Component-Level Residential Building Material Stock Characterization Using Computer Vision Techniques.

Residential building material stock constitutes a significant part of the built environment, providing crucial shelter and habitat services. The hypothesis concerning stock mass and composition has garnered considerable attention over the past decade. While previous research has mainly focused on the spatial analysis of building masses, it often neglected the component-level stock analysis or where heavy labor cost for onsite survey is required. This paper presents a novel approach for efficient component-level residential building stock accounting in the United Kingdom, utilizing drive-by street view images and building footprint data. We assessed four major construction materials: brick, stone, mortar, and glass. Compared to traditional approaches that utilize surveyed material intensity data, the developed method employs automatically extracted physical dimensions of building components incorporating predicted material types to calculate material mass. This not only improves efficiency but also enhances accuracy in managing the heterogeneity of building structures. The results revealed error rates of 5 and 22% for mortar and glass mass estimations and 8 and 7% for brick and stone mass estimations, with known wall types. These findings represent significant advancements in building material stock characterization and suggest that our approach has considerable potential for further research and practical applications. Especially, our method establishes a basis for evaluating the potential of component-level material reuse, serving the objectives of a circular economy.

Extending the Grading of Recommendations Assessment, Development and Evaluation (GRADE) in Traditional Chinese Medicine (TCM): The GRADE-TCM.

AIM: To extend and form the "Grading of Recommendations Assessment, Development and Evaluation in Traditional Chinese Medicine" (GRADE-TCM). METHODS: Methodologies were systematically reviewed and analyzed concerning evidence-based TCM guidelines worldwide. A survey questionnaire was developed based on the literature review and open-end expert interviews. Then, we performed expert consensus, discussion meeting, opinion collection, external examination, and the GRADE-TCM was formed eventually. RESULTS: 265 Chinese and English TCM guidelines were included and analyzed. Five experts completed the open-end interviews. Ten methodological entries were summarized, screened and selected. One round of consensus was conducted, including a total of 22 experts and 220 valid questionnaire entries, concerning 1) selection of the GRADE, 2) GRADE-TCM upgrading criteria, 3) GRADE-TCM evaluation standard, 4) principles of consensus and recommendation, and 5) presentation of the GRADE-TCM and recommendation. Finally, consensus was reached on the above 10 entries, and the results were of high importance (with voting percentages ranging from 50 % to 81.82 % for "very important" rating) and strong reliability (with the Cr ranging from 0.93 to 0.99). Expert discussion meeting (with 40 experts), opinion collection (in two online platforms) and external examination (with 14 third-party experts) were conducted, and the GRADE-TCM was established eventually. CONCLUSION: GRADE-TCM provides a new extended evidence-based evaluation standard for TCM guidelines. In GRADE-TCM, international evidence-based norms, characteristics of TCM intervention, and inheritance of TCM culture were combined organically and followed. This is helpful for localization of the GRADE in TCM and internationalization of TCM guidelines.