Abstract Large language models (LLMs) are increasingly used by students and professionals in the architecture, engineering, and construction (AEC) sector for learning and information retrieval. However, their reliability in performing construction management (CM) knowledge tasks remains insufficiently characterized. This study introduces CMExamSet, a benchmark data set consisting of 689 multiple-choice questions compiled from four professional CM certification programs. The data set covers core CM domains, including project and program management, safety management, cost control, scheduling, contract administration, and related professional knowledge areas. Four contemporary LLMs were evaluated using a standardized zero-shot protocol with five repeated runs per question. Performance was assessed using accuracy, response consistency, subject-area analysis, and structured error annotation. Mean accuracy ranged from 79.2% to 90.0% across the four examinations, with high overall agreement observed in repeated runs. Performance varied systematically by domain: higher accuracy was observed in information retrieval-based domain tasks, such as engineering concepts, construction geomatics, and sustainability, whereas lower accuracy was observed in operationally oriented domains such as bidding and estimating, time and schedule management, and cost control. When errors occurred, conceptual misunderstandings were the most frequently observed error type across domains, indicating that incorrect interpretation or application of domain principles remained a common source of failure. Performance improvements in newer models were generally modest across subject areas. These findings provide empirical evidence on the capabilities and limitations of LLMs in CM knowledge assessment and underscore the importance of structured verification, domain grounding, and instructional guidance when integrating LLM tools into construction education and professional preparation.
To holistically understand the biology of animals, we must unravel the complexities and specificities of host-microbe interactions across animal taxa. Birds represent enigmatic and scientifically compelling hosts in which to understand these interactions. Here, we present a brief summary of a series of conversations among avian microbiome researchers regarding methodological challenges facing the avian microbiome field, where most research to date has focused on bacterial communities of the gut. Collectively, we acknowledged a commonly shared but underreported issue facing the avian microbiome field: that of difficulty in obtaining high-quality and high-yield microbial DNA from avian fecal samples. We discuss some of the potential reasons underlying low DNA yields, such as inhibitory compounds and rapid DNA degradation, and provide recommendations for how researchers in the avian microbiome field might cope with these methodological challenges. Collective and dedicated efforts to address these challenges will be required for a robust understanding of host-microbe interactions in avian systems.
Organizational capacity is a concept frequently emphasized by funders, resource providers and practitioners alike, however, theoretical advancements in capacity and its relationship with organizational performance remain scarce in nonprofit contexts, including sport organizations. We examine the relationships between organizational capacity, social innovation and perceived organizational performance in the context of sport for development and peace (SDP) nonprofits. Specifically, we analyze cross-sectional survey data collected during 2019 from a global sample of 161 organizations. Organizational capacity was measured through a set of behavioral-anchored rating scales across five capacity dimensions. Social innovation was measured across three dimensions using a scale designed for direct human service nonprofits, and perceived organizational performance was measured through an established scale designed for nonprofits. Structural equation modeling provides empirical support for our theorized model regarding nonprofits' capacity-innovation-performance triad. A key contribution of this study is the importance of organizational capacity for nonprofit performance and the positive mediating role of social innovation. Control variables played a minimal role in the full model apart from organizations located in Africa. Our research contributes to theory by advancing social innovation can serve as a critical process for amplifying the relationship between existing capacities and performance. Broadly speaking, our study highlights the importance of organizational capacity for any SDP leader interested in developing innovative and high performing nonprofits. Our results warrant a shift in mindset toward strategically viewing innovation as a vital organizational ability for achieving desired outcomes by translating existing capacities into organizational performance.
Anxiety disorders are associated with prefrontal dysfunction, yet their impact on neural mechanisms underlying skilled motor learning remains poorly understood. We examined movement-readiness potentials (MRPs) using electroencephalography during a visuomotor adaptation task in 31 young adults (13 with clinically diagnosed anxiety disorders, 18 controls). MRPs were analyzed across three temporal components: early motor preparation (− 1500 to − 500 ms), late motor preparation (− 500 to − 100 ms), and movement execution (− 100 to + 100 ms). Individuals with anxiety disorders showed significantly reduced MRP amplitudes during late motor preparation (p = 0.033) and movement execution (p = 0.047) compared to controls, while early motor preparation remained intact. Despite these neural alterations, both groups demonstrated equivalent behavioral performance, with similar learning and retention of a visuomotor rotation task. Anxiety disorders selectively disrupt late-stage cognitive-motor integration processes during movement preparation and execution. The dissociation between impaired neural activity and preserved behavioral performance suggests compensatory mechanisms that maintain motor learning despite underlying neural inefficiencies. These findings reveal that anxiety affects integrated systems of cognition and action, providing new insights into their functional neurophysiological impact.
This review explores the metabolic pathways dysregulated in both atherosclerotic cardiovascular disease (ASCVD) and metabolic dysfunction-associated steatotic liver disease (MASLD), focusing on lipid, carbohydrate, amino acid, and energy metabolism and the specific alterations within major contributing cell types. In the setting of metabolic syndrome, lipid and carbohydrate overload impair hepatic metabolism, resulting in the accumulation of lipotoxic species and ensuing cellular damage, inflammation, oxidative stress, and cardiovascular consequences. Amino acid metabolism is emerging as a key regulator of cell fate and function in both MASLD and ASCVD. Mitochondrial dysfunction and cellular stress promote a pseudo-Warburg effect, shifting cells from efficient oxidative phosphorylation to anaerobic glycolysis and impairing homeostasis. Emerging therapies targeting hepatic metabolism to reduce cardiovascular risk and MASLD burden hold promise for future dual treatments. MASLD and ASCVD arise from common metabolic derangements that converge on shared cellular and molecular pathways. Defining these cross-tissue mechanisms may enable the development of integrated therapeutic approaches aimed at jointly mitigating hepatic and vascular injury, thus redefining treatment paradigms in cardiometabolic disease.
