Risk Analysis Of Systems Research Articles

HAZARD AND RISK ANALYSIS OF RAILWAY VEHICLE CONTROL SYSTEMS ACCORDING TO SAFETY INTEGRITY LEVELS

This article presents an approach to the verification of the safety integrity level (SIL) of rail vehicle subassemblies in accordance with the applicable railway standards PN-EN ISO 50126-1, PN-EN ISO 50126:2, and PN-EN ISO 50129. Particular attention has been given to the calculation procedure related to the determination of the tolerable hazard rate and tolerable functional failure rate indicators in a situation where various reliability indicators have been declared for components of rail vehicles, such as MTTFD or B10D. In this case, the verification of the safety integrity level using the above-mentioned railway standards may be difficult, and it becomes necessary to use additional standards for safety systems based on electronic components. An example is the PN-EN ISO 13849-1:2006-01 standard, which contains a calculation method based on the transformation of the exponential model, which is useful for hazard and risk analyses of electronic systems containing components with different reliability indices. Another supplementary standard is the PN-EN 61025:2007 standard, which concerns fault tree analysis. Based on the above-mentioned standards, an algorithm was developed to verify the safety integrity level of the frequency converter control system. The obtained results allowed us to confirm the fulfillment of the functional safety requirements of the considered system.

The accuracy of the Stroke Risk Analysis (SRA) system for predicting atrial fibrillation in patients in the postoperative period of myocardial revascularization

The accuracy of the Stroke Risk Analysis (SRA) system for predicting atrial fibrillation in patients in the postoperative period of myocardial revascularization

Stock profiling using time–frequency-varying systematic risk measure

This study proposes a wavelets approach to estimating time–frequency-varying betas in the capital asset pricing model (CAPM) framework. The dynamic of systematic risk across time and frequency is analyzed to investigate stock risk-profile robustness. Furthermore, we emphasize the effect of an investor’s investment horizon on the robustness of portfolio characteristics. We use a daily panel of French stocks from 2012 to 2022. Results show that varying systematic risk varies in time and frequency, and that its short and long-run evolutions differ. We observe differences in short and long dynamics, indicating that a stock’s betas differently fluctuate to early announcements or signs of events. However, short-run and long-run betas exhibit similar dynamics during persistent shocks. Betas are more volatile during times of crisis, resulting in greater or lesser robustness of risk profiles. Significant differences exist in short-run and long-run risk profiles, implying a different asset allocation. We conclude that the standard CAPM assumes short-run investment. Then, investors should consider time–frequency CAPM to perform systematic risk analysis and portfolio allocation.

Shipboard compressor system risk analysis by using rule-based fuzzy FMEA for preventing major marine accidents

Considering the shipboard machinery, the compressed air system directly powers the ship's diesel engines' starting and routine operations. Additionally, pressurized air is distributed throughout the ship, enabling the operation of various systems. However, a compressor failure could result in the entire compressed air system collapsing, which might also result in the ship losing its maneuverability. When a ship loses its ability to maneuver, various devastating risks can arise, including grounding, collision, contact, explosion, and fire. On the other hand, compressor system risk assessment is not a widely researched subject in the field of maritime. To fill this gap, this study provides a comprehensive risk assessment of the shipboard compressor system by utilizing the rule-based fuzzy Failure Mode and Effects Analysis (FMEA) method. 33 failure modes with their causes and consequences were determined with their expert-assigned O–S-D scores. In addition, 125 If-Then rules in the fuzzy logic system were created specifically for this study. Finally, the failure modes of the shipboard compressor system were prioritized. According to the results, the most critical failure modes are identified as FM18-Broken piston rings with a 6.43 fuzzy RPN score, FM08-Piston liner wear with 6.29, and FM11-Knocking compressor operation with a 5.59. The results of this study will contribute to the maritime sector by analyzing the risks of compressor systems and introduce them to safety specialists, ship crew, shipping companies, port authorities, inspection officers, etc.

Sensitivity Analysis of Risk Characteristics of Complex Engineering Systems: An Application to a Subsea Pipeline Monitoring System

One of the problems of risk analysis of complex engineering systems is the uncertainty of initial information about the time and damage associated with occurrence and development of the risk situation. The paper proposes a methodology and procedure for constructing a risk tree, loading it with initial data, calculating the corresponding characteristics: the distributions of time to reach the intermediate and main risk events and of associated with them damages, as well as their moments. Methodology involves the construction of the most dangerous path of risk situation development with respect to different criteria as well as analysis the sensitivity of risk characteristics to the initial information. The proposed approach is applied to a model of an automated system for remote monitoring of underwater gas pipeline. The proposed methodology and its implementation on a real-world example constitute the novelty of the work.

Systemic Risk with Multi-Channel Risk Contagion in the Interbank Market

The systematicness of banks is an important driver of financial crisis. Overlapping portfolios and assets correlation of banks’ investment are important reasons for systemic risk contagion. The existing systemic risk models are all analyzed from one aspect and cannot reflect the real situation of the banking system. In the present paper, considering the overlapping portfolios and assets correlation, a contagion network model with multi-channel risk is proposed, which is with interbank lending (direct contagion channel), overlapping portfolios (indirect contagion channel), and assets correlation (indirect contagion channel). In addition, the model takes investment risk as an impact factor and learns the operation rules of the banking system to help banks compensate for liquidity through asset depreciation. Based on the proposed model, the effects of assets correlation, assets diversity, assets investment strategy, interbank network structure, and the impact of market density on risk contagion are studied and analyzed quantitatively. The method in this paper can more truly reflect the banking system risk than the existing model. This paper provides a solution for quantitative analysis of systemic risk, which provides powerful tools for macroprudential stress testing and a reference for regulatory authorities to prevent systemic risk.

Application of QbD based approach in development and validation of RP-HPLC method for simultaneous estimation of methotrexate and baicalin in dual-drug-loaded liposomes.

The present study delineates the development of a novel, rugged and sensitive stability-indicating risk-based HPLC method for the concurrent estimation of methotrexate (MTX) and baicalin (BCL) in dual-drug-loaded-nanopharmaceuticals based on an analytical quality-by-design approach. Preliminary screening trials along with systemic risk analysis were performed, endeavouring to explicate the critical method attributes, namely pH, percentage of orthophosphoric acid and percentage of acetonitrile, that influence the critical quality attributes. Box-Behnken design was utilized for the optimization of the tailing factor as the response for MTX and BCL in a short run time. The chromatographic conditions were optimized by performing 17 experimental runs using design expert software. The chromatographic conditions were selected after the analysis of the optimized zone within the confines of the design space: water:acetonitrile adjusted to a pH of 3.0 with 0.05% orthophosphoric acid (60:40, %v/v) was the mobile phase, the flow rate was 1.0ml/min and an analytical C18 column was used at an isobestic wavelength of 282 nm. Furthermore, the optimized method was validated in accordance with the International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use guidelines and was found to be within the prescribed limits. Therefore, the developed reversed-phase-high-performance liquid chromatography method has a high degree of practical utility for synchronous detection of MTX and BCL in pharmaceutical nano-dosage forms such as protein-based nanoparticles, nanocrystals, polymeric nanoparticles and metallic nanoparticles in in vivo and in vitro studies.

Analytical quality by design oriented development of the UPLC method for analysing multiple pharmaceutical process intermediates: A case study of Compound Danshen Dripping Pills

This work presented the integration of the Analytical Quality by Design concept in developing a UPLC method for the quantification of saponins and phenolic acids in two Compound Danshen Dripping Pills intermediates of a concentrated extract and a supernatant. Prior knowledge and systematic risk analysis were conducted to identify potential critical method parameters (CMPs) that affected critical quality attributes (CQAs). A definitive screening design was employed to investigate the quantitative relationship among the intermediate type, CPPs, and CQAs. Intermediate type was added in the experimental design table as a categorical variable. After the models were built, the method operable design region (MODR) was calculated with an exhaustive search-Monte Carlo method. The CPP combinations with a 95 % or higher probability of reaching the preset standard were collected in MODR. The MODR robustness test was conducted with a Plackett–Burman design. The separation of analytes was achieved with a Waters Acquity HSS T3 (100 × 2.1 mm, 1.8 µm) column at 30 °C, using 0.05 % phosphoric acid and acetonitrile as the mobile phases in gradient elution at a flow rate of 0.40 mL/min. The elution was monitored at UV detection wavelengths of 280 nm and 203 nm. The optimized method was also validated. Good robustness, accuracy, precision, stability and repeatability, and linear regression (R > 0.9997) were obtained. All recoveries of the 9 compounds ranged from 97.8 % to 101.7 %, with an RSD of less than 3.49 %. Nine batches of Danshensu, protocatechualdehyde, rosmarinic acid, salvianolic acid B, salvianolic acid A, notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, and ginsenoside Rb1 were analysed. Danshensu was found to be the compound with the highest content.

Formation of state policy in the sphere of digital platforms and ecosystems

Problem setting. The scientific work is devoted to the study of directions and measures of regulation of digital platforms and digital ecosystems. The functioning of digital platforms and ecosystems has its advantages, but citizens, businesses and the state face risks of information security, inequality of relations, loss of sovereignty. That is why in countries with a developed digital economy, the issue of state regulation of platforms and ecosystems is among the priorities. For Ukraine, which is significantly lagging behind in the application of breakthrough innovations, it is important to study world experience in order to develop its own state policy. analysis of recent researches and publications. The issues of regulation of digital platforms and ecosystems are discussed in the scientific literature. In the studies of scientists, in particular, B. Chew, M. Jacobides, B. Kyra, J. Wu, a wide range of aspects are considered, such as the complexity of developing regulatory solutions in the digital economy due to constant innovations, the specifics of protecting competition, data, and human rights in digital ecosystems, the need for regular rethinking and updating of state influence approaches, the need for big data analytics by regulators to identify patterns of behavior of subjects, the feasibility of building a national digital ecosystem of state regulation. The question of the specifics of the development and implementation of an effective state policy in the field of digital ecosystems for emerging economies remains unexplored. Purpose of the research is to substantiate theoretical provisions, analyze legislation and develop practical recommendations for the formation of a state policy for the regulation of digital platforms and ecosystems in Ukraine. article’s main body. To solve the problems of the ecosystem economy, the European Union adopted a number of regulatory documents regulating the activities of digital platforms, in particular the Law on Digital Markets and the Law on Digital Services. The regulatory requirements of the EU for digital platforms are aimed at reducing the risks of monopolization, unfair competition, security of data and operations, misuse of information. Similar requirements can and should be introduced in developing countries. It is important for all countries to ensure the security and stability of a single digital ecosystem. To measure progress in achieving the EU’s digital development goals by 2030, the EU has introduced monitoring measures. On the basis of monitoring, it is expedient for each country to form state supervision over the functioning of digital ecosystems. The systematic approach to the formation of state policy is as follows. The strategic goal of regulating digital platforms and ecosystems must be aligned with national goals. The chosen goal should be decomposed by levels and directions for systematic processing and implementation of strategic decisions. Policy tasks should be defined taking into account the goals, identified weaknesses, risks and threats. conclusions and prospects for the development. States should respond to the potential and existing dangers of the ecosystem economy through the implementation of a policy for the regulation of digital platforms and ecosystems and its systematic updating. In conditions of insufficient funding and in the case of technological lag, emerging countries can implement effective low-cost public policy by implementing regulatory requirements for digital platforms, state supervision in the field of ecosystem economy, development of regulatory measures taking into account a systemic approach. The perspective of further research is the systematic analysis of risks in digital ecosystems and the development of regulatory measures for their management.

The Use of ERM in Systemic Risk Analysis in Banking: Take Silicon Valley Bank's Bankruptcy as an Example

The Use of ERM in Systemic Risk Analysis in Banking: Take Silicon Valley Bank's Bankruptcy as an Example

A One Health look into the emergence of zoonotic viruses at the human-animal-environment interface

Abstract Emerging zoonotic viruses are a major public health concern, and they have caused the majority of human infectious disease outbreaks in recent decades. It is known that the emergence of zoonotic diseases is facilitated by human-caused environmental changes such as deforestation and changes in global climatic conditions. However, the complex interactions between these environmental elements and the contribution of each factor to the emergence and spread of zoonotic viral pathogens are not sufficiently addressed. Therefore, this article presents an overview of the available scientific knowledge on the major anthropogenic and climatic drivers of emerging zoonotic viruses, and also discusses the interconnections among human health, animal health, and ecosystem health in the context of emerging zoonotic viruses, and how the One Health approach can be implemented in reducing the health risks of emerging zoonotic viral pathogens. One Health impact statement The One Health approach has got more attention post-COVID-19 pandemic. However, there are multiple challenges in its real-world application. This paper presents a general One Health application framework that describes how a national One Health risk analysis (OHRA) system can be designed and implemented to predict, prevent, and control emerging zoonotic viral pathogens at the human-animal-environment interface.

Ability to use available electronic resources for modeling the development of forest fires

The article discusses various types of monitoring of forest fires, studied and analyzed satellites that are used by the space monitoring system of the Ministry of Emergency Situations of Russia for remote sensing of the Earth. The statistical data of the Forestry Department on forest fires over the past 15 years in the territory of the Voronezh region are given. The dependence of the number of forest fires on meteorological conditions, in particular on the amount of precipitation, wind gusts and air temperature, was studied using the example of 2010 and 2020. The municipalities that are most prone to forest fires are identified. The monitoring systems of the forest fire situation on the territory of the Voronezh region, which are used in the crisis management center of the Main Directorate of the Ministry of Emergency Situations of Russia for the Voronezh region, are analyzed. The program "Forest Fires" has also been developed to predict the spread of forest fires based on the Methodology for assessing the consequences of forest fires, developed by the All-Russian Research Institute of Civil Defense and Emergency Situations in 1994 and put into effect by the order of the Ministry of Emergency Situations of Russia dated 14.04.1995. No. 194. A comparative analysis of the solution of the same problem with the same initial data in the developed program "Forest Fires" and in the risk analysis and management system (SAUR) of the automated information control system of the unified state system for the prevention and elimination of emergencies (AIUS RSChS) is presented.

Multi-hazards Shanghai - risk analysis and safety management system

Disaster Prevention and Resilience is an international, peer-reviewed, open access journal, which is devoted to developing knowledge and capacity in strategic and practical aspects of reducing the impact of natural and human-instigated disasters.

Environmental safety model of the region in conditions of large-scale mine liquidation

The article outlines the role of research work on the state of ecological safety of the region in the context of a large-scale mine disaster. The aim of the study is to develop a forecast for a full-scale forecast of the dynamics of the PTS state (forecast of man-made situations) based on a system analysis and synthesis of an assessment of man-made impacts. As a research method, a comprehensive system analysis is used for the practical implementation of research in the field of environmental safety. As a result of studying the main tasks of research work, analyzing the results in the field of technosphere safety in substantiating the program of measures for the restructuring of the coal industry in Russia. An organizational-structural-predictable system based on the combination of substances of methodological, technical, interpretive and organizational means, including a comprehensive real-time analysis, is proposed. It is based on the theoretical principles of system analysis, forecasting and risk analysis in modeling all stages of forecast work, the forecasting methodology and methodological assessment of the dynamics of mine flooding are presented. A permanent control model of the region's technospheric security has been developed. It should be noted that the developed "method-model" is an effective scientific development and uses a complex character.

Retracted: Systematic Risk Analysis of Semiconductor Global Market Based on Deep Feature Fusion K-Means Algorithm.

[This retracts the article DOI: 10.1155/2022/8036956.].

Debris flow gully zoning and risk assessment based on numerical simulation

In order to evaluate the zoning and risk of debris flow gully based on numerical simulation, a set of theoretical system and technical process of debris flow quantitative risk analysis suitable for mountainous towns in southwest China was constructed, taking buildings and roads as the research objects, in view of the particularity of disaster-bearing body types and debris flow disaster modes. It is mainly divided into three steps: (1) Using FLO-2D numerical model, the risk of debris flow is expressed by intensity index IDF; The simulation results of debris flow in Gully A 7·11 show that the area of correctly judged area is 50.02×104m2, the comprehensive accuracy index ω is 1.22, and the maximum IDF can reach 1013.25m3/s2, showing a general trend that the upstream is higher than the downstream, and the center of the drainage channel is higher than both sides. Using the data of debris flow damage in A ditch 7·11 in A city, a material vulnerability curve based on the probability of exceeding loss is constructed. Based on the establishment of disaster-bearing body database, the expected loss of disaster-bearing body can be expressed quantitatively by setting different future debris flow scenarios. The model verification and case application of A ditch in A city show that the quantitative risk analysis system of debris flow can well reflect the response mechanism of disaster-bearing body and debris flow, and can provide scientific basis for disaster prevention and mitigation in debris flow threat areas.

A novel approach to ultra-short-term wind power prediction based on feature engineering and informer

Wind power is prone to dramatic fluctuations in the short term, posing a threat to the safety and stability of the grid, so accurate forecasting of ultra-short-term wind power is important to ensure the stability and economy of the power system. The historical data of wind power is an enormous and nonlinear time series. It is expected to mine the independent features related to wind power from the original data through feature engineering, and then use the Informer model to solve the prediction problem of long-time series of wind power, thus reducing the space complexity and improving the prediction accuracy. In this paper, Turkey wind farm data are selected to predict ultra-short-term wind power of 10 min based on feature engineering and the Informer model. First, factor data with a high correlation with wind power is formed after feature engineering. Then, train the Informer model and conduct multiple experiments to obtain the optimal parameters. Finally, the prediction results are compared with the recurrent neural network (RNN) model, the long-short-term memory (LSTM) model, and the Transformer model. The experimental results show that the Informer model has high prediction accuracy and operation efficiency. Four evaluation metrics of mean absolute error, mean square error, symmetric mean absolute percentage error, and runtime decreased by at least 32.849, 8495.193, 5.544%, and 92, which proves the approach based on feature engineering and Informer has prominent advantages in ultra-short-term wind power prediction. Its prediction results can provide a reference for the coordinated dispatching, risk analysis, and scientific decision-making of wind power systems.

Scalable risk assessment of large infrastructure systems with spatially correlated components

Risk assessment of spatially distributed infrastructure systems under natural hazards shall treat the performance of individual components as stochastically correlated due to the common engineering practice in the community including similarities in building design code, regulatory practices, construction materials, construction technologies, and the practices of local contractors. Modelling the spatially correlated damages of an infrastructure system with many components can be computationally expensive. This study addresses the scalability issue of risk analysis of large-scale systems by developing an interpolation technique. The basic idea is to sample a portion of components in the systems and evaluate their correlated damages accurately, while the damages of remaining components are interpolated from the sampled components. The new method can handle not only linear systems, but also systems with complex connectivity such as utility networks. Two examples are presented to demonstrate the proposed method, including cyclone loss assessment of the building portfolios in a virtual community, and connectivity analysis of an electric power system under a scenario cyclone event.

Systematic risk analysis of radiation pneumonitis in breast cancer: role of cotreatment with chemo-, endocrine, and targeted therapy

PurposeA major complication of sequential and concomitant chemoradiation in breast cancer treatment is interstitial pneumonitis induced by radiation therapy (RT), systemic therapy, or a combination of both. Dose and volume of co-irradiated lung tissue directly correlate with the risk of radiation pneumonitis. Especially in case of combined treatment, it is often unclear which of the used therapeutic agents promote pneumonitis.MethodsThis was a prospective monocentric study including 396 breast cancer patients. A systematic analysis of single and combined therapeutic measures was performed in order to identify treatment-related factors enhancing the risk of pneumonitis post RT.ResultsOverall incidence of pneumonitis of any grade was 38%; 28% were asymptomatic (grade 1) and 10% were symptomatic (> grade 1). Pneumonitis > grade 2 did not occur. Beside age, smoking status, and mean lung dose, the combined treatment with goserelin and tamoxifen significantly enhanced the risk of pneumonitis in a supra-additive pattern (odds ratio [OR] 4.38), whereas each agent alone or combined with other drugs only nonsignificantly contributed to a higher pneumonitis incidence post RT (OR 1.52 and OR 1.16, respectively). None of the other systemic treatments, including taxanes, increased radiation pneumonitis risk in sequential chemoradiation.ConclusionCommon treatment schedules in sequential chemoradiation following breast-conserving surgery only moderately increase lung toxicity, mainly as an asymptomatic complication, or to a minor extent, as transient pneumonitis ≤ grade 2. However, combined treatment with tamoxifen and the LHRH analog goserelin significantly increased the risk of pneumonitis in breast cancer patients after chemoradiation. Thus, closer surveillance of involved patients is advisable.

Mexico

"Volume 2022 (2022): Issue 359 (Dec 2022): Mexico: Financial Sector Assessment Program-Technical Note on Systemic Risk Analysis and Stress Testing" published on 08 Dec 2022 by International Monetary Fund.