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This study delves into the complex prioritization process for Autism Spectrum Disorder (ASD), focusing on triaged patients at three urgency levels. Establishing a dynamic prioritization solution is challenging for resolving conflicts or trade-offs among ASD criteria. This research employs fuzzy multi-criteria decision making (MCDM) theory across four methodological phases. In the first phase, the study identifies a triaged ASD dataset, considering 19 critical medical and sociodemographic criteria for the three ASD levels. The second phase introduces a new Decision Matrix (DM) designed to manage the prioritization process effectively. The third phase focuses on the new extension of Fuzzy-Weighted Zero-Inconsistency (FWZIC) to construct the criteria weights using Single-Valued Neutrosophic 2-tuple Linguistic (SVN2TL). The fourth phase formulates the Multi-Attributive Border Approximation Area Comparison (MABAC) method to rank patients within each urgency level. Results from the SVN2TL-FWZIC weights offer significant insights, including the higher criteria values \"C12 = Laughing for no reason\" and \"C16 = Notice the sound of the bell\" with 0.097358 and 0.083832, indicating their significance in identifying potential ASD symptoms. The SVN2TL-FWZIC weights offer the base for prioritizing the three triage levels using MABAC, encompassing medical and behavioral dimensions. The methodology undergoes rigorous evaluation through sensitivity analysis scenarios, confirming the consistency of the prioritization results with critical analysis points. The methodology compares with three benchmark studies, using four distinct points, and achieves a remarkable 100% congruence with these prior investigations. The implications of this study are far-reaching, offering a valuable guide for clinical psychologists in prioritizing complex cases of ASD patients.

Background and Objectives: Triage systems help provide the right care at the right time for patients presenting to emergency departments (EDs). Triage systems are generally used to subdivide patients into three to five categories according to the system used, and their performance must be carefully monitored to ensure the best care for patients. Materials and Methods: We examined ED accesses in the context of 4-level (4LT) and 5-level triage systems (5LT), implemented from 1 January 2014 to 31 December 2020. This study assessed the effects of a 5LT on wait times and under-triage (UT) and over-triage (OT). We also examined how 5LT and 4LT systems reflected actual patient acuity by correlating triage codes with severity codes at discharge. Other outcomes included the impact of crowding indices and 5LT system function during the COVID-19 pandemic in the study populations. Results: We evaluated 423,257 ED presentations. Visits to the ED by more fragile and seriously ill individuals increased, with a progressive increase in crowding. The length of stay (LOS), exit block, boarding, and processing times increased, reflecting a net raise in throughput and output factors, with a consequent lengthening of wait times. The decreased UT trend was observed after implementing the 5LT system. Conversely, a slight rise in OT was reported, although this did not affect the medium-high-intensity care area. Conclusions: Introducing a 5LT improved ED performance and patient care.

Rainstorm disasters cause serious threats to people’s lives and property. Enhancing emergency response and decision-making capabilities for rainstorm disasters is necessary. In this paper, 87 rainstorm disasters worldwide were first analysed, and secondary events across 15 urban lifeline systems were summarized. Based on the obtained findings and the characteristics of rainstorm disaster evolution and complex network theory, a model of rainstorm disaster chains in urban lifeline systems was constructed, and both partial and overall analyses of this model were performed. With the use of the PageRank risk matrix method, quantitative node risk levels were calculated for different parts of the model, and complex network theory was applied to assess the overall chain risk. The results showed that the highest risk disaster chain was flood → houses submerged or collapsed → road damaged → traffic congestion or paralysis. The most important node was traffic congestion or paralysis, underlining the acute need for emergency response measures in urban traffic systems during rainstorm disasters. Overall, this research provides a crucial direction for preventing rainstorm disasters in urban lifeline systems.

The overuse of compression ultrasound procedures on patients with suspected deep vein thrombosis compromise the cost-effectiveness of deep vein thrombosis management and emphasize room for improvement of the current diagnostic algorithm. As the complement system and hemostasis are comprehensively intertwined, we aimed to investigate complement activation products as diagnostic tests for acute deep vein thrombosis alone or together with D-dimer. We performed a cross-sectional study using consecutive sampling of outpatients referred to the emergency department with suspected first-time deep vein thrombosis of the lower limbs, to investigate the diagnostic utility of the index tests C3bc and C5b-C9 terminal complex (TCC) with compression ultrasound as reference standard. For comparison of receiver operating characteristics, analyses were also performed for D-dimer and C-reactive protein in addition to analyses for the index tests on a D-dimer positive patient subgroup. Of the 366 included patients, 103 had deep vein thrombosis. The calculated effect sizes of differences between groups (Cohen's d) with 95% confidence intervals (95%CI) were 0.25 (95%CI 0.03-0.48) for C3bc, 0.33 (95%CI 0.09-0.57) for C5b-C9 terminal complex (TCC), 0.88 (95%CI 0.61-1.15) for C-reactive protein, and 1.64 (95%CI 1.37-1.91) for D-dimer. The areas under the curves derived from comparison receiver operating characteristics analyses with corresponding 95%CIs for C3bc, C5b-C9 terminal complex (TCC), C-reactive protein and D-dimer were 0.56 (95%CI 0.50-0.63), 0.64 (95%CI 0.58-0.69), 0.73 (95%CI 0.67-0.79) and 0.92 (95%CI 0.89-0.95), respectively. The plasma levels of the complement activation products C3bc and C5b-C9 terminal complex (TCC) were elevated in patients with acute deep vein thrombosis but displayed low diagnostic performance for deep vein thrombosis alone or together with D-dimer.

Purpose. To work out the method for activities efficiency assessment of the governing body’s task force under environmental emergency. In order to achieve this goal, it is proposed to apply an integrated approach that allows increasing the effectiveness of its work. Methodology. The method for activities efficiency assessment of the governing body’s task force under environmental emergency was applied which allowed determining the degree of its capabilities realization. To study this process, a systematic approach was used, according to which the governing body is considered as a complex system that has a hierarchical structure and is a set of functionally interconnected structural units, united in their activities by the shared goal, concept and action plan. Findings. As the task force’s activity basis, a reasonable decision was determined of the governing body’s head, at the development and implementation of which the task force’s work is aimed. The task force’s efforts coordination is carried out in accordance with the tasks, directions, areas, time and methods of tasks performing that are assigned to the subdivisions of the governing body. As the main factor in activities efficiency assessment, the training level of the governing body’s task force was determined, that stipulates its professional and personal features. Originality. The proposed method for activities efficiency assessment of the governing body’s task force is estimated using an integral index – the degree of its capabilities realization to perform tasks. In the mentioned method, the criterion for activities efficiency of the governing body’s task force is determined as a condition under which the quotient from division of the total capabilities realized by the governing body’s task force indicator by the indicator of its total potential capabilities is in the range 0.8–1. A diagram of the method for assessing the task force’s activities efficiency was elaborated, containing interrelated blocks (activities), direct connections and feedback, which generally characterizes the sequence and actions content of the governing body’s head when implementing the mentioned method. Practical value. An example of estimating the activities efficiency of the governing body’s task force to achieve the goal in terms of an integral index – the degree of its capabilities realization to perform tasks, which is calculated using the proposed method, was considered. The initial data for calculation were the main tasks performed by the environmental emergency response headquarters’ task force, standard time indicators and prescribed time for tasks performance designated by the governing body’s head. On this basis, an analysis of the headquarters’ actions on eliminating the emergency consequences connected with the blowing up of the Kakhovska HPP was carried out, its main tasks and features of the decision-making process in uncertain conditions were established. The directions of increasing activities efficiency of the governing body’s task force were elaborated, in particular by increasing their professional competence, implementing innovative approaches to the transformation of governing styles, rational tasks distribution.

To address the difficulty frontline commanders face in accurately perceiving fireground risks during the early stages of oil storage tank fires, in this study, we propose a method that integrates complex network theory with a multi-source information fusion approach based on cloud models and Dempster-Shafer (D-S) evidence theory for situational analysis and dynamic perception. Initially, the internal evolution of accident scenarios within individual tanks is modeled as a single-layer network, while scenario propagation between tanks is represented through inter-layer connections, forming a multi-layer complex network for the storage area. The importance of each node is evaluated to assess the risk level of scenario nodes, enabling preliminary situational awareness, with limited reconnaissance information. Subsequently, the cloud model’s capability to handle fuzziness is combined with D-S theory’s strength in fusing multi-source data. Multi-source heterogeneous information is integrated to obtain the confidence levels of key nodes across low, medium, and high-risk categories. Based on these results, high-risk scenarios in oil storage tank emergency response are dynamically adjusted, enabling the updating and prediction of accident evolution. Finally, the proposed method is validated using the 2015 Gulei PX plant explosion case study. The results demonstrate that the approach effectively identifies high-risk scenarios, enhances dynamic situational perception, and is generally consistent with actual accident progression, thereby improving emergency response capability.

Accurate storm surge forecasting is vital for saving lives and avoiding economic and infrastructural damage. Failure to accurately predict storm surge can have catastrophic repercussions. Advances in machine learning models show the ability to improve accuracy of storm surge prediction by leveraging vast amounts of historical and realtime data such as weather and tide patterns. This paper proposes a bidirectional attention-based LSTM storm surge architecture (BALSSA) to improve prediction accuracy. Training and evaluation utilized extensive meteorological and tide level data from 77 typhoon incidents in Hong Kong and Macao between 2017 and 2022. The proposed methodology is able to model complex non-linearities between large amounts of data from different sources and identify complex relationships between variables that are typically not captured by traditional physical methods. BALSSA effectively resolves the problem of long-term dependencies in storm surge prediction by the incorporation of an attention mechanism. It enables selective emphasis on significant features and boosts the prediction accuracy. Evaluation has been conducted using real-world datasets from Macao to validate our storm surge prediction model. Results show that accuracy and robustness of predictions were significantly improved by the incorporation of attention mechanisms in our models. BALSSA captures temporal dynamics effectively, providing highly accurate storm surge forecasts (MAE: 0.0126, RMSE: 0.0003) up to 72 h in advance. These findings have practical significance for disaster risk reduction strategies, saving lives through timely evacuation and early warnings. Experiments comparing BALSSA variations with other machine learning algorithms consistently validate BALSSA’s superior predictive performance. It offers an additional risk management tool for civil-protection agencies and governments, as well as an ideal solution for enhancing storm surge prediction accuracy, benefiting coastal communities.

The complement system (CS) plays a pivotal role in Coronavirus disease 2019 (COVID-19) pathophysiology. The objective of this study was to provide a comparative, prospective data analysis of CS components in an all-comers cohort and COVID-19 patients. Patients with suspected COVID-19 infection admitted to the Emergency department were grouped for definite diagnosis of COVID-19 and no COVID-19 accordingly. Clinical presentation, routine laboratory and von Willebrand factor (vWF) antigen as well as CS components 3, 4 and activated 5 (C5a) were assessed. Also, total complement activity via the classical pathway (CH50) was determined. Levels of calprotectin in serum were measured using an automated quantitative lateral flow assay. We included 80 patients in this prospective trial. Of those 19 (23.7%) were tested positive for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Patients with COVID-19 had higher levels of CS components 5a and 4 (54.79 [24.14–88.79] ng/ml vs. 35 [23.15–46.1] ng/ml; p = 0.0433 and 0.3772 [± 0.1056] g/L vs. 0.286 [0.2375–0.3748] g/L; p = 0.0168). COVID-19 patients had significantly higher levels of vWF antigen when compared to the control group (288.3 [± 80.26] % vs. 212 [151–320] %; p = 0.0469). There was a significant correlation between CS C3 and 5a with vWF antigen (rs = 0.5957 [p = 0.0131] and rs = 0.5015 [p = 0.042]) in COVID-19 patients. There was no difference in calprotectin plasma levels (4.786 [± 2.397] µg/ml vs. 4.233 [± 2.142] µg/ml; p = 0.4175) between both groups. This prospective data from a single centre all-comers cohort accentuates altered levels of CS components as a distinct feature of COVID-19 disease. Deregulation of CS component 3 and C5a are associated with increased vWF antigen possibly linking vascular damage to alternative CS activation in COVID-19.

Container transportation has the advantages of standardization, high efficiency, and high safety, which are essential for promoting the development of the world economy and trade. Emergencies such as severe weather, public health incidents, and social security incidents can negatively affect the operational reliability of the container shipping network. To ensure the network security and high-quality operation of container shipping, a double-layer coupled container transportation network is first described to analyze the evolution of the container shipping network and the risk propagation dynamics of operation participants. On this basis, a cascade failure model of the container shipping network considering risk level is constructed. To evaluate the vulnerability of the container shipping network, the transmission mechanism of cascade failure effects of the container shipping network under different emergency development trends and the evolution law and influence path of the container shipping network structure are both analyzed. Finally, we empirically studied the container shipping network in China and the United States, and characteristic parameters of the China–U.S. container shipping network are calculated and analyzed. The model’s validity is verified through practical cases and model simulation results, and the cascading failure process of the container shipping network in China and the United States under three types of attacks is simulated. Suggestions are provided for effective improvement in the vulnerability of the container shipping network under every kind of contingency.

Introduction The activation of the plasmatic coagulation system is a significant contributor to acute myocardial infarction (AMI). This study aimed to investigate the association between the levels of tissue plasminogen activator-inhibitor complex (t-PAIC), thrombin-antithrombin complex (TAT), plasmin-α2 plasmin-inhibitor complex (PIC), and thrombomodulin (TM) with clinical outcomes in patients with AMI. Methods Blood samples were collected from 368 patients presenting with acute myocardial infarction in the emergency department to assess levels of t-PAIC, TAT, PIC, and TM. Patients were subsequently followed up for a period of 6 months. Results t-PAIC levels were significantly elevated in AMI patients who died compared to those who survived ( P  < 0.0001). Specifically, of the 368 patients, 48 died and had higher t-PAIC levels above the determined cut-off value of 15.3 ng/mL, while 320 survived and had levels below this threshold ( P  < 0.001). Furthermore, among the survivors, t-PAIC levels were greater in the major adverse cardiovascular events (MACE) group than in the non-MACE group throughout the 6-month follow-up. Linear regression analysis indicated that high levels of t-PAIC were linked to mortality following acute myocardial infarction and raised the likelihood of MACE in survivors. The ROC curve study revealed that t-PAIC has predictive value for mortality following AMI, with an AUC of 0.871 (95% CI: 0.833–0.904), sensitivity of 81.25%, and specificity of 88.75%. Analysis of the ROC curve and Kaplan–Meier survival curve demonstrated that t-PAIC was able to forecast MACE in individuals who had experienced an AMI, with an AUC of 0.671 (95% CI: 0.620—0.719) for 6-month MACE occurrences. Conclusion Our findings suggest that increased t-PAIC levels are correlated with mortality in patients with AMI and the incidence of MACE within a six-month period in survivors.