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Numerical simulation and parallel implementation of freight train air brake system

Numerical simulations of railway air brake systems are becoming increasingly computationally demanding due to the growing complexity and length of trains. This study introduces a parallel computing-enhanced model for simulating pressure dynamics in heavy-haul trains. The proposed approach assigns dedicated threads to each vehicle, with additional threads managing the interface fluxes of brake pipe connections, and is implemented in C# using the ThreadPool and Parallel libraries. A train configuration consisting of one locomotive and 116 vehicles was simulated under various brake pipe pressure reduction conditions. The validity of the air braking system simulation model was confirmed through comparisons with experimental data. Furthermore, the impact of parallel computing on simulation efficiency was investigated. The results indicate that the efficiency of serial computing is primarily influenced by the CPU Boost Clock frequency. Parallel computing consistently outperforms serial computing, with speedup ratios increasing as the number of CPU threads grows. Although the simulation partitions tasks by vehicle units, the computations remain sufficiently fine-grained that the ThreadPool implementation outperforms the Parallel library, as it eliminates the dynamic scheduling overhead inherent to Parallel’s workload distribution mechanism. Additionally, parallel computing efficiency improves as the number of vehicles increases; however, beyond a certain threshold, efficiency stabilizes as workload distribution becomes fully optimized.

The Human Exersome Initiative (HEI): Rationale, study design, and protocol

Habitual physical activity and exercise training (PA/EX) confers numerous health-benefits. Phenotypic adaptations and clinical health outcomes attributable to PA/EX are well-established, and molecular markers and mediators of the PA/EX response have been described. To date, the majority of prior work focused on the biochemical response to PA/EX has leveraged convenience samples of trained athletes participating in events, patients undergoing clinically indicated exercise stress testing, or laboratory protocols comprised of a single dose of exercise. Accordingly, the impact of “exercise dose”, defined by the product of intensity, duration, modality, and frequency, on the human biochemical response to PA/EX remains largely unexplored. The Human Exersome Initiative (HEI) was designed to fill this scientific knowledge gap. Specifically, the HEI will couple carefully controlled laboratory-based acute exercise testing with comprehensive systemic biochemical profiling to isolate the impact of PA/EX duration and intensity on human biochemistry. Herein, we describe the initial phase of the HEI which will aim to comprehensively define the impact of “exercise dose” on blood-based biochemistry in healthy young men and women. The overarching goal of the HEI is to elucidate how the human exercise response varies as a function of phenotypic variability. Using comparator data derived from young men and women, future iterations of this protocol will seek to determine how key sources of human variability (i.e., age, ethnicity, and the presence of comorbid disease) impact the biochemical response to PA/EX. We anticipate results from this work will facilitate biomarker discovery, the elucidation of molecular pathways and mechanisms associated with metabolic responses to exercise, and the identification of optimal exercise doses for future clinical interventions (i.e., tailoring preventive and therapeutic strategies).

The Wnt pathway induces a naïve-like subpopulation in primed stem cells, while NME7AB leads to a homogeneous naïve-like population

The literature is replete with conflicting reports as to whether the Wnt/β-catenin pathway induces human stem cell differentiation or pluripotency. Recently, scientists showed that human stem cells expressing low levels of active β-catenin preferentially differentiate down a neuroectoderm lineage, whereas cells expressing high levels favor mesendoderm. However, these results appear to contradict two other studies, where researchers improved differentiation to both neuroectoderm and mesoderm by increasing levels of active β-catenin at the start of differentiation. Here, we show that stem cells cultured with naïve growth factor, NME7AB, express the highest levels of active β-catenin, yet readily differentiate into neuroectoderm and mesendoderm, without lineage preference. This raised the interesting question of whether activation of the Wnt/β-catenin pathway could itself play a role in maintaining or inducing a naïve-like state. The β-catenin agonist WNT3A was added to stem cells in the absence of any other growth factors, which induced the concurrent emergence of two segregated populations: an OCT4+, XaXa naïve-like population and an OCT4- population. This finding could explain the apparently inconsistent reports as to whether β-catenin induces pluripotency or differentiation, while raising additional questions. Notably, does the naïve-like sub-population, devoid of cell fate decisions, contribute to an increased differentiation potential? Conversely, are the OCT4- cells predisposed to differentiate more efficiently? To address these questions, we compared the differentiation of primed state stem cells, with or without pre-treatment with WNT3A, to that of naïve state stem cells. WNT3A pre-treatment improved the differentiation potential of primed stem cells, while having no effect in naïve stem cells. Furthermore, differentiation of the homogeneous population of naïve cells was superior to the primed state cells, even after WNT3A pre-treatment. This result is consistent with the idea that the improved differentiation is due to the sub-population of the WNT3A induced naïve-like cells.

Mediating role of growth mindset between college life stress and adjustment to college life among nursing students: A-cross sectional study

Adjusting to college life is important for nursing students to achieve academic and work performance successfully. Growth mindset has been proposed as a mediating concept that can induce positive psychological outcomes in stressful life contexts, and may be a potential facilitating factor for adjustment to college life among nursing students experiencing stressful college life. This study aimed to examine the mediating effect of growth mindset in the relationship between college life stress and adjustment to college life in nursing students. This was a cross-sectional descriptive study. The study participants were 250 undergraduate nursing students recruited from three nursing colleges in Korea. Self-reported data on college life stress, growth mindset and adjustment to college life were collected using the online survey questionnaire. The data were analyzed using an independent t-test, one-way ANOVA, Kruskal-Wallis H test, Pearson’s correlation, and multiple regression analysis. The mediating effects were verified through the bootstrapping method using the PROCESS macro for SPSS. Higher levels of adjustment to college life were reported in nursing students who were in good health status and were satisfied with the nursing major. Nursing students’ adjustment to college life was negatively affected by college life stress and positively affected by growth mindset. Growth mindset mediated the link between college life stress and adjustment to college life of nursing students. Educators may be aware that growth mindset can transform stress into challenging opportunities for nursing students. As both types of growth mindset—intelligence and personality—mediated the relationship between college life stress and adjustment to college life, pedagogical strategies cultivating growth mindset in both domains should be developed and implemented to support nursing students’ adjustment.

A rubric for assessing conformance to the Ten Rules for credible practice of modeling and simulation in healthcare

The power of computational modeling and simulation (M&S) is realized when the results are credible, and the workflow generates evidence that supports credibility for the context of use. The Committee on Credible Practice of Modeling & Simulation in Healthcare was established to help address the need for processes and procedures to support the credible use of M&S in healthcare and biomedical research. Our community efforts have led to the Ten Rules (TR) for Credible Practice of M&S in life sciences and healthcare. This framework is an outcome of a multidisciplinary investigation from a wide range of stakeholders beginning in 2012. Here, we present a pragmatic rubric for assessing the conformance of an M&S activity to the TR. This rubric considers the ability of an M&S study to communicate how well the study conforms to the Ten Rules for credible practice and facilitate outreach to a wide range of stakeholders from context-specific M&S practitioners to policymakers. It uses an ordinal scale ranging from Insufficient (zero) to Comprehensive (four) that is applicable to each rule, providing a uniform approach for comparing assessments across different reviewers and different modeling studies. We used the rubric to evaluate the conformance of two computational modeling activities: 1. six viral disease (COVID-19) propagation models, and 2. a model of hepatic glycogenolysis with neural innervation and calcium signaling. These examples were used to evaluate the applicability of the rubric and illustrate rubric usage in real-world M&S scenarios including those that bridge scientific M&S with policymaking. The COVID-19 M&S studies were of particular interest because they needed to be quickly operationalized by government and private decision-makers early in the COVID-19 pandemic and were accessible as open-source tools. Our findings demonstrate that the TR rubric represents a systematic tool for assessing the conformance of an M&S activity to codified good practices and enhances the value of the TR for supporting real-world decision-making.

HMGB1-BoxA gene therapy in reversing cisplatin resistance in non-small cell lung cancer

Cisplatin is a widely used chemotherapy agent in the treatment of non-small cell lung cancer (NSCLC). However, its clinical efficacy is limited by the development of drug resistance in patients with NSCLC. Recently, we demonstrated that HMGB1-BoxA gene therapy (BoxA) is an ideal cancer treatment that revitalizes normal cells while promoting cancer cells’ DNA break cascade. Increasing cytoplasmic HMGB1 is a reason for cisplatin resistance (Cis-R); in this study, we investigated the potential of BoxA to reverse acquired cisplatin resistance in two NSCLC cell lines, A549/Cis-R, and H460/Cis-R. The growth capacity of these cancer cells was significantly impaired upon BoxA treatment, resulting in a notable reduction in cell viability, colony formation, cancer stemness, and self-renewal capacity. Significantly, BoxA enhanced cisplatin sensitivity and promoted apoptosis in cisplatin-treated Cis-R cells. Furthermore, BoxA altered the subcellular localization of the HMGB1 protein, decreasing its cytoplasmic localization. BoxA can potentially reverse cisplatin resistance by altering the translocation of HMGB1.

Understanding the audiological care of patients with co-existing dementia or mild cognitive impairment and hearing loss in the United Kingdom National Health Service: A qualitative study

Background Hearing loss is common among people living with dementia and can exacerbate the symptoms associated with dementia. The effective management of hearing loss can positively impact quality of life and help alleviate dementia-related symptoms. Little is known about current audiological pathways in the National Health Service (NHS) for adults living with dementia or mild cognitive impairment. Objectives To understand the current NHS audiological care pathways for adults living with dementia or mild cognitive impairment. Design Qualitative study Results Thirty-three NHS audiologists in the United Kingdom (UK) completed a qualitative survey about current adult audiological care pathways for people living with dementia or mild cognitive impairment, and 14 of those also participated in a follow-up interview. Data from the surveys and interviews were combined and analysed using reflexive thematic analysis. The key findings included the importance of person-centred care, the active involvement of carers, and the need for tailored approaches, including using adapted and additional tests to assess hearing loss while offering a variety of hearing interventions. Audiologists expressed a desire for more service integration, such as domiciliary visits, and emphasised the importance of adapting environments and practices, such as dementia-friendly spaces and routine dementia education for staff, to better support individuals living with these co-existing conditions, Conclusions These findings can help inform the development of formal clinical practice guidelines and evidence-based training to support audiological care for people living with dementia and mild cognitive impairment in the United Kingdom.

A framework for detecting and predicting highway traffic anomalies via multimodal fusion and heterogeneous graph neural networks

This paper presents a novel framework for detecting and predicting abnormal traffic events on highways. Current traffic monitoring systems often rely on single data sources, which limits their detection accuracy and robustness in complex environments. To address these limitations, we propose a framework based on multimodal deep fusion and heterogeneous graph neural networks (HGNNs), incorporating an Ensemble Contrastive Pessimistic Likelihood Estimation (CPLE) algorithm to optimize performance. The framework integrates static and dynamic traffic data, such as video images, traffic flow, vehicle speed, and tunnel weather conditions. Experimental results demonstrate that the model performs well in various scenarios, showing significant improvement in accuracy and stability over existing models like AGC-LSTM and AttentionDeepST. For instance, the proposed MHGNN-CPLE model achieves superior accuracy and F1 score in static detection tasks while maintaining high accuracy under different noise levels in dynamic detection scenarios. This study provides a significant advancement in traffic event analysis by effectively combining multimodal data and leveraging HGNNs to capture complex spatiotemporal dependencies.

Effect of telemedicine-supported structured exercise program in patients with chronic low back pain: a randomized controlled trial

Background Structured exercise programs delivered via telemedicine have the potential to benefit patients with chronic low back pain (CLBP). However, evidence-practice gaps exist, such as low exercise adherence and lack of attention to the mental health of CLBP, so further research is needed to investigate the impact of telemedicine-supported structured exercise program on patients with CLBP. Objectives To compare the clinical outcomes of patients with CLBP following a telemedicine intervention versus usual care therapy. Materials and methods An open label, randomized controlled trial (RCT) was conducted over eight weekly sessions. Participants with CLBP were randomly assigned to either the Experimental Group (EG) or the Control Group (CG) in a 1:1 ratio, using a randomized numeric table. The EG received an intervention consisting of patient education, health coaching, and structured exercise program delivered through mobile health (mHealth) apps. The CG received usual care therapy, including patient education and paper handouts describing home exercises. The outcome measures included disability, pain intensity, mental health status, quality of life, walking ability, and exercise adherence. These were evaluated using the Roland Morris Disability Questionnaire (RMDQ), the Numerical Rating Scale (NRS), Depression-Anxiety-Stress Scale (DASS21), 12-item Short Form Health Survey (SF-12), Time Up and Go (TUG), and Exercise Adherence Rating Scale (EARS), respectively. Linear mixed-effects model analysis was conducted at baseline, after 4 weeks (during treatment), and after 8 weeks (post-treatment), adhering to the principles of intention-to-treat (ITT) analysis. Results The study included a total of 78 participants, with 39 randomly assigned to each group. Changes were significantly different between groups at 8 weeks in disability (estimated value: −3.96, 95% CI: −5.45 to −2.47, P < 0.001), pain (estimated value: −1.69, 95% CI: −2.14 to −1.24, P < 0.001) and the physical health dimensions of quality of life (estimated value: 4.5, 95% CI: 1.29 to 7.71, P = 0.006). However, there were only within-group differences at 8 weeks in mental health status (estimated value: −3.81, 95% CI: −4.99 to −2.63, P < 0.001), mental health dimensions of quality of life (estimated value: 5.01, 95% CI: 2.9 to 7.13, P < 0.001), walking ability (estimated value: −0.92, 95% CI: −1.17 to −0.68, P < 0.001), and exercise adherence (Z: 1.91, P = 0.06) over time. Conclusion This study suggests that a telemedicine-based structured exercise program is more effective than usual care therapy in improving disability, pain, and physical health dimensions of quality of life in patients with CLBP. Furthermore, the telemedicine program is equally effective as usual care therapy in enhancing mental health status, mental health dimensions of quality of life, walking ability, and exercise adherence. These findings indicate that implementing such a program could reduce the burden on patients with CLBP. Trial registration This trial was registered at China Clinical Trial Registration Center with the identifier ChiCTR2300071560.

Correction: In vivo biocompatibility and long-term durability of nanofibrillated cellulose as a urethral bulking agent in rats and Beagle dogs

Subtypes of hypertension and their association to comorbidities and ethnicity in pregnant women

Objectives We analyzed the subtypes of arterial hypertension and their relationship with different comorbidities and ethnicity during pregnancy. Study design This is a retrospective observational cohort study in 17,177 pregnant women during the years 2012–2018 in the health region of Lleida. Main outcome measures We analyzed the relationship of chronic hypertension, gestational hypertension, and pre-eclampsia with different variables, including comorbidities, vascular risk factors, and ethnicity. We calculated the adjusted odds ratio (OR) and the 95% confidence interval (CI) with multivariate logistic regression models. Results The total prevalence of arterial hypertension among pregnant women was 3.10%; of these, 1.53% had chronic hypertension, 0.65% had gestational hypertension, and 0.78% had pre-eclampsia. Superimposed pre-eclampsia on chronic hypertension occurred in 25 cases (0.14%). Chronic hypertension was associated with age (OR = 1.07), overweight (OR = 4.32), obesity (OR = 2.11), diabetes mellitus (OR = 2.38), hypothyroidism (OR = 2.23), and sub-Saharan origin (OR = 3.36). Gestational hypertension was correlated with age (OR = 1.06), overweight (OR = 5.84), obesity (OR = 1.89), and Asian/Middle Eastern origin (OR = 3.71). Finally, pre-eclampsia was associated with overweight (OR = 2.37) and Sub-Saharan Africa origin (OR = 2.45). Conclusions Pregnant women with hypertension may benefit from the knowledge of the subtype and a consequent coordinated prenatal and pregnancy approach.

Life-time experience of violence among women and girls living with disability in Nepal

Background Violence against women and girls with disabilities remains a serious, yet underexplored, global concern. This paper aims to investigate the prevalence and factors associated with life-time experience of violence within this vulnerable population in Nepal. Methods This cross-sectional study was conducted in 28 municipalities representing all seven provinces as well as all three ecological regions of Nepal. A total of 1,294 women and girls with disability aged 15–59 years participated in this study. Data were collected in the period August to October 2021. This was done by trained enumerators using the KoBo application on smartphones or tablets. Both written and oral informed consent was sought from all participants. Each participant was assured of utmost confidentiality and privacy. Cross-tabulations were performed in STATA 18 to determine the distribution of the prevalence of violence. Also, bivariable and multivariable logistic regression models were fitted to establish association between the participants’ characteristics and odds of experiencing violence. Results Overall, 457 (35.32%) women living with disabilities had ever experienced violence at a point in their lifetime. Psychological/emotional violence was the most prevalent violence (74.40%) followed by physical violence (31.07%) and denial of services (28.67%). Age was positively associated with the likelihood of experiencing violence. Women belonging to the Brahman/Chhetri ethnic group had reduced odds of violence [AOR = 0.56; 95%CI: 0.37–0.85] compared to Hill Dalits. Divorced or separated women showed a markedly higher likelihood of experiencing violence [AOR = 6.69; 95%CI: 2.31–19.40] compared to currently married women. Participants who had not witnessed violence against other women exhibited significantly higher odds of experiencing violence [AOR = 1.86; 95%CI: 1.20–2.89]. Women living in the Koshi province [AOR = 4.04; 95%CI: 2.54–6.42], Madhesh province [AOR = 2.16; 95%CI: 1.15–4.08] and Bagmati province [AOR = 2.21; 95%CI: 1.41–3.46] reported significantly higher odds of experiencing violence compared to those in Karnali. Conclusion The study concludes that age, ethnicity, marital status, and provincial residence are significant predictors of violence among women living with disability in Nepal. Interventions aimed at addressing violence against women living with disability in Nepal must prioritize older women and those who were previously married. Also, priority must be given to Koshi, Madhesh and Bagmati provinces where the prevalence and risk of experiencing violence is highest.

Exploring a role for Chemerin in the cardiovascular and musculoskeletal benefits of intradialytic exercise in the hemodialysis population

Background Cardiovascular disease is the leading cause of death for people receiving hemodialysis. Intradialytic cycling (IDC) has been shown to improve cardiovascular health in the hemodialysis population, but specific mechanisms require elucidation. Chemerin is an adipokine which contributes to the inflammatory process and may be associated with the cardiovascular benefits of IDC and physical function in hemodialysis population. Methods Adults undertaking ≥3 months hemodialysis were randomized to either IDC (30 min each time, moderate intensity, thrice weekly) and usual care; or usual care only (control group). 88 blood samples were retrospectively analyzed for chemerin concentrations using ELISA. Unadjusted and adjusted linear regression was used to understand how changes in chemerin are associated with changes in cardiovascular and musculoskeletal health in response to IDC. Results There was a significant increase of plasma chemerin concentration after 6 months in both groups. A positive association was detected between chemerin and short physical performance battery at baseline (β = 0.264, p = 0.017). There was no correlation of chemerin with cardiovascular, body composition, and other physical function markers. Conclusions This study is the first to show plasma level of chemerin increases with time on hemodialysis. No evidence was found to support a role for chemerin in modifying cardiac structure and function in people undertaking IDC. Further studies should investigate the associations between chemerin and physical performance.

Biomimetic Metal–Organic Nanotubular Host for Straight-Chain Fatty Acids Recognition

SNAI2 cooperates with MEK1/2 and HDACs to suppress BIM- and BMF-dependent apoptosis in TERT promoter mutant cancers

Cancers with TERT promoter mutations (TPM) display elevated RAS pathway signaling and mesenchymal traits, and associate with lower patient survival rates. We examined whether RAS pathway signaling in TPM cancers cooperates with mesenchymal features to drive resistance to apoptosis. We observed that RAS pathway signaling in TPM cancers inhibited apoptosis by downregulating the pro-apoptotic protein BIM. By using inhibitors of MEK1/2 kinases, we rescued the ability of TPM cancer cells to undergo apoptosis, which may have implications for targeted therapies. To further capitalize on this rescue, we explored combination treatments to drive apoptotic cell death. Treatment with the pan-BCL2 inhibitor, navitoclax (NX), in combination with MEK inhibition, significantly increased apoptosis, indicating that these cells are capable of undergoing intrinsic apoptosis, with BIM likely playing a critical role. Further, we found that transcriptional reprogramming of the mesenchymal state of TPM cancers using histone deacetylase inhibitors (HDACi) resulted in a synergistic increase in apoptosis, contingent upon BIM de-repression. Notably, the cause of this apoptosis appeared to be independent of DNA damage. The suppression of the mesenchymal transcription factor SNAI2, which has known roles in recruiting HDACs to silence gene expression, amplified apoptosis. Mechanistically, knockdown of SNAI2 impaired the cellular DNA repair leading to elevated basal levels of phosphorylated H2AX. Our findings show that TPM cancers exhibit specific small molecule vulnerabilities, driven by the convergence of RAS-MEK signaling and impaired HDAC regulation dependent on pro-apoptotic BH3-only proteins. Based on our findings, we propose that stratifying cancers based on TPM may identify a subset of tumors that are responsive to innovative combinations of inhibitors targeting these axes.

Evaluation of potential of targeted sequencing through mutational signature simulation

Background Targeted sequencing is critical in cancer diagnosis, treatment selection, and monitoring. However, the effectiveness of these methods for reflecting whole-exome sequencing (WES)-level mutational signatures remains unclear. Therefore, we addressed this issue through simulation-based analysis to clarify how well targeted sequencing can reproduce WES-level mutational signatures. Methods We compared the correlation and similarity of mutational signatures between whole-exome sequencing-level mutation data and downsampled data for gene sets targeted by each sequencing method in 13 cancer types. Additionally, a similarity analysis of the mutational signatures was conducted using randomly downsampled data. Results The comparison between whole-exome sequencing and targeted sequencing showed a low correlation based on Pearson’s correlation coefficient but a high similarity based on the Dice similarity index. As a result of the downsampling of data with cancer-related genes and whole genes to evaluate similarity, the cancer-related gene random set showed high similarity when 200–400 genes were selected. However, the whole-genome random set required 2–3 times as many genes as the cancer-related gene random set to show high similarity. Among cancer types, colorectal and lung cancers demonstrated high similarity with fewer downsampled genes, whereas breast and prostate cancers required more downsampled genes to achieve high similarity. Conclusion This study demonstrated that current clinically used targeted sequencing methods can reflect whole-exome sequencing-level mutational signatures. This suggests that considering the cancer type and average number of gene mutations in each patient when selecting targeted sequencing methods can lead to more effective treatment choices.

Leveraging multi-modal data for early prediction of severity in forced transmission outages with hierarchical spatiotemporal multiplex networks

Extended power transmission outages caused by weather events can significantly impact the economy, infrastructure, and residents’ quality of life in affected regions. One of the challenges is providing early, accurate warnings for these disruptions. To address this challenge, we introduce HMN-RTS, a hierarchical multiplex network designed to predict the duration of a forced transmission outage by leveraging a multi-modal approach. We investigate outage duration prediction over two years at the county level, focusing on the states of the Pacific Northwest region, including Idaho, California, Montana, Washington, and Oregon. The multiplex network layers collect diverse data sources, including information about power outages, weather data, weather forecasts, lightning, land cover, transmission lines, and social media. Our findings demonstrate that this approach enhances the accuracy of predicting power outage duration. The HMN-RTS model improves 3 hours ahead outage predictions, achieving a macro F1 score of 0.79 compared to the best alternative of 0.73 for a five-class classification. The HMN-RTS model provides valuable predictions of outage duration across multiple time horizons and seasons, enabling grid operators to implement timely outage mitigation strategies. Overall, the results underscore the HMN-RTS model’s capability to deliver early and practical risk assessments.

Association between CYP17A1 rs743572 polymorphism and cancer risk: A meta-analysis

The role of the CYP17A1 gene’s rs743572 polymorphism in cancer susceptibility has been a subject of extensive investigation, yet existing evidence remains inconclusive. In this meta-analysis, we systematically reviewed and synthesized data from 29 studies to assess the CYP17A1 rs743572 polymorphism’s relationship with cancer susceptibility. We strictly searched on EMBASE, PubMed, and Web of Science databases and explored rs743572 polymorphism’s association with cancer risks according to search strategy, enrolling 29 studies (13,767 cases and 17,441 controls). rs743572 was markedly related to enhanced cancer susceptibility risk; FPRP and TSA analyses were employed for confirmation. According to cancer type-based stratified analyses, rs743572 exhibited a notable association with bladder cancer, breast cancer, non-Hodgkin lymphoma, and hepatocellular cancer. In conclusion, systematic meta-analysis suggests a significant role for the rs743572 polymorphism in cancer pathogenesis, with particular prominence observed in bladder cancer, breast cancer, non-Hodgkin lymphoma, and hepatocellular cancer.

Demographic rise of sea urchin Centrostephanus sylviae on Robinson Crusoe and Santa Clara Islands at the Juan Fernandez Archipelago: A biophysical and ecological approach

The large increase in the population of long-spined sea urchins (Centrostephanus sylviae) has gained significant attention in the past decade due to the rise in the number of individuals reported as bycatch in Juan Fernandez rock lobster traps (Jasus frontalis) and the risks associated with changes in the ecosystem structure due to the increase in bleaching of reefs in the Juan Fernandez Archipelago (JFA). We explored the demographic surge of the C. sylviae population on Robinson Crusoe and Santa Clara islands (RC-SC) through changes in the relative abundance of adult sea urchins during the years 2015–2022. To seek an explanation for this phenomenon, we explored the potential contributions of early life stages of sea urchins to the adult population via biophysical modeling. We performed simulations of larval dispersal patterns and connectivity between release and recruitment zones for three study years (2013, 2015, and 2018). The results from larval drift simulations combined with observation data from the crustacean fishery monitoring program helped identify recruitment zones (primarily located in the eastern, southeastern, and southwestern areas of RC-SC). Also, we explored the relationship between the relative abundance of adult sea urchins and traits associated with lobsters due to the predator-prey relationship evident in other ecosystems (i.e., in Tasmania and New Zealand). We explored the potential control by lobsters of the sea urchin population size through generalized linear models by analyzing several predictor variables. The results showed that once all zones were combined there was an inverse correlation between the relative abundance of sea urchins and the largest lobsters found in the traps around the islands. This work highlights the complex ecological dynamics resulting from the increase in the C. sylviae population in the JFA system, emphasizing the importance of addressing this issue through ecosystemic and socio-ecologically integrated approaches.

Construction of VAE-GRU-XGBoost intrusion detection model for network security

With the advent of the big data era, the threat of network security is becoming increasingly severe. In order to cope with complex network attacks and ensure network security, a network intrusion detection model is constructed relying on deep learning technology. In order to extract and analyze network intrusion features, this study uses variational auto-encoders to extract and reduce the dimensionality of the invaded network traffic, and combines the advantages of extreme gradient boosting to perform classification tasks. Finally, a network intrusion detection model for network security is constructed by combining the gated recurrent unit. The results showed the area under the curve of the research model reached 97.48% and 95.24% in the KDD99 dataset and OODS dataset, respectively. In the confusion matrix experiment, the model achieved classification accuracy greater than 0.91 for different attack traffic samples in both the training and testing sets. When the sample sizes were 10000 and 40000, the shortest time and longest feature extraction time of the model were 0.030s and 0.112s, respectively. In summary, the constructed model on the basis of improved variational auto-encoder for network security has high accuracy in network intrusion detection.