Risk Assessment Technology Research Articles

Research hotspots and evolution trends of food safety risk assessment techniques and methods

AbstractFood safety incidents frequently occur in China and other countries. Food safety risk management has evolved from harm‐based to risk‐based approaches to control risks more scientifically and effectively. Risk assessment is at the core of risk control and provides a scientific basis for the development of risk management measures. Therefore, analyzing the research status and development trends of food safety risk assessment technologies and methods is important for improving food safety risk assessment and risk management. In this study, CiteSpace software was used to analyze a knowledge graph of popular research topics in the field of food safety risk assessment over the past 14 years, identify research keywords, and provide centrality statistics. Food safety risk assessments primarily focus on in vitro high‐throughput testing, computational toxicology, predictive microbiology, mechanistic research, and other technical methods. In the future, international coordination, cooperation, and cross‐integration of relevant disciplines should be strengthened, and research on and application of innovative technologies for food safety risk assessment should be promoted. Research on food safety risk assessment technologies and methods is in an active development stage and has good prospects for further exploration and application.

Clinical Application and Risk Assessment of CAR-T Cell Technology in Cancer Immunotherapy

As a cutting-edge personalized treatment method, CAR-T cell technology transforms patients' own T cells through genetic engineering, making them have the ability to specifically identify and kill tumor cells. The aim of this paper is to thoroughly organize the foundational principles and clinical utility of CAR-T cell technology, highlighting its recent advancements in treating both hematological and solid tumors. Through a comprehensive assessment of CAR-T cell technology's efficacy and risks, this study aims to inform clinical decision-making. Initially, the paper outlines the basic mechanisms of CAR-T cell technology, followed by an analysis of its notable therapeutic outcomes in hematological tumors. Additionally, it addresses the challenges posed by solid tumor treatment, including antigen expression complexity and tumor microenvironment impact. Emphasis is placed on the crucial role of regulatory bodies in enhancing oversight and developing risk management strategies to safeguard patient safety.

Trusted data sharing for mineral exploration and mining tenements

In mineral exploration, the exploration-discovery-mining (EDM) cycle may take 10–13 years. New and innovative approaches that can shorten the EDM cycle are fundamental to boosting the supply of mineral resources in the global market. In this paper, we propose a methodology for accelerating the EDM cycle by enabling confidentiality-preserving minerals data sharing, potentially shortening the exploration and discovery parts of the cycle. However, it is a highly challenging problem due to the need to balance diverse aspects related to the loss of confidential information and protecting competitive advantage. We investigate how data confidentiality risk assessment and data obfuscation technologies can be brought together to enable the sharing of otherwise sensitive data. We have defined several metrics to quantify the data confidentiality loss and utility gain in sharing data and developed various methods to obfuscate data by suppressing or sampling values. The confidentiality loss and utility loss caused by different obfuscation methods have been studied and empirically validated using a real-life mineral dataset provided by an Australian minerals company. Our proposed methods will enable mining and exploration companies to make informed decisions on what and how much information could be shared to achieve mutual benefits in mineral exploration at an acceptable cost of data confidentiality loss.

Advances and future directions of environmental risk research: A bibliometric review

Environmental risk is one of the world’s most significant threats, projected to be the leading risk over the next decade. It has garnered global attention due to increasingly severe environmental issues, such as climate change and ecosystem degradation. Research and technology on environmental risks are gradually developing, and the scope of environmental risk study is also expanding. Here, we developed a tailored bibliometric method, incorporating co-occurrence network analysis, cluster analysis, trend factor analysis, patent primary path analysis, and patent map methods, to explore the status, hotspots, and trends of environment risk research over the past three decades. According to the bibliometric results, the publications and patents related to environmental risk have reached explosive growth since 2018. The primary topics in environmental risk research mainly involve (a) ecotoxicology risk of emerging contaminants (ECs), (b) environmental risk induced by climate change, (c) air pollution and health risk assessment, (d) soil contamination and risk prevention, and (e) environmental risk of heavy metal. Recently, the hotspots of this field have shifted into artificial intelligence (AI) based techniques and environmental risk of climate change and ECs. More research is needed to assess ecological and health risk of ECs, to formulize mitigation and adaptation strategies for climate change risks, and to develop AI-based environmental risk assessment and control technology. This study provides the first comprehensive overview of recent advances in environmental risk research, suggesting future research directions based on current understanding and limitations.

A novel electrochemical immunosensor based on AuNPs/PNR/CS@MWCNTs-COOH for rapid detecting warning markers-BNP of heart failure caused by myocardial infarction

Heart failure (HF) is an insidious and dangerous disease that significantly impairs a patient’s quality of life and safety. It is not easy to detect in mild cases, and once it progresses to severe stages, deterioration can be rapid and challenging to reverse. Currently, early warning and prognostic risk assessment technologies are lacking, and there is an urgent need for precise early warning, risk assessment and diagnosis and treatment of HF at the cellular or molecular level. In this study, an electrochemical immunosensor based on AuNPs/PNR/CS@MWCNTs-COOH was prepared to detect brain natriuretic peptide (BNP), a biomarker for early warning of HF caused by myocardial infarction. Among them, the CS@MWCNTs-COOH nanocomposites and the polymerized neutral red (PNR) films on the electrode surface effectively enhanced the conductivity of the modified electrodes and significantly increased the specific surface area through the formation of three-dimensional nanostructures. AuNPs loaded on PNR/CS@MWCNTs-COOH provided a stable gold-ammonia bond for the specific antibody loading of BNP, facilitating the development of an electrochemical immunosensor with high selectivity for BNP detection. Furthermore, this work used cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) to improve aspects that influence the immunosensor’s analytical performance. Under ideal conditions, the immunosensor was tested for immunological qualities using differential pulse voltammetry (DPV), resulting in sensitive measurement of BNP concentration in undiluted serum samples.The peak current Ip of the response signal is linearly proportional to the LgCBNP in the range of 1.95 × 10−3 ng mL−1 to 8.0 ng mL−1, with a detection limit of 0.80 × 10−3 ng mL−1 (S/N=3). It can achieve highly sensitive identification and detection of trace BNP in complex biological samples and provide a convenient and efficient method for HF-related marker detection. Furthermore, it also can serve as a scientific basis and a new method for the development of early warning technology for HF and related pathological mechanism research.

Digital and Virtual Technologies for Work-Related Biomechanical Risk Assessment: A Scoping Review

Digital and Virtual Technologies for Work-Related Biomechanical Risk Assessment: A Scoping Review

Incident Response and Threat Intelligence in Healthcare: A Study on Cybersecurity Incident Management

India and other Asian nations are seeing an unparalleled pace of advancement in the modernisation of their healthcare systems. In this endeavour, information technology is crucial. Though the healthcare industry has made great progress, information security is still lagging behind the protection requirements attained in technologically developed nations such as the United States and the United Kingdom. This study is an honest attempt to pinpoint vulnerabilities and dangers in the field of cybersecurity and offers a few targeted remedies in three main domains: risks, vulnerabilities, and IoMT. Using a qualitative research methodology, this research culminates in the creation of a security maturity model for Indian healthcare. Furthermore, in light of these attacks, the well-known National Institute of Standards and Technology (NIST) risk assessment system and its guiding principles are examined. Evaluating the risks intrinsic to these hacks analytically becomes crucial given the comparatively low information risk management maturity levels in Asian healthcare organisations. While several nations in Asia and throughout the world are battling the COVID-19 outbreak, cybercriminals have been attempting to spread misinformation about vaccines. Additionally, some people and organisations are attempting to undermine specific vaccines in order to promote their COVID-19 treatments. Hacking research data, virus testing, and clinical studies that reveal side effects or possible issues are of particular interest to profit-seeking businesses. The secure methodology for identifying network attacks is suggested by this study.

The fate and behavior mechanism of antibiotic resistance genes in different-sized aerobic granular sludge under antibiotics pressure

Aerobic granular sludge (AGS) is a promising wastewater treatment technology. Studying the distribution of ARGs in different-sized AGS under antibiotic pressure is crucial for ARGs risk assessment and control technology development. Herein, the risk of intracellular ARGs (iARGs) in viable/dead bacteria within small (0–1 mm), moderate (1–2 mm), and big (2–3 mm) AGS (S/M/B-AGS) were clarified under tetracycline and sulfadiazine stress. Besides, the potential mechanism of ARGs enrichment differences in S/M/B-AGS was revealed. M−AGS had the lowest iARGs risk (30–60 days) in both viable (3.3E+08 copies/g-dw) and dead (6.7E+08 copies/g-dw) bacteria, averaging 29.8 % lower than B-AGS and 72.1 % lower than S-AGS, respectively. The average changes in abundance of the top 20 genera in S/M/B-AGS were 3.0 %, 2.6 %, and 2.9 % from day 30 to day 60, respectively. The complexity between ARGs and bacterial communities was highest in S-AGS, followed by B-AGS and M−AGS. Among the 19–20 identified hosts in S/M/B-AGS, only 11 hosts were shared. Extracellular polymeric substances (EPS) and protein, particularly those with α-helical structure, adsorbed antibiotics and envelop bacteria, enhancing mass transfer resistance and effectively reducing antibiotic stress on bacteria. M−AGS exhibited the highest contents of EPS and protein compared to S/B-AGS, potentially explaining the lowest iARGs risk observed. Overall, this study discovered the different behaviors of iARGs in viable/dead bacteria in S/M/B-AGS, offering a novel perspective on granular size modulation strategies to reduce ARGs risk.

Resilience of socio-ecological and energy systems: Intelligent information technologies for risk assessment of natural and technogenic threats

A method for studying the resilience of energy and socio-ecological systems is considered; it integrates approaches developed at the International Institute of Applied Systems Analysis and the Melentyev Institute of Energy Systems (MESI) of the Siberian Branch of the Russian Academy of Sciences. The article discusses in detail the methods of using intelligent information technologies, in particular semantic technologies and knowledge engineering (cognitive probabilistic modeling), which the authors propose to use in assessing the risks of natural and man-made threats to the resilience of the energy sector and social and ecological systems. More attention is paid to the study and adaptation of the integral indicator of quality of life, which makes it possible to combine these interdisciplinary studies.

Review on Aging Risk Assessment and Life Prediction Technology of Lithium Energy Storage Batteries

Review on Aging Risk Assessment and Life Prediction Technology of Lithium Energy Storage Batteries

Quantitative assessment of machine learning reliability and resilience.

Advances in machine learning (ML) have led to applications in safety-critical domains, including security, defense, and healthcare. These ML models are confronted with dynamically changing and actively hostile conditions characteristic of real-world applications, requiring systems incorporating ML to be reliable and resilient. Many studies propose techniques to improve the robustness of ML algorithms. However, fewer consider quantitative techniques to assess changes in the reliability and resilience of these systems over time. To address this gap, this study demonstrates how to collect relevant data during the training and testing of ML suitable for the application of software reliability, with and without covariates, and resilience models and the subsequent interpretation of these analyses. The proposed approach promotes quantitative risk assessment of ML technologies, providing the ability to track and predict degradation and improvement in the ML model performance and assisting ML and system engineers with an objective approach to compare the relative effectiveness of alternative training and testing methods. The approach is illustrated in the context of an image recognition model, which is subjected to two generative adversarial attacks and then iteratively retrained to improve the system's performance. Our results indicate that software reliability models incorporating covariates characterized the misclassification discovery process more accurately than models without covariates. Moreover, the resilience model based on multiple linear regression incorporating interactions between covariates tracks and predicts degradation and recovery of performance best. Thus, software reliability and resilience models offer rigorous quantitative assurance methods for ML-enabled systems andprocesses.

Review of AI in Civil Engineering

This paper reviews the transformative impact of Artificial Intelligence (AI) on civil engineering. It explores AI's fundamental concepts and its applications across structural analysis, construction management, transportation, geotechnical engineering, and sustainability. The review highlights AI's role in automating tasks, predicting outcomes, and optimizing designs throughout project lifecycles. Recent advancements in AI-driven technologies for structural health monitoring, predictive maintenance, and risk assessment are discussed, along with challenges like data quality and model interpretability. Future trends such as autonomous construction and digital twins are examined, emphasizing the need for continued research and interdisciplinary collaboration. In conclusion, this paper offers insights for leveraging AI to address evolving challenges and opportunities in civil engineering, fostering innovation, sustainability, and resilience in infrastructure development.

Temporal metabolic dynamics and heterogeneity of viable but nonculturable Pseudomonas aeruginosa induced by chlorine disinfection at single-cell resolution

Characterizing the metabolic network and dynamics of Viable But Nonculturable (VBNC) bacteria is crucial for their identification and control. In this study, single-cell Raman spectroscopy was used to explore the metabolic intricacies of VBNC P. aeruginosa induced by chlorine disinfection over 24 h. VBNC P. aeruginosa exhibited significant reductions of 75.98 %, 84.26 % and 81.07 % in carbohydrate, protein and nucleic acid Raman peaks, signaling decreased metabolic activity in these crucial components. Intriguingly, lipid metabolism in VBNC P. aeruginosa remained robust, indicating a potential adaptation to environmental stress. Furthermore, this study analyzed Raman characteristic peaks to examine metabolic conversion in these bacteria. VBNC P. aeruginosa displayed distinct phase-specific metabolic conversion patterns compared to culturable ones. These findings shed light on the temporal dynamics of metabolic processes, such as lipid-carbohydrate conversion, which appeared to be ongoing throughout the incubation period in VBNC P. aeruginosa. Compared to the culturable state, VBNC P. aeruginosa exhibited reduced isotopic assimilation rates for carbon, nitrogen and hydrogen by 40.57 %, 44.62 % and 39.45 %, indicating decreased substrate uptake for biomolecular synthesis. Additionally, the metabolic heterogeneity index of the VBNC bacterial population increased by 37.28 %, with this heterogeneity displaying a progressive increase with the duration of the culture. This observation suggests VBNC P. aeruginosa differentiation into distinct subpopulations, believed crucial for survival in challenging environments. These findings reveal the metabolic dynamics of VBNC state bacteria, providing insights into their adaptive strategies and implications for environmental health risk assessment and precise control technologies.

Comprehensive Risk Assessment of Farmer Households in Flood and Earthquake Prone Areas Based on Multidimensional Information Diffusion Model

In recent years, the global practice of regional natural disaster reduction and comprehensive risk prevention has promoted the integration of multiple disciplines, and the theory and technology of comprehensive risk assessment for multiple natural disaster chains urgently need innovation. This article is based on multiple natural disaster chain scenarios and sets secondary indicators for multiple influencing factors based on the first level indicators composed of basic risk factors such as hazard factors, vulnerability of disaster bearing bodies, and disaster prevention and reduction capabilities. By using multidimensional information diffusion technology, multiple hazard factor hazard combination factors, vulnerability combination factors of disaster bearing bodies, and comprehensive disaster prevention and reduction capability combination factors reflecting various natural disaster scenarios are constructed, A household comprehensive risk assessment index system for multi-dimensional information diffusion assessment of natural disaster comprehensive risk was designed by quantifying risk factors such as the intensity of comprehensive disaster causing factors, vulnerability of disaster bearing bodies, and comprehensive disaster prevention and reduction capabilities in disaster scenarios. This paper expands the traditional information diffusion comprehensive risk assessment model, makes up for the lack of information on geographical units, establishes a multi impact factor multi dimension natural disaster risk comprehensive assessment model for multi risk factors of complex disaster scenarios with small samples, obtains the theoretical value of multi-dimensional information Diffusion model comprehensive risk assessment for complex disaster scenarios, breaks through the sample size limit of natural disaster risks, and makes up for the lack of information on small samples of small probability events, Improved the reliability and accuracy of comprehensive risk assessment for multiple natural disaster chains. Then, take the disaster scenario formed by the comprehensive risk of earthquake and flood in a place in the upper reaches of the Fujiang River basin as the analysis sample, calculate the comprehensive risk assessment value of flood and earthquake damage in the study area's micro samples (rural households in villages and towns). By comparison, it is found that the comprehensive risk value assessed by the multi-dimensional information Diffusion model has good reliability and high accuracy, which is significantly better than the traditional Kriging interpolation method and geographical weighted regression method. This article provides a comprehensive risk assessment of natural disasters at the micro household level, which can better reflect the diversity and regionality of risks, help clarify the hidden risks of rural natural disasters, and provide scientific basis for government emergency management decision-making.

A comprehensive Analysis of the Application of GIS and RS Technologies in Flood Prediction and Risk Assessment, with a Focus on Wadi Baysh Dam in the Jazan region. KSA

A comprehensive Analysis of the Application of GIS and RS Technologies in Flood Prediction and Risk Assessment, with a Focus on Wadi Baysh Dam in the Jazan region. KSA

Leadership and safety culture in drilling operations: strategies for zero incidents

This paper offers an overview of key strategies, emerging trends, and collective efforts required to attain zero incidents in drilling operations. The journey towards zero incidents begins with the establishment of clear safety objectives and expectations, fostering a culture of accountability and continuous improvement, implementing effective training and communication programs, harnessing technology for risk assessment and incident prevention, and promoting employee engagement and involvement in safety initiatives. These strategies serve as pillars for building a robust safety framework that safeguards the well-being of individuals involved in drilling operations. Emerging trends in leadership and safety culture reflect a shift towards transformational leadership, psychological safety, data-driven decision-making, technology integration, and continuous learning and development. These trends underscore the importance of proactive risk management, employee empowerment, and technological innovation in driving safety excellence and achieving zero incidents. A call to action is essential for fostering an industry-wide commitment to safety culture in drilling operations. It requires collaboration and collective effort from all stakeholders, including companies, regulators, industry associations, and employees. By prioritizing safety as a core value and business imperative, investing in leadership development, safety training, technology integration, and continuous improvement initiatives, organizations can create safer work environments and drive towards zero harm. The vision for a future with zero harm in drilling operations is one where every individual returns home safely at the end of each day, incidents are minimized, and safety excellence is celebrated. Achieving zero incidents requires a collective commitment from all stakeholders, from organizational leaders to frontline workers, from regulators to industry associations. Through collaboration, innovation, and unwavering dedication to safety, we can turn the vision of zero harm into a reality in drilling operations. Keywords: Drilling, Safety Leadership, Zero Incidents, Safety Culture, Continuous Improvement, Stakeholder Engagement.

Survey Analysis of Potential Nuclear Safety Research of Thailand for International Research Collaborative Reinforcement in the 2020s

Abstract To achieve the long-term challenge of nuclear energy public acceptance in Thailand, nuclear safety research needed to be properly determined in both domestic and international directions, especially in the 2020s which was a period passing the Fukushima disaster over 10 years. Thailand Institute of Nuclear Technology (TINT) has studied nuclear safety research after the Fukushima accident to answer technical and social issues of nuclear power. An update of nuclear safety research from domestic experts and international surveys was needed in order to identify potential collaborative research to serve the goal of public acceptance reinforcement. The objective of this study was to survey, assess and rank the importance and knowledge level of nuclear safety research in Thailand among domestic experts in various fields. The survey was extended to collect the opinion of international participants of the ASEAN Network on Nuclear Power Safety Research (ASEAN NPSR) to analyze the similarity of the nuclear research interest for reinforcing the future collaborative project. As a result, the importance and knowledge level showed diverse important research topics with the priority of research scopes on human factor novel reactor technologies, and risk assessment. According to the ASEAN NPSR survey, the nuclear safety research of severe accidents, risk assessment, and novel reactor technologies were listed as potential collaborative projects. Also, the domestic and ASEAN NPSR survey results helped support the new collaborative research extension session in the annual ASEAN NPSR meeting to together discuss the potential nuclear safety research between members for the 2020s.

The Influence of Artificial Intelligence and Digital Technology on ESG Reporting Quality

Environmental, social, and governance (ESG) reporting is crucial for conveying a company's sustainability performance. However, challenges related to standardization, consistency, and data quality persist. This study explores the potential of artificial intelligence (AI) and digital technology to enhance ESG reporting by addressing these challenges. AI and digital technology utilize advanced tools like natural language processing, machine learning, data analytics, and blockchain to streamline data collection, improve quality, and facilitate communication. Regression analysis using A-share listed companies' data from 2012 to 2021 examines the relationship between digital transformation and corporate ESG performance. The research emphasizes the implications of ESG reporting, AI, and digital technology for corporate management, risk assessment, shareholder value, and social responsibility. AI and digital technology are vital for growth, innovation, efficiency, and competitiveness. ESG reporting significantly impacts a company's risk profile, reputation, performance, and overall value, contributing to sustainable development. Through a comprehensive review, methodology exploration, and in-depth analysis, this study provides valuable insights and recommendations for leveraging AI and digital technology in advancing ESG reporting. It concludes that implementing AI and digital technology enhances the comprehensiveness and assurance level of ESG reporting.

Transoral laser exoscopic surgery of the larynx: state of the art and comparison with traditional transoral laser microsurgery.

To evaluate the efficacy of transoral laser exoscopic surgery (TOLES) in a unicentric series of patients affected by benign and malignant glottic and supraglottic lesions, and compare outcomes with those of transoral laser microsurgery (TOLMS). To demonstrate the non-inferiority of TOLES in terms of operative time, margin status and complication rates, we compared outcomes of 93 patients treated by TOLES between July 2021 and July 2023 with those of a match-paired group of 107 historical patients treated by TOLMS. To perform a multiparametric ergonomic evaluation of TOLES vs TOLMS, we used observational methods for biomechanical overload risk assessment and wearable technologies comparing 15 procedures with TOLES vs a paired match of 13 surgeries performed with TOLMS by the same surgeon. No significant differences were found in terms of surgical duration, positive margins, or complications between TOLES and TOLMS. Ergonomics assessment by inertial measurement units and electromyographic surface electrodes demonstrated a reduced biomechanical overload with TOLES compared to TOLMS. The many advantages of TOLES, such as its superior didactic value, better digital control of light even through small-bored laryngoscopes, improved binocular vision, and increase in surgical performance by 3 or 4-hand techniques, are difficult to be quantified. In contrast, its non-inferiority in terms of oncological results and better ergonomics compared to TOLMS are demonstrated herein.

Nanoparticles‐based double‐stranded RNA delivery as an antiviral agent in shrimp aquaculture

AbstractThe review encapsulates the comprehensive exploration of RNA interference technology's application in shrimp aquaculture, covering molecular intricacies, production methods, and practical applications. The emphasis is on exploring the stability and delivery of gene‐specific double‐stranded RNA, particularly through nanoencapsulation. This is because the susceptibility of dsRNA to degradation and limited cellular penetration, emphasising the need for effective delivery mechanisms. The review presents an in‐depth exploration of nanoparticles for the encapsulation and delivery of dsRNA, including virus‐like particles (VLPs), and non‐viral based nanoparticles such as liposomes, chitosan, and beta‐glucan. VLPs, derived from non‐infectious shrimp virus structures, exhibit biocompatibility and natural functionality, making them suitable carriers for dsRNA. The application of chitosan and its derivatives are explored for their efficacy in reducing viral infections in shrimp. Beta‐glucan particles are examined for their immunostimulant properties in shrimp aquaculture. The text emphasises the use of yeast‐based glucan particles for encapsulating dsRNA, showcasing their potential in preventing viral diseases in shrimp. The review introduces cautionary considerations for nanoparticle formulation, highlighting factors such as pH, organic solvents, metal ions, and environmental ribonuclease that can impact dsRNA stability during synthesis. In conclusion, the text discusses the potential economic worthiness and environmental risk assessment of dsRNA technology in shrimp aquaculture. While acknowledging successful applications in other environments, it underscores the need for regulatory approval and risk assessment for dsRNA‐based products in the aquaculture industry. The evaluation of dsRNA in real‐world shrimp farms is deemed necessary for commercial utilisation, taking into account income, expenses, safety, and environmental considerations.