Research on safety condition assessment methodology for single tower steel box girder suspension bridges over the sea based on improved AHP-fuzzy comprehensive evaluation.

In order to propose a reliable method for assessing the safety condition for single-tower steel box girder Suspension bridges over the sea, a condition monitoring system is established by installing sensors on the bridge structure. The system is capable of gathering monitoring data that influence the safety status of the bridge. These include cable tension, load on the main tower and pylon, bearing displacement, wind direction, wind speed, and ambient temperature and humidity. Furthermore, an improved Analytic Hierarchy Process (AHP) algorithm is developed by integrating a hybrid triangular fuzzy number logic structure. This improvement, coupled with comprehensive fuzzy evaluation methods, improves the consistency, weight determination, and security evaluation capabilities of the AHP algorithm. Finally, taking the No.2 Channel Bridge as an example and based on the data collected by the health monitoring system, the application of the safety assessment method proposed in this paper provides favorable results in evaluating the overall safety status of the bridge in practical engineering applications. This provides a basis for management decisions by bridge maintenance departments. This project confirms that the research results can provide a reliable method for assessing the security status of relevant areas.

Enhanced YOLO v3 for precise detection of apparent damage on bridges amidst complex backgrounds.

A bridge disease identification approach based on an enhanced YOLO v3 algorithm is suggested to increase the accuracy of apparent disease detection of concrete bridges under complex backgrounds. First, the YOLO v3 network structure is enhanced to better accommodate the dense distribution and large variation of disease scale characteristics, and the detection layer incorporates the squeeze and excitation (SE) networks attention mechanism module and spatial pyramid pooling module to strengthen the semantic feature extraction ability. Secondly, CIoU with better localization ability is selected as the loss function for training. Finally, the K-means algorithm is used for anchor frame clustering on the bridge surface disease defects dataset. 1363 datasets containing exposed reinforcement, spalling, and water erosion damage of bridges are produced, and network training is done after manual labelling and data improvement in order to test the efficacy of the algorithm described in this paper. According to the trial results, the YOLO v3 model has enhanced more than the original model in terms of precision rate, recall rate, Average Precision (AP), and other indicators. Its overall mean Average Precision (mAP) value has also grown by 5.5%. With the RTX2080Ti graphics card, the detection frame rate increases to 84 Frames Per Second, enabling more precise and real-time bridge illness detection.

Inequities among patient placement in emergency department hallway treatment spaces.

BACKGROUND: Limited capacity in the emergency department (ED) secondary to boarding and crowding has resulted in patients receiving care in hallways to provide access to timely evaluation and treatment. However, there are concerns raised by physicians and patients regarding a decrease in patient centered care and quality resulting from hallway care. We sought to explore social risk factors associated with hallway placement and operational outcomes. STUDY DESIGN/METHODS: Observational study between July 2017 and February 2020. Primary outcome was the adjusted odds ratio (aOR) of patient placement in a hallway treatment space adjusting for patient demographics and ED operational factors. Secondary outcomes included left without being seen (LWBS), discharge against medical advice (AMA), elopement, 72-h ED revisit, 10-day ED revisit and escalation of care during boarding. RESULTS: Among 361,377 ED visits, 100,079 (27.7%) visits were assigned to hallway beds. Patient insurance coverage (Medicaid (aOR 1.04, 95% CI 1.01,1.06) and Self-pay/Other (1.08, (1.03, 1.13))) with comparison to private insurance, and patient sex (Male (1.08, (1.06, 1.10))) with comparison to female sex are associated with higher odds of hallway placement but patient age, race, and language were not. These associations are adjusted for ED census, triage assigned severity, ED staffing, boarding level, and time effect, with social factors mutually adjusted. Additionally adjusting for patients' social factors, patients placed in hallways had higher odds of elopement (1.23 (1.07,1.41)), 72-h ED revisit (1.33 (1.08, 1.64)) and 10-day ED revisit (1.23 (1.11, 1.36)) comparing with patients placed in regular ED rooms. We did not find statistically significant associations between hallway placement and LWBS, discharge AMA, or escalation of care. CONCLUSION: While hallway usage is ad hoc, we find consistent differences in care delivery with those insured by Medicaid and self-pay or male sex being placed in hallway beds. Further work should examine how new front-end processes such as provider in triage or split flow may be associated with inequities in patient access to emergency and hospital care.

Sociodemographic Disparities in Queue Jumping for Emergency Department Care.

Importance: Emergency department (ED) triage models are intended to queue patients for treatment. In the absence of higher acuity, patients of the same acuity should room in order of arrival. Objective: To characterize disparities in ED care access as unexplained queue jumps (UQJ), or instances in which acuity and first come, first served principles are violated. Design, Setting, and Participants: Retrospective, cross-sectional study between July 2017 and February 2020. Participants were all ED patient arrivals at 2 EDs within a large Northeast health system. Data were analyzed from July to September 2022. Exposure: UQJ was defined as a patient being placed in a treatment space ahead of a patient of higher acuity or of a same acuity patient who arrived earlier. Main Outcomes and Measures: Primary outcomes were odds of a UQJ and association with ED outcomes of hallway placement, leaving before treatment complete, escalation to higher level of care while awaiting inpatient bed placement, and 72-hour ED revisitation. Secondary analysis examined UQJs among high acuity ED arrivals. Regression models (zero-inflated Poisson and logistic regression) adjusted for patient demographics and ED operational variables at time of triage. Results: Of 314 763 included study visits, 170 391 (54.1%) were female, the mean (SD) age was 50.46 (20.5) years, 132 813 (42.2%) patients were non-Hispanic White, 106 401 (33.8%) were non-Hispanic Black, and 66 465 (21.1%) were Hispanic or Latino. Overall, 90 698 (28.8%) patients experienced a queue jump, and 78 127 (24.8%) and 44 551 (14.2%) patients were passed over by a patient of the same acuity or lower acuity, respectively. A total of 52 959 (16.8%) and 23 897 (7.6%) patients received care ahead of a patient of the same acuity or higher acuity, respectively. Patient demographics including Medicaid insurance (incident rate ratio [IRR], 1.11; 95% CI, 1.07-1.14), Black non-Hispanic race (IRR, 1.05; 95% CI, 1.03-1.07), Hispanic or Latino ethnicity (IRR, 1.05; 95% CI, 1.02-1.08), and Spanish as primary language (IRR, 1.06; 95% CI, 1.02-1.10) were independent social factors associated with being passed over. The odds of a patient receiving care ahead of others were lower for ED visits by Medicare insured (odds ratio [OR], 0.92; 95% CI, 0.88-0.96), Medicaid insured (OR, 0.81; 95% CI, 0.77-0.85), Black non-Hispanic (OR, 0.94; 95% CI, 0.91-0.97), and Hispanic or Latino ethnicity (OR, 0.87; 95% CI, 0.83-0.91). Patients who were passed over by someone of the same triage severity level had higher odds of hallway bed placement (OR, 1.01; 95% CI, 1.00-1.02) and leaving before disposition (OR, 1.02; 95% CI, 1.01-1.04). Conclusions and Relevance: In this cross-sectional study of ED patients in triage, there were consistent disparities among marginalized populations being more likely to experience a UQJ, hallway placement, and leaving without receiving treatment despite being assigned the same triage acuity as others. EDs should seek to standardize triage processes to mitigate conscious and unconscious biases that may be associated with timely access to emergency care.