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Journal articles on the topic 'Multi-Risks'

Author: Grafiati

Published: 25 May 2024

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1

Andersen, Per Kragh, Steen Z. Abildstrom, and Susanne Rosthøj. "Competing risks as a multi-state model." Statistical Methods in Medical Research 11, no. 2 (April 2002): 203–15. http://dx.doi.org/10.1191/0962280202sm281ra.

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2

Depietri, Yaella, Khila Dahal, and Timon McPhearson. "Multi-hazard risks in New York City." Natural Hazards and Earth System Sciences 18, no. 12 (December 21, 2018): 3363–81. http://dx.doi.org/10.5194/nhess-18-3363-2018.

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Abstract. Megacities are predominantly concentrated along coastlines, making them exposed to a diverse mix of natural hazards. The assessment of climatic hazard risk to cities rarely has captured the multiple interactions that occur in complex urban systems. We present an improved method for urban multi-hazard risk assessment. We then analyze the risk of New York City as a case study to apply enhanced methods for multi-hazard risk assessment given the history of exposure to multiple types of natural hazards which overlap spatially and, in some cases, temporally in this coastal megacity. Our aim is to identify hotspots of multi-hazard risk to support the prioritization of adaptation strategies that can address multiple sources of risk to urban residents. We used socioeconomic indicators to assess vulnerabilities and risks to three climate-related hazards (i.e., heat waves, inland flooding and coastal flooding) at high spatial resolution. The analysis incorporates local experts' opinions to identify sources of multi-hazard risk and to weight indicators used in the multi-hazard risk assessment. Results demonstrate the application of multi-hazard risk assessment to a coastal megacity and show that spatial hotspots of multi-hazard risk affect similar local residential communities along the coastlines. Analyses suggest that New York City should prioritize adaptation in coastal zones and consider possible synergies and/or trade-offs to maximize impacts of adaptation and resilience interventions in the spatially overlapping areas at risk of impacts from multiple hazards.

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3

Khan, Saleh, and Arvind Ashta. "Managing Multi-Faceted Risks in Microfinance Operations." Strategic Change 22, no. 1-2 (February 2013): 1–16. http://dx.doi.org/10.1002/jsc.1918.

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4

Bogdanov, K. "The Escalation Risks of Multi-Domain Battles." World Economy and International Relations 67, no. 4 (2023): 29–39. http://dx.doi.org/10.20542/0131-2227-2023-67-4-29-39.

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The outpacing development of doctrinal concepts of warfare at the present stage becomes an additional source of instability in the strategic landscape. Combined with the restructuring of the world order and the active introduction of emerging technologies, the development of new doctrines leads to increased escalation risks, including due to the poorly understood mutual influences of the operating factors in a complex environment. The Multi-Domain Battle theory is an excellent example of this impact. The article analyzes the main provisions of this theory in terms of potentially emerging escalation risks The problem is considered in the light of recent proposals for new escalation models, including the principles of the “escalation vortex” and the “wormhole escalation”. The emerging risks of applying doctrinal principles that blur distinct thresholds in the escalation space, including the thresholds of clearly distinguishing between war and peace, are analyzed. It shows a direct link between the Multi-Domain Battle theory and the concept of “integrated deterrence”, realized in the same logic of graded escalation control. A number of new emerging nuclear risks have been demonstrated, including links to long-standing theories of limited nuclear warfare options, as well as the new concept of the 2010s, the so-called “conventional-nuclear integration”. Conclusions are drawn about the need to implement a structured sequence of practical steps aimed at limiting the escalation risks generated by this doctrinal concept. A possible connection of this sequence with the longer-term task of rebuilding and strengthening the arms control framework has been established.

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5

Li, Xiaopeng, and Fuqiu Li. "Reliability Assessment of Space Station Based on Multi-Layer and Multi-Type Risks." Applied Sciences 11, no. 21 (November 1, 2021): 10258. http://dx.doi.org/10.3390/app112110258.

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A space station is a typical phased-mission system, and assessing its reliability during its configuration is an important engineering action. Traditional methods usually require extensive data to carry out a layered reliability assessment from components to the system. These methods suffer from lack of sufficient test data, and the assessment process becomes very difficult, especially in the early stage of the configuration. This paper proposes a reliability assessment method for the space station configuration mission, using multi-layer and multi-type risks. Firstly, the risk layer and the risk type for the space station configuration are defined and identified. Then, the key configuration risks are identified comprehensively, considering their occurrence likelihood and consequence severity. High load risks are identified through risk propagation feature analysis. Finally, the configuration reliability model is built and the state probabilities are computed, based on the probabilistic risk propagation assessment (PRPA) method using the assessment probability data. Two issues are addressed in this paper: (1) how to build the configuration reliability model with three layers and four types of risks in the early stage of the configuration; (2) how to quantitatively assess the configuration mission reliability using data from the existing operational database and data describing the propagation features. The proposed method could be a useful tool for the complex aerospace system reliability assessment in the early stage.

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6

Renner, Rebecca. "Predicting chemical risks with multi-media fate models." Environmental Science & Technology 29, no. 12 (December 1995): 556A—559A. http://dx.doi.org/10.1021/es00012a002.

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7

Vyzhitovich, Aleksandr. "Financial Management of Risks: Multi-Agency Investment Projects." Bulletin of Kemerovo State University. Series: Political, Sociological and Economic sciences 2022, no. 4 (December 8, 2022): 521–28. http://dx.doi.org/10.21603/2500-3372-2022-7-4-521-528.

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Effective risk management needs new approaches to risk analysis, especially in multi-agent investment projects. The article focuses on cluster projects currently active in the Novosibirsk Region, as well as on specific financial risks that occur between interacting organizations of various ownership forms. The author studied the assessment methodology for risks that develop as a result of unreliable or incomplete information, violation of state subsidies, their repayment, etc. The analysis of Novosibirsk clusters involved the Kontur. Focus software. The proposed methods included defining key parameters of the control model, procedures for input reliability check, a diagnostic methodology for project members, and integrating the effectiveness of the cluster control system. These approaches and methods can be included in a new integrated approach to the mesolevel risk management of multi-agent cluster projects as part of state and corporate control.

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8

Stewart, Mark G., and John Mueller. "Terrorism Risks for Bridges in a Multi-Hazard Environment." International Journal of Protective Structures 5, no. 3 (September 2014): 275–89. http://dx.doi.org/10.1260/2041-4196.5.3.275.

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9

Fu, Zhixuan, Shuangge Ma, Haiqun Lin, Chirag R. Parikh, and Bingqing Zhou. "Penalized Variable Selection for Multi-center Competing Risks Data." Statistics in Biosciences 9, no. 2 (October 31, 2016): 379–405. http://dx.doi.org/10.1007/s12561-016-9181-9.

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10

Jones-Berry, Stephanie. "Possible multi-year pay deal has opportunities – and risks." Nursing Standard 32, no. 24 (February 7, 2018): 12–14. http://dx.doi.org/10.7748/ns.32.24.12.s10.

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11

Knight, Andrew J., and Rex Warland. "Determinants of Food Safety Risks: A Multi-disciplinary Approach*." Rural Sociology 70, no. 2 (June 2005): 253–75. http://dx.doi.org/10.1526/0036011054776389.

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12

Putter, H., M. Fiocco, and R. B. Geskus. "Tutorial in biostatistics: competing risks and multi-state models." Statistics in Medicine 26, no. 11 (2007): 2389–430. http://dx.doi.org/10.1002/sim.2712.

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13

LEE, O. K. D., and D. V. BABY. "MANAGING DYNAMIC RISKS IN GLOBAL IT PROJECTS: AGILE RISK-MANAGEMENT USING THE PRINCIPLES OF SERVICE-ORIENTED ARCHITECTURE." International Journal of Information Technology & Decision Making 12, no. 06 (November 2013): 1121–50. http://dx.doi.org/10.1142/s0219622013400117.

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Risk management in global information technology (IT) projects is becoming a critical area of concern for practitioners. Global IT projects usually span multiple locations involving various culturally diverse groups that use multiple standards and technologies. These multiplicities cause dynamic risks through interactions among internal (i.e., people, process, and technology) and external elements (i.e., business and natural environments) of global IT projects. This study proposes an agile risk-management framework for global IT project settings. By analyzing the dynamic interactions among multiplicities (e.g., multi-locations, multi-cultures, multi-groups, and multi-interests) embedded in the project elements, we identify the dynamic risks threatening the success of a global IT project. Adopting the principles of service-oriented architecture (SOA), we further propose a set of agile management strategies for mitigating the dynamic risks. The mitigation strategies are conceptually validated. The proposed framework will help practitioners understand the potential risks in their global IT projects and resolve their complex situations when certain types of dynamic risks arise.

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14

Prakash, Surya, Gunjan Soni, and Ajay Pal Singh Rathore. "Multi-echelon closed-loop supply chain network design and configuration under supply risks and logistics risks." International Journal of Logistics Systems and Management 28, no. 1 (2017): 1. http://dx.doi.org/10.1504/ijlsm.2017.085882.

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Rathore, Ajay Pal Singh, Gunjan Soni, and Surya Prakash. "Multi-echelon closed-loop supply chain network design and configuration under supply risks and logistics risks." International Journal of Logistics Systems and Management 28, no. 1 (2017): 1. http://dx.doi.org/10.1504/ijlsm.2017.10006284.

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16

Cahyandari, Rini, Susan Kamelia, and Volodymyr Rusyn. "Multiobjective Optimization of Stock Portofolio." International Journal of Mathematics, Statistics, and Computing 2, no. 1 (February 1, 2024): 9–15. http://dx.doi.org/10.46336/ijmsc.v2i1.65.

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Diversification is a method used to reduce risks by allocating several financial, industrial, and other instruments. Investors might need to use this method to allocate their companies’ funding as efficient as they should be. Mean variance portfolio is a diversification theory designated for investors who are aware of potential risks. On the other hand, multi-objective portfolio optimization is another theory that suits for investors who are more unaware, or choose to neglect potential business risks. Multi-objective optimization can boost source of income and minimize the risks while utilizing k weighting coefficient as risk aversion index. This research aims to form an optimal portfolio from each perspective of selected investors using multi-objective optimization, as well as to analyze the benefits and risks that the investors will have. Samples used in this research are sharia stocks actively involved in Jakarta Islamic Index (JII) and non-sharia stocks which are actively involved in LQ-45 from January 2013 to January 2018.

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17

Lytvyn, Vasyl, and Ihor Rishnyak. "MODELING AND EVALUATION OF PROJECT RISKS IN MULTI-PROJECT ENVIRONMENT." Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska 4, no. 2 (June 18, 2014): 34–36. http://dx.doi.org/10.5604/20830157.1109370.

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18

Lu, Da-Yong, Peng-Peng Zhu, Ting-Ren Lu, and Jin-Yu Che. "The Suicidal Risks and Treatments, Seek Medications from Multi-disciplinary." Central Nervous System Agents in Medicinal Chemistry 16, no. 3 (October 6, 2016): 231–39. http://dx.doi.org/10.2174/1871524916666160210142734.

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19

Mittnik, Stefan, Willi Semmler, and Alexander Haider. "Climate Disaster Risks—Empirics and a Multi-Phase Dynamic Model." Econometrics 8, no. 3 (August 18, 2020): 33. http://dx.doi.org/10.3390/econometrics8030033.

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Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback effects on the macroeconomy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the former work to study disaster risks in the macroeconomics of climate change and to spell out policy needs. Empirically, the link between carbon dioxide emission and the frequency of climate related disaster is investigated using a panel data approach. The modeling part then uses a multi-phase dynamic macro model to explore the effects of rare large disasters resulting in capital losses and rising risk premia. Our proposed multi-phase dynamic model, incorporating climate-related disaster shocks and their aftermath as a distressed phase, is suitable for studying mitigation and adaptation policies as well as recovery policies.

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20

Barrieu, Pauline, and Giacomo Scandolo. "General Pareto Optimal Allocations and Applications to Multi-Period Risks." ASTIN Bulletin 38, no. 01 (May 2008): 105–36. http://dx.doi.org/10.2143/ast.38.1.2030405.

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In this paper, we consider the problem of Pareto optimal allocation in a general framework, involving preference functionals defined on a general real vector space. The optimization problem is equivalent to a modified sup-convolution of the different agents’ preference functionals. The results are then applied to a multi-period setting and some further characterization of Pareto optimality for an allocation is obtained for expected utility for processes.

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21

Ivanova, K. S., I. V. Zhuravlev, and Yu P. Stepin. "Multi-criteria risks evaluation and effectiveness of AGZK regional development." Problems of Economics and Management of Oil and Gas Complex, no. 11 (2021): 17–25. http://dx.doi.org/10.33285/1999-6942-2021-11(203)-17-25.

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22

Olivier, Timothée, Jenny Gill, and Vinay Prasad. "Multi-Cancer Screening Tests: Communicating About Risks Should be Prioritized." American Journal of Medicine 135, no. 4 (April 2022): 413–15. http://dx.doi.org/10.1016/j.amjmed.2021.09.012.

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23

Olivier, Timothée, Jenny Gill, and Vinay Prasad. "Multi-Cancer Screening Tests: Communicating About Risks Should be Prioritized." American Journal of Medicine 135, no. 4 (April 2022): 413–15. http://dx.doi.org/10.1016/j.amjmed.2021.09.012.

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24

Mittnik, Stefan, Willi Semmler, and Alexander Haider. "Climate Disaster Risks – Empirics and a Multi-Phase Dynamic Model." IMF Working Papers 19, no. 145 (July 11, 2019): 1. http://dx.doi.org/10.5089/9781498320849.001.

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Recent research in financial economics has shown that rare large disasters have the potential to disrupt financial sectors via the destruction of capital stocks and jumps in risk premia. These disruptions often entail negative feedback e?ects on the macroecon-omy. Research on disaster risks has also actively been pursued in the macroeconomic models of climate change. Our paper uses insights from the former work to study disaster risks in the macroeconomics of climate change and to spell out policy needs. Empirically the link between carbon dioxide emission and the frequency of climate re-lated disaster is investigated using cross-sectional and panel data. The modeling part then uses a multi-phase dynamic macro model to explore this causal nexus and the e?ects of rare large disasters resulting in capital losses and rising risk premia. Our proposed multi-phase dynamic model, incorporating climate-related disaster shocks and their aftermath as one phase, is suitable for studying mitigation and adaptation policies.

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25

Pukkala, Timo. "Multiple risks in multi-objective forest planning: integration and importance." Forest Ecology and Management 111, no. 2-3 (December 1998): 265–84. http://dx.doi.org/10.1016/s0378-1127(98)00339-9.

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26

Barrieu, Pauline, and Giacomo Scandolo. "General Pareto Optimal Allocations and Applications to Multi-Period Risks." ASTIN Bulletin 38, no. 1 (May 2008): 105–36. http://dx.doi.org/10.1017/s0515036100015087.

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In this paper, we consider the problem of Pareto optimal allocation in a general framework, involving preference functionals defined on a general real vector space. The optimization problem is equivalent to a modified sup-convolution of the different agents’ preference functionals. The results are then applied to a multi-period setting and some further characterization of Pareto optimality for an allocation is obtained for expected utility for processes.

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27

Horan, Richard D., David Finnoff, Kevin Berry, Carson Reeling, and Jason F. Shogren. "Managing Wildlife Faced with Pathogen Risks Involving Multi-Stable Outcomes." Environmental and Resource Economics 70, no. 3 (February 13, 2018): 713–30. http://dx.doi.org/10.1007/s10640-018-0227-y.

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28

Cagno, Enrico, Franco Caron, and Mauro Mancini. "A Multi-Dimensional Analysis of Major Risks in Complex Projects." Risk Management 9, no. 1 (January 22, 2007): 1–18. http://dx.doi.org/10.1057/palgrave.rm.8250014.

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29

Regős, Gábor. "Comparison of power plants’ risks with multi criteria decision models." Central European Journal of Operations Research 21, no. 4 (July 22, 2012): 845–65. http://dx.doi.org/10.1007/s10100-012-0257-4.

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30

Adam-M�ller, Axel F. A. "Exports and hedging exchange rate risks: the multi-country case." Journal of Futures Markets 20, no. 9 (2000): 843–64. http://dx.doi.org/10.1002/1096-9934(200010)20:9<843::aid-fut3>3.0.co;2-g.

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31

Faranosov, Vadim, Dmitry Surinsky, and Oleg Nikolsky. "Multi-criteria management of anthropogenic risks hazards of electrical installations." АгроЭкоИнфо 2, no. 56 (March 30, 2023): 13. http://dx.doi.org/10.51419/202132213.

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An approach to the construction of a decision support system (DSS) is considered, including object-oriented models and software tools using ontology – a model representing a computer form of a knowledge base (BZ) in the form of semantic (information-logical) networks. With the help of these networks, the interrelationships of components of a human-machine system with different physical nature (human, electrical installation, environment) are established. At the same time, ontologies perform an integral function, providing a general conceptual basis in decision-making processes in the subject area under consideration. Keywords: MAN-MACHINE SYSTEM, MAN-MADE FIRES, LEAKAGE CURRENTS IN ELECTRICAL INSTALLATIONS, THERMAL OVERLOAD

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32

GLAVAN, ALINA, DANIEL GHEORGHICA, and VICTOR CROITORU. "MULTI-ACCESS EDGE COMPUTING ANALYSIS OF RISKS AND SECURITY MEASURES." REVUE ROUMAINE DES SCIENCES TECHNIQUES — SÉRIE ÉLECTROTECHNIQUE ET ÉNERGÉTIQUE 68, no. 2 (July 3, 2023): 206–11. http://dx.doi.org/10.59277/rrst-ee.2023.68.2.15.

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5G efficiently uses technologies like network slicing (NS), network function virtualization (NFV), software-defined network (SDN), and multi-access edge computing (MEC). At the same time, embracing these technologies and creating new services opens the network to a new set of security challenges. This paper presents a threat analysis of MEC features. The paper's novelty resides in viewing MEC as common ground for the telco and IT sectors. This paper studies the measures according to ISO/IEC 27001:2022 controls. ISO/IEC 27001 is the most popular standard for information security management systems, with a new version published in 2022.

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33

Kizaki, Keisuke, Taiga Saito, and Akihiko Takahashi. "Equilibrium multi-agent model with heterogeneous views on fundamental risks." Automatica 160 (February 2024): 111415. http://dx.doi.org/10.1016/j.automatica.2023.111415.

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34

Gallina, Valentina, Silvia Torresan, Alex Zabeo, Andrea Critto, Thomas Glade, and Antonio Marcomini. "A Multi-Risk Methodology for the Assessment of Climate Change Impacts in Coastal Zones." Sustainability 12, no. 9 (May 2, 2020): 3697. http://dx.doi.org/10.3390/su12093697.

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Climate change threatens coastal areas, posing significant risks to natural and human systems, including coastal erosion and inundation. This paper presents a multi-risk approach integrating multiple climate-related hazards and exposure and vulnerability factors across different spatial units and temporal scales. The multi-hazard assessment employs an influence matrix to analyze the relationships among hazards (sea-level rise, coastal erosion, and storm surge) and their disjoint probability. The multi-vulnerability considers the susceptibility of the exposed receptors (wetlands, beaches, and urban areas) to different hazards based on multiple indicators (dunes, shoreline evolution, and urbanization rate). The methodology was applied in the North Adriatic coast, producing a ranking of multi-hazard risks by means of GIS maps and statistics. The results highlight that the higher multi-hazard score (meaning presence of all investigated hazards) is near the coastline while multi-vulnerability is relatively high in the whole case study, especially for beaches, wetlands, protected areas, and river mouths. The overall multi-risk score presents a trend similar to multi-hazard and shows that beaches is the receptor most affected by multiple risks (60% of surface in the higher multi-risk classes). Risk statistics were developed for coastal municipalities and local stakeholders to support the setting of adaptation priorities and coastal zone management plans.

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35

Khabibulin, Renat Shamil'yevich, and Denis Viacheslavovich Tarakanov. "Multi-criteria analysis of fire risks. A model of the quantitative importance of risks "one to many"." Technology of technosphere safety, no. 101 (2023): 105–13. http://dx.doi.org/10.25257/tts.2023.3.101.105-113.

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Introduction. The problem of management in the organizational system of fire safety is considered using a conceptual approach to formalize decision-making procedures based on the comprehensive minimization of fire risks. Practice shows that managerial decision-making when creating an effective fire protection system provides for contradictory situations when it is necessary to minimize several types of fire risks at the same time. At the same time, the preferred values of some risks cause less preferred values of other risks, which causes a contradiction. In the theory of decision-making, such a situation requires the development of special decision-making mechanisms based on additional information about the relative importance of fire risks. This work is devoted to the application of information about the relative importance of fire risks for management decision making. Goals and objectives. The study of formalized procedures for making managerial decisions in the organizational system of fire safety. Development of a model of the quantitative importance of fire risks "one to many" and the formation of proposals for its application in the process of managerial decision-making. Methods. The research uses methods of set-theoretic description of complex processes; the theory of the relative importance of criteria; methods for solving systems of linear equations - Kramer's method. Results and discussion. A model of accounting for the quantitative importance of fire risks has been developed and recommendations for its application in the process of managerial decision-making are given. Conclusion. The paper substantiates a conceptual approach to fire risk management in the development of a fire protection system using a multi-criteria model. A theoretical generalization of methods for constructing practice-oriented fire risk management technologies has been formed. A set-theoretic description of the decision-making process in fire risk management is carried out. A model of the relative importance of fire risks "one to many" has been developed. Practical recommendations on the application of a multi-criteria model in the process of making managerial decisions are given. Keywords: multicriteria analysis; selection criteria; fire risks; fire safety system.

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36

Yang, Xi, and Xiang Yu. "Preventing Patent Risks in Artificial Intelligence Industry for Sustainable Development: A Multi-Level Network Analysis." Sustainability 12, no. 20 (October 19, 2020): 8667. http://dx.doi.org/10.3390/su12208667.

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In recent years, assessing patent risks has attracted fast-growing attention from both researchers and practitioners in studies of technological innovation. Following the existing literature on risks and intellectual property (IP) risks, we define patent risks as the lack of understanding of the distribution of patents that lead to losing a key patent, increased research and development costs, and, potentially, infringement litigation. This paper aims to propose an explorative approach to investigating patent risks in the target technology field by integrating social network analysis and patent analysis. Compared to previous research, this study makes an important contribution toward identifying patent risks in the overall technological field by employing a patent-based multi-level network model that has not appeared in existing methodologies of patent risks. In order to verify the effectiveness of this approach, we take artificial intelligence (AI) as an example. Data collected from the Derwent Innovation Index (DII) database were used to build the patent-based multi-level network on patent risks from market, technology, and assignee perspectives. The results indicate that the lack of international collaborations among assignees and industry–university–research collaboration may lead to patent collaboration risks. Regarding patent market risks, the lack of overseas patent applications, especially the lack of distribution in the main competitive markets, is a key factor. As for patent technology risks, most of the leading assignees lack awareness of the distribution in the following technological fields: industrial electric equipment, engineering instrumentation, and automotive electrics. In summary, assignees from the U.S. with first mover advantages are still powerful leaders in the AI technology field. Although China is catching up very rapidly in the total number of AI patents, the apparent patent risks under the perspectives of collaboration, market, and technology will obviously hamper the catch-up efforts of China’s AI industry. We conclude that, in practice, the proposed patent-based multi-level network model not only plays an important role in helping stakeholders in the AI technological field to prevent patent risks, find new technology opportunities, and obtain sustainable development, but also has significance for guiding the industrial development of various emerging technology fields.

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37

Wu, Weitiao, Jian Ma, Ronghui Liu, and Wenzhou Jin. "Multi-class hazmat distribution network design with inventory and superimposed risks." Transportation Research Part E: Logistics and Transportation Review 161 (May 2022): 102693. http://dx.doi.org/10.1016/j.tre.2022.102693.

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38

Kim, Hyun Sik, and Doo-Sub Kim. "Adolescents of Multi-Cultural Families and Differential Risks of Suicidal Behaviors." Korean Journal of Sociology 48, no. 2 (April 30, 2014): 35. http://dx.doi.org/10.21562/kjs.2014.04.48.2.35.

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39

Kim, Hyun Sik. "Differential Risks of Juvenile Delinquency Among Adolescents of Multi-Cultural Families." Korean Journal of Sociology 50, no. 1 (February 29, 2016): 41. http://dx.doi.org/10.21562/kjs.2016.02.50.1.41.

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40

Lv, Zitong, JunShen Wang, Shaozhen Chen, Bo Wang, and Ke Yang. "Application of Multi-Modal Biometrics in Financial Risks Prevention and Controls." IOP Conference Series: Earth and Environmental Science 252 (July 9, 2019): 032032. http://dx.doi.org/10.1088/1755-1315/252/3/032032.

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41

Fang, Chen, and Lirong Cui. "Balanced Systems by Considering Multi-state Competing Risks Under Degradation Processes." Reliability Engineering & System Safety 205 (January 2021): 107252. http://dx.doi.org/10.1016/j.ress.2020.107252.

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42

Isemonger, Alan G. "The Benefits and Risks of Virtual Bidding in Multi-Settlement Markets." Electricity Journal 19, no. 9 (November 2006): 26–36. http://dx.doi.org/10.1016/j.tej.2006.09.010.

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43

Selva, Jacopo. "Long-term multi-risk assessment: statistical treatment of interaction among risks." Natural Hazards 67, no. 2 (March 5, 2013): 701–22. http://dx.doi.org/10.1007/s11069-013-0599-9.

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44

Bowen, Kathryn J., and Kristie L. Ebi. "Governing the health risks of climate change: towards multi-sector responses." Current Opinion in Environmental Sustainability 12 (February 2015): 80–85. http://dx.doi.org/10.1016/j.cosust.2014.12.001.

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Taillandier, Franck, Patrick Taillandier, Esra Tepeli, Denys Breysse, Rasool Mehdizadeh, and Fadi Khartabil. "A multi-agent model to manage risks in construction project (SMACC)." Automation in Construction 58 (October 2015): 1–18. http://dx.doi.org/10.1016/j.autcon.2015.06.005.

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Mangwana, Sadhana, Atin Kacker, and Nikhil Simon. "Red cell alloimmunization in multi-transfused, oncology patients: Risks and management." Global Journal of Transfusion Medicine 4, no. 1 (2019): 74. http://dx.doi.org/10.4103/gjtm.gjtm_11_19.

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AOTANI, Takumi, Taisuke KOBAYASHI, and Ryuta OZAWA. "Punishment Shaping Algorithm for Multi-Agent Reinforcement Learning with Primitive Risks." Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec) 2023 (2023): 1P1—F22. http://dx.doi.org/10.1299/jsmermd.2023.1p1-f22.

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Acharya, Sandeep, Shu Liao, Woo Seok Jung, Edward Kang, Vaha Akbary Moghaddam, Mary Feitosa, Michael Province, and Michael Brent. "MULTI-OMICS INTEGRATION IDENTIFIES GENES INFLUENCING TRAITS ASSOCIATED WITH CARDIOVASCULAR RISKS." Innovation in Aging 7, Supplement_1 (December 1, 2023): 1084. http://dx.doi.org/10.1093/geroni/igad104.3482.

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Abstract The Long Life Family Study (LLFS) enrolled 4,953 participants in 539 pedigrees displaying exceptional longevity. To identify genetic mechanisms that protect LLFS participants against age-related cardiovascular risks, we developed a freely available multi-omics integration pipeline and applied it to 11 traits associated with cardiovascular risks. Using our pipeline, we aggregated gene-level statistics from Rare-Variant Analysis, GWAS, and gene expression-trait association by Correlated Meta-Analysis (CMA). Across all traits, CMA identified 51 significant genes after Bonferroni correction (P ≤ 2.8×10-7). CETP, NLRC5, SLC45A3, and TOMM40 lie within 50 Kb of a known trait-associated variant (previously associated genes). Analysis of protein-protein interaction (PPI) networks identified another 63 genes (passing genes) that (1) have CMA p-value ≤ 5×10-3, (2) lie in a PPI module (highly connected subnetwork) enriched for genes with low P-values, and (3) are annotated with a biological process that is enriched among module genes, ten of which were previously associated with the same traits. Permutation analysis showed that passing genes have a false positive rate of 1 in 14876 and are more likely to be previously known than non-passing genes with similar p-values. CMA improved on the 3 input analyses by producing the largest number of modules enriched for genes with low P-values and highly enriched for genes participating in shared biological processes. Overall, module analysis identified highly plausible candidate causal genes whose P-values after CMA alone were merely suggestive.

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Moura, Josely Pinto de, and Elucir Gir. "Nursing staff knowledge of multi-resistant bacterial infections." Acta Paulista de Enfermagem 20, no. 3 (September 2007): 351–56. http://dx.doi.org/10.1590/s0103-21002007000300018.

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OBJECTIVE: To assess professional nurses', associate degree prepared nurses', licensed practical nurses', and nursing assistants' knowledge of the causes of multi-resistant bacterial infections, the risks theses infections pose to health care providers, the chain of transmission of these infections, and patients' susceptibility to colonization of these multi-resistant bacterial infections. METHODS: This descriptive study was conducted in a major general hospital in Minas Gerais, Brazil. The sample consisted of 42 nursing staff from a medical clinical unit. Descriptive statistics were used to analyze and present the data. RESULTS: Nursing staff had unsatisfactory knowledge of the causes of multi-resistant bacterial infections, the chain of transmission of multi-resistant bacterial infections, and patients' susceptibility to colonization of multi-resistant bacterial infections. However, the majority of participants had some knowledge about the risks that multi-resistant bacterial infections posed to health care providers. CONCLUSION: Lack of knowledge among nursing staff compromise adherence to preventive measures and nursing management of multi-resistant bacterial infections.

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Брежнев, Евгений Витальевич, Владислав Вячеславович Бородавка, and Ренат Витальевич Салахов. "РАЗРАБОТКА МЕТОДА НЕЧЕТКОГО ОЦЕНИВАНИЯ РИСКОВ КИБЕРБЕЗОПАСНОСТИ ТРАНСПОРТНЫХ СРЕДСТВ." Radioelectronic and Computer Systems, no. 1 (January 10, 2017): 28–35. http://dx.doi.org/10.32620/reks.2017.1.03.

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Proposed cyber security risk assessment method for vehicles, which is based on the use of multi-level fuzzy output (Multi Fuzzy Inference System - MFIS), which allows to reduce the requirements to the completeness of statistical data characterizing the individual elements of the model (threats, risks, assets, etc.) and get fuzzy evaluation cyber security risks of vehicles, to predict the effects of the mutual influence of the system components, as well as to form a plurality of countermeasures aimed at increasing cyber security. The method is based on the model of threats and risks, taking into account the interaction between risk assets and countermeasures, as well as between the vehicle nodes and risk factors

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