Over the past decade, crowdsourcing has emerged as a powerful tool in various scenarios and has led to an increasing need for crowdsourced emergency management. An important aspect of emergency management includes the acquisition of crowdsourced emergency information. Therefore, to study the emergency information acquisition, we propose a crowdsourced framework. During crowdsourcing, the public is recruited to work on collection of emergency information, such as photos and videos. Therefore, a considerable challenge in crowdsourced emergency information acquisition is to efficiently attract the public to engage in this work. A task price is a significant potential factor that influences public participation. Therefore, a random forest algorithm-based task pricing model and task-accomplished model are computed based on the task attributes and neighboring-workers attributes. In addition,the making money by taking photos dataset is used for a simulation of the proposed method in scikit-learn. Our simulation results demonstrate that the proposed method has an average reduction in Mean Squared Error (MSE) by 44.16 % for task pricing and an average increase in accuracy of 17.71 % for task-accomplished prediction compared to traditional regression models. It is shown that the proposed method has high accuracy and efficiency in crowdsourced emergency information acquisition. Moreover, the proposed method can provide valuable references in the future for emergency information acquisition strategy studies.

BACKGROUND:Transjugular intrahepatic portosystemic shunt (TIPS) is a highly effective treatment for complications associated with portal hypertension. However, stent fracture, although extremely rare, represents a potentially serious complication following TIPS creation. Timely identification and management are crucial for preventing further adverse events. CASE SUMMARY:We report a 56-year-old male patient who underwent a TIPS procedure for recurrent melena caused by portal hypertension secondary to hepatitis B and experienced a stent fracture 15 months post-procedure. He was readmitted 30 months after the initial TIPS due to recurrent esophagogastric variceal bleeding and ascites. An attempt to revise the dysfunctional shunt via a stent-in-stent approach was unsuccessful. Consequently, a parallel TIPS procedure was successfully performed via the proximal end of the fractured stent to decompress the portal venous system. At the 1-month follow-up, the patient exhibited no recurrent variceal bleeding, and his ascites had significantly decreased. Twelve-month postoperative monitoring revealed no hepatic encephalopathy and no recurrence of bleeding or ascites. Additionally, we review the existing literature on post-TIPS stent fractures to explore the underlying mechanisms contributing to this complication. CONCLUSION:Early recognition and prompt intervention are essential in managing stent fractures after TIPS creation to mitigate potential risks and ensure optimal patient outcomes.

Obtaining high-quality data often poses significant challenges in real-world scenarios, resulting in poorly performing traditional machine learning (ML) models. To address this issue, this study developed a decision-making approach that combines ML with expert subjective examination and applied it to assessing house damage caused by typhoons. First, an ML model was constructed based on similar cases, selecting data from the optimal number of similar cases as the training data, thereby significantly improving data quality. Subsequently, a decisionmaking method was developed based on evidential reasoning. By integrating the predictive results of multiple ML models, the advantages of various models were utilized to enhance prediction accuracy and robustness. Additionally, expert opinions were integrated to introduce domain knowledge and experience, further optimizing the prediction results. Finally, experiments verified the effectiveness of the proposed decision-making method in evaluating house damage caused by typhoons and compared it with traditional ML algorithms. The results indicate that the proposed method provides a flexible decision-making approach that combines ML and expert subjective examination, thereby effectively enhancing decision accuracy.

With the rapid development of modern technology and the frequent occurrence of public crises, efficient volunteer dispatch has become a key issue in emergency rescue. This paper proposes a volunteer dispatch method based on the Q-learning algorithm and two-sided matching theory to achieve optimal matching between volunteers and rescue tasks. By combining multi-attribute similarity assessment with interview results, a Q-table and a reward table are constructed to overcome the shortcomings of relying on subjective weight settings in traditional dispatch methods and achieve dynamic adaptive optimisation of dispatch plans. The experimental results show that this method outperforms conventional methods in terms of matching accuracy, computational efficiency, and decision adaptability, particularly in terms of robust convergence and stability in large-scale data environments. This study provides a flexible and efficient solution for volunteer dispatch, which holds significant potential for application for volunteer management during public crises.

A method for internal participation in rescue decision-making of emergency volunteer teams considering psychological behavior is proposed to address the time sequence of rescue tasks.Firstly,the problem of multi-tasking and multi-operation within the emergency volunteer team is described.Secondly,considering that task leaders are influenced by behavioral and psychological factors in the evaluation,the required time for the job is used as a reference point,and the expected time that volunteers can complete the job is used as an attribute value.The task leader's prospect satisfaction value for each volunteer is calculated based on prospect theory,and the perceived utility values of disappointment theory and regret theory are calculated to measure the task leader's satisfaction with each volunteer.Furthermore,a multilayer coded genetic algorithm is used to construct an optimization model for emergency volunteer decision-making with the objective of maximizing the satisfaction value.Finally,the feasibility and effectiveness of this method are illustrated by an example analysis.The result shows that the efficiency of rescue tasks can be improved through decision optimization within the volunteer team.

PurposeThis study aims to enhance the classification and processing of online appeals by employing a deep-learning-based method. This method is designed to meet the requirements for precise information categorization and decision support across various management departments.Design/methodology/approachThis study leverages the ALBERT–TextCNN algorithm to determine the appropriate department for managing online appeals. ALBERT is selected for its advanced dynamic word representation capabilities, rooted in a multi-layer bidirectional transformer architecture and enriched text vector representation. TextCNN is integrated to facilitate the development of multi-label classification models.FindingsComparative experiments demonstrate the effectiveness of the proposed approach and its significant superiority over traditional classification methods in terms of accuracy.Originality/valueThe original contribution of this study lies in its utilization of the ALBERT–TextCNN algorithm for the classification of online appeals, resulting in a substantial improvement in accuracy. This research offers valuable insights for management departments, enabling enhanced understanding of public appeals and fostering more scientifically grounded and effective decision-making processes.

Background: Drug-eluting bead transarterial chemoembolization (DEB-TACE) has shown efficacy for treating hepatocellular carcinoma (HCC) with portal vein tumor thrombus (PVTT). However, whether DEB-TACE is superior to conventional TACE (cTACE) remains unclear. Objective: This randomized controlled trial aimed to compare the efficacy and safety of DEB-TACE versus cTACE in treating HCC with PVTT. Methods:The study was conducted at a tertiary care center in Southeast China. HCC patients with PVTT were randomized at a 1:1 ratio into the DEB-TACE or cTACE groups. The primary endpoint was progression-free survival (PFS), and the secondary endpoints were overall survival (OS) and the incidence of adverse events (AEs). An independent review committee assessed the radiologic response according to the modified Response Evaluation Criteria in Solid Tumors (mRECIST). AEs were assessed by the Common Terminology Criteria for Adverse Events (CTCAE) version 4.0. Systemic therapies were not restricted. Results:Between September 2018 and July 2020, 163 patients were randomized to undergo DEB-TACE (n=82) or cTACE (n=81). Nine patients were excluded, and 154 patients were included in the final analysis; the median age was 55 years (range, 24-78 years), and 140 (90.9%) were male. The median PFS in the DEB-TACE group was 6.0 months (95% CI, 5.0-10.0) versus 4.0 months (95% CI, 3.0-5.0) in the cTACE group (hazard ratio, 0.63; 95% CI, 0.42-0.95; P=0.027). The DEB-TACE group showed a higher response rate [51 (66.2%) vs. 36 (46.8%); P=0.0015] and a longer median OS [12.0 months (95% CI, 9.0-16.0) vs. 8.0 months (95% CI, 7.0-11.0), P=0.039] than the cTACE group. Multivariate analysis showed that the treatment group, ALBI score, distant metastasis and additional TKIs were the four independent prognostic factors correlated with PFS. In addition, the treatment group, PVTT group and combination with surgery were independently associated with OS. AEs were similar in the two groups, and postembolization syndrome was the most frequent AE. Conclusion:DEB-TACE is superior to cTACE in treating HCC patients with PVTT, demonstrating improved PFS and OS with an acceptable safety profile, and may thus emerge as a promising treatment strategy for HCC patients with PVTT.

Purpose This paper aims to solve the major assessment problem in matching the satisfaction of psychological gratification and mission accomplishment pertaining to volunteers with the disaster rescue and recovery tasks. Design/methodology/approach An extended belief rule-based (EBRB) method is applied with the method's input and output parameters classified based on expert knowledge and data from literature. These parameters include volunteer self-satisfaction, experience, peer-recognition, and cooperation. First, the model parameters are set; then, the parameters are optimized through data envelopment analysis (DEA) and differential evolution (DE) algorithm. Finally, a numerical mountain rescue example and comparative analysis between with-DEA and without-DEA are presented to demonstrate the efficiency of the proposed method. The proposed model is suitable for a two-way matching evaluation between rescue tasks and volunteers. Findings Disasters are unexpected events in which emergency rescue is crucial to human survival. When a disaster occurs, volunteers provide crucial assistance to official rescue teams. This paper finds that decision-makers have a better understanding of two-sided match objects through bilateral feedback over time. With the changing of the matching preference information between rescue tasks and volunteers, the satisfaction of volunteer's psychological gratification and mission accomplishment are also constantly changing. Therefore, considering matching preference information and satisfaction at two-sided match objects simultaneously is necessary to get reasonable target values of matching results for rescue tasks and volunteers. Originality/value Based on the authors' novel EBRB method, a matching assessment model is constructed, with two-sided matching of volunteers to rescue tasks. This method will provide matching suggestions in the field of emergency dispatch and contribute to the assessment of emergency plans around the world.

Volunteer teams provide valuable support after large-scale disasters. However, excessive volunteer participation poses challenges for formal operations. Therefore, an appropriate decision-making method is required to quickly determine the number of volunteers required after a disaster. This study proposes a data-driven decision-making (D3M) method for typhoon disaster volunteerism that can effectively predict the number of volunteers required. Disaster data from actual cases were gathered, analyzed, and preprocessed to prepare the model. Feature selection, D3M model training and optimization, and model validation were performed to fine-tune the volunteer participant predictions. Using data from an actual typhoon in the Philippines, the rationality and efficacy of the method were verified through a comparative analysis of the experimental results. The proposed method learns from disaster-event data to quickly predict the number of volunteers needed, such that it not only reasonably allocates volunteers to assist professional teams in rescue but also avoids secondary problems caused by an overwhelming response.

According to management by objectives (MBO) theory, the significance of management objectives must be considered as a reference point in a performance evaluation. Cross efficiency evaluation has always been considered to be one of the important performance evaluation methods. However, few studies to date have considered the impact of management objectives on cross efficiency. According to prospect theory, the choice of reference point will cause irrational psychology in decision makers. A management objective is a natural reference point, which will cause a ‘gain and loss’ psychology in enterprises and may create irrational psychology. Performance level is an important index by which to evaluate resource allocation, which in turn can be regarded as an important enterprise management objective. This paper proposes a cross efficiency evaluation method based on performance level. Cross efficiency evaluation models are constructed, based on the irrational psychology that occurs under organization objectives, personal objectives and composite objectives. This method not only considers the bounded rational behavior of enterprises, but is also more flexible. A numerical example is given to illustrate the application of the bounded rational cross efficiency evaluation method in data envelopment analysis (DEA) ranking.

Background and Aim: Treatment strategy for hepatocellular carcinoma (HCC) and Vp4 [main trunk] portal vein tumor thrombosis (PVTT) remains limited due to posttreatment liver failure. We aimed to assess the efficacy of irradiation stent placement with 125 I plus transcatheter arterial chemoembolization (TACE) (ISP-TACE) compared to sorafenib plus TACE (Sora-TACE) in these patients. Methods: In this multicenter randomized controlled trial, participants with HCC and Vp4 PVTT without extrahepatic metastases were enrolled from November 2018 to July 2021 at 16 medical centers. The primary endpoint was overall survival (OS). The secondary endpoints were hepatic function, time to symptomatic progression, patency of portal vein, disease control rate, and treatment safety. Results: Of 105 randomized participants, 51 were assigned to the ISP-TACE group, and 54 were assigned to the Sora-TACE group. The median OS was 9.9 months versus 6.3 months (95% CI: 0.27–0.82; P =0.01). Incidence of acute hepatic decompensation was 16% (8 of 51) versus 33% (18 of 54) ( P =0.036). The time to symptomatic progression was 6.6 months versus 4.2 months (95% CI: 0.38–0.93; P =0.037). The median stent patency was 7.2 months (interquartile range, 4.7–9.3) in the ISP-TACE group. The disease control rate was 86% (44 of 51) versus 67% (36 of 54) ( P =0.018). Incidences of adverse events at least grade 3 were comparable between the safety populations of the two groups: 16 of 49 (33%) versus 18 of 50 (36%) ( P =0.73). Conclusion: Irradiation stent placement plus TACE showed superior results compared with sorafenib plus TACE in prolonging OS in patients with HCC and Vp4 PVTT.

A multi-person multi-task optimization dispatch method, which considers two-sided matching, is proposed for volunteers to enable them to assist government departments with disaster relief activities more efficiently. First, the method uses disappointment theory and a linear weighting method to calculate the bilateral satisfaction. More specifically, the method is based on the conditions and needs of the different evaluation indicators on both sides, and takes into account the psychological perception of the disappointment and rejoicing of both parties. Second, combined satisfaction is calculated with the goal of achieving the highest bilateral satisfaction consistency. Then, according to the demand of both parties, a multi-person multi-task optimization model is built, and an improved predator search algorithm is used to solve the model. The efficacy of the proposed method was evaluated using the "8.12" dangerous goods fire and explosion at Tianjin Port in China as an example. The results are compared and analyzed in terms of the three aspects to demonstrate the feasibility and superiority of this method.

BACKGROUND:Transjugular intrahepatic portosystemic shunt (TIPS) is a well-established therapeutic option for the management of variceal hemorrhage in patients with cirrhosis. The simultaneous migration of the coil and n-butyl-2-cyanoacrylate (NBCA) is an extremely rare but significant complication after TIPS. Because of its rare presentation, there are currently no definitive recommendations for the management of this condition.CASE PRESENTATION:A 46-year-old man with hepatitis B cirrhosis underwent TIPS placement for uncontrolled gastroesophageal varix (GEV) bleeding secondary to portal hypertension in August 2018. During the procedure, large GEVs were embolized using a coil and NBCA. After a year, coil and NBCA migration into the stomach was observed. Attempts to remove the coil using biopsy forceps during esophagogastroduodenoscopy failed. The patient refused further intervention on the coil to prevent further complications and received conservative therapy instead. Close surveillance with endoscopy is recommended for detecting coils and varices.CONCLUSIONS:The present case reports an extremely rare but significant complication after TIPS, which highlights the management and follow-up recommendation for such rare complications. Our experience may provide guidance for the management of future similar cases and stimulate discussion about treatment methods of similar patients.

To solve the problem of volunteer dispatch during the Coronavirus Disease 2019 (COVID-19) epidemic, a many-to-many two-sided matching volunteer dispatch method based on an improved predator-search algorithm is proposed. First, different evaluation index sets for volunteers and rescue tasks were developed, and weightings were determined using the analytic hierarchy process. Subsequently, the actual and expected values of the different indicators of the two parties were determined, and the triangular fuzzy number was used to calculate the satisfaction of the two parties. Based on this number, we used a linear weighting method to calculate the combined satisfaction and build a many-to-many two-sided matching model according to the demands of both parties. Subsequently, an improved predator-search algorithm was used to solve the model. Finally, taking the recruitment of volunteers for pneumonia epidemic prevention and control in Chun'an County as an example, the method proposed in our study was verified. A comparison and analysis of the results further demonstrated the feasibility and advantages of this method.

PurposeThe Chinese believe that “man will conquer the sky” and “fighting with the sky brings endless joy”. Considering that disaster assessment can be regarded as a two-person, zero-sum game problem between nature and human beings, this paper proposes a multi-attribute decision-making method based on game theory and grey theory in a single-value neutrosophic set environment. Due to the complexity and uncertainty of the decision-making environment, the method builds a decision matrix based on single-valued neutrosophic numbers.Design/methodology/approachFirst, the authors use the single-value neutrosophic information entropy to calculate the attribute weights and the weighted decision matrix. Second, the optimal mixed strategy method based on linear programming solves the optimal mixed strategy for both sides of the game so that the expected payoff matrix can be obtained. Finally, grey correlation analysis is used to obtain the closeness coefficient of each alternative based on the expectation payoff matrix to identify the ranking result of the alternative.FindingsAn example is used to verify the effectiveness of the proposed method, and its rationality is verified through a comprehensive comparison and analysis of the various aspects.Practical implicationsThe proposed decision-making method can be applied to typhoon disaster assessment. Such assessment results can provide intelligent decision support to the relevant disaster management departments, thereby reducing the negative impact of typhoon disasters on society, stabilizing society and improving people's happiness. Further, the method can be used for decision-making, recommendation and evaluation in other fields.Originality/valueThe proposed method uses single-value neutrosophic numbers to solve the information representation problem of decision-making in a complex environment. Under a new perspective, game theory is used to handle the decision matrix, while grey relational analysis converts inexact numbers to exact numbers for comparison and sorting. Thus, the proposed method can be used to make reasonable decisions while preserving information to the extent possible.

BACKGROUND:Hepatocellular carcinoma (HCC) associated with macroscopic vascular invasion and distant metastasis is an advanced-stage disease with an extremely poor prognosis and low survival rate. Therefore, there is an urgent need to develop novel therapeutic strategies to extend the lives of patients with advanced HCC.CASE PRESENTATION:We represent a case of HCC with macroscopic vascular invasion and pulmonary metastasis responding dramatically to the combination treatment with drug-eluting beads transarterial chemoembolization (DEB-TACE) and Huaier granule. A 64-year-old man with hepatitis B virus (HBV)-induced liver cirrhosis was diagnosed with advanced HCC involved renal vein and inferior vena cava accompanied by pulmonary metastasis. The patient received three cycles of on-demand DEB-TACE from 9th September 2016 to 22nd August 2017 and combined with Huaier granule 20 g three times a day orally. Eight months following the treatment, complete response occurred with regression of HCC and vascular thrombus and disappearance of pulmonary metastasis. The levels of AFP had decreased from 8165.8ng/mL to within the normal range (1.7 ng/mL). This is the first case report of complete response of HCC to the combination treatment with DEB-TACE and Huaier granule. At the most recent follow-up, he remained in remission 36 months after cessation of treatment without clinical or imaging evidence of disease recurrence. The current overall survival is 54 months since the initial treatment.CONCLUSION:Data from this clinical case report suggest that the combination treatment with DEB-TACE and Huaier granule is a promising therapeutic option for advanced HCC with macroscopic vascular invasion and distant metastasis.

In the wake of a large-scale disaster, volunteer teams provide invaluable assistance. There is a pressing need to design a suitable model to solve the problem of volunteer team dispatching. This paper proposes a novel approach from the perspective of two-sided matching, which could stimulate the enthusiasm of volunteers. However, it is almost impossible to use one or more fixed indicators to evaluate each volunteer team or rescue task. Even if the indicators can be determined, the values of some indicators are difficult to obtain. Therefore, the proposed approach uses the available information to recommend potential matching targets and revises some key targets based on the subjective preferences of participants. It effectively avoids the bias in decision-making caused by the unavailability of sufficient information and improves the satisfaction of bilateral participants. Furthermore, it can effectively solve the two-sided matching problem when the preference order is unknown. The proposed approach is illustrated with a simulation case that focuses on an explosion accident in China. The rationality and effectiveness of the approach is validated through comparisons and analyses of the experimental results.

Cross-efficiency evaluation methods have long been suggested as an alternative for the ranking of decision making units (DMUs) in data envelopment analysis (DEA). So far, little research on cross-efficiency evaluation takes the bounded rationality of DMUs into account. In this paper, we propose a neutral cross-efficiency evaluation method based on interval reference points (IRPs) to consider bounded rational behavior. As such, we take the prospect value, which reflects the bounded rationality of DMUs when facing gain and loss, as secondary goals. This approach allows us to determine the input and output weights for each DMU from its own point of view. Each reference point (RP) of the prospect value is defined as an elastic interval reference point (IRP), which can degenerate into a precise reference point (PRP) or an IRP by adjusting the parameters. As a result, the proposed cross-efficiency evaluation method not only takes the bounded rational behavior of DMUs into account, but is also more neutral and flexible. Numerical examples are provided to illustrate the applications of the cross-efficiency evaluation method based on IRPs in DEA ranking. (C) 2020 Elsevier B.V. All rights reserved.

Aim: The purpose of our study was to conduct a retrospective analysis to compare the effectiveness of transjugular intrahepatic portosystemic shunts (TIPS) in the treatment of patients with cirrhosis with or without portal vein thrombosis (PVT).Methods: We included a total of 203 cirrhosis patients successfully treated with TIPS between January 2015 and January 2018, including 72 cirrhosis patients with PVT (35.5%) and 131 without PVT (64.5%). Our subjects were followed for at least 1 year after treatment with TIPS. Data were collected to estimate the mortality, shunt dysfunction, and complication rates after TIPS creation.Results: During the mean follow-up time of 19.5 ± 12.8 months, 21 (10.3%) patients died, 15 (7.4%) developed shunt dysfunction, and 44 (21.6%) experienced overt hepatic encephalopathy (OHE). No significant differences in mortality (P = 0.134), shunt dysfunction (P = 0.214), or OHE (P = 0.632) were noted between the groups. Age, model for end-stage liver disease (MELD) score, and refractory ascites requiring TIPS were risk factors for mortality. A history of diabetes, percutaneous transhepatic variceal embolization (PTVE), 8-mm diameter stent, and platelet (PLT) increased the risk of shunt dysfunction. The prevalence of variceal bleeding and recurrent ascites was comparable between the two groups (16.7 vs. 16.7% P = 0.998 and 2.7 vs. 3.8% P = 0.678, respectively).Conclusions: Transjugular intrahepatic portosystemic shunts are feasible in the management of cirrhosis with PVT. No significant differences in survival or shunt dysfunction were noted between the PVT and no-PVT groups. The risk of recurrent variceal bleeding, recurrent ascites, and OHE in the PVT group was generally similar to that in the no-PVT group. TIPS represents a potentially feasible treatment option in cirrhosis patients with PVT.