of EBNA-2 gene and LMP-1 gene, respectively. Results showed that the prevalence rate of EBV-VCA IgM antibodies among cancer patients was 12% while in healthy individuals was 8%. EBVDNA positivity were 66.7% (4/6) and 50% (2/4) for cancer patients (cases) and controls, respectively. Also, all EBV-DNA positive cases in both cancer patients and controls were genotype 1 and sub-genotype Med- with a rate of 100% both of them. The results presented genotypes and sub-genotype of EBV circulating in Sana'a city. It is worth mentioning that genotype 1 and Med- strain was first time recorded in Yemen. This study concluded that genotype 1 and Med- strain being predominant in Sana'a city, Yemen. Clinical significance of these finding have not been investigated and shall be evaluated in future studies. [ABSTRACT FROM AUTHOR]

The success of a construction project depends on different factors, the knowledge of the project managers, and the type of project being developed. In this paper, based on a review of the literature, 23 factors are identified as critical and they are grouped into top-management support, project manager's skills, project team skills, and stakeholder-management knowledge. A framework with 23 hypotheses is developed to assess the relation between these factors and project performance. The analysis of the framework is conducted based on the responses obtained from a survey of 266 engineers working on construction projects in Qatar. The results show a positive relationship between critical success factors and project performance. The highest positive perception is shown for stakeholder engagement by the top management (mean = 5.589 ± 0.582) and the lowest positive perception for the need to predict stakeholder influence (mean = 3.939 ± 0.852). The analysis of the relative importance of these factors shows that the top-management support category is ranked highest for the success of a project. Although the perceptions are based on Qatar's study, the success factors, their relationship with project success criteria, and project performance are global; therefore, the framework could be tailored and applied in different project contexts. [ABSTRACT FROM AUTHOR]

The construction industry has grown significantly to fulfill the expanding need for accommodation, facilities, welfare, and services resulting from the rapid increase in the global population. Infrastructure projects in particular facilitate transportation and services for both new and existing areas, yet they are also one of the primary producers of construction waste, which is harmful to both society and the environment. Hence, the objective of this paper is to identify the factors affecting construction waste management in infrastructure projects (CWMIIP) and study their respective impacts on construction waste management (CWM) performance. This study makes a unique contribution by not only addressing the factors that influence the development of construction wastes and their importance, but also by giving quantifiable solutions and action plans to reduce the waste. Using a literature review, 26 factors were selected as the major contributors to construction waste in infrastructure projects. An online questionnaire was then developed to collect data on the respective impacts of these factors. A total of 167 complete responses to the questionnaire were collected, and a structural equation model (SEM) was developed to quantitatively measure the impact of each factor on waste management performance. The model was validated using goodness of fit (GOF), multivariate normality, construct validity, reliability, and hypotheses analyses. The results indicate that the most significant factors affecting the generation of construction wastes are "quantity take-off error by contractor," "unforeseen incidents damaging site and/or completed works," "design errors," and "extreme weather conditions damaging completed works." The model results showed that all predefined hypotheses were supported, except for the positive effect of the logistics group, which was dropped during model development. Individual factors were also divided into groups, and the total impact of each group was assessed; the "management" group had the greatest impact, followed by "execution," "others," and "procurement." Based on these findings, we make several recommendations to construction industry professionals to reduce waste and mitigate its harmful effects, such as requiring a construction waste management implementation plan before awarding a project to a contractor; engaging with project suppliers to provide execution training for contractor staff; ensuring proper implementation of health, safety, and environmental plans; and purchasing locally available materials. This research built a model based on structural equation modeling that will help researchers better understand the links between building waste management parameters. To examine the impact of each waste component on construction waste management performance, a quantitative model is built based on the data obtained. This quantitative waste management model could be used to track construction waste management performance. The findings of this study are not limited to infrastructure projects because they may be tailored to fit any project. As a result, it is recommended that project contractors and supervision consultants rely on the factors responsible for construction waste generation identified in this study to capture their actual construction waste factors. Also, having a record and log of all construction wastes generated during a project, as well as the reasons for these wastes, would help the organization improve its waste management learning curve for future projects. [ABSTRACT FROM AUTHOR]

Change orders are a major challenge in the construction industry due to the associated time and cost impacts. Thus, managing change effectively assists in alleviating cost overruns and delays. Avoiding change orders and controlling them during project phases requires comprehensive research on the factors affecting the change orders management (COM) performance. This study contributes to existing knowledge by introducing a COM performance measurement framework to help construction professionals evaluate, track, and manage COM performance. A comprehensive literature review, personal meetings, and the Delphi technique are utilized to identify 49 performance factors, categorized into 7 COM groups. 13 Delphi panel members are selected according to purposive sampling technique. The collected data are examined through normality and reliability tests and then analyzed by Spearman's correlation coefficient, score percentage, and the mean to standard deviation ratio to decide whether to continue with the Delphi method. Consensus between the panelists is reached after the second round of Delphi by the utilization of nonparametric statistical tests. The Delphi study results are followed up by measuring the inter-rater agreement (IRA) and ranking the COM performance factors using the sum rank weighting method. Finally, an operational support system framework that takes into consideration the project life cycle of a project is developed to manage and control these factors to decrease disputes between project parties that occur due to improper COM performance. [ABSTRACT FROM AUTHOR]

Managing change order is a critical area of concern in the construction industry, owing to the resulting disputes, claims, productivity losses, delays, and cost repercussions. There have been various studies proposing both quantitative and qualitative approaches to tackle the effect of change orders on project performance and success. Previous studies have almost solely focused on specific organizational policies, procedures, causes, and recommendations with the goal of capturing the essence of change-order management (CHM) within an area, organization, or kind of contract. However, their contributions are context-specific, limited to simple statistical method and make no reference to an inclusive concept of CHM performance factors. Furthermore, the existing literature urges a need for a realistic strategy to managing change orders, as well as limiting their negative consequences. Therefore, to address the research gap in the literature, this study proposes an operational and systematic CHM framework based on multidimensional performance factors to enhance the overall project success (OPS) factors, utilizing a partial least squares structural equation modeling (PLS-SEM) approach to develop the model. For evaluating CHM's performance in terms of OPS, a conceptual model was developed. A questionnaire survey was used to conduct an empirical analysis to test the conceptual model. The information was gathered from 334 construction specialists that work in the field. The result of the analysis found that the explanatory power (R2) value of the CHM model is 0.665, which revealed that CHM performance factors in projects is responsible for 66.5% of project performance, which has a significant impact and demonstrating a strong influence. Furthermore, the management of communication and relationships, dispute resolution, and financial issues have a significant impact on CHM based on outer loading values of (β) 0.433, 0.432, and 0.422, respectively. Documentation, procurement, design, and quality management come next in terms of influence on CHM effectiveness, with outer loading values of (β) 0.402, 0.367, 0.345, and 0.289, respectively. This study adds to the body of knowledge by providing new insights and assisting in the identification and better understanding of CHM performance factors in construction projects and their impact on OPS, as well as the use of an advanced statistical method, PLS-SEM. The outcomes of this study can be utilized as a starting point for implementing CHM in construction projects. The practical applications of the proposed quantitative approach model can be utilized by the client, the consultant, and the contractor to successfully plan, manage, evaluate, monitor, and control the CHM performance. The findings of this study will aid policymakers and decision makers around the world in focusing on the industry's most critical difficulties and challenges. [ABSTRACT FROM AUTHOR]

Change order management is a major challenge in the construction business due to the associated disputes, claims, productivity losses, delays, and cost implications. As a result, effective change order management (COM) is required to ensure the success of construction projects. The cost overruns and schedule delays caused by change orders have been recognized and researched by scholars and construction practitioners for decades. However, in modern construction management, there are additional performance factors that affect the performance of COM throughout construction activities. This study contributes to existing knowledge by identifying a comprehensive and multidimensional set of performance factors affecting COM and developing an adaptive neurofuzzy inference system (ANFIS) to model these factors quantitatively and evaluate COM implementation performance in the construction industry. Through an exhaustive literature search and engagement with specialists, 49 COM performance parameters were identified and then classified into seven groups. Then, 334 responses from building specialists were gathered via an online survey to determine the relative importance of each component and group. The obtained data were examined for normality, reliability, and independence and then analyzed using the Relative Importance Index (RII). The ANFIS model was constructed using a fuzzy clustering approach that took into account the clustering of input and output data sets, the fuzziness level of clusters, and the optimization of five Gaussian membership functions. The ANFIS model was subsequently validated using qualitative structural and behavioral testing (k -fold cross-validation). The findings of this study can be used as guidance in construction management for managing and evaluating the overall COM performance index of construction projects. [ABSTRACT FROM AUTHOR]

Building Information Modeling (BIM) is mainly used for the design and construction of new buildings. However, one of the main challenges facing BIM adoption for existing or old buildings constructed without consideration for their modeling is obtaining raw and accurate building data and converting it to the BIM model. Based on this challenge, this study develops a framework that uses different data capture techniques for existing buildings and then transforms this captured data into 3D BIM models, through which it can improve its management processes as facilities during their service life. Specifically, 3D laser scanning techniques were used to capture indoor building data, while drones equipped with high-definition cameras (UAV) were used to capture outdoor building data such as geometric dimensions, material shapes, surfaces, and various shapes. Then, the captured data was converted into a high-resolution 3D model. This has verified the accuracy of this engineering model by converting the twodimensional engineering plans to three-dimensional through the well-known engineering design tools. Moreover, the 3D model has been integrated with the Web Based Building Management System (BMS) platform. This research framework helps in developing engineering facility management processes and modern digital transformation processes that aim at speeding up facility management during their service period using modern technologies. This study aims to develop current knowledge in the construction industry and facility management by reviewing a comprehensive understanding of how to use modern technologies to obtain various information to develop BIM models for existing and nonmodeled buildings in order to exploit and integrate them with advanced facility management systems and platforms, which constitutes a major progress in this field allowing to save a lot of effort and money in the future. [ABSTRACT FROM AUTHOR]

Background: Few studies have reported how students enact learner agency in a team setting or examined what elements of team settings students perceive as more supportive of their learning in problem‐ and project‐based learning (PBL) processes. Purpose This study explores how engineering students perceive their enactment of learner agency, particularly which aspects of the PBL process they find most important. Method: Thirty‐nine students from two PBL civil engineering courses in Qatar participated in the study. Q methodology was chosen for both qualitative and quantitative data collection and analysis. A 40‐item Q set based on a theoretical model of learner agency was used. Results: Eight significantly different student viewpoints emerged from the Q methodological factor analysis, indicating a range of individual perceptions of learner agency. Intrapersonal dimensions were highlighted by three of the eight viewpoints, behavioral dimensions were underlined by seven viewpoints, and environmental dimensions were valued by all viewpoints. Conclusion: While the results reveal a wide range of individual experiences with learner agency across the three dimensions, students addressed self‐directed learning aspects both actively and passively, suggesting that many participants still value instructors' roles of providing direct instruction and authorized knowledge in PBL. The results highlight the need for more awareness of learner agency and more opportunities for students to enact learner agency by increasing PBL knowledge, skills, and efficacy. Q methodology can contribute to engineering education research by providing new theoretical and empirical insights into learners' subjective understanding of agency in a PBL setting as a complex system. [ABSTRACT FROM AUTHOR]