Safety Systems Research Articles

Assessing the Public Health Consequences of Terrorist Attacks on Telecommunications Infrastructure: A Global Analysis.

This study investigates the public health implications of terrorist attacks on telecommunications infrastructure globally, assessing the direct and indirect impacts on emergency response and medical services. Utilizing retrospective analysis, this research delves into incidents recorded in the Global Terrorism Database (GTD) from 1970 to 2020. The study employs descriptive statistical methods to identify patterns and examine the regional distribution and frequency of these attacks, alongside the types of weaponry used and the direct casualties involved. The analysis underscores a significant focus on telecommunications by terrorist groups, revealing a frequent use of high-impact weapons like explosives and incendiary devices aimed at maximizing disruption. The study highlights considerable regional variations in the frequency and nature of attacks, emphasizing the strategic importance of these infrastructures to public safety and health systems. The findings demonstrate the critical need for robust security enhancements tailored to regional threats and the integration of advanced technologies in public safety strategies. The research advocates for enhanced international cooperation and policymaking to mitigate the impacts of these attacks, ensuring telecommunications resilience in the face of global terrorism.

Whole-genome sequencing and metagenomics reveal diversity and prevalence of Listeria spp. from soil in the Nantahala National Forest.

As a foodborne pathogen, Listeria continues to cause numerous illnesses in humans and animals. Studying the diversity and distribution of Listeria in soil is crucial for understanding potential sources of contamination and developing effective strategies to prevent foodborne outbreaks of listeriosis. Additionally, examining the ecological niches and survival mechanisms of Listeria in natural habitats provides insights into its persistence and adaptability, informing risk assessments and public health interventions. This research contributes to a broader understanding of microbial ecology and the factors influencing foodborne pathogen emergence, ultimately enhancing food safety and protecting public health. Moreover, using a metagenomic approach provides a detailed understanding of the soil microbial ecosystems, leading to more effective monitoring and control of foodborne pathogens. This study also highlights the potential for integrating metagenomics into routine surveillance systems for food safety in the near future.

A new hernia blocking system to prevent recurrent lumbar disc herniation: surgical technique, intraoperative findings and six-months post-operative outcomes.

The aim of this study was to evaluate the performance and safety of a new hernia blocking system (HBS), implanted after a limited discectomy, to prevent recurrence of lumbar disc herniation. Prospective, multicenter (6 sites), cohort clinical investigation. Thirty patients with a postero-lateral disc herniation between L4-S1 and large annular defects (> 6mm wide), who underwent a limited discectomy and were treated with a new HBS (DISC care, NEOS Surgery S.L.), were included. This article presents details about the investigational device, its surgical technique, intraoperative parameters, and up to 6months follow-up outcomes. The primary endpoint of the study was to assess the incidence of early symptomatic reherniation. In addition, disc height, leg and back pain (NRS 0-10), Oswestry Disability Index (ODI), quality of life (EQ-5D-5L) and device safety, were evaluated. gov: NCT04188236; date: 27th November 2019. Thirty patients (43.3% female, 41.7 ± 10.9years) were implanted with the device under evaluation in a mean of 16 ± 9.6min. Six months after surgery, no symptomatic reherniation was detected and disc height was maintained in all patients included. All patients had a significant reduction in leg pain (> 2 points in the NRS), 92.9% improved > 15 points in the ODI and 82.6% significantly improved their quality of life (≥ 12 points in EQ VAS score). No product-related serious adverse events nor reoperations occurred. The implantation of an HBS is a feasible and safe procedure that prevents early disc herniation recurrence in patients at high risk of reherniation.

AI in Structural Health Monitoring for Infrastructure Maintenance and Safety

This study explores the growing influence of artificial intelligence (AI) on structural health monitoring (SHM), a critical aspect of infrastructure maintenance and safety. This study begins with a bibliometric analysis to identify current research trends, key contributing countries, and emerging topics in AI-integrated SHM. We examine seven core areas where AI significantly advances SHM capabilities: (1) data acquisition and sensor networks, highlighting improvements in sensor technology and data collection; (2) data processing and signal analysis, where AI techniques enhance feature extraction and noise reduction; (3) anomaly detection and damage identification using machine learning (ML) and deep learning (DL) for precise diagnostics; (4) predictive maintenance, using AI to optimize maintenance scheduling and prevent failures; (5) reliability and risk assessment, integrating diverse datasets for real-time risk analysis; (6) visual inspection and remote monitoring, showcasing the role of AI-powered drones and imaging systems; and (7) resilient and adaptive infrastructure, where AI enables systems to respond dynamically to changing conditions. This review also addresses the ethical considerations and societal impacts of AI in SHM, such as data privacy, equity, and transparency. We conclude by discussing future research directions and challenges, emphasizing the potential of AI to enhance the efficiency, safety, and sustainability of infrastructure systems.

An Azomethine Derivative, BCS3, Targets XIAP and cIAP1/2 to Arrest Breast Cancer Progression Through MDM2-p53 and Bcl-2-Caspase Signaling Modulation

Background: Breast cancer influences more than 2 million women worldwide annually. Since apoptotic dysregulation is a cancer hallmark, targeting apoptotic regulators encompasses strategic drug development for cancer therapy. One such class of apoptotic regulators is inhibitors of apoptosis proteins (IAP) which are a class of E3 ubiquitin ligases that actively function to support cancer growth and survival. Methods: The current study reports design, synthesis, docking analysis (based on binding to IAP-BIR3 domains), anti-proliferative and anti-tumor potential of the azomethine derivative, 1-(4-chlorophenyl)-N-(4-ethoxyphenyl)methanimine (BCS3) on breast cancer (in vitro and in vivo) and its possible mechanisms of action. Results: Strong selective cytotoxic activity was observed in MDA-MB-231, MCF-7, and MDA-MB-468 breast cancer cell lines that exhibited IC50 values, 1.554 µM, 5.979 µM, and 6.462 µM, respectively, without affecting normal breast cells, MCF-10A. For the evaluation of the cytotoxic potential of BCS3, immunofluorescence, immunoblotting, and FACS (apoptosis and cell cycle) analyses were conducted. BCS3 antagonized IAPs, thereby causing MDM2-p53 and Bcl-2-Caspase-mediated intrinsic and extrinsic apoptosis. It also modulated p53 expression causing p21-CDK1/cyclin B1-mediated cell cycle arrest at S and G2/M phases. The in vitro findings were consistent with in vivo findings as observed by reduced tumor volume and apoptosis initiation (TUNEL assay) by IAP downregulation. BCS3 also produced potent synergistic effects with doxorubicin on tumor inhibition. Conclusions: Having witnessed the profound anti-proliferative potential of BCS3, the possible adverse effects related to anti-cancer therapy were examined following OECD 407 guidelines which confirmed its systemic safety profile and well tolerability. The results indicate the promising effect of BCS3 as an IAP antagonist for breast cancer therapy with fewer adverse effects.

The '5 Moments for Hand Hygiene': casting a critical eye on the implications for practice.

The '5 Moments' approach is a time-space framework that delineates when hand hygiene should be performed and provides a resource for educators and auditors. It has become the dominant paradigm for organisations, practice, policy, and research in relation to hand hygiene. It is a concept that adopts the 'precautionary principle' that if the relative risk of a specific care task is unknown, a safe system must be to treat them on an equal level. However, a literal interpretation will frequently result in an extraordinary, implausible number of hand-hygiene opportunities and if this then becomes the standard to audit practice, within a policy document that espouses zero tolerance, it is likely to generate inauthentic data. If used effectively the 5 Moments concept provides an opportunity to enhance practice and reduce healthcare-associated infections but the healthcare provider organisation must embody a 'just culture' and collect the data in a climate of openness, transparency, and learning.

Development and rollout of a national plan on cardiovascular health. Spain's cardiovascular health strategy (ESCAV).

Cardiovascular disease (CVD) remains the leading cause of death in most countries; however, few specific political actions have been implemented to increase cardiovascular health at the national or international level. We aimed to describe the methodology used for the development and initial rollout of Spain's Cardiovascular Health Strategy of the National Health System (ESCAV, Estrategia en Salud Cardiovascular del Sistema Nacional de Salud). A multidisciplinary team comprising all relevant stakeholders developed a national strategy to reduce the burden of CVD in Spain. The team used qualitative methodologies to identify and select priorities and design strategic map models. The strategy was structured within a matrix composed of 6 cross-cutting themes (citizen empowerment; health promotion, prevention, and early CVD detection; comprehensive management of acute and chronic CVD; health care coordination; equity; and knowledge management) and 4 longitudinal lines (ischemic heart disease, heart failure, arrhythmias, and valve disease). These were framed by 3 overarching axes: continuity of care, patient safety, and leveraging of information systems. A total of 27 critical points were selected, leading to the definition of 99 strategic objectives (32 general and 67 specific) and 136 actions through iterative reviews and prioritization. Strategic maps were developed for the overall strategy and for each action line, incorporating 61 indicators to facilitate and monitor the development of the strategy. ESCAV is one of the most ambitious initiatives to change a nation's cardiovascular health. The steps taken and the methods used to develop this strategy may serve as a valuable reference for other countries seeking to implement similar initiatives. In addition, it may provide an incentive to advance efforts toward establishing a European plan for cardiovascular health.

The influence and development of artificial intelligence on automobile emergency system

In the automobile industry, the application of artificial intelligence is more and more extensive, among which the emergency hedging system of automobile is one of the important fields of artificial intelligence application. With the increasing growth of automobiles, traffic road safety has become a topic often talked about in People's Daily life. With the rapid development of artificial intelligence, many automobile companies begin to use artificial intelligence to help the car emergency hedging system. Artificial intelligence will greatly enhance the timeliness, accuracy and safety of the automobile emergency system. This paper aims to discuss the influence and development of artificial intelligence on automobile emergency avoidance system, and analyze its advantages and disadvantages and future development trend. Which has a very obvious help to the automatic driving technology, but also laid the development of automatic driving technology.

Analysis of Occupational Safety Policies in the Manufacturing Industry Related to Compliance and its Impact on Occupational Accidents

Occupational safety is a very important aspect in the manufacturing industry, given the high risk of work accidents that can occur in this environment. The manufacturing industry is known for the use of heavy machinery, hazardous chemicals, and complex production processes, which increase the chance of occupational accidents if there is no effective work safety system (Fauzi, 2024). This research uses quantitative and qualitative approaches (mixed methods). The quantitative approach was used to measure the level of compliance with work safety policies and its impact on work accidents. Table 1 shows that the variables of knowledge, motivation and personality have a significant value > 0.05. Table 2 shows that the variables of training and communication do not have a significant relationship with labour compliance in using PPE. Table 3 shows that the PPE availability variable does not have a significant relationship with labour compliance in using PPE. It is important that companies continue to develop and implement comprehensive safety policies, involve workers in the drafting process, and provide ongoing training to create a safer and more productive work environment.

Analysis of the Effectiveness of Social Media Campaigns in Promoting Healthy Lifestyles Among Teenagers

Occupational safety is a very important aspect in the manufacturing industry, given the high risk of work accidents that can occur in this environment. The manufacturing industry is known for the use of heavy machinery, hazardous chemicals, and complex production processes, which increase the chance of occupational accidents if there is no effective work safety system (Fauzi, 2024). This research uses quantitative and qualitative approaches (mixed methods). The quantitative approach was used to measure the level of compliance with work safety policies and its impact on work accidents. Table 1 shows that the variables of knowledge, motivation and personality have a significant value > 0.05. Table 2 shows that the variables of training and communication do not have a significant relationship with labour compliance in using PPE. Table 3 shows that the PPE availability variable does not have a significant relationship with labour compliance in using PPE. It is important that companies continue to develop and implement comprehensive safety policies, involve workers in the drafting process, and provide ongoing training to create a safer and more productive work environment.

An adaptive thresholding approach for open set fault diagnosis

Abstract Cross-domain fault diagnosis using deep learning plays a critical role in ensuring the reliability and safety of mechanical systems. However, real-world industrial scenarios often involve unknown fault classes, which introduce significant challenges beyond environmental differences between training and testing phases. These unknown fault classes, which do not appear in the training data, create a cross-domain open set fault diagnosis problem where the target domain includes both known and unknown fault types with distinct distribution characteristics. Traditional domain adaptation methods that align source and target domains often overlook the spatial distribution of each class in the feature space, leading to potential negative transfer and misclassification of unknown faults. To address these challenges, this paper proposes a k-nearest neighbors based adaptive thresholding (KNNAT) method, which dynamically adjusts classification thresholds based on the spatial distribution of each class in the feature space. This approach effectively isolates unknown faults, reducing their impact on domain adaptation and improving the reliability of the diagnostic process. Extensive experiments on the publicly available CWRU bearing and PHM09 datasets demonstrate that the proposed KNNAT method outperforms other state-of-the-art methods, achieving higher accuracy and robustness in identifying known faults while successfully isolating unknown faults. These results highlight the potential of using the KNNAT method to enhance the reliability of mechanical systems in cross-domain fault diagnosis applications.

CFD simulation of injection point design for emergency core cooling system of ALLEGRO

The Emergency Core Cooling System (ECCS) is one of the critical safety systems in the Gas-cooled Fast Reactor (GFR) demonstrator ALLEGRO. The ECCS design must be improved to enhance fundamental safety functions, particularly in removing heat from the core under postulated plant conditions. In this paper, we focused on exploring the effect of coolant injection point on the performance of ECCS, for more efficient core cooling under Loss Of Coolant Accident (LOCA) scenarios. We initially performed a 1D primary system loop thermal hydraulic simulation to determine appropriate boundary conditions in case of a LOCA. These conditions were then applied to a CFD model of the ALLEGRO reactor pressure vessel, including injection nozzles at two positions. Transient 3D CFD simulations of LOCA in ALLEGRO were carried out using Fluent to determine location of the most effective emergency coolant injection point. We simulated the flow distribution through the core up to around 30 s after both small- and large-break LOCA events. The results suggest that bottom injection of the emergency coolant is preferred in an updated ECCS design. It provides a more uniform flow distribution across the core and therefore more advantageous than the previously suggested location in the downcomer.

Digital Voting with Blockchain using Interplanetary File System and Practical Byzantine Fault Tolerance

Traditional voting schemes are often overwhelmed by problems such as deception, influence, and incompetence, which can be resolved by applying blockchain technology with transparency, decentralization, and immutability. This study proposes a safe and indisputable digital voting system with blockchain technology to maintain the integrity of the voting procedure. The reliability and privacy of the voting procedure are upheld with distributed ledger technology and cryptographic techniques. The essence of the proposed method is the immutability of the blockchain ledger, which ensures a tamper-proof record of each cast vote, promoting transparency and offering a way of audit for free verification. The proposed method employs cryptographic protocols to protect individual votes while preserving complete transparency and verifiability of the voting procedure. The InterPlanetary Filesystem (IPFS) is applied to ensure data integrity. Moreover, the practical Byzantine Fault Tolerance (pBFT) consensus algorithm is utilized to remove glitches in distributed settings. The proposed approach provides a decentralized platform where voters can cast their votes from anywhere without difficulty using an internet connection, eliminating the need for physical ballot papers and polling stations. Using immutable ledger and cryptographic security aspects in blockchain, the reliability of the voting procedure can be protected while maintaining voter anonymity and confidentiality. Finally, it is shown that the proposed scheme outweighs other existing approaches.

Effects of undulating printing paths on axial compressive behaviors of 3D-printed continuous fiber-reinforced multi-cell thin-walled structure

Thin-walled structures are widely used in passive safety systems of the vehicles because of their excellent lightweight and stable progressive deformation behavior. Recently, continuous fiber 3D printing technique has been successfully applied in the manufacturing of thin-walled structures, providing a promising path to meet increasing requirements for energy absorbers as vehicle speed increases. This paper proposed a range of novel undulating printing paths to fabricate two kinds of continuous Kevlar fiber reinforced multi-cell thin-walled structures (CFMSs) with different cross-section shapes, named MT1 and MT2, respectively. For each type of CFMS, three different printing paths (moving back and forth between two layers) were designed to manufacture CFMS with the wall thickness comprised of only a single deposited line. The axial compressive tests were conducted to investigate the compressive response of CFMSs. It was found that undulating printing paths affect both the mechanical behavior and collapse mode of CFMSs. During the compression process, MT1 and MT2 printed with path 3 showed progressively folding deformation modes (differed from the progressive crushing mode of composite laminated thin-walled structures). Thus, compared to MT2 printed with path 1 and path 2, which exhibit global buckling, MT1 and MT2 printed with path 3 exhibited more stable energy absorption performance. Besides, although the local failure mode in different CFMSs caused by the same path was similar, the same printing path had different influences on the axial compressive properties of different CFMSs.

BLESS Behavior Correctness Proof as ConvincingVerification Artifact

Safety-critical cyber-physical systems require evidence they are indeed safe. In practice, such evidence is results of system tests. Unfortunately, tests can only demonstrate the presence of software errors, not their absence, and can practically cover a tiny fraction of system state space. Valiant efforts to formally verify program correctness have either been excruciatingly difficult (theorem proving) or incomplete (static analysis, model checking, SAT or SMT solving). The BLESS Methodology was created specifically for engineers in industry to formally verify software controlling machines. The BLESS Methodology transforms programs that control machines, annotated with assertions to form proof outlines, into deductive proofs that every possible program execution will conform to its specification. To the extent that cyber-physical system specifications have been validated to express system safety and performance, a deductive proof can be a convincing argument to a person of program correctness. This paper uses a simple safety-critical system to argue that behavior correctness proof under the BLESS Methodology is a convincing verification artifact in addition to customary testing.

Safety and Efficacy of BioMime Sirolimus-Eluting Stent System in All-Comers Real-World Population With Coronary Artery Stenosis: MILES Global Registry

Safety and Efficacy of BioMime Sirolimus-Eluting Stent System in All-Comers Real-World Population With Coronary Artery Stenosis: MILES Global Registry

A hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction

Efficient and accurate wind power prediction is crucial for enhancing the reliability and safety of power system. The data-driven forecasting methods are regarded as an effective solution. However, the inherent randomness and nonlinearity of wind power systems, along with the abundance of redundant information in measurement data, present challenges to forecasting methods. The integration of precise and efficient techniques for data feature decomposition and extraction is essential in conjunction with advanced data-driven forecasting models. Focus on the seasonal variation characteristics of wind energy, a hybrid wind power prediction model based on seasonal feature decomposition and enhanced feature extraction is proposed. The effectiveness and superiority of the proposed method in predictive accuracy are demonstrated through comprehensive multi-model experiment comparisons.

Study on icing characteristics of bundled conductor of transmission line based on shadowing effect analysis

Icing on transmission lines significantly threatens the safety and stability of power system. Particularly for bundled conductors, the shadowing effect of the upwind conductor on the downwind one affects airflow and droplet distribution, leading to unique icing characteristics. This paper employs numerical simulations and icing tests to investigate the icing shadowing effect of bundled conductors. Firstly, the distributions of airflow and droplets around the bundled conductor are solved by the Eulerian-Eulerian two-phase flow model. Then, by solving mass and thermodynamic balance equations, the icing mass and shape accreted on the bundled conductors under various icing conditions are obtained. Further, two novel parameters, the shadowing coefficient and the offset angle, are introduced to quantify the shadowing effect's impact on ice mass and shape. The findings indicate that the ice mass ratio on the downwind conductor to the upwind conductor is influenced by wind speed, wind angle, bundle spacing, conductor diameter, and droplet parameters. In most cases, the ratio is less than 1; however, under certain wind angles, this ratio exceeds 1. The shadowing effect also impacts the ice shape on the downwind conductor, inducing an additional offset in the ice shape. The magnitude of this offset angle is also correlated with environmental parameters. Finally, the accuracy of our numerical simulations is validated by the outcomes of natural icing tests.

A Mesoporous Silica-Based Nano-Drug Co-Delivery System with Gemcitabine for Targeted Therapy of Pancreatic Cancer.

To investigate the efficacy and safety of the mesoporous silica-based nano-drug co-delivery system with gemcitabine (GEM) in the treatment of pancreatic cancer. Experimental study. Place and Duration of the Study: Wenzhou Central Hospital, Zhejiang Province, China, between July 2022 and November 2023. Ce6@MSN-Fe3O4/GEM@DPM nanoparticles were prepared and structurally characterised, then their drug loading and entrapment efficiency were calculated, and in vitro drug release and cytotoxicity assays were performed. In addition to that, mesoporous silica nanorods were prepared and structurally characterised for cellular uptake, cytotoxicity, and reactive oxygen species detection. The mesoporous silica nanoparticles were spherical in shape and possessed a unique core-shell structure. The prepared nanoparticles had good entrapment efficiency and drug loading, and exibited pharmacotoxic and phototoxic effects on cells. The mesoporous silica nanorods were taken up by pancreatic cancer cells and exbitied cytotoxicity. Mesoporous silica-based nano-drug co-delivery system, which carries GEM, is an effective targeted drug delivery system to provide new research ideas for the treatment of pancreatic cancer. Pancreatic cancer, Gemcitabine, Magnetic nanocomposites, Photodynamic therapy, Targeted drug delivery.

Evaluation of grounding grid corrosion extent based on laser-induced breakdown spectroscopy (LIBS) combined with machine learning

As one of the most widely used forms of energy, the safety and stability of power systems are crucial to modern society. Grounding grids dissipate current and reduce touch and pace voltage during lightning strikes or fault currents, ensuring the safety of personnel and equipment. However, prolonged submersion in soil causes inevitable corrosion, compromising grounding efficacy by increasing resistance and reducing current dissipation. This deterioration can result in unsafe local potential differences. This study uses Laser-Induced Breakdown Spectroscopy (LIBS) to measure corrosion degrees in grounding grids. Spectral data from samples with varying corrosion extent were collected, with outliers removed using the Local Outlier Factor (LOF) algorithm. Principal Component Analysis (PCA) reduced data dimensionality, revealing clustering in spectral data corresponding to corrosion extent. Three machine learning models were compared: Adaptive Boosting - Backpropagation Neural Network (Adaboost-BP), Support Vector Machine (SVM), and Random Forest (RF). The RF model showed the highest accuracy in predicting corrosion degree (R²=0.9845, MSE=0.0296), outperforming Adaboost-BP and SVM, especially for intermediate corrosion extent. These findings validate the effectiveness and reliability of combining LIBS with machine learning for predicting grounding grid corrosion, providing a theoretical foundation for the safe operation of power systems.