Risk Analysis Of Systems Research Articles

Estrogenic compounds in drinking water: A systematic review and risk analysis

Estrogenic compounds are the endocrine disruptors that receive major attention because of their ability to imitate the natural female hormone, 17β-estradiol and cause adverse effects on the reproductive system of animals. The presence of estrogenic compounds in drinking water is a warning to assess the risks to which human beings are exposed. The present work has the objectives of carrying out a systematic review of studies that investigated estrogenic compounds in drinking water around the world and estimate the human health and estrogenic activity risks, based on the concentrations of each compound reported. The systematic review returned 505 scientific papers from the Web of Science®, SCOPUS® and PubMED® databases and after careful analysis, 45 papers were accepted. Sixteen estrogenic compounds were identified in drinking water, from the classes of hormones, pharmaceutical drugs and personal care products, plasticizers, corrosion inhibitors, pesticides and surfactants. Di-(2-ethylhexyl) phthalate (DEHP) was the compound found at the highest concentration, reaching a value of 1.43 mg/L. Non-carcinogenic human health risk was classified as high for 17α-ethynilestradiol and DEHP, medium for dibutyl phthalate, and low for bisphenol A. The estrogenic activity risks were negligible for all the compounds, except DEHP, with a low risk. None of the estrogenic compounds presented an unacceptable carcinogenic risk, due to estrogenic activity. However, the risk assessment did not evaluate the interactions between compounds, that occurs in drinking water and can increase the risks and adverse effects to human health. Nonetheless, this study demonstrates the need for improvement of drinking water treatment plants, with more efficient technologies for micropollutant removal.

A Survey of Function Failure Identification and Propagation Analysis Methods for System Design

Abstract In the context of model-based product and system design, the capability to assess the impact of potential component faults, undesired interactions, and fault propagation is important for design decision-making. Addressing these potential negative outcomes should occur as early in the design process as possible to enable designers to make impactful changes to the design. To this end, a set of tools and methods have been developed over the last 20 years that leverage a function-based approach assessing the potential faults and fault propagation and develop system health management strategies. These tools and methods must overcome challenges of high abstraction and satisfaction of safety or risk requirements with limited design specification. This paper provides a detailed survey of a particular function-based analysis tool as a lens to understanding the challenges for other tools in this domain. Specifically, development and evolution of the Function Failure Identification and Propagation Framework (FFIP) is used as a lens to survey the challenges of this field. The objective of this paper is to explore the specific challenges and advancements of the FFIP framework and related tools that address similar modeling and analysis challenges. We provide an overall categorization and summary of the research efforts to date and identify specific known limitations and unaddressed challenges in the area of design-stage system risk and safety analysis.

Systemic Risk Analysis of Safety, Progress, and Investment in the Construction of a Water Transfer Project and the Importance of Common Cause Failure

Safety, progress, and investment risks are correlated during the construction period of large-scale water transfer projects. However, previous studies have only considered individual risk factors, overlooking the potential systemic risk posed to safety, progress, and investment, as well as any underlying common cause failures. Since traditional risk analysis methods are ill-suited to addressing common cause failure, this paper’s objective was to establish a comprehensive evaluation index framework and to identify the basic events of common cause failure. To do that, we developed a risk analysis method that models common cause failure based on a Bayesian network for assessing that systemic risk. The Henan Section of the Yangtze-to-Huaihe River Water Diversion Project in China was then used as a case study. The results show that a variety of common cause failure events, such as epidemic disease, design alteration, lagged approval process, heavy rain in the flood season, renewal material and failing equipment, construction accidents, and external interference, can significantly impact the safety, progress, and investment systemic risk. Design alteration poses the greatest risk, with renewal material and failing equipment exerting the strongest influence among all common cause failure events. It is also possible to elucidate the predominant causal chains; specifically, the contributing influence of each basic failure event to the systemic risk can be clarified by adjusting their respective initial state. The failure of renewal material and failing equipment was found to significantly increase the safety risk. This study effectively simulated the complex causal relationships and uncertainties of pertinent risk factors, thereby enhancing our understanding of the systemic risk associated with safety, progress, and investment in large-scale water transfer projects.

A probabilistic extension of existing site-specific liquefaction triggering and liquefaction manifestation methods for regional scale evaluations

Liquefaction hazard analyses are needed for regional-scale applications, such as risk analysis and upgrades of electrical transmission, water conveyance, and highway systems. In this paper, we expand well-established site-specific liquefaction triggering and manifestation analysis methods for regional scale application by explicitly addressing the uncertainty in groundwater conditions, soil behavior classification, and cyclic resistance. The uncertainty inherent to regional-scale geotechnical properties is quantified by considering the inputs into conventional liquefaction triggering and manifestation analyses as random variables. With this flexible and extensional formulation, the geostatistical properties needed for regional scale analyses may be estimated by either averaging borehole information or spatially interpolating geotechnical properties across broad geologic deposits. We demonstrate the utility of the method by analyzing the liquefaction hazard throughout the south San Francisco Bay area, California, U.S.A. The resulting estimates of the probability of liquefaction manifestation tend to be lower than previously published estimates, largely owing to the geologic structure of the area and the uncertainty in liquefaction surface manifestation once liquefaction is triggered at depth. Uncertainties in groundwater conditions, soil behavior classification, penetration resistance, and liquefaction manifestation are quantified by the regional scale analyses, which provide a complete and systematic evaluation of the liquefaction hazards, localize the uncertainties in subsurface conditions, and facilitate supplemental investigations at areas of high uncertainty to fill data gaps.

Geometrical Variation Analysis of Landslides in Different Geological Settings Using Satellite Images: Case Studies in Japan and Sri Lanka

Over the past three decades, Sri Lanka has observed a substantial rise in landslide occurrences linked to intensified rainfall. However, the lack of comprehensive landslide inventories has hampered the development of effective risk analysis and simulation systems, requiring Sri Lanka to rely heavily on foreign-developed models, despite the difficulty of fully examining the similarities between the characteristics of landslides in Sri Lanka and the areas where the model has been developed. Satellite images have become readily available in recent years and have provided information about the Earth’s surface conditions over the past few decades. Thus, this study verifies the utility of satellite images as a cost-effective remote-sensing method to clarify the commonalities and differences in the characteristics of landslides in two regions Ikawa, Japan, and Sabaragamuwa, Sri Lanka, which exhibit different geological formations despite similar annual rainfall. Using Google Earth satellite images from 2013 to 2023, we evaluated land-slide density, types, and geometry. The findings reveal that Ikawa exhibits a higher landslide density and experiences multiple-type landslides. In contrast, both areas have similar initiation areas; however, Sabaragamuwa predominantly experiences single landslides that are widespread and mobile. The findings also reveal that various characteristics of landslides are mainly influenced by varied topography. Here, we confirmed that even in areas where comprehensive information on landslides is conventionally lacking, we can understand the characteristics of landslides by comparing landslide geometry between sites using satellite imagery.

Prospective systematic risk analysis of the digital technology use within pharmaceutical care

BackgroundDigital technologies are present in every phase of a drug lifecycle, from drug design and development to its dispensing and use. However, given the rapid development and implementation of digital solutions, their monitoring, evaluation, and risk assessment are limited and lacking. ObjectiveThis research is aiming to identify potential errors, quantify and prioritize associated risks in the context of certain technologies used in pharmaceutical care, as well as define corrective measures to improve patient safety and the quality of pharmaceutical care. MethodsA 10-member multidisciplinary team conducted Failure Mode and Effect Analysis (FMEA) to identify critical risks, their causes and effects, along with developing corrective measures within the selected digital health components: Telepharmacy, mHealth, Artificial intelligence (AI), and Software infrastructure and systems. Critical risks were determined by calculating risk priority numbers (RPNs) from severity, occurence, and detectability scores. ResultsThis study identified 42 risks regarding the 4 components. After calculating RPNs and the threshold RPN (RPN=30), 8 critical risks were identified. Corrective measures were proposed for these failure modes, after which the risks were re-evaluated (RPN sum was reduced from 414 to 156). The risk with the highest RPN value was Internet/identity fraud, while the rest included inadequate and incomplete data entry and management, flawed implementation, human and technology errors, and lack of transparency, personalization and infrastructure. For the critical risks, 42 different causes were recognized on a system, technological and individual level while their effects were discussed in terms of patient safety and business management in pharmacies. ConclusionDigitalization of pharmaceutical practice promises greater effectiveness of pharmaceutical care, but in order to achieve this, efforts, resources and initiatives must be directed toward timely identification of problems, appropriate monitoring, and building adequate infrastructure that can support safe implementation of digital tools and services despite the swift development of innovations.

Implementing analytical quality by design in reversed phase-high performance liquid chromatography for simultaneous estimation of teriflunomide and quercetin: Applicability in dual drug loaded topical microemulsion

The current study reports the development of a novel, robust, and sensitive reversed-phase high-performance liquid chromatography (RP-HPLC) method for the simultaneous estimation of teriflunomide (TFD) and quercetin (QCN) in dual drug-loaded microemulsion. TFD and QCN have been reported to exhibit anti-inflammatory effects by targeting various inflammatory mediators involved in the pathogenesis of rheumatoid arthritis (RA). This analytical method employs a risk-based approach and follows the principles of analytical quality by design (AQbD). The study involved preliminary screening trials and systematic risk analysis to identify critical method attributes, that significantly impact the critical quality attributes (CQAs). For the optimization of method,a face centered central composite design was utilized, and 16 experimental runs were performed using design expert software version 7.0.0. Chromatographic conditions were carefully optimized using AQbD, falling within the design space and consisting of ammonium acetate buffer (pH 3.5) and acetonitrile (60:40, % v/v) with a flow rate of 1.0 mL/min. An analytical Hibar Lichospher 100 RP-18e column (250 × 4.6 mm, 5 µm) was employed, with detection wavelength of 280 nm and 367 nm for TFD and QCN, respectively. The optimized method underwent validation according to ICH guidelines and demonstrating applicability for evaluating topical microemulsion.

Systematic Risk Analysis of Listed Financial Institutions from the Perspective of Complex Network

Based on the complex network theory, this paper studies the systemic financial risks in China’s financial market. According to the industry classification of the China Securities Regulatory Commission in 2012, the daily closing prices of 45 listed financial institutions are collected and the daily return rates of each financial institution are measured according to the logarithmic return rate calculation formula. In this paper, the risk spillover value ΔCoVaR is used to measure the contribution degree of each financial institution to systemic risk. Finally, the relationship between the risk spillover value ΔCoVaR and the node topology index of the risk transmission network is investigated by using a regression model, and some policy suggestions are put forward based on the regression results.

Analysis of Systemic Risk on the Financial Performance during the COVID-19 Pandemic: The Case of the Colombian Banking Industry

This study seeks to analyze the financial performance of the Colombian banking industry during the COVID-19 pandemic. The frame of reference is based on the concept of systemic risk; concerning this, the pandemic is conceived as an external shock, which impacted the dynamics of the banking industry. To conduct this study, a descriptive-correlational scope is proposed, from which an analysis of different accounting items related to the banking business is made and validated by expert judgment. The analysis horizon covers six years, but the focus is placed on March 2020, when COVID-19 was declared a pandemic by the World Health Organization (WHO). For this purpose, a longitudinal design is proposed, which analyzes the time series describing the behavior of some relevant items in the management of the banking business, such as operating revenue, provisions, interest on deposits and drawings, valuation of trading derivatives, and technology-related expenses. In addition, these items’ correlation with banking establishments’ performance is analyzed. The results of the study show that during the pandemic period, there was a significant increase in the level of volatility in the foreign exchange market, which impacted the operating revenue of banking establishments. It is concluded that, although exchange rate volatility affected the results of the banking industry, the main factor related to the financial performance of Colombian banks is their business itself, i.e., revenue from the loan portfolio and the quality of the loan portfolio. Therefore, systemic risk must be addressed regarding its implications on banks’ main profit drivers, such as portfolio revenue, cost of deposits, and provisions. Based on the above, it is recommended that Colombian banking establishments make greater efforts to diversify their sources of income to reduce their exposure to systemic risk situations.

Natural hazard risk analysis in the framework of water safety plans.

The available literature on natural hazard risk analysis focused on the implementation of water safety plans (WSPs) is surprisingly quite poor, despite the significant increase in the number and severity of disasters and adverse effects on drinking water supply systems generated by natural hazards. At the same time, WSPs that conveniently account for natural hazards with a comprehensive approach 'from source to tap' are still scarce as they typically occur at larger spatial scales and adequate prevention, mitigation and adaptation require efficient inter-institutional collaborations. The aim of this paper is to highlight the main bottlenecks for water utilities to include natural hazards in the development of their WSPs. The research adopted a stakeholders-oriented approach, involving a considerable number of water utilities (168), water sectoral agencies (15) and institutions (68) across the Adriatic-Ionian Region through a stepwise process that generated joint SWOT analysis, the development of a decision support system (DSS) focused on WSPs procedures and tabletop exercises. The final outcomes generated strategic documents (REWAS - Adrion Road map for resilient water supply) that highlighted the necessity for efficient cross-sectoral and inter-institutional cooperation in the development of well-founded and robust WSPs to address natural hazard risk analysis for water supply systems (DWSS).

Systematic Analysis of Risks in Industry 5.0 Architecture

Industry 4.0, which was proposed ten years ago to address both the industry’s strengths and faults, has finally been replaced by Industry 5.0. It seeks to put human welfare at the core of manufacturing systems, achieving societal goals beyond employment and growth to firmly provide wealth for the long-term advancement of all of humanity. The purpose of this research is to examine the risks involved in the adoption of Industry 5.0’s architecture. The paper discusses the significance of Industry 5.0 and the advanced technology needed for this industrial revolution, followed by a detailed discussion of Industry 5.0’s human-centric strategy. The comprehensive literature review has resulted in the identification of risks and their mitigation strategies in Industry 5.0 architecture. A taxonomy with respect to different categories of risks has also been proposed. This study classifies Industry 5.0 system assets, identifies platform-independent risks, and develops countermeasures to protect against potential threats, irrespective of the business or domain.

Counterparty risk and contagion in financial networks

ABSTRACT Based on the concept of multi-orbit contagion, we develop a network-based probabilistic model to illustrate the risk contagion among institutions and the stability of financial networks. Our examination focuses on two key aspects: the size of component, which the network divided into different components, and the number of institutional partners. Our study finds a non-monotonic relationship between the systemic risk and the connection density, and there needs a trade-off between the number of partners and the risk contagion to reduce systemic risk. Furthermore, our analysis of core-periphery structures provides an understanding of why the”too big to fail” phenomenon occurs. Our research contributes to systemic risk analysis and has significant theoretical implications for regulators.

Model predictive control and rainfall Uncertainties: Performance and risk analysis for drainage systems

Urban flooding resulting from severe rainstorms is an increasing challenge for cities worldwide due to climate change and rapid urbanization. Model predictive control (MPC) has emerged as a promising approach for real-time management of urban drainage systems to mitigate flooding impacts. However, existing MPC research often relies on idealized rainfall forecasts without adequately accounting for forecast uncertainty, which can compromise the effectiveness of MPC strategies. This study aims to address this critical research gap by developing a framework to evaluate the impacts of forecast uncertainty on MPC performance for urban drainage management. The framework consists of 3 components, (1) martingale model of forecast evolution based on Langevin dynamics for generating rainfall data under different uncertainty conditions (2) MPC, which accepts the rainfall inputs and obtains the real-time control results under different uncertainty conditions and (3) the Scheduling Performance Indicator module, which performs a systematic evaluation of the real-time control system. Using a case study of the Doumen region in Fuzhou City, the results reveal two key findings: First, MPC performance remains close to optimal when forecast uncertainty levels are between 0.1 and 0.3, but deteriorates significantly at uncertainty levels from 0.3 to 0.5. Second, while the MPC error feedback module can occasionally degrade performance for individual events, its overall impact is beneficial in reducing performance deviation risks.

Mekanisme Penilaian Pemberian Kredit Dalam Meminimalisir Risiko Kredit Pada Bank BJB KCP Mojokerto

Bank BJB KCP Mojokerto which is located on Jl Majapahit No. 333C-333D, Kranggan, Mojokerto City is one of the banks that provides credit facilities for the public. This research aims to determine the credit assessment mechanism of Bank BJB KCP Mojokerto in minimizing credit risk. This research uses qualitative methods with observation, interview and documentation techniques. The research results show that bank BJB KCP Mojokerto has implemented good credit assessment using the 5C principles with character and capacity as the bank's main assessment in minimizing credit risk. This research suggests banks improve the risk analysis system, strengthen risk management, strengthen collaboration between the credit assessment department and the risk management department, and provide education to creditors regarding the systematics of credit applications.

Analyses and algorithms of personnel safety in mines using event tree and Bayesian network method

Determination of the hazard index in ensuring the safety of personnel in underground mines requires a comprehensive approach. Different methods can be applied depending on the specifics and conditions of work. This article discusses event tree and Bayesian network methods as tools for systematic analysis and assessment of personnel safety risks. The event tree method allows the sequence of events that lead to certain outcomes to be ordered and visualised. Analysing this event tree can help identify critical points and determine likely ways to prevent accidents. The Bayesian grid method is a graphical model of the probabilistic relationships between different variables. When analysing personnel safety, the Bayesian grid method can take into account the probability of events, the factors affecting safety and their interrelationships.

Modeling, Simulation, and Risk Analysis of Battery Energy Storage Systems in New Energy Grid Integration Scenarios

Modeling, Simulation, and Risk Analysis of Battery Energy Storage Systems in New Energy Grid Integration Scenarios

Risk Analysis of Energy Systems Integrated With Renewable Energy Resources

Risk Analysis of Energy Systems Integrated With Renewable Energy Resources

Fuzzy adaptive resonance theory failure mode effect analysis non-healthcare setting for infectious disease: review

<span>Fuzzy adaptive resonance theory (ART) is an ART network that is developed as one of the alternative methods to evaluate risk priority number (RPN) in failure mode and effect analysis (FMEA). Not only is FMEA are common technique as an analysis tool in industrial sectors, but also, especially during the global emergency COVID-19 pandemic hits, FMEA is used in prevention and mitigation measures. Many alternative methods have been proposed. However, not many investigations use clustering models such as Fuzzy ART in FMEA. This paper aims to provide a comprehensive review and then propose a model for systematic risk analysis which implement the fuzzy ART model, named clustering- transmission causes and effects analysis (c-TCEA), for the prevention and mitigation of infectious diseases.</span>

Method for systemic risk analysis of mining and economic assessment of high-mountain ore deposits in the Kyrgyz Republic

The prevailing uncertainties that arise during the development of high-mountain deposits are identified, and a method is given for their subsequent minimization and cost reduction, which makes it possible to more reliably and objectively carry out pre-feasibility studies. The results can serve as an assessment of the planned capital and operating costs, which significantly affects the profitability of the development of high-mountain deposits and risk events.

Development of the Automated System for Radiation Risk Analysis: goals, tasks and the vision for progress

This paper describes the preconditions of creation and the process of development of the Automated System for Radiation Risk Analysis. Three main objectives for the development of an automated system for radiation risk analysis were identified: creation of a tool for the development and scientific justification of hygienic standards and other protective quantities in the field of ionizing radiation application; practical implementation of the principles of justification and optimization in radiation protection on the basis of monetary assessment of radiation health risks; and comparative analysis of risks of different nature on the basis of comparable indicators of population health. The Russian software platform 1C: Enterprise was chosen as the development platform for the Automatized System for Radiation Risk Analysis. The choice of this platform was related to simplification of integration with other computer systems being developed at the Research Institute of Radiation Hygiene after Prof. P.V. Ramzaev, such as the Automated System for Radiation Exposure Control of Rospotrebnadzor. Before the practical development of the system in accordance with the terms of reference, the main parameters in view of its interaction with the user were determined: arrangement of the user interface elements, main input parameters, primary calculated indicators and output calculation results, etc. The estimation of annual increase in the probability of radiation-induced malignant neoplasms depending on the organ dose, sex and age of the exposed person and other parameters according to the models of the UN Scientific Committee on the Effects of Atomic Radiation, the U.S. Environmental Protection Agency and Publications 103 and 152 of the International Commission on Radiological Protection was implemented in the system. The capabilities of the system include calculation of a number of modern lifetime radiation risk indicators used for risk characterization in various scientific publications over the last 35 years, including calculation of population risks based on national medical and demographic data of several dozen states published over the last 50 years.