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Journal articles on the topic 'Risk assessment - Mathematical models'

Author: Grafiati

Published: 4 June 2021

Last updated: 26 January 2023

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1

Park, Colin N. "Mathematical models in quantitative assessment of carcinogenic risk." Regulatory Toxicology and Pharmacology 9, no. 3 (June 1989): 236–43. http://dx.doi.org/10.1016/0273-2300(89)90062-7.

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2

De Wrachien, D., and S. Mambretti. "Mathematical models for flood hazard assessment." International Journal of Safety and Security Engineering 1, no. 4 (December 31, 2011): 353–62. http://dx.doi.org/10.2495/safe-v1-n4-353-362.

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3

Kodell, Ralph L. "The use of mathematical models in carcinogenesis risk assessment." Mathematical and Computer Modelling 11 (1988): 146–51. http://dx.doi.org/10.1016/0895-7177(88)90470-0.

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Сычев, Михаил, Mikhail Sychev, Владимир Минаев, Vladimir Minaev, Александр Фаддеев, and Aleksandr Faddeev. "Seismic risk assessment in tourist-recreational areas: mathematical models." Servis Plus 9, no. 2 (June 15, 2015): 25–34. http://dx.doi.org/10.12737/11309.

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The article highlights the problem of evaluation of seismic risks in the tourism and recreational areas. To this end, the grounded and practically being tested mathematical model for evaluating the seismic stability of tourist-recreational area on the example of the Black Sea, the Caspian and the Mediterranean region. This model combines the influences of disturbances associated with the anomalous gravity field (vertical component), and takes into account modern crustal movements (horizontal component), calculated according to the space geodesy. The physical model of the geological environment

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5

Euhus, David M. "Understanding Mathematical Models for Breast Cancer Risk Assessment and Counseling." Breast Journal 7, no. 4 (July 2001): 224–32. http://dx.doi.org/10.1046/j.1524-4741.2001.20012.x.

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6

Seigneur, Christian, Akula Venkatram, Don Galya, Paul Anderson, David Liu, Donna Foliart, Rudolph von Burg, Yoram Cohen, Thomas Permutt, and Leonard Levin. "Review of mathematical models for health risk assessment: I. Overview." Environmental Software 7, no. 1 (January 1992): 3–7. http://dx.doi.org/10.1016/0266-9838(92)90018-y.

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7

Seigneur, Christian. "Review of mathematical models for health risk assessment: VI. population exposure." Environmental Software 9, no. 2 (January 1994): 133–45. http://dx.doi.org/10.1016/0266-9838(94)90005-1.

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Liu, David. "Review of mathematical models for health risk assessment: VII. chemical dose." Environmental Software 9, no. 3 (January 1994): 153–60. http://dx.doi.org/10.1016/0266-9838(94)90027-2.

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Zirka, Andrii, Mariia Zirka, and Natalia Kadet. "FEATURES OF RISK ASSESSMENT IN THE CREATION OF UAV FOR VARIOUS PURPOSES." Science-based technologies 51, no. 3 (October 28, 2021): 193–204. http://dx.doi.org/10.18372/2310-5461.51.15994.

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One of the perspective directions of the development to modern aviation is connected with designing and producing unmanned aerial vehicles (UAV) of various functionalities for applying in military and civilian spheres. The syntheses of UAV control systems, regardless of their type and purpose presumes the creation of adequate mathematical models, first of all adequate aerodynamic mathematical models. In the paper results that forms and justify the aerodynamic mathematical model and as well as the results of building a general mathematical model of the longitudinal movement of the perspective U

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Minaev, V. A., N. G. Topolsky, A. O. Faddeev, R. O. Stepanov, and D. S. Grachev. "Risk assessment models with functionally different influences on natural and technical systems." Technology of technosphere safety 89 (2020): 8–19. http://dx.doi.org/10.25257/tts.2020.3.89.8-19.

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Introduction. The complex combination of natural and technogenic factors that lead to dangerous threats to the health and life of the population, as well as to material values, creates a need to develop special mathematical models for risk assessment in the relevant territories. Herewith it is important to take into account the significant differences between these factors. The new areas of research are models that describe natural and technogenic risks using differential equations that reflect different types of functions. The article presents the development of this research area. Goals and

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Kostyuchenko, Mikhail, Volodymyr Gogo, Boris Kobilyansky, Oleg Kruzhilko, Ihor Yefremov, Kyrylo Hriadushchyi, and Oleksandr Tkachuk. "ANALYSIS OF PRODUCTION RISK ON EXAMPLES OF MINERS ‘LABOR." JOURNAL of Donetsk Mining Institute, no. 2 (2021): 159–75. http://dx.doi.org/10.31474/1999-981x-2021-2-159-175.

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Objective: Based on the review of the array of publications to analyze the methods and models of general risk assessment, the nature of industrial risks and management processes on the examples of labor of coal miners. Propose a classification of mathematical models of industrial risk and identify the most appropriate model for the work of miners in the stochastic system “man-machine-environment”. Methodology: Applied to the use of situational analysis, qualimetry, probability theory and risk theory, methods of classification of occupational risks. Results: Based on a systematic analysis of mu

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12

Brannigan, Vincent, and Carol Meeks. "Computerized Fire Risk Assessment Models: A Regulatory Effectiveness Analysis." Journal of Fire Sciences 13, no. 3 (May 1995): 177–96. http://dx.doi.org/10.1177/073490419501300302.

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Computerized Fire Risk Assessment Models have been proposed for regulatory use. The models normally are used to examine alternative designs to determine whether they are equivalent to standard code approved Structures. However, mathematical equivalence in a model may not constitute social or technical equivalence, if the assumptions and methods used in the model are not property specified. Regulatory Effectiveness Analysis is a tool which can be used to determine whether the model satisfies the regulator's legal requirements, and whether it is properly responsive to public judgments of fire sa

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13

Minaev, V. A., R. O. Stepanov, and A. O. Faddeev. "Problem of Mathematical Model Adequacy in Assessing the Seismic Risk." Herald of the Bauman Moscow State Technical University. Series Instrument Engineering, no. 4 (137) (December 2021): 93–108. http://dx.doi.org/10.18698/0236-3933-2021-4-93-108.

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The problem of mathematical models' adequacy in assessing seismic risk is considered. It is demonstrated that the currently used methods of testing such models make it possible to assess only the consistency of simulation and real data by counting the number of earthquake epicenters that appear in the areas with increased values of the fields with various indicators. The paper proposes a fundamentally new approach to testing adequacy of the seismic risk assessment models based on examining statistical hypotheses. Application of this approach is considered in a seismic risk assessment model for

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14

Ivanyo, Yaroslav, Nina Fedurina, and Zhanna Varanitsa-Gorodovskaya. "Mathematical models of agricultural production management in high risk environments." E3S Web of Conferences 222 (2020): 01018. http://dx.doi.org/10.1051/e3sconf/202022201018.

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The paper presents an algorithm for modeling the production of agricultural products in the formation of agrometeorological events. Stochastic models of variability of downpours, early snow-fall and crop yields are constructed to assess the likelihood of extreme events. Based on a probabilistic assessment of crop bio-productivity by a normative method, economic losses from agrometeorological events are determined. A model for optimizing crop production taking into account natural risks was built and implemented for an agricultural organization. The results were obtained according to data of th

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15

Shuryak, Igor. "Enhancing low-dose risk assessment using mechanistic mathematical models of radiation effects." Journal of Radiological Protection 39, no. 4 (September 27, 2019): S1—S13. http://dx.doi.org/10.1088/1361-6498/ab3101.

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16

Ryan, Patrick. "Review of mathematical models for health risk assessment: IV. Intermedia chemical transport." Environmental Software 8, no. 3 (January 1993): 157–72. http://dx.doi.org/10.1016/0266-9838(93)90012-7.

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17

Venkatram, Akula, and Christian Seigneur. "Review of mathematical models for health risk assessment: II. Atmospheric chemical concentrations." Environmental Software 8, no. 2 (1993): 75–90. http://dx.doi.org/10.1016/0266-9838(93)90018-d.

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18

Brown, Stephen L., and Brad Schwab. "Review of mathematical models for health risk assessment: VIII. dose/response relationships." Environmental Software 9, no. 3 (January 1994): 161–74. http://dx.doi.org/10.1016/0266-9838(94)90028-0.

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19

Gosling, John Paul. "Harnessing mathematical models and uncertainty in toxicological risk assessments." Toxicology Letters 229 (September 2014): S160. http://dx.doi.org/10.1016/j.toxlet.2014.06.551.

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20

Sivakova, Lenka, Anna Zubkova, and Witalis Pellowski. "Application of a Priori and a Posteriori Estimate on Risk Assessment." Communications - Scientific letters of the University of Zilina 20, no. 2 (June 30, 2018): 56–61. http://dx.doi.org/10.26552/com.c.2018.2.56-61.

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The problem of setting the values and interconnections between elements of the models in the safety, protection and security field, appears as the biggest obstacle in taking crisis management decisions. The article attempts to represent a mathematical approach to modify the expected values and interconnections that can occur in the models describing the protected system in order to minimize errors caused by subjectivity. Here presented procedures are described in the examples of their potential use. The main idea is to focus on improving estimates for better response to reality, then to find n

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21

Kodell, Ralph L. "Bioassay Designs for Validating Biologically Based Mathematical Models of Carcinogenesis for Risk Assessment." Drug Metabolism Reviews 28, no. 1-2 (January 1996): 219–23. http://dx.doi.org/10.3109/03602539608994001.

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22

Brandt, Jan-M., Márton Benedek, Jeffrey S. Guerin, and Jörg Fliege. "Reliability-as-a-Service for bearing risk assessment investigated with advanced mathematical models." Internet of Things 11 (September 2020): 100178. http://dx.doi.org/10.1016/j.iot.2020.100178.

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23

Fasching, Peter A., Mayada R. Bani, Carolin Nestle-Krämling, Tim O. Goecke, Dieter Niederacher, Matthias W. Beckmann, and Michael P. Lux. "Evaluation of mathematical models for breast cancer risk assessment in routine clinical use." European Journal of Cancer Prevention 16, no. 3 (June 2007): 216–24. http://dx.doi.org/10.1097/cej.0b013e32801023b3.

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24

Minasyan, V. В. "Risk Assessment Models of the Companies Implementing R&D Projects." Finance: Theory and Practice 23, no. 1 (February 27, 2019): 133–46. http://dx.doi.org/10.26794/2587-5671-2019-23-1-133-146.

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Companies implementing R&D projects face their unique features. There is the need for large capital investments, long-term implementation, high growth potential, low probability of success, and diffculties in fnancing among them. Implementation of such projects is associated with high risks. This leads to underfunding as uncertain results deter investors. The problem of assessing the risks arising from the implementation of such projects has not yet been suffciently studied at the level of mathematical analysis models. The objective of the article is to develop a model allowing to explore

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25

Rozhina, Viktoria D. "CREDIT RISK ASSESSMENT MODELS AT THE BEHAVIOR-SCORING STAGE." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 7/1, no. 127 (2022): 128–40. http://dx.doi.org/10.36871/ek.up.p.r.2022.07.01.013.

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Credit risk management is one of the most important tasks in banking risk management. Credit risk is the possibility of financial losses if the borrower fails to fulfill its obligations in a timely manner and in full, in particular as a result of a delay or non-repayment of a payment on a banking product. This article is devoted to the search for optimal methods for assessing the main component of the credit risk model - the probability of default of the borrower (PD) at the stage of building behavioral models. The paper considers two blocks of mathematical models - quantitative and classifica

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26

Purchase, I. F. H. "Risk assessment. Principles and consequences." Pure and Applied Chemistry 72, no. 6 (January 1, 2000): 1051–56. http://dx.doi.org/10.1351/pac200072061051.

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Risk assessment is an important tool in deciding how to allocate resources to controlling risks. In most cases it is based on hazard data derived from animal experiments and on exposure data from an assessment of the likely or actual exposure of the population of interest. Recent advances have improved the understanding of the use of the no adverse effect level (NOAEL) and safety factor for risk assessment by providing a scientific justification of the 100-fold safety factor. Concern about the risks of exposure by various routes simultaneously (aggregate exposure) and the risks of exposure to

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27

Gavaghan, David, Alan Garny, Philip K. Maini, and Peter Kohl. "Mathematical models in physiology." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 364, no. 1842 (March 22, 2006): 1099–106. http://dx.doi.org/10.1098/rsta.2006.1757.

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Computational modelling of biological processes and systems has witnessed a remarkable development in recent years. The search-term ( modelling OR modeling ) yields over 58 000 entries in PubMed, with more than 34 000 since the year 2000: thus, almost two-thirds of papers appeared in the last 5–6 years, compared to only about one-third in the preceding 5–6 decades. The development is fuelled both by the continuously improving tools and techniques available for bio-mathematical modelling and by the increasing demand in quantitative assessment of element inter-relations in complex biological sys

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28

Ge, Hui Lin, Shu Shen Liu, Bing Xia Su, and Zhi Xu. "Mathematical Derivation of Concentration Addition, Independent Action and Effect Summation Models." Applied Mechanics and Materials 361-363 (August 2013): 1054–57. http://dx.doi.org/10.4028/www.scientific.net/amm.361-363.1054.

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The assessment of the combined effects of substances is usually based on concentration addition (CA), independent action (IA) or effect summation (ES) models. Both concepts are founded on different modes of actions of substances, but the knowledge about their relationship is rare. In this paper, we derived a series of inequalities for CA, IA and ES models, and proposed two novel models i.e., ES with the exponent e (ESE) model and ES with the power of the number of components n (ESN) model to evaluate the mixture effect. Our results may have certain significance in mixture risk assessment pract

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29

Victorov, Alexey, and Veronika Kapralova. "RISK ASSESSMENT BASED ON MATHEMATICAL MORPHOLOGY OF LANDSCAPE MODELS (CASE STUDY OF THERMOKARST PLAINS)." GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 6, no. 2 (June 1, 2013): 63–71. http://dx.doi.org/10.24057/2071-9388-2013-6-2-63-71.

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30

Victorov, Alexey, and Veronika Kapralova. "RISK ASSESSMENT BASED ON MATHEMATICAL MORPHOLOGY OF LANDSCAPE MODELS (CASE STUDY OF THERMOKARST PLAINS)." GEOGRAPHY, ENVIRONMENT, SUSTAINABILITY 6, no. 2 (June 14, 2013): 63–71. http://dx.doi.org/10.15356/2071-9388_02v06_2013_06.

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31

BROWN, MARTYN H., KENNETH W. DAVIES, CHRISTELLE M. P. BILLON, CAROL ADAIR, and PETER J. McCLURE. "Quantitative Microbiological Risk Assessment: Principles Applied to Determining the Comparative Risk of Salmonellosis from Chicken Products." Journal of Food Protection 61, no. 11 (November 1, 1998): 1446–53. http://dx.doi.org/10.4315/0362-028x-61.11.1446.

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Ensuring microbiological safety requires identification of realistic hazards and the means of controlling them. The risk assessment framework proposed by Codex Alimentarius allows the impact of raw materials and processes to be appreciated, and the output can be used for risk management and communication. Mathematical models allow numerical information to be processed by a Computer and interpreted to give quantitative or comparative risk assessments. In this example, models have been put together according to the Codex Alimentarius principles, providing a quantitative risk assessment (QRA) of

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32

Mitrovic, S., and V. P. Suits. "A methodology for applying modern information technologies in the economic analysis of organization's risks." Economic Analysis: Theory and Practice 19, no. 2 (February 28, 2020): 268–85. http://dx.doi.org/10.24891/ea.19.2.268.

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Subject. The article examines theoretical, methodological and practical aspects of applying modern methods and information technologies to improve the economic risk analysis of organizations. Special attention is focused on internal audit and control, in particular, on the self-assessment procedure, being an innovative tool for monitoring and assessing risks to identify and minimize them within the corporate governance system. Objectives. The purpose is to study possibilities for improving the methodology for economic risk analysis of organizations through modern information technologies, inno

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33

Lovell, David P., and Gail Thomas. "Quantitative risk assessment and the limitations of the linearized multistage model." Human & Experimental Toxicology 15, no. 2 (February 1996): 87–104. http://dx.doi.org/10.1177/096032719601500201.

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1 Quantifying carcinogenic risk is an important objec tive for assisting in the assessment and management of risks from chemical exposure. The most widely used ofthe many mathematical models proposed for extrapolation of carcinogenicity data from animal studies to low dose human exposures is the linearized multistage (LMS) model. This has, in effect, become the default approach for much of Quantitative Risk Assessment (QRA). The practical properties of this model have been investigated. 2 Analysis of simulated data using the LMS model showed (i) that the Maximum Likelihood Estimate (MLE) of th

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34

Kruzhilko, O., N. Volodchenkova, V. Maystrenko, B. Bolibrukh, V. Kalinchyk, A. Zakora, A. Feshchenko, and S. Yeremenko. "Mathematical modelling of professional risk at Ukrainian metallurgical industry enterprises." Journal of Achievements in Materials and Manufacturing Engineering 1, no. 108 (September 1, 2021): 35–41. http://dx.doi.org/10.5604/01.3001.0015.4797.

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Purpose: To develop a more advanced methodology, the application of which will provide an informational and computational and analytical basis for planning and implementing effective preventive measures aimed at minimizing occupational risks with limited resources, as well as in the absence of organizational and technical capabilities to create absolutely safe working conditions Design/methodology/approach: For the study, statistical data were used that obtained from enterprises of the metallurgical industry of Ukraine. Research methods: analysis and generalization of known scientific results,

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35

Orlov, A. I. "Mathematical methods for studying risks (resumptive article)." Industrial laboratory. Diagnostics of materials 87, no. 11 (November 21, 2021): 70–80. http://dx.doi.org/10.26896/1028-6861-2021-87-11-70-80.

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We define risk as an unwanted opportunity and divide risk theory into three stages — risk analysis, risk estimation, risk management. Safety and risk are directly related to each other, being like a «mirror image» of each other which necessitates developing both the general theory of risk and particular theories of risk in specific areas. General risk theory allows for a uniform approach to the analysis, estimation and management of risks in specific situations. Currently, three main approaches to accounting for the uncertainty and describing risks are used — probabilistic and statistical appr

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36

Singh, Amrik, and K. R. Ramkumar. "Risk assessment for health insurance using equation modeling and machine learning." International Journal of Knowledge-based and Intelligent Engineering Systems 25, no. 2 (July 26, 2021): 201–25. http://dx.doi.org/10.3233/kes-210065.

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Due to the advancement of medical sensor technologies new vectors can be added to the health insurance packages. Such medical sensors can help the health as well as the insurance sector to construct mathematical risk equation models with parameters that can map the real-life risk conditions. In this paper parameter analysis in terms of medical relevancy as well in terms of correlation has been done. Considering it as ‘inverse problem’ the mathematical relationship has been found and are tested against the ground truth between the risk indicators. The pairwise correlation analysis gives a stabl

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37

Tymchuk, Oleg, Maryna Iepik, and Artyom Sivyakov. "Information Security Risk Assessment Model Based on Computing with Words." MENDEL 23, no. 1 (June 1, 2017): 119–24. http://dx.doi.org/10.13164/mendel.2017.1.119.

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The basis for company IT infrastructure security is information security risks assessment of IT services. The increased complexity, connectivity and rapid changes occurring in IT services make it impossible to apply traditional models of quantitative/qualitative risk assessment. Existing quantitative assessment models are time-consuming, at the same time, qualitative assessment models do not take into account the subjective expert assessments and the uncertainty of risk factors. This paper presents the new information security risk assessment model for IT services based on computing with words

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38

Giordano, Marie, Rebecca Zale, Betsy Ruffle, Elizabeth Hawkins, and Paul Anderson. "Review of mathematical models for health risk assessment: V. chemical concentrations in the food chain." Environmental Software 9, no. 2 (January 1994): 115–31. http://dx.doi.org/10.1016/0266-9838(94)90004-3.

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39

Jin, Peng Kang, Xing Wang Ning, Xin Jin, and Xian Bao Wang. "Health Risk Assessment of Wastewater with Carbinol in Gas Field." Applied Mechanics and Materials 178-181 (May 2012): 424–28. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.424.

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The carbinol in wastewater from inhalation and direct contact present more risk to human health, as well as cause hazard to ecological environment through waste water emission directly and soil infiltration. In this paper, health risk assessment of wastewater with carbinol in gas field is performed using mathematical models of non-carcinogenic health risk assessment. The results show that the non-carcinogenic health risks caused by wastewater with carbinol are in the range of 6.33×10-5 to 9.20×10-5, which are much higher than the acceptable risk level 7.00×10-5. Through the calculation of the

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Mikhalevich, V. S., P. S. Knopov, and A. N. Golodnikov. "Mathematical models and methods of riks assessment in ecologically hazardous industries." Cybernetics and Systems Analysis 30, no. 2 (March 1994): 259–73. http://dx.doi.org/10.1007/bf02366429.

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Fu, Hui, Yahong Zhang, Rama Subbareddy, and Thanjai Vadivel. "Mathematical modeling on workplace violence hazard assessment and security analysis using Optimized Grey Dynamic System Theory." Work 68, no. 3 (March 26, 2021): 835–43. http://dx.doi.org/10.3233/wor-203417.

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BACKGROUND: Employers must provide their workers with a safe working environment. Violence at the workplace is considered to pose risks for mental health. However, it is rarely investigated whether or not violence at the workplace in a setting can further increase the risk of mental disorders among employees. Risk assessment of workplace violence is still a major challenge for law enforcement, mental health, and other professionals. These critical and specific evaluations need an innovative approach. OBJECTIVES: In this paper, the Optimized Grey Dynamic System Theory (OGDST) is used to analyze

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42

Wang, Shun Qing, and Hai Yan Chen. "Research on Information Security Risk Assessment Based on Discrete Dynamic Bayesian Network." Applied Mechanics and Materials 608-609 (October 2014): 295–99. http://dx.doi.org/10.4028/www.scientific.net/amm.608-609.295.

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Being important in the field of information security, it is essential to study the major process and the mathematical models of information security risk assessment.This paper proposed amodel based on the discrete dynamic Bayesian network and further studied the major process of the assessment.The experiment which works on the implementing platform shows the results are reasonable and feasible. The model proves that it iseffective to calculate the probability of the risk.

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COSER, ALEXANDRU, MONICA MIHAELA MAER-MATEI, and CRISAN ALBU. "Predictive Models for Loan Default Risk Assessment." ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH 53, no. 2/2019 (June 16, 2019): 149–65. http://dx.doi.org/10.24818/18423264/53.2.19.09.

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44

Kazaryan, R., N. Galaeva, R. Avetisyan, and Sh Aliev. "Building lifecycle management based on 4D modelling as the main workspace for building risk assessment." E3S Web of Conferences 224 (2020): 02023. http://dx.doi.org/10.1051/e3sconf/202022402023.

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The use of information technology in the management of construction projects has become a decisive factor for the successful completion of projects, taking into account time, quality and financial costs. There are challenges in visualizing the planning process and integrating information between stakeholders. The paper considers some aspects of the development trend of information technology in construction. The element base, including the risks arising during the design and construction, associated with the direct use of computer and mathematical models of the object in the design is consider

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Atoyev, Konstantin, and Pavel Knopov. "Assessment of Environmental, Social, Governance and Technogenic Components of Investment Risks." Cybernetics and Computer Technologies, no. 3 (November 29, 2022): 37–45. http://dx.doi.org/10.34229/2707-451x.22.3.4.

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Introduction. To assess the investment attractiveness (IA) and development opportunities for investment objects (IO), non-financial factors characterizing the environmental, social, governance and technogenic (ESGT) features of objects of possible financing have been increasingly used recently. The purpose of this data analysis is to establish how the ESGT-parameters of IO may reflect their financial health and performance prospects in a rapidly changing world. Having built an ESGT risk profile with the help of mathematical models, the IA of the object of study and the strategy of practical me

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46

Cheng, Jianwei, Xixi Zhang, and Apurna Ghosh. "Explosion risk assessment model for underground mine atmosphere." Journal of Fire Sciences 35, no. 1 (December 14, 2016): 21–35. http://dx.doi.org/10.1177/0734904116676495.

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In the coal mining industry, explosions or mine fires present the most hazardous safety threats for coal miners or mine rescue members. Hence, the determination of the mine atmosphere explosibility and its evolution are critical for the success of mine rescues or controlling the severity of a mine accident. However, although there are numbers of methods which can be used to identify the explosibility, none of them could well indicate the change to the explosion risk time evolution. The reason is that the underground sealed atmospheric compositions are so complicated and their dynamical changes

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Del Ponte, Emerson M., Cláudia V. Godoy, Marcelo G. Canteri, Erlei M. Reis, and X. B. Yang. "Models and applications for risk assessment and prediction of Asian soybean rust epidemics." Fitopatologia Brasileira 31, no. 6 (December 2006): 533–44. http://dx.doi.org/10.1590/s0100-41582006000600001.

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Asian rust of soybean [Glycine max (L.) Merril] is one of the most important fungal diseases of this crop worldwide. The recent introduction of Phakopsora pachyrhizi Syd. & P. Syd in the Americas represents a major threat to soybean production in the main growing regions, and significant losses have already been reported. P. pachyrhizi is extremely aggressive under favorable weather conditions, causing rapid plant defoliation. Epidemiological studies, under both controlled and natural environmental conditions, have been done for several decades with the aim of elucidating factors that affe

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Levin, S. F. "Inadequacy for mathematical models of measurement objects and risk calculations according to ISO/IEC 17025-2019." Izmeritel`naya Tekhnika, no. 7 (2020): 13–21. http://dx.doi.org/10.32446/0368-1025it.2020-7-13-21.

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The problem of inadequacy of mathematical models of measurement objects is considered in connection with the problem of “definitional uncertainty of measurement” and the need for risk management in accordance with GOST ISO/IEC 17025-2019 “General requirements for the competence of testing and calibration laboratories”. The prehistory of the problem is described: from the formation of moment and compositional approaches to estimating accuracy to the introduction of a special term “inadequacy error for mathematical model of measurement object”. The negative impact of hopelessness of conceptual a

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Villars, Monique, Mark Gerath, and Don Galya. "Review of mathematical models for health risk assessment: III. Chemical concentrations in surface water, groundwater and soil." Environmental Software 8, no. 3 (January 1993): 135–55. http://dx.doi.org/10.1016/0266-9838(93)90011-6.

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Ihekwaba, Adaoha E. C., Ivan Mura, Pradeep K. Malakar, John Walshaw, Michael W. Peck, and G. C. Barker. "New Elements To Consider When Modeling the Hazards Associated with Botulinum Neurotoxin in Food." Journal of Bacteriology 198, no. 2 (September 8, 2015): 204–11. http://dx.doi.org/10.1128/jb.00630-15.

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Botulinum neurotoxins (BoNTs) produced by the anaerobic bacteriumClostridium botulinumare the most potent biological substances known to mankind. BoNTs are the agents responsible for botulism, a rare condition affecting the neuromuscular junction and causing a spectrum of diseases ranging from mild cranial nerve palsies to acute respiratory failure and death. BoNTs are a potential biowarfare threat and a public health hazard, since outbreaks of foodborne botulism are caused by the ingestion of preformed BoNTs in food. Currently, mathematical models relating to the hazards associated withC. bot

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