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The construction industry is characterized by long production cycles, poor mobility of workers, various kinds of outdoor operations and complex construction processes, leading to frequent safety accidents. To explore the occurrence rule of the construction accidents in building construction, this paper applied knowledge graph technology in the field of artificial intelligence to analyze construction accidents. Firstly, defining the conceptual architecture of the domain knowledge graph. Secondly, extracting key knowledge elements from construction accident data. The knowledge graph of construction accidents has been established by using the Neo4j graph database. Further, a construction accident analysis process based on the knowledge graph has been proposed. The intelligent analysis, such as query, statistical analysis and correlation path analysis for accident information have been conducted. The results shows that based on knowledge graph technology, construction accidents in visual graphics or tables could be visualized. The accident information in the form of knowledge could be saved and queried quickly. The study can provide knowledge support for accident prevention and improve the efficiency of accident analysis. Besides, it can provide innovative ideas as well as decision support for safety management.

Solar energy is potentially the largest source of renewable energy for providing electrical power for human society. However, significant advances are required to make photovoltaic technologies have a low-carbon footprint in manufacture, be environmentally friendly at the end of their lives through recyclability, and be biodegradable. Here we report dissolvable organic photovoltaic devices based on poly(2-hydroxyethyl methacrylate), which show equal power conversion efficiency to their glass substrate-based counterparts. We use a novel method of including smectic liquid crystal (7-dioctyl[1]benzothieno[3,2- b][1]benzothiophene, C8-BTBT) as a crystal phase regulator in the heterojunction donor:acceptor polymer system to maintain the disposable organic solar cell efficiency without pre- or post-thermal annealing. The results show strong promise not only for more sustainable solar-cell fabrication but also as disposable and biocompatible solar cells for self-powered (energy harvesting) wearable and biomedical devices. [ABSTRACT FROM AUTHOR]

Background: In patients with Cushing's disease, the preoperative identification of pituitary adenomas is crucial to treatment. However, increasing diagnostic accuracy remains an unresolved issue. Purpose: To evaluate the diagnostic accuracy and the impact of readers' experience regarding high‐resolution contrast‐enhanced magnetic resonance imaging (hrMRI) for identifying pituitary adenomas in comparison with conventional contrast‐enhanced MRI (cMRI) and dynamic contrast‐enhanced MRI (dMRI). Study Type: Retrospective. Population: Sixty‐five patients (median age, 39 years; interquartile range [IQR], 28–53 years; 60% females) with treatment‐naïve Cushing's disease. Field Strength/Sequence: 3‐T, seven fast spin echo sequences. Assessment: The diagnostic accuracies of identifying pituitary adenomas on cMRI, dMRI, combined cMRI and dMRI (cdMRI), and hrMRI were independently evaluated by six readers with three experience levels (high: >20 years, modest: 10–20 years, low: <10 years; two readers for each experience level). Readers were asked to localize the lesion, and measure its diameter on the sequence where identified. The reference standard was postoperative histopathology. The impact of readers' experience and interobserver agreement were assessed. Image quality was assessed using a 5‐point Likert scale, including overall image quality, sharpness, and structural conspicuity. Statistical Tests: McNemar's test, Cochran's test, Wilcoxon signed‐rank test, Mann–Whitney U test, and κ statistics for interobserver agreement. A P‐value <0.05 was considered statistically significant. Results: For identifying pituitary adenomas (median diameter, 5 mm; IQR, 4–5 mm), hrMRI had significantly higher sensitivity (87.7%–93.8%) than cMRI, dMRI, and cdMRI (52.3%–75.4%) for readers with different experience levels. The interobserver agreement was moderate (κ = 0.461–0.523). The sensitivity for hrMRI was comparable between readers with different experience levels (P = 0.371). All image quality scores on hrMRI were significantly higher than cMRI and dMRI (5.0 vs. 4.0). Data Conclusion: For identifying pituitary adenomas in patients with treatment‐naïve Cushing's disease, hrMRI may show high diagnostic accuracy and seems not to be affected by readers' experience. Level of Evidence: 3 Technical Efficacy: Stage 2 [ABSTRACT FROM AUTHOR]

There are various methods to evaluate the forming limit of a sheet, and these criteria can be classified as position-dependent, time-dependent, and position-time dependent according to the basis of judgment. However, these criteria have a single function and can only find the forming limit of the sheet and cannot determine the strain distribution, strain change, or fracture location during the sheet forming process. This paper introduces a time–location-dependent method, i.e., the spatial strain rate method, which is used to detect the onset of necking of a sheet. The spatial strain rate is directly based on the strain and can not only find the forming limit of the sheet but also depict the strain distribution and strain variation during the two phases of the experimental process—distributed instability and concentrated instability—as well as predict the location of sheet fracture. The spatial strain rate of AA5083 aluminum alloy of different widths was analyzed and verified in detail via Nakazima experiments using digital image correlation techniques and compared with the guidelines published in the literature in recent years. [ABSTRACT FROM AUTHOR]

The asymmetric calibration method is a very interesting technology for differential output probes. It has been proven that the asymmetric calibration method (ACM) can broaden the application scenarios of the electromagnetic field dual probe. However, ACM is not verified on a back‐to‐back double‐loop differential magnetic field probing system. This paper calibrates a back‐to‐back double‐loop differential magnetic field probing system by inserting a connector for creating an asymmetry using ACM. The calibration results show that ACM can be used to calibrate an asymmetric back‐to‐back double‐loop differential magnetic field probing system. The calibration results are further verified by measuring the standing wave magnetic field, and the verification results show that the asymmetric calibration method is effective in eliminating the asymmetry of the back‐to‐back double‐loop differential magnetic field probing system and the work frequency band reaches up to 12 GHz. [ABSTRACT FROM AUTHOR]