Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged in Wuhan, China, in December 2019 and has subsequently spread worldwide, causing a pandemic of coronavirus disease 2019 (COVID-19). Recent studies have suggested that hypertension and type 2 diabetes mellitus (T2DM) were the most frequent comorbidities in infected patients and are also considered independent risk factors for disease severity and mortality. 1-4 However, hypertension and T2DM are commonly encountered together. Epidemiological

The construction industry is undergoing a digital revolution due to the emergence of new technologies. A significant trend is that construction projects have been transformed and upgraded to the digital and smart mode in the whole life cycle. As a critical technology for the construction industry’s innovative development, building information modeling (BIM) is widely adopted in building design, construction, and operation. BIM has gained much interest in the research field of smart buildings in recent years. However, the dimensions of BIM and smart building applications have not been explored thoroughly so far. With an in-depth review of related journal articles published from 1996 to July 2020 on the BIM applications for smart buildings, this paper provides a comprehensive understanding and critical thinking about the nexus of BIM and smart buildings. This paper proposes a framework with three dimensions for the nexus of BIM application in smart buildings, including BIM attributes, project phases, and smart attributes. According to the three dimensions, this paper elaborates on (1) the advantages of BIM for achieving various smartness; (2) applications of BIM in multiple phases of smart buildings; and (3) smart building functions that be achieved with BIM. Based on the analysis of the literature in three dimensions, this paper presents the cross-analysis of the nexus of BIM and smart buildings. Lastly, this paper proposes the critical insights and implications about the research gaps and research trends: (1) enhancing the interoperability of BIM software; (2) further exploring the role of BIM in the operation and refurbishment phase of smart buildings; (3) paying attention to BIM technology in the field of transportation infrastructure; (4) clarifying the economic benefits of BIM projects; and (5) integrating BIM and other technologies.

The pandemic of coronavirus Disease 2019 (COVID-19) caused enormous loss of life globally. 1-3 Case identification is critical. The reference method is using real-time reverse transcription PCR (rRT-PCR) assays, with limitations that may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that application of deep learning (DL) to the 3D CT images could help identify COVID-19 infections. Using the data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 patients. COVIDNet achieved an accuracy rate of 94.3% and an area under the curve (AUC) of 0.98. Application of DL to CT images may improve both the efficiency and capacity of case detection and long-term surveillance.

The pandemic of Coronavirus Disease 2019 (COVID-19) is causing enormous loss of life globally. Prompt case identification is critical. The reference method is the real-time reverse transcription PCR (RT-PCR) assay, whose limitations may curb its prompt large-scale application. COVID-19 manifests with chest computed tomography (CT) abnormalities, some even before the onset of symptoms. We tested the hypothesis that the application of deep learning (DL) to 3D CT images could help identify COVID-19 infections. Using data from 920 COVID-19 and 1,073 non-COVID-19 pneumonia patients, we developed a modified DenseNet-264 model, COVIDNet, to classify CT images to either class. When tested on an independent set of 233 COVID-19 and 289 non-COVID-19 pneumonia patients, COVIDNet achieved an accuracy rate of 94.3% and an area under the curve of 0.98. As of March 23, 2020, the COVIDNet system had been used 11,966 times with a sensitivity of 91.12% and a specificity of 88.50% in six hospitals with PCR confirmation. Application of DL to CT images may improve both efficiency and capacity of case detection and long-term surveillance.

Due to the repeated bearing of mechanical operations and natural factors, the container will suffer various types of damage during use. Adopting effective container damage detection methods plays a vital role in prolonging the service life and using function. This paper proposes a multitype damage detection model for containers based on transfer learning and MobileNetV2. In addition, a data set containing nine typical types of container damage is established. To ensure the validity and practicability of the model, we conducted tests and verifications in the actual port environment. The results show that the model can identify multiple types of container damage. Compared with the existing models, the damage detection model proposed in this paper can ensure the identification effect of various types of container damage, which is more suitable for the actual container detection situation. This method can provide a new idea of damage detection for container management in ports.

The high operation cost of green building, insufficient informationization and automation management capability, and the lack of effective operation cost control seriously restrict the development of the industry and the realization of green goals. In order to solve the problem of insufficient capability of green building operation cost management, based on the digital twin technology in the manufacturing field, we analyze the characteristic requirements and theoretical basis of green building operation cost management for system, propose a green building operation cost management system based on digital twin, and refine the design of each structural layer of this system. It is necessary to set up a series of lines, although it takes a certain amount of time. There are four types of applications, namely, the number of types of applications, the completion of the effective number, the comparison of functions, and the implementation capabilities. The study shows that the proposed system framework can improve the efficiency and quality of green building operation cost management through technology upgrade and process optimization. The implementation of digital twin and human-machine collaboration is an advanced stage in the development of digital architecture because virtual things and real things, materials, and numbers are mutually promoting processes. The inspiration of this technological view for architecture is that digital twin and human-machine collaboration not only allow the interaction between virtual and reality and emphasize the feedback of actual construction to virtual simulation but also promote a kind of mutual promotion of human and machine thinking and construction ability.

The near-sea offshore oil extraction and transportation system use heterogeneous fleets to transfer crude oil from the floating production storage and offloading to the land-based oil storage port. Based on the characteristics of this system, the short sea inventory routing problem is investigated considering the shuttle tanker fleet and inventory management. In order to minimize the total operation cost and maximize the system reliability, a semi-continuous model for the shuttle tanker scheduling problem is established. The model optimizes the tanker scheduling plan and the design of the tanker fleet. To solve the complex model, this paper proposes an improved non-dominated sorting genetic algorithm with differential evolution operator to solve the optimization of the multi-objective model. This research also uses public vessel operation data to test the modeling and optimizing efficiency. The Pareto Fronts associated with the total operation cost and the system reliability from the optimization outcome is analyzed to provide scheduling priority advice. The results indicate that proposed optimization algorithms are effective, and the operation could be optimized with the proposed model and algorithm. INDEX TERMS Maritime inventory routing problem, non-dominated sorting genetic algorithm (NSGA-II), offshore oil transportation, semi-continuous model, shuttle tanker, system reliability.

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