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Corporate fraud risk detection is a branch of fraud. It may exist in various industries and cause economic problems. Effective identification of corporate fraud can protect the safety of funds for investors in some sense. This paper proposes a classifier model of a fractional-order immune BP neural network based on the self-attention mechanism to improve efficiency. The improved artificial immune algorithm with dynamic region contraction strategy is used to optimize the initialization process of the BP neural network. Furthermore, it combines the self-attention mechanism to design the input layer. Finally, Caputo fractional noncausal calculus is used to optimize the parameter updating process in BP neural network. The experiment results indicate that our model has fast convergence rate and powerful capacity of detection, and performs efficiently in detecting fraud behaviors. [ABSTRACT FROM AUTHOR]

BACKGROUND: Three-dimensional (3D)--printed models are cost-effective and can be customized by trainers. This study designed a 3D-printed airway suction simulator for use by respiratory therapy (RT) students. The objective was to demonstrate the cost-effectiveness and application of 3D-printed models in respiratory care training, aiming to enhance the educational experience for RT students. METHODS: This study developed a 3D-printed airway suction simulator that was cost-effective. A randomized controlled trial was conducted involving RT students to compare effectiveness in a 3D-model group and a control group. Skill assessments and written examinations were used to evaluate the participants' knowledge and skills. RESULTS: A total of 38 second-year RT students were randomly assigned to either the 3D-model group (n = 19) or the control group (n = 19). One participant in the 3D-model group was lost to follow-up during the planned direct observation of procedural skills (DOPS) assessment and satisfaction questionnaire completion. The posttest written examination scores were significantly higher in the 3D-model group than in the control group (100% vs 80%, P = .02). The scores from the DOPS and satisfaction questionnaire were comparable in the 2 groups. CONCLUSIONS: This study demonstrated that 3D printing can be used to create a safe and cost-effective airway suction simulator for use by RT students, with potential to enhance training methods. Further research is necessary. [ABSTRACT FROM AUTHOR]

Lifestyle intervention encompassing nutrition and physical activity are effective strategies to prevent progressive lipid deposition in the liver. This study aimed to explore the effect of dietary change, and/or high-intensity interval training (HIIT) on hepatic lipid accumulation in high fat diet (HFD)-induced obese rats. We divided lean rats into lean control (LC) or HIIT groups (LH), and obese rats into obese normal chow diet (ND) control (ONC) or HIIT groups (ONH) and obese HFD control (OHC) or HIIT groups (OHH). We found that dietary or HIIT intervention significantly decreased body weight and the risk of dyslipidemia, prevented hepatic lipid accumulation. HIIT significantly improved mitochondrial fatty acid oxidation through upregulating mitochondrial enzyme activities, mitochondrial function and AMPK/PPARα/CPT1α pathway, as well as inhibiting hepatic de novo lipogenesis in obese HFD rats. These findings indicate that dietary alone or HIIT intervention powerfully improve intrahepatic storage of fat in diet induced obese rats. [ABSTRACT FROM AUTHOR]

The globalization of work raises important questions related to the employment of workers across geographies and how the complementarity or substitution of workers across country borders influences firm profitability. In particular, tension often exists regarding the substitution or complementarity of workers located outside the U.S. or within the U.S. for American firms. We investigate this question in the context of information technology (IT) professionals and assess how domestic and foreign IT professionals contribute to firm profit by utilizing a rare firm-level dataset with information on the locational composition of IT professionals within and outside the U.S. Exploiting a labor market supply-side exogenous shock induced by the American Competitiveness in the Twenty-First Century Act (AC21), which increased the availability of H-1B visas in the U.S. in 2001, we find that foreign IT professionals located offshore and American IT professionals located onshore complement each other in generating profits. Our model and empirical findings are important both for informing firm choices and for shaping and creating public policies that so far appear to have been informed more by emotion than by data and science. [ABSTRACT FROM AUTHOR]

Few-shot scene classification methods aim to obtain classification discriminative ability from few labeled samples and has recently seen substantial advancements. However, the current few-shot learning approaches still suffer from overfitting due to the scarcity of labeled samples. To this end, a few-shot semi-supervised method is proposed to address this issue. Specifically, semi-supervised learning method is used to increase target domain samples; then we train multiple classification models using the augmented samples. Finally, we perform decision fusion of the results obtained from the multiple models to accomplish the image classification task. According to the experiments conducted on two real few-shot remote sensing scene datasets, our proposed method achieves significantly higher accuracy (approximately 1.70% to 4.33%) compared to existing counterparts. [ABSTRACT FROM AUTHOR]

This article explores the orthodontic treatment of a horizontally impacted mandibular second molar. The case report focuses on a patient who had an impacted molar causing dental complications. Instead of extracting the tooth, a cantilever uprighting spring made of stainless steel wire was used to upright the molar without surgery or additional anchorage. The treatment involved the extraction of other teeth, followed by the insertion and activation of the cantilever spring. After nine months, the molar was successfully exposed and brought into occlusion, resulting in a stable occlusion and improved facial profile. The article also discusses other methods for aligning the tooth after it has been uprighted and exposed. [Extracted from the article]

Our previous study finds that exosomal microRNA (miR)-186-5p promotes viability and invasion of vascular smooth muscle cells to accelerate atherosclerosis via inactivating phosphoinositide 3 kinase/protein kinase B/mammalian target of rapamycin pathway. Subsequently, this study aimed to identify the linkage of serum exosomal miR-186-5p with clinical features and major adverse cardiovascular events (MACE) in coronary heart disease (CHD) patients. Serum exosomal miR-186-5p was quantified in 175 CHD patients and 50 healthy controls (HCs) via reverse transcription quantitative polymerase chain reaction. Our study revealed that serum exosomal miR-186-5p was enhanced in CHD patients vs. HCs (P < 0.001). In CHD patients, serum exosomal miR-186-5p was positively correlated with total cholesterol (P = 0.002) and low-density lipoprotein cholesterol (P = 0.003). Elevated serum exosomal miR-186-5p was linked with increased Gensini score (P = 0.028) and stenosis degree categorized by the Gensini score (P = 0.018). Regarding MACE, the 1-year and 2-year accumulating MACE rate was 6.6% and 15.6%, respectively. Serum exosomal miR-186-5p was elevated in CHD patients with MACE vs. those without (P = 0.042). By Kaplan-Meier curves and log-rank analyses, serum exosomal miR-186-5p > 1.000 (P = 0.404) and > 1.610 (P = 0.328) was not related to accumulating MACE. While serum exosomal miR-186-5p > 3.390 exhibited a correlative trend with increased accumulating MACE, but not achieving statistical significance (P = 0.071). The 1-year and 2-year accumulating MACE rate of patients with serum exosomal miR-186-5p > 3.390 was 11.5% and 21.5%, respectively; while the rate was 3.3% and 11.5% in patients with serum exosomal miR-186-5p = 3.390, accordingly. Conclusively, serum exosomal miR-186-5p positively associates with lipid level, coronary stenosis degree, and the risk of MACE in CHD patients. [ABSTRACT FROM AUTHOR]

Our previous study revealed oxidized-low density lipoprotein (oxLDL)-stimulated macrophages delivered exosomes to exacerbate vascular smooth muscle cell (VSMC) viability and invasion; and microRNA-320b was enriched in exosomes from oxLDL-stimulated macrophages. This study aimed to further explore molecular mechanisms of exosomal microRNA-320b from oxLDL-stimulated macrophages on cellular functions of VSMCs. Exosomes from oxLDL-stimulated macrophages with microRNA-320b mimic/inhibitor transfection were used to treat VSMCs. Next, microRNA-320b mimic/inhibitor, and microRNA-320b mimic with or without peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A) overexpression vector were transfected into VSMCs. Viability, invasion, apoptosis, contractile/synthetic phenotype markers, and MEK/ERK pathway were detected in VSMCs. Exosomes from microRNA-320b mimic-treated macrophages promoted viability, invasion, and synthetic phenotype marker osteopontin, while suppressed apoptosis and contractile phenotype marker α-smooth muscle actin in VSMCs. Importantly, direct microRNA-320b mimic treatment aggravated viability, invasion, and synthetic phenotype transition in VSMCs. However, microRNA-320b inhibitor showed the opposite effects as microRNA-320b mimic. Next, luciferase reporter gene assay showed that microRNA-320b directly bound to PPARGC1A; microRNA-320b also inversely regulated PPARGC1A in VSMCs. Moreover, the effect of microRNA-320b mimic on cellular functions of VSMCs was hampered by PPARGC1A overexpression vector (all P < 0.05). Additionally, microRNA-320b activated MEK/ERKT pathway, which was also suppressed by PPARGC1A overexpression vector (all P < 0.05). OxLDL-stimulated macrophages deliver exosomal microRNA-320b to exacerbate viability, invasion, and synthetic phenotype transition in VSMCs via modulating PPARGC1Amediated MEK/ERK pathway, thus participating in the progression of atherosclerosis. [ABSTRACT FROM AUTHOR]

In this paper, we examine the role of reciprocity enabled by digital social platforms for offline healthy behavior. Although reciprocity is a fundamental aspect of human psychology, its application in promoting healthy behavior has been limited. We conduct a randomized field experiment with over 1,700 pairs of users on a mobile social network platform. Individuals in the reciprocity treatment group receive a gift from their friends and are asked to return this favor by participating in a running challenge. Their performance is compared to the self-interest incentives widely used in practice. Building on social exchange theory, we argue that reciprocity-based incentives will outperform self-interest incentives with modest reward for motivating behavior change. We find that, on average, reciprocity is stronger than self-interest in inducing exercise behavior by a substantial amount. Furthermore, our results reveal that the magnitude of the reciprocity effect is contingent on the social closeness between senders and receivers. Interestingly, social closeness has an inverted U-shaped influence on the reciprocity effect. The effect is strongest when closeness is moderate, and wanes when closeness is either too strong or too weak. Compared to commonly used self-interest based financial incentives, our findings offer a potentially more powerful avenue for mechanism design in promoting healthy behavior. [ABSTRACT FROM AUTHOR]

Previous studies have suggested that γδT cells play an important role in the pathogenesis of ankylosing spondylitis (AS). In this pilot study, the peripheral blood mononuclear cells (PBMCs) of patients with ankylosing spondylitis (AS) and healthy volunteers were stained and analyzed by flow cytometry to distinguish γδ T cells and its subtypes, and then to report the distribution of γδ T cells and iyts subtypes and their correlation with ankylosing spondylitis. A total of 17 patients with active AS and 10 age- and gendermatched healthy volunteers were enrolled in this study, and their peripheral blood were drawn to collect mononuclear cells (PBMCs). Flow cytometry was used to analyze γδ T cell subpopulations by measuring the surface and intracellular expressions of phenotypic markers. Serum levels of inflammatory and bone turnover markers were measured, and their correlations with subpopulations of γδ T cells were evaluated. In patients with AS, the Vδ2 fractions within γδ T cells and CD3+ T cells decreased significantly, in particular, the proportions of CD27+ Vδ2 T cells, CD86+CD80+ Vδ1 T cells, and IL17A-secreting and TNFα-secreting Vδ1 T cells within the parental cells decreased significantly. γδ T cells/PBMCs, Vδ2 cells/γδ T cells, and Vδ2 cells/CD3+ T cells were negatively correlated with CRP, whereas Vδ1 cells/CD3+ T cells were negatively correlated with ESR. Vδ1 cells/γδ T cells were positively correlated with CRP, γδ T cells/PBMCs were positively correlated with β-CTx, CD69+CD25+ and IL-17A-secreting Vδ1 cells were positively correlated with TP1NP, and CD69+CD25+ Vδ1 and Vδ2 cells were positively correlated with osteocalcin. Decreases in peripheral Vδ2, CD27+ Vδ2, CD86+CD80+ Vδ1, and IL17A or TNFα-secreting Vδ1 T cells are associated with AS. The correlations between γδ T cell subpopulations and CRP and the CD69+CD25+ subpopulation with TP1NP or osteocalcin suggest that an imbalance in peripheral γδ T cell subpopulations contributes to the pathogenesis of AS. [ABSTRACT FROM AUTHOR]

Under the backdrop of the robust growth of the global economy, the water transport industry is experiencing rapid development, resulting in an increase in ship collisions and a critical water traffic safety situation. This study uses text mining techniques to gather a corpus of data. The corpus includes human factors, ship factors, natural environmental factors, and management factors, which are used as target data to obtain a high-dimensional sparse original feature vector space set comprising eigenvalues and eigenvalue weight attributes. Chi-square statistics are utilised to reduce dimensionality, resulting in a final set of 33-dimensional text feature items that determine the causal factors of ship collision risk. Taking the four steps involved in the collision process as the primary focus, a Bayesian network structure for ship collision risk is constructed based on the "human-ship-environmentmanagement" system. By incorporating existing ship collision accident/danger reports, conditional probability tables are computed for each node in the Bayesian network structure, enabling the modelling of ship collision risk. The model is validated through an example, revealing that, under relevant conditions, the probability of collision exceeds 90 %. This finding demonstrates the validity of the model and allows one to deduce the primary cause of ship collision accidents. [ABSTRACT FROM AUTHOR]

In this paper, the downlink of the multicast based spatial modulation systems is investigated. Specifically, physical layer multicasting is introduced to increase the number of access users and to improve the communication rate of the spatial modulation system in which only single radio frequency chain is activated in each transmission. To minimize the bit error rate (BER) of the multicast based spatial modulation system, a joint optimizing algorithm of antenna selection and multicast precoding is proposed. Firstly, the joint optimization is transformed into a mixed-integer non-linear program based on single-stage reformulation. Then, a novel iterative algorithm based on the idea of branch and bound is proposed to obtain the quasi-optimal solution. Furthermore, in order to balance the performance and time complexity, a low-complexity deflation algorithm based on the successive convex approximation is proposed which can obtain a sub-optimal solution. Finally, numerical results are showed that the convergence of our proposed iterative algorithm is between 10 and 15 iterations and the signal-to-noise-ratio (SNR) of the iterative algorithm is 1-2dB lower than the exhaustive search based algorithm under the same BER accuracy conditions. [ABSTRACT FROM AUTHOR]

Inhibition of extensive osteoclastogenesis and bone resorption is considered a potential therapeutic target for the treatment of osteoporosis. Isobavachalcone (IBC) is derived from the traditional Chinese herb Psoralea corylifolia Linn. We showed that IBC dose-dependently suppressed receptor activator of nuclear factor kappa B ligand (RANKL)-induced osteoclastogenesis in bone marrow monocyte/macrophage (BMMs) and osteoclastic bone-resorption function without cytotoxicity at a dose of no more than 8 μm in vitro. Mechanistically, the results of western blot and quantitative real-time polymerase chain reaction (qRT-PCR) indicated that IBC inhibited the RANKL-induced degradation of IκBα and phosphorylation of nuclear factor kappa B (NF-κB) in BMMs, and subsequently downregulated the expression of osteoclastic-specific genes and osteoclastogenesis-related proteins. TRAP staining and qRT-PCR showed that IBC can inhibit osteoclast differentiation by down-regulating the expression of miR-193-3p on osteoclast differentiation. Overall, our findings suggest that IBC may serve as a promising compound for the treatment of osteoporosis and other metabolic bone diseases. The signaling pathway of IBC inhibiting RANKL-induced osteoclast formation. [ABSTRACT FROM AUTHOR]

Edge detection is highly susceptible to streaking caused by speckles in polarimetric synthetic aperture radar (PolSAR) imagery. In this article, we address hysteresis thresholding for suppress streaking in PolSAR's edge detection. As an example, an approach is suggested by combining the constant false alarm ratio (CFAR) detector and the hysteresis thresholding. After thinning edges obtained by the CFAR detector, the hysteresis thresholding is employed to reduce edge streaking, which is caused by abundant speckles. A ratio of the high to the low threshold Pfa in the hysteresis thresholding is pointed out for linking edges. Experiments are carried out on both simulated and real PolSAR data sets, and the results reveal that hysteresis thresholding obviously promotes the performance of the CFAR detector. [ABSTRACT FROM AUTHOR]

BACKGROUND: Intensive systolic blood pressure (SBP) lowering has been increasingly used; however, its effect on cardiac remodeling remains not fully understood. This secondary analysis of the Strategy of Blood Pressure Intervention in the Elderly Hypertensive Patients trial aims to determine the changes in left ventricular hypertrophy (LVH) that occur in the context of intensive SBP lowering. METHODS: A total of 7141 older patients with hypertension were randomly assigned to intensive treatment (SBP target, 110-130 mm Hg) or standard treatment (130-150 mm Hg). LVH was defined according to the Peguero-Lo Presti criteria on a standard 12-lead echocardiogram. RESULTS: At baseline, the prevalence of LVH (16.6% versus 16.5%) and the mean Peguero-Lo Presti value (1811 versus 1808 µV) were comparable between the treatment groups. During a median follow-up of 3.24 years, intensive SBP lowering was associated with a significantly lower risk of new LVH occurrence (hazard ratio, 0.76 [95% CI, 0.66-0.89]; P=0.001) and slower progression of the mean Peguero-Lo Presti index value by -23.47 µV/y (95% CI, -34.93 to -12.01; P=0.000). However, the rates of regression of baseline LVH did not differ significantly. Notably, the beneficial effect of intensive SBP lowering in terms of cardiovascular events (hazard ratio, 0.75 [95% CI, 0.59-0.97]) was not markedly attenuated after adjusting for LVH as a time-varying covariate (hazard ratio, 0.76 [95% CI, 0.59-0.97]). CONCLUSIONS: Intensive SBP lowering protects against LVH development in older hypertensive patients, however, this favorable effect could not explain most of the reduction in cardiovascular events associated with intensive SBP lowering. [ABSTRACT FROM AUTHOR]

Continuous integration and continuous deployment (CI/CD) are best practices for automating the software development process. People leverage them to ensure rapid iteration and delivery of product development. The rapid lifecycle makes traditional security management vulnerable to its lack of agility, exposing the urgent need to put security into DevOps processes. Development, security, and operation, quoted as DevSec Ops, advocates shift-left security, promotes people to implant security best practices into all DevOps stages, and builds continuous security analysis, testing, and management with automation. Based on CI/CD, this study defines continuous security practices and applies application security processes on a DevSecOps pipeline to implement shift-left security. The CodeHawk platform, based on the proposed secure pipeline and open source software, is developed to free the development team from testing manually, enable them to focus on development, gain the corresponding security assurance, and lower the operating costs. Experiments show that our DevSecOps pipeline design significantly improves the efficiency of the DevSecOps process. [ABSTRACT FROM AUTHOR]

Purpose -- This study aims to explore the perception of local society regarding the government's hosting of a large-sport event such as the MotoGP in Indonesia, using social exchange theory such as economic, social, cultural, and environmental aspects to support tourism development and destination image. Design/methodology -- This study provides the locals' perception of the large-sport events of MotoGP Indonesia in 2022 using a quantitative approach through Structural Equation Model-Partial Least Square (SEM-PLS). Findings -- The results indicate that economic, social, and cultural perceptions significantly support tourism development and destination image in Indonesia. However, environmental perceptions were not significant and did not support the hypothesis that they support tourism development. Therefore, it can be concluded that this significant event can contribute to the development of tourism and destination image in Indonesia. Originality of the research -- To the best of the authors' knowledge, this is the first study to examine the mega sporting event and tourism destination using multiple indicators, such as economic, social, cultural, and environmental. In addition, this is the first study to examine the host perception of the MotoGP mega sporting event in Indonesia. [ABSTRACT FROM AUTHOR]

The detection of changes in synthetic aperture radar (SAR) images based on deep learning has been widely used in landslides detection, flood disaster monitoring, and other fields of change detection due to its high classification accuracy. However, the inherent speckle noise in SAR images restricts the performance of existing SAR image change detection algorithms by clustering analysis. Therefore, this paper proposes a novel method for SAR image change detection based on clustering fusion and deep neural networks. We first used hierarchical fuzzy c-means clustering (HFCM) to process two different images to obtain HFCM classification results. Then a fusion strategy is designed to obtain the fused image from the two HFCM classified images as the pre-classification result. Furthermore, a lightweight deep neural network composed of a decomposition convolution module and an auxiliary classification module was proposed; the former module could reduce network parameters by 28%, and the latter could reduce network parameters by 33.3%. To improve the recognition performance of the network, the classification layer was replaced by the regression layer at the outcome of the network. By comparing the experiments of different methods on five data sets, the performance of our proposed method is superior. [ABSTRACT FROM AUTHOR]

Sustainability has become increasingly important globally, due to climate change, and has become a key focus within New Product Development (N PD), drawing attention from academia, media, and industry. The increase pressure to be more sustainable as a humanity and within industry has led to the identification of the need to ensure that students are suitably educated on key sustainability issues related to their field. This paper shows that design and engineering education, with a focus on sustainability issues, currently being taught in university is having an impact on industry. Previous literature has highlighted gaps within the knowledge which could better the teaching in this area. The paper proposes a framework which aims at facilitating the adoption of the teaching and learning of sustainability within design and engineering undergraduate education, specifically focusing on the overall impact oftheir future positions within the NPD process. The main goal of the framework is to support students and educators in the learning and education of key sustainability issues throughout the typical undergraduate degree period, focusing on teaching methods and key themes which will be valuable as students' progress into industry. Future Research objectives have also been outlined. [ABSTRACT FROM AUTHOR]

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Mining a large number of students' behavior data can analyze the differences of students' behavior characteristics. Mining based on students' behavior data can explore the influence mechanism of students' learning enthusiasm, and can provide reference opinions and suggestions for improving students' positive emotions in learning and helping students with poor grades to achieve academic success. The data collected and conclusions obtained by the existing research are not accurate and reliable, and other personality characteristics of students are not fully considered. Therefore, this article studies the influence mechanism of students' learning enthusiasm based on educational big data. It studies the performance of students with good learning enthusiasm in social relations, and mines students' social intercourse at school based on association rules. It analyzes the regularity of students' behavior and their diligence, and realizes the characterization of students' sustainability and enthusiasm in learning. Combining the differences of behavior characteristics between students with and without learning enthusiasm, this article constructs a learning enthusiasm recognition model and compares it by classification. Experimental results verify the effectiveness of the model. [ABSTRACT FROM AUTHOR]

Background: Cirrhosis-related acute-on-chronic liver failure (ACLF) is associated with high morbidity and mortality rates. Prognostic models of ACLF have been developed; however, few studies have focused on the occurrence of ACLF. This study aimed to identify the factors that predict the development of ACLF, hepatic encephalopathy (HE), and infection in patients with cirrhosis. Methods: Patients with cirrhosis were enrolled, and the serum levels of calcitriol, Cluster of Differentiation 26 (CD206), and macrophage- inducible lectin receptor (Mincle) were measured, and lymphocyte-to-monocyte ratio (LMR) and neutrophil-to-lymphocyte ratio were calculated; all the patients were tracked for 6 months. A generalized estimating equation (GEE) was used to assess the factors associated with ACLF development, HE, and infection. The aforementioned model was derived based on immunological markers, and receiver operating characteristic analysis with area under the curve (AUC) was adopted to evaluate accuracy. Results: After screening 325 patients with cirrhosis, 65 patients were eligible. In the GEE model, low levels of calcitriol (odds ratio [OR] = 3.259; 95% confidence interval [CI] = 1.118-8.929) and CD206 (OR = 2.666; 95% CI = 1.082-6.567) were associated with the development of ACLF, and the LMR was a protective factor (OR = 0.356; 95% CI = 0.147-0.861). Low calcitriol levels were a risk factor for HE (OR = 3.827) and infection (OR = 2.489). LMR was found to be a protective factor against HE (OR = 0.388). An immunological model for the discrimination of ACLF development within 6 months was proposed, with an AUC of 0.734 (95% CI = 0.598-0.869). Conclusion: Single and combined immunological markers, including low LMR and low levels of calcitriol and CD206, were promising for early prediction of the development of ACLF, HE, and infection in patients with cirrhosis. [ABSTRACT FROM AUTHOR]

To facilitate front-line teachers to provide more efficient cases for classroom teaching activities in limited teaching time, it is necessary to conduct clustering analysis of online teaching cases. The existing clustering study on textbased teaching resources focuses on the representation and fusion of different views of texts and the discovery of consistent clustering allocation, and ignores the high-dimensional sparsity of text data. To this end, this paper studies clustering analysis of online teaching cases and evaluation of teaching results. This paper gives the design flow of online teaching with case teaching as the core and proposes a text multi-view clustering algorithm based on case subject alignment, and presents a clustering model structure based on subject alignment. Based on the grey system theory, this paper compares online classroom teaching results before and after teachers use clustering algorithm to process teaching cases. Finally, the experimental setup is given, and the effectiveness of the proposed algorithm is verified by experiment. [ABSTRACT FROM AUTHOR]

In view of the problem that the current wireless sensor network is vulnerable to malicious attacks, mainly in hospitals where it is very important for data about each person to be secure, the security and stability of the wireless sensor network can be better guaranteed. An improved anti-malicious attack method for wireless sensors in hospital networks based on improved particle swarm optimization is proposed. The distributed network attack detection algorithm is used to calculate the trust value of the data packet in the wireless network. By setting the threshold value of the trust value, when the wireless network data packet trust value is less than the set threshold, a network malicious attack occurs. In order to protect the security of the network, it is necessary to block the malicious intrusion of the network with the lowest cost. The improved particle swarm optimization algorithm is used to solve the attack model, and the optimized solution of the minimum key strategy set of the attack graph is obtained, which successfully blocks the attack of the malicious network. The experimental results show that the proposed method has a long duration of anti-malicious attacks on wireless sensor networks, and the network vulnerability after anti-malware attacks is low. [ABSTRACT FROM AUTHOR]