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With the continuous development of military technology, intelligent aviation ammunition has become an important part of modern military operations. However, the safety of intelligent aviation munitions systems has always been a matter of concern. This study aims to explore the safety technology of intelligent aviation ammunition systems to ensure their reliability and stability in combat. First, this study reviews the current development status and application fields of intelligent aviation ammunition systems. Subsequently, it focused on analyzing the security threats and risks that intelligent aviation ammunition systems may face, including perception security, planning security, communication security, and evaluation and testing security. In response to these security challenges, a series of technologies and strategies have been proposed, and comprehensive security measures have been adopted to effectively reduce the security risks of intelligent aviation ammunition systems and improve their credibility and availability in actual combat. This research provides theoretical support and practical guidance for the safety technology of intelligent aviation ammunition systems, and provides a reference for its future development and application.

In this paper, we discuss the patterns of the transmission of how the Human papillomavirus (HPV) spreads in the public. We analyze the behaviors of infectious disease in SIR, SEIR, and Multistrian models. In terms of this disease, HPV has many subtypes, some are high-risk, and some are low-risk. Unfortunately, many people in some areas are not aware of it. That will always cause many delays for the disease and aggravations. The harm caused by HPV is different for different groups of people, people will take various measures to handle the situation according to the severity. We divided them into 3 cases. That is case1-negative for people who may have caught HPV; case 2-negative people who may have caught HPV, but excluding exposures; case 3-negative for people who is sure to catch HPV. After that, by computing the disease-free equilibrium (DFE) to get the value for calculating reproduction number R0 to estimate the stability for every case. Then the way of getting the derivatives and partitioned matrix and computing reproduction number with the measure of the Jacobian matrix were used for deciding the response for the epidemic eventually.

In this paper, we discuss the patterns of the transmission of how the Human papillomavirus (HPV) spreads in the public. We analyze the behaviors of infectious disease in SIR, SEIR, and Multistrian models. In terms of this disease, HPV has many subtypes, some are high-risk, and some are low-risk. Unfortunately, many people in some areas are not aware of it. That will always cause many delays for the disease and aggravations. The harm caused by HPV is different for different groups of people, people will take various measures to handle the situation according to the severity. We divided them into 3 cases. That is case1-negative for people who may have caught HPV; case 2-negative people who may have caught HPV, but excluding exposures; case 3-negative for people who is sure to catch HPV. After that, by computing the disease-free equilibrium (DFE) to get the value for calculating reproduction number R 0 to estimate the stability for every case. Then the way of getting the derivatives and partitioned matrix and computing reproduction number with the measure of the Jacobian matrix were used for deciding the response for the epidemic eventually.

The literature has confirmed that when managers increase profits through earnings management, the readability of annual reports may be reduced Lo (2017), Ye (2018). Whether this conclusion is suitable for Chinese corporate social responsibility (CSR) reports, however, is still unclear. Based on the panel data of 5083 Chinese non-financial listed companies from 2010 to 2019, this paper adopts multiple linear regression to investigate the impact of earnings management on the readability of Chinese CSR reports. The results show that: (1) There is a significant negative correlation between earnings management and the readability of Chinese CSR reports, with the readability of Chinese annual reports as a mediating variable. (2) The negative effect is more significant when companies are not punished for violations, when the internal control index is low, when companies lack ISO14001 certification and when companies do not have independent third-party authentication for Chinese CSR reports. (3) When earnings management just exceeds zero, the readability of Chinese CSR reports decreases. (4) The economic consequences of reducing the readability of Chinese CSR reports are that financing costs are increased and environmental performance is decreased. To improve the quality of information disclosure of listed companies, the recommendations are as follows: First, the government should issue CSR reporting standards to reduce the manipulation of Chinese CSR reports. Second, Chinese CSR reports disclosed by listed companies must be audited by independent third parties to enhance the credibility of the information. Third, the company needs to strengthen its external and internal supervision to reduce the manipulation space for the readability of Chinese CSR reports. This study extends the negative relationship between earnings management and the readability from annual reports to Chinese CSR reports. To prevent investors from detecting earnings management, the readability of Chinese CSR reports may be reduced. At the same time, the study has definitely added value to the existing literature in the domain of CSR.

Zinc (Zn2+) is the second most abundant necessary trace element in the human body, exerting a critical role in many physiological processes such as cellular proliferation, transcription, apoptosis, growth, immunity, and wound healing. It is an essential catalyst ion for many enzymes and transcription factors. The maintenance of Zn2+ homeostasis is essential for the central nervous system, in which Zn2+ is abundantly distributed and accumulates in presynaptic vesicles. Synaptic Zn2+ is necessary for neural transmission, playing a pivotal role in neurogenesis, cognition, memory, and learning. Emerging data suggest that disruption of Zn2+ homeostasis is associated with several central nervous system disorders including Alzheimer’s disease, depression, Parkinson’s disease, multiple sclerosis, schizophrenia, epilepsy, and traumatic brain injury. Here, we reviewed the correlation between Zn2+ and these central nervous system disorders. The potential mechanisms were also included. We hope that this review can provide new clues for the prevention and treatment of nervous system disorders.

Fever has long been recognized as one of the earliest clinical indicators of illness and remains a leading reason for seeking medical care worldwide. It is typically classified based on its duration and underlying etiology. In clinical settings, intractable fever is as common as acute fever, particularly in patients with brain injuries. Beyond infectious causes, stroke survivors often experience recurrent intractable fever due to central or neurogenic mechanisms. This study aims to retrospectively investigate the incidence and clinical characteristics of acute and intractable fever in patients undergoing stroke rehabilitation. It explores the associations between these characteristics and the different types of fever. Additionally, the study seeks to identify potential risk factors contributing to the development of intractable fever, aiming to guide clinical management and optimize treatment strategies for stroke-related fever. This study evaluated 1,065 stroke patients in the rehabilitation phase who were admitted to the Neurorehabilitation Center between January 1, 2023, and December 31, 2023. Of these, 230 febrile patients met the inclusion criteria and were included in the analysis, comprising 194 cases of acute fever and 36 cases of intractable fever. Medical records and clinical characteristics were collected, and the data from the two groups of febrile patients were analyzed using t-tests, Mann-Whitney U tests, and chi-square tests. Logistic regression analysis was performed to identify risk factors associated with intractable fever, while receiver operating characteristic (ROC) curves were used to assess the predictive performance of individual and combined risk factors. A p-value of less than 0.05 was considered statistically significant. 15.7% of patients experienced intractable fever, which was significantly associated with brainstem lesions ( P  < 0.05). Compared to patients with acute fever, those with intractable fever had higher NIHSS scores (33.3% vs. 15.5%, P  < 0.05), a greater incidence of consciousness disorders (66.7% vs. 28.9%, P  < 0.05), and a higher rate of tracheostomy (55.6% vs. 15.5%, P  < 0.05). All patients received antibiotic treatment, and gabapentin was administered to 16 cases. Patients with brainstem lesions were less likely to be treated with gabapentin (37.5% vs. 90%, P  < 0.05), while those with intracerebral hemorrhage were more likely to receive gabapentin (87.5% vs. 10%, P  < 0.05). Logistic regression analysis revealed that consciousness disorders and tracheostomy status were significant risk factors for intractable fever ( P  = 0.047, OR 6.691, 95% CI 1.030–43.478; P  = 0.021, OR 5.366, 95% CI 1.282–22.465). Brainstem lesions also significantly increased the risk ( P  = 0.002, OR 9.617, 95% CI 2.277–40.614). Although limited in scope, this retrospective study highlights the increased risk of intractable fever during stroke rehabilitation among patients with consciousness disorders, tracheostomy, and brainstem injuries. The key risk factors identified include higher NIHSS scores, impaired consciousness, tracheostomy status, and brainstem lesions.

Background Bladder cancer (BLCA) exists a profound molecular diversity, with basal and luminal subtypes having different prognostic and therapeutic outcomes. Traditional methods for molecular subtyping are often time-consuming and resource-intensive. This study aims to develop machine learning models using deep learning features from hematoxylin and eosin (H&E)-stained whole-slide images (WSIs) to predict basal and luminal subtypes in BLCA. Methods RNA sequencing data and clinical outcomes were downloaded from seven public BLCA databases, including TCGA, GEO datasets, and the IMvigor210C cohort, to assess the prognostic value of BLCA molecular subtypes. WSIs from TCGA were used to construct and validate the machine learning models, while WSIs from Shanghai Tenth People’s Hospital (STPH) and The Affiliated Guangdong Second Provincial General Hospital of Jinan University (GD2H) were used as external validations. Deep learning models were trained to obtained tumor patches within WSIs. WSI level deep learning features were extracted from tumor patches based on the RetCCL model. Support vector machine (SVM), random forest (RF), and logistic regression (LR) were developed using these features to classify basal and luminal subtypes. Results Kaplan-Meier survival and prognostic meta-analyses showed that basal BLCA patients had significantly worse overall survival compared to luminal BLCA patients (hazard ratio = 1.47, 95% confidence interval: 1.25–1.73, P  < 0.001). The LR model based on tumor patch features selected by Resnet50 model demonstrated superior performance, achieving an area under the curve (AUC) of 0.88 in the internal validation set, and 0.81 and 0.64 in the external validation sets from STPH and GD2H, respectively. This model outperformed both junior and senior pathologists in the differentiation of basal and luminal subtypes (AUC: 0.85, accuracy: 74%, sensitivity: 66%, specificity: 82%). Conclusions This study showed the efficacy of machine learning models in predicting the basal and luminal subtypes of BLCA based on the extraction of deep learning features from tumor patches in H&E-stained WSIs. The performance of the LR model suggests that the integration of AI tools into the diagnostic process could significantly enhance the accuracy of molecular subtyping, thereby potentially informing personalized treatment strategies for BLCA patients.

Molybdenum isotopes serve as critical proxies for reconstructing ancient ocean oxygenation, yet the modern oceanic Mo isotopic budget remains incompletely understood. Deep-sea pelagic sediments enriched in Fe-Mn (hydro)oxides represent a major oxic sink, but their authigenic Mo isotopic composition is poorly constrained. Here, we show Mo isotope data from Pacific deep-sea sediment cores revealing systematic depth-dependent δ 98 Mo enrichment from ‒0.55‰ to 0.19‰, controlled by Fe-Mn cycling during early diagenesis. Combined with existing datasets, we calculate a revised authigenic oxic Mo flux of 1.52 × 10⁸ mol yr⁻¹ with δ 98 Mo = ‒0.09 ± 0.23‰—more than double previous estimates and ~0.6‰ heavier than Fe-Mn crusts. These findings necessitate recalibration of the global Mo isotope budget and demonstrate that pelagic sediments exert greater influence on oceanic Mo cycling than previously recognized with implications for quantitative paleoceanographic reconstructions. Deep-sea sediments are a key sink for molybdenum (Mo). Here it is found that the their isotopic composition is heavier than typical endmembers; refining the global Mo budget, and improving reconstructions of past ocean oxygen levels.

There has been a significant increase in the number of diagnostic and predictive models for myelitis. These models aim to provide clinicians with more accurate diagnostic tools and predictive methods through advanced data analysis and machine learning techniques. However, despite the growing number of such models, their effectiveness in clinical practice and their quality and applicability in future research remain unclear. To conduct a comprehensive methodological assessment of existing literature concerning myelitis modeling methodologies. We queried PubMed, Web of Science, and Embase for publications through October 23, 2024. Extracted parameters covered: study design, data origin, outcome criteria, cohort size, predictors, modeling techniques, and validation metrics. Methodological quality was evaluated using the PROBAST instrument, assessing potential biases and clinical applicability. Among the 11 included studies, six focused on predictive diagnostic models, while five were centered on prognostic models. Modeling approaches comprised: logistic regression (n=6), Cox regression (n=2), deep learning (n=1), joint modeling (n=1), and hybrid machine learning/scoring algorithms (n=1). Multivariable logistic regression was the most frequently employed modeling algorithm in the current field. The most commonly used predictors for training diagnostic or prognostic models in myelitis were sex (n=6) and age (n=4). PROBAST evaluation indicated: (1) High bias risk (n=6): primarily from suboptimal data sourcing and analytical reporting gaps; (2) Unclear risk (n=4): mainly due to non-transparent analytical workflows; (3) Low risk (n=1). Pooled AUC for eight validated models reached 0.83 (95%CI: 0.75-0.91), demonstrating robust discriminative capacity. Although existing models demonstrate good discrimination in predicting myelitis, according to the PROBAST criteria, only one study exhibited a low risk of bias; analysis of data accessibility indicated that the model from only one study was directly available for public use. Consequently, future research should prioritize the development of models with larger cohort sizes, rigorous methodological design, high reporting transparency, and validation through multicenter external studies, enabling direct clinical translation to enhance their application value in clinical practice and improve healthcare delivery. https://www.crd.york.ac.uk/prospero/, identifier CRD42024623714.

Central Post-Stroke Pain (CPSP) is a primary sequelae of stroke that can develop in the body part corresponding to the cerebrovascular lesion after stroke, most typically after ischemic stroke but also after hemorrhagic stroke. The pathogenesis of CPSP is currently unknown, and research into its mechanism is ongoing. To summarize current research on the CPSP mechanism and provide guidance for future studies. Use “central post-stroke pain,” “stroke AND thalamic pain,” “stroke AND neuropathic pain,” “post-stroke thalamic pain” as the search term. The search was conducted in the PubMed and China National Knowledge Infrastructure databases, summarizing and classifying the retrieved mechanism studies. The mechanistic studies on CPSP are extensive, and we categorized the included mechanistic studies and summarized them in terms of relevant pathway studies, relevant signals and receptors, relevant neural tissues, and described endoplasmic reticulum stress and other relevant studies, as well as summarized the mechanisms of acupuncture treatment. Studies have shown that the pathogenesis of CPSP involves the entire spinal-thalamo-cortical pathway and that multiple substances in the nervous system are involved in the formation and development of CPSP. Among them, the relevant receptors and signals are the hotspot of research, and the discovery and exploration of different receptors and signals have provided a wide range of therapeutic ideas for CPSP. As a very effective treatment, acupuncture is less studied regarding the analgesic mechanism of CPSP, and further experimental studies are still needed. Graphical Abstract