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Abstract Engineering design is undergoing a transformative shift with the advent of AI, marking a new era in how we approach product, system, and service planning. Large language models have demonstrated impressive capabilities in enabling this shift. Yet, with text as their only input modality, they cannot leverage the large body of visual artifacts that engineers have used for centuries and are accustomed to. This gap is addressed with the release of multimodal vision-language models (VLMs), such as GPT-4V, enabling AI to impact many more types of tasks. Our work presents a comprehensive evaluation of VLMs across a spectrum of engineering design tasks, categorized into four main areas: Conceptual Design, System-Level and Detailed Design, Manufacturing and Inspection, and Engineering Education Tasks. Specifically in this paper, we assess the capabilities of two VLMs, GPT-4V and LLaVA 1.6 34B, in design tasks such as sketch similarity analysis, CAD generation, topology optimization, manufacturability assessment, and engineering textbook problems. Through this structured evaluation, we not only explore VLMs’ proficiency in handling complex design challenges but also identify their limitations in complex engineering design applications. Our research establishes a foundation for future assessments of vision language models. It also contributes a set of benchmark testing datasets, with more than 1000 queries, for ongoing advancements and applications in this field. 

PurposeElectric trucks and platooning are promising technologies to reduce greenhouse gas emissions in the freight sector. To maximize the benefits of these two technologies, effective coordination of charging and platooning is essential, especially considering insufficient charging stations (CSs), long charging duration and tight freight delivery window for middle-mile electric trucks. Therefore, this paper aims to jointly optimize the scheduling of charging and platooning of electric trucks over the freight transportation network. Design/methodology/approachThis paper proposes a mixed integer linear programming model to minimize the total costs from en-route charging, depot charging, and delivery delay. This also presents scenario analyses to understand the impacts of key features on system costs, including battery capacity, number of charging plugs at CSs, charging speed, availability of alternative paths and platoon energy-saving percentage. To solve the model with a large fleet size, a warm-start-based parameter-tuned solver approach, and hybrid metaheuristics of variable neighborhood search and local branching were implemented and compared based on performance. FindingsThe proposed model was implemented using the freight network in Florida. In a case study with a small fleet size, platoon scheduling reduced 19% of en-route charging cost and 30% of delivery delay cost compared with the case of only charge scheduling. Electric trucks were charged around three times with an average duration of 35 min per session to facilitate platoon scheduling and minimize the total cost. Originality/valuePrevious models optimized charging and platoon scheduling for single routes that cannot be generalized for network level and multiple origin-destination pairs; this study addresses network-level optimization. 

The viability of the electrolysis of water currently relies on expensive catalysts such as Pt that are far too impractical for industrial-scale use. Thus, there is considerable interest in developing low-cost, earth-abundant nanomaterials and their alloys as a potential alternative to existing standard catalysts. To address this issue, a synergistic approach involving theory and experiment was carried out. The former, based on density functional theory, was conducted to guide the experiment in selecting the ideal dopant and optimal concentration by focusing on 3d, 4d, and 5d elements as dopants on Ni (001) surface. Subsequently, a series of Ni_1−xCr_x(x= 0.01–0.09) alloy nanocrystals (NCs) with size ranging from 8.3 ± 1.6–18.2 ± 3.2 nm were colloidally synthesized to experimentally investigate the hydrogen evolution reaction (HER) activity. A compositional dependent trend for electrocatalytic activity was observed from both approaches with Ni_0.92Cr_0.08NCs showed the lowest ΔG_Hvalue and the lowest overpotential (η₋₁₀) at −10 mA cm⁻²current density (j), suggesting the highest HER activity among all compositions studied. Among alloy NCs, the highest performing Ni_0.92Cr_0.08composition displayed a mixed Volmer–Heyrovsky HER mechanism, the lowest Tafel slope, and improved stability in alkaline solutions. This study provides critical insights into enhancing the performance of earth-abundant metals through doping-induced electronic structure variation, paving the way for the design of high-efficiency catalysts for water electrolysis. 

Cardiac rehabilitation (CR) is a medically supervised program designed to improve heart health after a cardiac event. Despite its demonstrated clinical benefits, CR participation among eligible patients remains poor due to low referral rates and individual barriers to care. To evaluate CR participation by patients who receive care from hospital-integrated physicians compared with independent physicians, and subsequently, to examine CR and recurrent cardiac hospitalizations. This retrospective cohort study evaluated Medicare Part A and Part B claims data from calendar years 2016 to 2019. All analyses were conducted between January 1 and April 30, 2024. Patients were included if they had a qualifying event for CR between 2017 and 2018, and qualifying events were identified using diagnosis codes on inpatient claims and procedure codes on outpatient and carrier claims. Eligible patients also had to continuously enroll in fee-for-service Medicare for 12 months or more before and after the index event. Physicians’ integration status and patients’ CR participation were determined during the 12-month follow-up period. The study covariates were ascertained during the 12 months before the index event. ExposureHospital-integration status of the treating physician during follow-up. Main Outcomes and MeasuresPostindex CR participation was determined by qualifying procedure codes on outpatient and carrier claims. ResultsThe study consisted of 28 596 Medicare patients eligible for CR. Their mean (SD) age was 74.0 (9.6) years; 16 839 (58.9%) were male. A total of 9037 patients (31.6%) were treated by a hospital-integrated physician, of which 2995 (33.1%) received CR during follow-up. Logistic regression via propensity score weighting showed that having a hospital-integrated physician was associated with an 11% increase in the odds of receiving CR (odds ratio [OR], 1.11; 95% CI, 1.05-1.18). Additionally, CR participation was associated with a 14% decrease in the odds of recurrent cardiovascular-related hospitalizations (OR, 0.86; 95% CI, 0.81-0.91). The findings of this cohort study suggest that hospital integration has the potential to facilitate greater CR participation and improve heart care. Several factors may help explain this positive association, including enhanced care coordination and value-based payment policies. Further research is needed to assess the association of integration with other appropriate high-quality care activities.