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Having a significant economic impact in country's GDP and being a major workforce, construction industry is yet characterized by low production rate, low technological advancement, minimum automation and robotic usage, and so on. With the visionary idea of Industry 4.0 that focuses on digitization of the value chain of a product and improving productivity through a variety of technologies and automated manufacturing environment, this research aims to develop a framework to adopt Construction 4.0 within a construction company. Current state of the art of the technologies in construction associated with the notion of Industry 4.0 (e.g., Building Information Modelling, virtual reality, augmented reality, Drone, etc.) is explored through extensive literature studies. The proposed framework incorporates current technological advancement related to construction industry, legislative requirements, barriers, enterprise transformation requirements and so on. Construction 4.0 would make a great impact in construction industry through improved value chain of construction projects, productivity improvement, and safe and sustainable construction. Indeed, the proposed framework would contribute to the advancement of new knowledge in the worlds' construction companies and provide potentials of new research focuses.

Solvation thermodynamic data of dl-serine and dl-phenylalanine in aqueous mixtures of dimethylsulfoxide at 298.15 K were determined from solubility measurement.

Background Urothelial bladder cancer (BLCA) is one of the most common internal malignancies worldwide with poor prognosis. This study aims to explore effective prognostic biomarkers and construct a prognostic risk score model for patients with BLCA. Methods Weighted gene co-expression network analysis (WGCNA) was used for identifying the co-expression module related to the pathological stage of BLCA based on the RNA-Seq data retrieved from The Cancer Genome Atlas database. Prognostic biomarkers screened by Cox proportional hazard regression model and random forest were used to construct a risk score model that can predict the prognosis of patients with BLCA. The GSE13507 dataset was used as the independent testing dataset to test the performance of the risk score model in predicting the prognosis of patients with BLCA. Results WGCNA identified seven co-expression modules, in which the brown module consisted of 77 genes was most significantly correlated with the pathological stage of BLCA. Cox proportional hazard regression model and random forest identified TPST1 and P3H4 as prognostic biomarkers. Elevated TPST1 and P3H4 expressions were associated with the high pathological stage and worse survival. The risk score model based on the expression level of TPST1 and P3H4 outperformed pathological stage indicators and previously proposed prognostic models. Conclusion The gene co-expression network-based study could provide additional insight into the tumorigenesis and progression of BLCA, and our proposed risk score model may aid physicians in the assessment of the prognosis of patients with BLCA. Electronic supplementary material The online version of this article (10.1186/s41065-019-0100-1) contains supplementary material, which is available to authorized users.

The use of hexagonal boron nitride (hBN) to modify a semiconductor photocatalyst is one of the promising methods for the production of hydrogen from water splitting. This is due to the unique characteristics of the hBN-suppressing recombination of the photogenerated charge carriers and hence increase in the redox reactions. In the present work, a hBN-modified Ni2P-containing excess boron composite (B-hBN-Ni2P) was prepared through an electroless plating method. The solid structure, elemental composition, and morphology were investigated via X-ray diffraction, energy-dispersive X-ray spectroscopy, scanning electron microscopy, UV–visible spectroscopy, and photoluminescence spectroscopy. The composite coating was tested for solar water splitting, and a hydrogen evolution rate of 883 μmol/h was achieved. The role of excess B was revealed through an electrochemical acidic leaching. By gradually removing boron from the structure, a monotonous drop in the water splitting activity was observed. Our study identifies B as a sacrificial agent/hydrogen production booster. It contributes to the higher catalytic activity with an additional hydrogen generation through the oxidation of its surplus amount from the composite coating. The enhanced hydrogen evolution activity for the composite coating in the present study is highly competitive with the other modern photocatalysts.

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