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Building stocks represent an extensive reservoir of secondary resources. However, common bottom‐up characterization of these, often based on archetypal classification of buildings and their corresponding material intensity, are still not suitable to adequately inform circular economic strategies. Indeed, these approaches typically result in a loss of building‐specific details, and a building stock characterization in terms of material mass, for example, glass, rather than component, for example, window. To deliver this higher resolution of details, a scalable approach to urban stock characterization, that enables a bottom‐up estimation of building stocks at the building component level, is needed. In this paper, we present a framework to automate the characterization of urban stock. By using and combining a mobile‐sensing approach with computer vision, urban stocks can be captured as 3D surface maps allowing the identification and semantic classification of stock objects, components, and materials. We demonstrate the potential of this framework through a case study of a neighborhood in Sheffield, UK, by using a prototype workflow comprising a custom‐made mobile‐sensing platform and an existing suite of neural network models to calculate an estimate count of buildings external doors and windows. The prototype implementation of the framework achieves comparable total and building‐level component counts with those achieved through manual human counts. Such automated estimation of components enables an understanding of opportunities across the circular economic hierarchies and informs stakeholders across the supply chain to better prepare for the implementation of circular strategies including building refurbishments. [ABSTRACT FROM AUTHOR]

In this study, we aim to evaluate the efficiency and safety of traditional Chinese medicine foot bath combined with acupoint massage for the treatment of diabetic peripheral neuropathy. A total of eight online databases were searched to collect studies published up to February 2019. Study quality of each included article was evaluated by the Cochrane Collaboration risk of bias tool. Systematic reviews and meta-analyses were conducted based on the Cochrane systematic review method by using the RevMan 5.3 software. Traditional Chinese medicine foot bath combined with acupoint massage was the main therapy in experimental group. Interventions in control groups include western medicine, oral traditional Chinese medicine, other symptomatic treatment of western medicine, and blank control. Primary outcomes in this study include sensory nerve conduction velocity (SNCV), motor nerve conduction velocity (MNCV), total effective rate, and neuropathic syndrome score. Finally, 31 trials involving 3284 participants were included. The results of systematic reviews and meta-analyses showed that traditional Chinese medicine foot bath combined with acupoint massage was significantly better compared with the control groups in terms of the total effective rate, SNCV, MNCV, and neuropathic syndrome score. No case of adverse effect was reported. These findings show that traditional Chinese medicine foot bath combined with acupoint massage may be safer and more effective for the treatment of DPN. However, due to the low methodological quality, further research with randomized controlled trials (RCTs) of higher quality is required to prove its efficacy and better evidence for clinical treatment. [ABSTRACT FROM AUTHOR]