There is a lack of decision-making tools for water efficiency design and construction to maximize project benefits and water conservation. An increasing number of research studies indicate that building information modelling (BIM) can enhance the cooperation, improve work efficiency, and conduct simulation and analysis of sustainability performance in building projects. However, BIM’s potential to enhance water efficiency is yet to be established, such as water gird design optimization, clash detection, combination of BIM with smart appliances and sensors. The research adopted a mixed method approach to investigate the potential impact of BIM on water efficiency in building projects. It involved 50 practitioners from the Architectural, Engineering and Construction (AEC) industry through a questionnaire survey and the follow-up interviews. The quantitative results of questionnaire data and qualitative results of interviews were used to develop a “BIM-based Water Efficiency (BWe) Framework” which was subsequently validated by five experienced practitioners and researchers in the form of semi-structured interviews. The framework applies BIM to optimize traditional water efficiency measures based on an information database. The geometry, attributes, status information of building components or non-component objects stored in the database greatly improve information integration degree of construction engineering. This study provided a reference for the use of BIM for water conservation in building design and construction.

The public has always been concerned about the problem behaviors of children and teenagers (such as cigarette and alcohol use), especially among disadvantaged groups (e.g., left-behind children in China); in the current information era, left-behind children’s use of social media also has increasingly expanded, which has diverse effects on their adaptation. Accordingly, the present study examined the association between exposure to relevant content on social media and left-behind children’s tobacco and alcohol use, as well as the underlying mechanisms—the mediating effect of deviant peer affiliation and the moderating effect of parent–child contact, the gender differences were also investigated. A sample of 515 Chinese left-behind children (Mage = 13.39 ± 2.52 years, 45.0% girls) was recruited to complete a set of questionnaires assessing the main variables. The results show that social media exposure was positively associated with tobacco and alcohol use and that deviant peer affiliation significantly mediated this relationship. Furthermore, parent–child interaction attenuated the link between social media exposure and cigarette and alcohol use among left-behind girls, but this moderating effect was not statistically significant among left-behind boys. The moderating role of parent–child contact in the association between deviant peer affiliation and tobacco and alcohol use was insignificant in both boys and girls. These findings may have significance in several ways—theoretically, they not only deepen our understanding of the risk factors and mechanism of tobacco and alcohol use among left-behind children in the current information era and the influences of social media use; practically, they provide direction for the health improvement of left-behind children of different genders.

Landslides, which can cause significant losses of lives or property damages, result from several different environmental factors whose influences are very complex. Thus, the statistical multi-layer perceptron (MLP) and heuristic analytical hierarchy process (AHP) are employed in the evaluation of landslide susceptibility. However, the landslide susceptibility maps drawn by these two methods are always affected by subjectivity and randomness. In the present study, we introduce variable weight theory (VW) to improve the MLP and AHP methods, and two novel hybrid models, AHP-VW and MLP-VW, are respectively proposed. VW theory is used to redistribute the weights of the factors in the two constant weight evaluations. This is so that the weights of the factors change with different evaluation units, thereby eliminating the subjectivity and randomness problems. The landslide susceptibility maps of the study area were categorized into very low, low, moderate, high, and very high susceptibility grades. The landslide susceptibility maps of the four models are validated by the receiver operating characteristic (ROC) curve. The area under the curve (AUC) is 0.825 for the AHP model, 0.879 for the MLP model, 0.873 for the AHP-VW model, and 0.915 for the MLP-VW model. The results show that the landslide susceptibility map drawn by statistical MLP is better than that drawn by heuristic AHP, which is consistent with many other current research results. Furthermore, VW can significantly improve the performance of constant-weight single models. Landslide susceptibility maps drawn by the statistical MLP model hybrid VW can be used for regional land use planning and landslide hazard mitigation purposes.

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