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Zhou, Zu Xu. "Research on the Preventive Measures of Sports Injury Based on Causality Diagram and Analytic Hierarchy Process." Applied Mechanics and Materials 380-384 (August 2013): 1838–42. http://dx.doi.org/10.4028/www.scientific.net/amm.380-384.1838.
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Because of the frequent occurrence of injury accident in the sports curriculum, the security of physical education cannot be ignored. So, this paper analyzes the factors of injury accident in physical education teaching process and proposes prevention measures. The establishment of security system in physical education is an urgent problem. This paper studies the causes and countermeasures of sports injury accidents based on two methods: causality diagram and analytic hierarchy process. The first section introduces the principles of causality diagram and hierarchical analysis in detail. The second part of the article establishes mathematical model of the analysis method. The part three of the text investigates and analyzes the accident status and prevention measures of 100 primary schools and universities in Heilongjiang province in the form of literature researches and questionnaires. It also proposes weight coefficients and causality diagrams of Sports Injury Accidents using causal analysis theory. It converts causal diagram into a hierarchical model using the analytic hierarchy process AHP.
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Wu, Bing, Luyao Kou, and Qi Ma. "Research on HFACS Based on Accident Causality Diagram." Open Journal of Safety Science and Technology 07, no. 02 (2017): 77–85. http://dx.doi.org/10.4236/ojsst.2017.72007.
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Wang, Hongchun. "A Fuzzy Reasoning Algorithm in Hybrid Causality Diagram." Journal of Algorithms & Computational Technology 6, no. 4 (2012): 623–38. http://dx.doi.org/10.1260/1748-3018.6.4.623.
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Mahardhika, Galih S., Inggis Raka Achmad, and Kusuma Hani Putri. "Causality Analysis between ESG Performance and Financing Support." Journal of Business and Political Economy : Biannual Review of The Indonesian Economy 3, no. 2 (2024): 93–108. http://dx.doi.org/10.46851/130.
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Recent global trends in electric vehicles (EV) triggered Indonesia to participate in battery industry development. Rich in geological resources, the government promotes various capital-intensive industries that process raw mining commodities, particularly limonite nickel ore, to support the EV industry in Indonesia. Inarguably, financial support is needed from various financial institutions and investors. On the contrary, the mining industry is closely related to environmental issues that attract the attention of financial institutions and investors. Therefore, understanding the relationship between “sustainability” and “financing activity” is essential, as it may not only practically guide the business to re-examine their environmental, social, and governance (ESG) initiatives but also extend the literature review on these matters. Therefore, this paper aims to describe the system through the Causal Loop Diagram (CLD) formed by ESG factors related to the financing process in mining companies in Indonesia. The research method used in this paper is developing causal loop diagrams from primary data and literature reviews. The CLD is constructed through a literature review and confirmed by an expert from the mining company. The result explains the causal loop between sustainability and financing. Improving ESG performance will increase financial support from global investors and financial institutions. To support practice and concept sustainability in Indonesia, the government should encourage mining companies to increase local partnerships and CSR Allocation as it will support the company's financing activity and trigger community improvement. Creating a supporting environment to attract global investors to finance the mining company in Indonesia is also necessary. Keywords: Causal Loop Diagram, ESG Performance, Financial Performance, Mining Industry, Sustainability JEL : M14, Q01, G32
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Zhang, Chun You, and Xiao Qiang Wu. "Intrusion Scenario Dynamic Correlation Algorithm Based on Single Value Causality Diagram." Advanced Materials Research 926-930 (May 2014): 3063–67. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3063.
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In order to obtain the effective network intrusion alarm information, and reveal the intention of attackers, an intrusion scenario dynamic correlation algorithm is proposed based on single value causality diagram. According to the composition principle of single value causality diagram, the key factors of the cause and effect diagram are defined. By relating the alarm information of intrusion detection system, attack scenarios are constructed based on cause and effect diagram, and dynamic correction is conduct. Based on the MIT Lincoln laboratory data sets, the correlation test is done using the above attack scenario correlation algorithm. Test results show that the reconstruction of attack scenarios and actual condition have very good consistency, proving that the proposed correlation algorithm can correctly reflect the real hacker intrusion process. The research of this paper provides effective help for the security administrator to implement effective management measures.
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Yang, Shu Xia, and Qi Han. "System Dynamics Model about the Mode of Energy Transmission." Advanced Materials Research 732-733 (August 2013): 1406–9. http://dx.doi.org/10.4028/www.scientific.net/amr.732-733.1406.
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With the rapidly growing economy, the energy demand increases greatly. Due to energy distribution imbalance in the space, part of the areas lack of energy resources, relying on energy call to ensure energy security. In this paper, first of all, we put forward the steps of comparatively studying different modes of energy transmission with system dynamics model and carry out a causal analysis. Then we analyze the causality among model variables. Finally, we draft a causality diagram of model elements. Based on this, we establish quantitative relations among variables and draft a system flow diagram.
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Jin, Feng, Jun Zhao, Chunyang Sheng, and Wei Wang. "Causality diagram-based scheduling approach for blast furnace gas system." IEEE/CAA Journal of Automatica Sinica 5, no. 2 (2018): 587–94. http://dx.doi.org/10.1109/jas.2017.7510715.
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Mahadevan, Sridhar. "Universal Causality." Entropy 25, no. 4 (2023): 574. http://dx.doi.org/10.3390/e25040574.
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Universal Causality is a mathematical framework based on higher-order category theory, which generalizes previous approaches based on directed graphs and regular categories. We present a hierarchical framework called UCLA (Universal Causality Layered Architecture), where at the top-most level, causal interventions are modeled as a higher-order category over simplicial sets and objects. Simplicial sets are contravariant functors from the category of ordinal numbers Δ into sets, and whose morphisms are order-preserving injections and surjections over finite ordered sets. Non-random interventions on causal structures are modeled as face operators that map n-simplices into lower-level simplices. At the second layer, causal models are defined as a category, for example defining the schema of a relational causal model or a symmetric monoidal category representation of DAG models. The third layer corresponds to the data layer in causal inference, where each causal object is mapped functorially into a set of instances using the category of sets and functions between sets. The fourth homotopy layer defines ways of abstractly characterizing causal models in terms of homotopy colimits, defined in terms of the nerve of a category, a functor that converts a causal (category) model into a simplicial object. Each functor between layers is characterized by a universal arrow, which define universal elements and representations through the Yoneda Lemma, and induces a Grothendieck category of elements that enables combining formal causal models with data instances, and is related to the notion of ground graphs in relational causal models. Causal inference between layers is defined as a lifting problem, a commutative diagram whose objects are categories, and whose morphisms are functors that are characterized as different types of fibrations. We illustrate UCLA using a variety of representations, including causal relational models, symmetric monoidal categorical variants of DAG models, and non-graphical representations, such as integer-valued multisets and separoids, and measure-theoretic and topological models.
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Meng, Fan Jun, Li Hong Liu, Yun He Zhang, et al. "Analysis Methods of QC Group Activity." Advanced Materials Research 909 (March 2014): 265–68. http://dx.doi.org/10.4028/www.scientific.net/amr.909.265.
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This article analysis QC group activity common method, including permutation diagram, causality diagram, countermeasure table, and discussion methods---brainstorming method. It grasp the design process and the actual value, point out the direction and laid a solid foundation for work of QC group activities in the enterprise effectively. It also create broad platform for innovation of enterprise product quality and increase of team cohesion.
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Guan, Jing, Boyang Liu, and Wenxin Shen. "Development of an Evaluation System for Intelligent Construction Using System Dynamics Modeling." Buildings 14, no. 6 (2024): 1489. http://dx.doi.org/10.3390/buildings14061489.
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Under the new wave of scientific and technological revolution, the construction industry finds itself with a critical need to alter the traditional and outdated production mode through technological innovation in order to realize industry transformation and move towards a new era characterized by digitalization, informatization, and intelligence. As intelligent construction is the indispensable pathway for the transformation and upgrading of the construction industry, it is of great significance to conduct in-depth research on its evaluation indicators and causality. This paper adopts the system dynamics method, based on the overall structure of intelligent construction, extracts the causality chain and causal feedback loop of intelligent construction, and presents a causality diagram and system dynamics diagram to build a robust system dynamics model for intelligent construction. On this basis, an evaluation index system for intelligent construction is constructed from the five dimensions—investment, design, construction, operation, and environment—for a holistic assessment of the current state of intelligent construction. The research aims to provide a valuable reference for professionals focusing on intelligent construction and the broader development of the industry.
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Wang, Xiang, Gang Tao, and Li Jing Zhang. "What Contributes to Fireworks-Related Injuries: Risk-Based Supervision Model." Advanced Materials Research 1065-1069 (December 2014): 2368–71. http://dx.doi.org/10.4028/www.scientific.net/amr.1065-1069.2368.
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According to statistic analysis of consumer fireworks-related injuries (CFRI) of domestic and overseas, the risk factors causing injuries are determined. Two methods are used to solve problem. Firstly, all the risk factors leading to injures are expressed by the Causality Diagram. Then this Causality Diagram is transferred into hierarchical structure model of AHP for quantitative analysis. By working out the model, the weight of each factor could be obtained. Thereby the significance of each factor is determined. Finally, the hinge factors leading to CFRI can be figured out as the terms of the risk-based supervision model that based on the important aspects to be focused on within self-protection and supervision for consumers in the residential community both of rural and urban, as well as industrial workers of the enterprises.
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Zhang, Boyi, Pengjian Shang, and Jinzhao Liu. "Transition-based complexity-entropy causality diagram: A novel method to characterize complex systems." Communications in Nonlinear Science and Numerical Simulation 95 (April 2021): 105660. http://dx.doi.org/10.1016/j.cnsns.2020.105660.
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Jia, Lulu, Yi Ren, Dezhen Yang, Qiang Feng, Bo Sun, and Cheng Qian. "Reliability analysis of dynamic reliability block diagram based on dynamic uncertain causality graph." Journal of Loss Prevention in the Process Industries 62 (November 2019): 103947. http://dx.doi.org/10.1016/j.jlp.2019.103947.
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Liu, Wen Sheng, and Ming Zhu. "The Study of Coalmine Safety Prediction Based on System Dynamics." Advanced Materials Research 466-467 (February 2012): 1045–49. http://dx.doi.org/10.4028/www.scientific.net/amr.466-467.1045.
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This paper pointed out the importance of safety prediction, introduced system dynamics into coal mine safety prediction, analyzed main controllable safety factors in coalmine and causality diagram, established the system dynamics flow chart model and used the method of simulation data to demonstrate the theoretical effectiveness which provided a reference for safety managers to make decision.
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Yu, Yong Tao, Ying Ding, and Yong Xin Yu. "System Dynamics Model Simulation of Sea Battlefield Situation Assessment." Advanced Materials Research 811 (September 2013): 710–15. http://dx.doi.org/10.4028/www.scientific.net/amr.811.710.
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The fundamental basis of Navy operational command decision support system is efficient to make an objective assessment of the complex dynamic sea battlefield situation. According to the study proposes the sea battlefield situation based on a system dynamics model evaluate simulation. First sea battlefield situation system analysis; second system causality analysis, to establish a causal loop diagram; again is based on the sea battlefield situation to assess the relationship between flow diagram, build SD simulation model; enter the initial parameter; finally, based on the events of the battlefield to enter the initial parameter, assessment simulation sea battlefield situation, analysis simulation conclusion, put forward suggestions.
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Zhang, Qin. "A frequency and knowledge tree/causality diagram based expert system approach for fault diagnosis." Reliability Engineering & System Safety 43, no. 1 (1994): 17–28. http://dx.doi.org/10.1016/0951-8320(94)90092-2.
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Yan, Xie. "Simulation research of port competitiveness based on system dynamics." SHS Web of Conferences 163 (2023): 04020. http://dx.doi.org/10.1051/shsconf/202316304020.
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It is an urgent problem for Chinese large and medium-sized ports to improve their competitiveness. With the method of system dynamics and the software Vensim-PLE, the simulation model of port competitiveness is constructed to explore the internal factors influencing mechanism and development trend of port competitiveness. By constructing causality diagram and system flow diagram, the paper analyzes the influence mechanism of related factors on port competitiveness. Taking Nanjing Port as the specific research object, it predicts the change trend of cargo throughput and other related variables and port competitiveness. Then it designs four simulation schemes to improve the port competitiveness of Nanjing Port ,and compares the improvement effects of different schemes. Finally, it puts forward some countermeasures and suggestions to improve port competitiveness.
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Wang, Hairui, Junming Li, and Guifu Zhu. "A Data Feature Extraction Method Based on the NOTEARS Causal Inference Algorithm." Applied Sciences 13, no. 14 (2023): 8438. http://dx.doi.org/10.3390/app13148438.
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Extracting effective features from high-dimensional datasets is crucial for determining the accuracy of regression and classification models. Model predictions based on causality are known for their robustness. Thus, this paper introduces causality into feature selection and utilizes Feature Selection based on NOTEARS causal discovery (FSNT) for effective feature extraction. This method transforms the structural learning algorithm into a numerical optimization problem, enabling the rapid identification of the globally optimal causality diagram between features and the target variable. To assess the effectiveness of the FSNT algorithm, this paper evaluates its performance by employing 10 regression algorithms and 8 classification algorithms for regression and classification predictions on six real datasets from diverse fields. These results are then compared with three mainstream feature selection algorithms. The results indicate a significant average decline of 54.02% in regression prediction achieved by the FSNT algorithm. Furthermore, the algorithm exhibits exceptional performance in classification prediction, leading to an enhancement in the precision value. These findings highlight the effectiveness of FSNT in eliminating redundant features and significantly improving the accuracy of model predictions.
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CHEN, HUA, and DANIEL MATTIS. "COULOMB CORRELATIONS AND INSTABILITY OF SPINLESS FERMION GAS IN 1D AND 2D." Modern Physics Letters B 08, no. 16 (1994): 985–93. http://dx.doi.org/10.1142/s0217984994000996.
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We study the stability of the ordinary Landau Fermi liquid phase for interacting, spinless electrons. We require causality and demand that the Pauli principle be obeyed. We find a phase diagram determined by two parameters: the particle density and the interaction strength. We find that the homogeneous, constant density Fermi liquid phase of a spinless Fermion gas is never stable in 1D, but that it may have a restricted domain of stability in 2D.
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Huang, Yi Sheng, and Tso Hsien Liao. "Modeling and Designing of Urban Traffic Control Systems by Statecharts." Advanced Materials Research 308-310 (August 2011): 1582–85. http://dx.doi.org/10.4028/www.scientific.net/amr.308-310.1582.
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Statechart has been utilized as a visual formalism for the modeling of complex systems. It illuminates the features on describing properties of causality, concurrency and synchronization. The reachability structure is used to represented dynamic model by a Boolean function. In this paper, we try to describe State invariant method and equation function for hierarchical tree diagram. Finally, we used them to analyze the urban traffic control systems which are modeled by using Statecharts. Their formalism provides a concept of propositional logic for presenting control strategy.
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Zhang, Xian. "Modeling and Simulation of Enterprise Alliance Running Status Based on System Dynamics." Applied Mechanics and Materials 55-57 (May 2011): 898–903. http://dx.doi.org/10.4028/www.scientific.net/amm.55-57.898.
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In this paper the key factors of the enterprise alliance running status were studied based on system dynamic theory. These factors include intrinsic restraint, achievement, core competencies and compatibility. A causality diagram and a system dynamic model which can reflect the growing process of enterprise alliance running phase were established. A program simulating the system dynamic model of the enterprise alliance running phase is also achieved, and the validation was infered by a qualitative analysis. The results show that it is a workable method to study the enterprise alliance running status with system dynamic theory．
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Scripcaru, Răzvan, Angela Digulescu, Leontin Tuță, and Alexandru Șerbănescu. "Discussion upon the Stationarity and the Causality of a Time Series Using the Phase Diagram Representation." Journal of Military Technology 2, no. 2 (2019): 11–16. http://dx.doi.org/10.32754/jmt.2019.2.02.
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Zhang, Mengyao, Deming Yu, Tianyu Wang, and Can Xu. "Coupling Analysis of Tunnel Construction Safety Risks Based on N-K Model and SD Causality Diagram." Buildings 13, no. 4 (2023): 1081. http://dx.doi.org/10.3390/buildings13041081.
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Tunnel construction is characterized by its large scale, long periods and vulnerability to environmental impact, which pose great challenges to tunnel construction safety. In order to analyze the coupling mechanism of tunnel construction safety risks and assess these risks, we conducted a study on the coupling evaluation of these risks in order to improve tunnel construction safety risk management. By analyzing 150 accident cases related to tunnel construction safety, an N-K model (natural killing model) was constructed to quantify the risk level of each coupling form from four aspects—personnel risk factors, equipment risk factors, environmental risk factors and management risk factors—and the SD (system dynamics) causality diagram was used to construct risk element conduction paths and identify the key influencing factors of different coupling forms. The research results show that with the increase in risk coupling factors, the risk of tunnel construction safety accidents also increases; weak personnel safety awareness, aging and wear of equipment, poor operating environment and construction site management chaos are the key risk factors whose prevention needs to be focused on. The related research results can provide a new method for decision makers to assess tunnel construction safety risks and enrich the research on tunnel construction safety risk management.
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Zhang, Tao, Mengqi Liu, and Wenyuan Liu. "The Causality Research between Syndrome Elements by Attribute Topology." Computational and Mathematical Methods in Medicine 2018 (July 2, 2018): 1–12. http://dx.doi.org/10.1155/2018/9707581.
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Background. The traditional Chinese medicine (TCM) is an empirical medical system and has its own diagnosis and treatment method. The syndrome elements are atoms to modern TCM diagnosis proposed by Professor Zhu Wenfeng. Researching and analyzing the syndrome element system is one of the active issues for TCM research. At present, most related researches focus on the correlativity and hierarchical relationship of the diseases and symptoms, but the causality researches between syndrome elements themselves have not been reported so far. Methods. To explore the causality between syndrome elements, a method named causality by attribute topology (CAT) is proposed. Based on the subordinate relations in attribute topology, the inference method analyzes and reasons the dependency relationship between the sets of objects which contain attributes. Through the removal of attributes in the attribute topology, the formal context is updated constantly. Thus, the causal relationship among the attributes is deduced. In this method, 500 records are mathematically transferred to a binary context for syndrome element analysis. Through the analysis and verification of the potential causal relationship between the syndrome elements, knowledge discovery of the diagnostic data of traditional Chinese medicine based on attribute topology structure diagram is conducted. Results. This paper has verified the causal transformation between these syndrome elements. The experimental results between the female group data and the male group data show that different genders have different characteristics and relations of syndrome elements. The experimental results are basically consistent with the traditional Chinese medicine theory. Conclusion. The experiment shows that causality by attribute topology (CAT) is feasible to describe the causality between TCM syndrome elements. Further research on possible knowledge discovery in TCM diagnostic data should be conducted through the analysis of the potential causal relationship between TCM diagnostic data and each syndrome element.
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Chen, Jing, Yong Jie Yang, and Qing Gui Cao. "Analysis and Application about Coal Mine System Dynamics Model Based on Non-Linear Regression." Applied Mechanics and Materials 675-677 (October 2014): 1473–78. http://dx.doi.org/10.4028/www.scientific.net/amm.675-677.1473.
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Author thinks that the three factors’ state of person, things, environment is decided by safety input, their different state meeting determined safe production. It can reduce accident by reducing three factors’ occurrence probability and changing safety investment object and quantity. According to the rule, the paper construct coal mine safety system dynamics causality diagram by using system dynamics theory from safety management angle, and made data quantitative analysis by non-linear regression, found out the function relationship that can reflect system elements dynamic change. At last, took one coal mine as an example, it made macroscopic analysis using the model.
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Liu, Chun-Chu, Chin-Tarn Lee, Yu-Feng Guo, Kon-Ning Chiu, and Tse-Yu Wang. "The Study of Sustainable Rural Development in Taiwan—A Perspective of Causality Relationship." Agriculture 12, no. 2 (2022): 252. http://dx.doi.org/10.3390/agriculture12020252.
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From the perspective of sustainable development and based on literature review, this paper introduces modified Delphi and Decision Making and Trial Evaluation Laboratory (DEMATEL) to explore the critical factors of sustainable development in rural areas and their correlation. Through literature review and modified Delphi analysis, nine key factors of rural sustainable development are first identified, namely industrial activation, working environment, living conditions, infrastructure, public involvement, rural culture, government-related departments, educational resources, and health and welfare. DEMATEL is then adopted to determine the classification of the aforementioned factors, in which four (government-related departments, public involvement, infrastructure, and educational resources) are classified in the cause group and five (health and welfare, living conditions, rural culture, working environment, and industrial activation) are classified in the effect group. According to the centrality and relation of these factors, the causal network diagram is finally drawn before making practical suggestions based on the overall results, with a view to providing a reference for decision-makers in their follow-up rural sustainable development planning.
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Zhang, Xian. "Analysis of the Granularity of Task Decomposition in Enterprise Alliance Based on System Dynamics." Advanced Materials Research 314-316 (August 2011): 487–91. http://dx.doi.org/10.4028/www.scientific.net/amr.314-316.487.
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The influence brought by the granularity of task decomposition on the key factors of enterprise aliance was studied based on system dynamics method. These factors includs inter-restriction, product manufacturing time, collaboration fee, Alliance leader benefit, capability and compatibility. Causality diagram and system dynamics model were established for these factors. This paper also developed a simulation program for the granularity of task decomposition based on the system dynamics model and validated the effectiveness of the proposed model by a qualitative analysis. The results show that it is a workable method to research the granularity of task decomposition in enterprise aliance using system dynamics theory.
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Miwakeichi, Fumikazu, and Andreas Galka. "Comparison of Bootstrap Methods for Estimating Causality in Linear Dynamic Systems: A Review." Entropy 25, no. 7 (2023): 1070. http://dx.doi.org/10.3390/e25071070.
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In this study, we present a thorough comparison of the performance of four different bootstrap methods for assessing the significance of causal analysis in time series data. For this purpose, multivariate simulated data are generated by a linear feedback system. The methods investigated are uncorrelated Phase Randomization Bootstrap (uPRB), which generates surrogate data with no cross-correlation between variables by randomizing the phase in the frequency domain; Time Shift Bootstrap (TSB), which generates surrogate data by randomizing the phase in the time domain; Stationary Bootstrap (SB), which calculates standard errors and constructs confidence regions for weakly dependent stationary observations; and AR-Sieve Bootstrap (ARSB), a resampling method based on AutoRegressive (AR) models that approximates the underlying data-generating process. The uPRB method accurately identifies variable interactions but fails to detect self-feedback in some variables. The TSB method, despite performing worse than uPRB, is unable to detect feedback between certain variables. The SB method gives consistent causality results, although its ability to detect self-feedback decreases, as the mean block width increases. The ARSB method shows superior performance, accurately detecting both self-feedback and causality across all variables. Regarding the analysis of the Impulse Response Function (IRF), only the ARSB method succeeds in detecting both self-feedback and causality in all variables, aligning well with the connectivity diagram. Other methods, however, show considerable variations in detection performance, with some detecting false positives and others only detecting self-feedback.
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Ghufran, Maria, Khurram Iqbal Ahmad Khan, Fahim Ullah, Wesam Salah Alaloul, and Muhammad Ali Musarat. "Key Enablers of Resilient and Sustainable Construction Supply Chains: A Systems Thinking Approach." Sustainability 14, no. 19 (2022): 11815. http://dx.doi.org/10.3390/su141911815.
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In the globalized world, one significant challenge for organizations is minimizing risk by building resilient supply chains (SCs). This is important to achieve a competitive advantage in an unpredictable and ever-changing environment. However, the key enablers of such resilient and sustainable supply chain management are less explored in construction projects. Therefore, the present research aims to determine the causality among the crucial drivers of resilient and sustainable supply chain management (RSSCM) in construction projects. Based on the literature review, 12 enablers of RSSCM were shortlisted. Using the systems thinking (ST) approach, this article portrays the interrelation between the 12 shortlisted resilience enablers crucial for sustainability in construction projects. The causality and interrelationships among identified enablers in the developed causal loop diagram (CLD) show their dynamic interactions and impacts within the RSSCM system. Based on the results of this study, agility, information sharing, strategic risk planning, corporate social responsibility, and visibility are the key enablers for the RSSCM. The findings of this research will enable the construction managers to compare different SCs while understanding how supply chain characteristics increase or decrease the durability and ultimately affect the exposure to risk in the construction SCs.
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Ye, Shi Feng, Dong Xiang Chen, Tai Yong Wang, and Dan Wang. "Petri Nets in the Emu Pantograph Application of Fault Tree Analysis (FTA)." Key Engineering Materials 693 (May 2016): 1385–90. http://dx.doi.org/10.4028/www.scientific.net/kem.693.1385.
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This paper presents the fault mode and barb causality diagram of the pantograph of the emu, by settling and counting fault information of the pantograph. And fault analysis of the pantograph is used to establish the fault tree. The Petri net model of the pantograph is simplified on the base of the principle of duality and resorption by combining the modeling theory of Petri net and the fault tree. The minimum cut set is obtained by solving the above simplified model with incidence matrix. Compared to common solution of the fault tree, this integrated model efficiently simplifies computation of complicated fault tree. The method raised here saves the time of computation which increases the efficiency of analysis, and improves the accuracy of fault diagnosis.
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Jäger, Susanne, Rafael Cuadrat, Per Hoffmann, Clemens Wittenbecher, and Matthias B. Schulze. "Desaturase Activity and the Risk of Type 2 Diabetes and Coronary Artery Disease: A Mendelian Randomization Study." Nutrients 12, no. 8 (2020): 2261. http://dx.doi.org/10.3390/nu12082261.
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Estimated Δ5-desaturase (D5D) and Δ6-desaturase (D6D) are key enzymes in metabolism of polyunsaturated fatty acids (PUFA) and have been associated with cardiometabolic risk; however, causality needs to be clarified. We applied two-sample Mendelian randomization (MR) approach using a representative sub-cohort of the European Prospective Investigation into Cancer and Nutrition (EPIC)–Potsdam Study and public data from DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) and Coronary ARtery DIsease Genome wide Replication and Meta-analysis (CARDIoGRAM) genome-wide association studies (GWAS). Furthermore, we addressed confounding by linkage disequilibrium (LD) as all instruments from FADS1 (encoding D5D) are in LD with FADS2 (encoding D6D) variants. Our univariable MRs revealed risk-increasing total effects of both, D6D and D5D on type 2 diabetes (T2DM) risk; and risk-increasing total effect of D6D on risk of coronary artery disease (CAD). The multivariable MR approach could not unambiguously allocate a direct causal effect to either of the individual desaturases. Our results suggest that D6D is causally linked to cardiometabolic risk, which is likely due to downstream production of fatty acids and products resulting from high D6D activity. For D5D, we found indication for causal effects on T2DM and CAD, which could, however, still be confounded by LD.
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Li, Fawen, Dong Yu, Yong Zhao, and Runxiang Cao. "Inter-annual change of the drought limit water level of a reservoir based on system dynamics." Water Policy 21, no. 1 (2018): 91–107. http://dx.doi.org/10.2166/wp.2018.112.
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Abstract Drought is one of the major natural disasters affecting the development of economies and society. Drought early warning is the primary step and most important non-engineering measure for drought relief. This paper took Yuqiao Reservoir in Tianjin as a case study and analysed inter-annual changes of the drought limit water level. First, the causality between variables in the water supply–demand system was analysed, and a structural diagram of water sources allocation was drawn. Coupled with the parameters and a structural diagram, a system dynamics (SD) model of the water supply volume was established. Secondly, simulation results were tested to ensure that the model was valid. The water supply volume from 2003 to 2020 was simulated by using the model. Finally, based on the inflow process and the water supply volume, the drought limit water level was calculated. The results showed the water supply volume of Yuqiao Reservoir has changed remarkably. The drought limit water levels in 2003–2012 and in 2016–2020 were 16.70 m and 16.30 m, respectively: a difference of 0.40 m. The regulation curve of guarantee for water supply during 2016–2020 is significantly lower than that of 2003–2012. This research is of great significance for drought resistance, disaster mitigation and reservoir management.
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Agustina, Isnaeni, and A. Artiningsih. "Evaluasi Implementasi Masterplan Kawasan Agropolitan Ciwidey Menggunakan Logic Models." Jurnal Wilayah dan Lingkungan 5, no. 1 (2017): 1. http://dx.doi.org/10.14710/jwl.5.1.1-10.
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The rural development should be encouraged to reduce inequalities in urban and rural areas, including through the program of agropolitan area development. The government of Bandung District has compiled the Masterplan of Agropolitan Ciwidey in 2007, implemented in 2008-2012, and evaluated in 2013-2016. This study aims to find out the performance of the Ciwidey’s agropolitan development programs and activities. The study was conducted using logic models analysis that describes the input, output, outcome, and impact on a diagram and then described using causality description. The findings address that the development program of Ciwidey agropolitan has the positive impacts for physical and social characteristics, while it has adverse effects for economic characteristics. This study recommends that the robust support from the institutional of agribusiness activity is needed to develop an agropolitan area.
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Kurstedt, Harold. "8.1.3 Applying Engineering Principles to Human Components in Complex Systems." INCOSE International Symposium 10, no. 1 (2000): 127–34. http://dx.doi.org/10.1002/j.2334-5837.2000.tb00367.x.
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AbstractSystems engineers must understand the workings within and the relationships among human as well as non‐human subsystems in the larger systems they're engineering. To be systems thinkers, we must easily and comfortably integrate human subsystems into complex systems. A key to approaching the human subsystems is to incorporate solution‐focused thinking that is based on circular and mutual causality rather than cause and effect. However, systems engineers can quite well apply their engineer's laws of physical science to human subsystems. The fundamental building block for systems that include humans is the dyad (two people). When anxiety rises in a dyad, the two people will attract a third human or non‐human subsystem to form a triangle. We can diagram dyads and triangles to better analyze, design, and implement complex systems containing human subsystems.
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Zhang, Sainan, and Yuncai Ning. "The Network Transmission Path Risk Assessment and Application of Chemical Substances in Toys." Mathematical Problems in Engineering 2022 (May 26, 2022): 1–10. http://dx.doi.org/10.1155/2022/2702325.
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Through the analysis of the risk transmission mechanism of chemical substances in toys, this paper identifies risk sources, transmission carriers, key nodes, and risk recipients, and draws a risk transmission path diagram. Taking the risk factors in the supply chain system as the research subject, this paper constructs a risk index system for chemical substances’ limit in toys, and calculates the probability of risk and the degree of influence by the fuzzy evaluation method. Based on the Bayesian network model, this paper analyzes the causality of risk transmission effects. Through the comprehensive use of fuzzy evaluation and Bayesian network methods, a relatively complete chemical substance risk transmission path assessment system has been established using China’s Guangdong toy companies as the data store to provide a feasible basis for responding to the risk control measures of toxic and hazardous chemical substances in toys.
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ZAINAL ABIDIN, NORHASLINDA, SHRI DEWI APPLANAIDU, MOHAMMED BABA ABDULLAHI, and SURIANIE BAKAR. "UNDERSTANDING PADDY PRODUCTIVITY AT MADA ESTATE FROM A SYSTEM DYNAMICS PERSPECTIVE: A MAPPING TOOL OF CAUSAL LOOP DIAGRAM." JOURNAL OF SUSTAINABILITY SCIENCE AND MANAGEMENT 18, no. 2 (2023): 81–1012. http://dx.doi.org/10.46754/jssm.2023.02.007.
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The Muda Agricultural Development Authority (MADA) paddy estate project represents Malaysia’s national effort to enhance food security. However, the Economic Transformation Programme (ETP) by Malaysia falls short of attaining the 10 MT/Ha paddy productivity potential. Amidst rising food insecurity, national efforts have focused on improving the efficiency of domestic productivity, this study specifically assessed factors influencing paddy productivity under the MADA estate project. Against the econometric technique, the causal loop diagram (CLD) in the system dynamics (SD) approach was used to analyse the systemic character of productivity and its drivers. The systemic relationship was explored using expert interviews and an extensive literature reviews. Findings established four major sub-systems of the rice value chain. These include paddy production, rice production, government subsidy and self-sufficiency level. The loop polarity feature was used to establish the causal relationships and directions of causality between the sub-systems. This study contributes directly to EPP10 and EPP11 of the ETP. As a result, it supports Malaysia’s effort towards strengthening food security and self-sufficiency.
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Gholipour, Amir, Rita Fragoso, Ana Galvão, and David C. Finger. "Mapping the causality of interacting perceptions for nature-based solution and sludge treatment reed bed: A causal loop diagram in Iceland." Nature-Based Solutions 3 (December 2023): 100049. http://dx.doi.org/10.1016/j.nbsj.2023.100049.
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Baeza-Serrato, Roberto, and José Antonio Vázquez-López. "Transition from a predictive multiple linear regression model to an explanatory simple nonlinear regression model with higher level of prediction: A systems dynamics approach." Revista Facultad de Ingeniería Universidad de Antioquia, no. 71 (February 12, 2014): 59–71. http://dx.doi.org/10.17533/udea.redin.14469.
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One of the main assumptions of the linear regression analysis is the existence of a causal relationship between the variables analyzed, which the regression analysis does not demonstrate. This paper demonstrates the causality between the variables analyzed through the construction and analysis of the feedback from the variables under study, expressed in a causal diagram and validated through dynamic simulation. The major contribution of this research is the proposal of the use of the system dynamics approach to develop a method of transition from a multiple regression predictive model to a simpler nonlinear regression explanatory model, which increases the level of prediction of the model. The mean square error (MSE) is taken as a criterion for prediction. The validation in the transition model was performed with three linear regression models obtained experimentally in a textile company, showing a method for increasing the reliability of prediction models.
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Magin, Richard L., and Ervin K. Lenzi. "Fractional Calculus Extension of the Kinetic Theory of Fluids: Molecular Models of Transport within and between Phases." Mathematics 10, no. 24 (2022): 4785. http://dx.doi.org/10.3390/math10244785.
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The application of fractional calculus in the field of kinetic theory begins with questions raised by Bernoulli, Clausius, and Maxwell about the motion of molecules in gases and liquids. Causality, locality, and determinism underly the early work, which led to the development of statistical mechanics by Boltzmann, Gibbs, Enskog, and Chapman. However, memory and nonlocality influence the future course of molecular interactions (e.g., persistence of velocity and inelastic collisions); hence, modifications to the thermodynamic equations of state, the non-equilibrium transport equations, and the dynamics of phase transitions are needed to explain experimental measurements. In these situations, the inclusion of space- and time-fractional derivatives within the context of the continuous time random walk (CTRW) model of diffusion encodes particle jumps and trapping. Thus, we anticipate using fractional calculus to extend the classical equations of diffusion. The solutions obtained illuminate the structure and dynamics of the materials (gases and liquids) at the molecular, mesoscopic, and macroscopic time/length scales. The development of these models requires building connections between kinetic theory, physical chemistry, and applied mathematics. In this paper, we focus on the kinetic theory of gases and liquids, with particular emphasis on descriptions of phase transitions, inter-phase mixing, and the transport of mass, momentum, and energy. As an example, we combine the pressure–temperature phase diagrams of simple molecules with the corresponding anomalous diffusion phase diagram of fractional calculus. The overlap suggests links between sub- and super-diffusion and molecular motion in the liquid and the vapor phases.
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Ariyano, Ariyano, Amay Suherman, and Handiansyah Akhmadi. "Development of Multimedia Based on Autodesk Inventor Software on the Concept of Relative Velocity to Increase Students’ Generic Science Skill." Journal of Vocational Education Studies 3, no. 2 (2020): 111. http://dx.doi.org/10.12928/joves.v3i2.2482.
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This research aims to develop autodesk inventor-based multimedia that was designed to increase students’ generic science skill on the application of relative velocity at kinematics and dynamics courses. This study used the mini course method developed by Borg and Gall, including the stage of analysing and planning, developing early product, and validating from the expert and revision the early product. Based on the analysis conducted, it was revealed that there were five indicators that students had difficulties with, including illustrating kinematic diagram, illustrating velocity direction, calculating absolute velocity, illustrating velocity polygon, and calculating velocity based on velocity polygon. Those five indicators were related to six generic science aspects, including modelling, symbolic language, laws of causality, logical consistency, scale awareness, and observation. The developed multimedia consists of nine displays of slider-crank mechanism and eight displays of four-bar mechanisms, using .idw, .iam, and .mp4 formats and has been validated by material and media experts. Based on the judgment from the experts, the inventor-based multimedia was worthy to be applied in the course.
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Song, Jiekun, Kaixin Zhang, and Zijian Cao. "3Es System Optimization under Uncertainty Using Hybrid Intelligent Algorithm: A Fuzzy Chance-Constrained Programming Model." Scientific Programming 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/2675759.
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Harmonious development of 3Es (economy-energy-environment) system is the key to realize regional sustainable development. The structure and components of 3Es system are analyzed. Based on the analysis of causality diagram, GDP and industrial structure are selected as the target parameters of economy subsystem, energy consumption intensity is selected as the target parameter of energy subsystem, and the emissions of COD, ammonia nitrogen, SO2, andNOXand CO2emission intensity are selected as the target parameters of environment system. Fixed assets investment of three industries, total energy consumption, and investment in environmental pollution control are selected as the decision variables. By regarding the parameters of 3Es system optimization as fuzzy numbers, a fuzzy chance-constrained goal programming (FCCGP) model is constructed, and a hybrid intelligent algorithm including fuzzy simulation and genetic algorithm is proposed for solving it. The results of empirical analysis on Shandong province of China show that the FCCGP model can reflect the inherent relationship and evolution law of 3Es system and provide the effective decision-making support for 3Es system optimization.
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M. Trajković, Dragana, and Branislav Dimitrijević. "BOND GRAPH BICAUSALITY MODELING THE HYDRAULIC SYSTEM." KNOWLEDGE - International Journal 54, no. 3 (2022): 521–25. http://dx.doi.org/10.35120/kij5403521t.
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This papers represents one of the most widely challenging control problems. The most accepted blockdiagrams in automatic control used to describe processes have been replaced by control based on bond graphmodeling. The bond graph model one physical model hydraulic process is presented. The goal of the research is toobtain a model of process with and without knowledge of the mathematical model, which is used to obtain asimulation and prediction model. Due to the feedback effect of the liquid in the pipes (power and flow), a bicausalbond graph was used as the flow source. Bond graphs have a basic concept in their physics - energy that isexchanged through connectors 0 and 1 (ports). Effort e (force, voltage, pressure, etc.) and flow f (current, velocity,volume, etc.) are general physical quantities that are used to analyze the appropriate physical model and descriptionfor bond graph modeling and that very successfully. Bond-graph modeling is a powerful tool for modelingengineering systems, especially when physical domains are involved. Submodels graph can be reused, because linkgraph models are not causal. Connection graphs are labeled and directed graphs, in which vertices representsubmodels and arrows represent the ideal energy connection between power ports. Bond has a direction of strengthand a direction of causality. The assigned computational causality dictates which port variable will be computed asthe result (output) and accordingly, another port variable will be the cause (input). Graphs can be connected to partsof the block diagram, submodels of the connection graph can have power connections, signal inputs and signaloutputs as their interface elements. Aspects such as the physical domain of the connection (energy flow) can be usedto support the modeling process. The research in this work is on obtaining a fast and adequate physical model withgood knowledge of physical changes.
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FOFANA, Seguena, Abdoulaye TOURÉ, and Kafana SORO. "Hygienic Quality and Conservation of Market Gardening Products Sold in the City of Korhogo (Northern Côte d’Ivoire)." Scholars Academic Journal of Biosciences 10, no. 08 (2022): 178–84. http://dx.doi.org/10.36347/sajb.2022.v10i08.002.
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Market gardening is an activity commonly practiced in the city of Korhogo. This study made it possible to take stock of this activity with a view to improving it for the benefit of consumers. A survey was therefore conducted among 100 market gardeners in the Kassirimé, Natio-Kobadara, Koko and Téguérré neighborhoods and 100 vendors at the Sinistré and Belle-Ville markets and at the large market. The results showed that the majority of market gardeners and sellers are women who have not been educated, with more than 10 years of experience. The analysis of production sites through the requirements of the GLOBALGAP standard showed non-compliance rates above 90%. The study on market gardening sites and markets using the ISHIKAWA causality diagram made it possible to identify the risk factors and to propose measures for controlling the dangers. The survey showed that vendors use aeration, ventilation, immersion, drying and sprinkling for the preservation of vegetables. Moreover, market gardeners, like sellers, encounter problems in the practice of this activity. These problems are linked to the lack of supervision, access to agricultural credit and pest’s attacks.
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Li, Xingong, and Xiaokai Li. "The Impact of Different Internet Application Contexts on Knowledge Transfer between Enterprises." Systems 9, no. 4 (2021): 87. http://dx.doi.org/10.3390/systems9040087.
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This paper investigates the effect of different Internet application scenarios on the forward and reverse knowledge transfer between architecture enterprises and component enterprises in the context of modular production in manufacturing enterprises. After dividing the Internet contexts into three the perspectives of Internet tools, Internet platforms, and Internet resources, this paper adopts a system dynamics approach to construct a causality model and a system flow diagram of the influence of different Internet contexts on the knowledge transfer between architecture enterprises and component enterprises, and uses Vensim PLE software to simulate and conduct a sensitivity analysis of the model. The results show that the three Internet contexts, namely Internet tools, Internet platforms, and Internet resources, can promote both positive and negative knowledge transfer between architecture enterprises and component enterprises, and exhibit a steadily growing trend of promotion; Internet tools and Internet resources are more conducive to positive knowledge transfer from architecture enterprises to component enterprises, and Internet platforms have a stronger facilitation effect on the reverse knowledge transfer from the component enterprises to the architecture enterprises. Our research offers useful recommendations for businesses on how to utilize various Internet settings to promote and assist effective knowledge transfer.
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Zhang, Changlu, Jian Zhang, and Qiong Yang. "Identifying Critical Risk Factors in Green Product Certification Using Hybrid Multiple-Criteria Decision-Making." Sustainability 14, no. 8 (2022): 4513. http://dx.doi.org/10.3390/su14084513.
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Green product certification (GPC) is an important means of eliminating the asymmetry of information between consumers and manufacturers in the context of sustainable development. This study examined the critical risk factors in GPC and provided relevant suggestions for managers to reduce risk and ensure the correctness of the process. First, 18 risk factors were summarized along four dimensions: the certification institution, the entrusting enterprise, the certification business, and the implementation of the certification. Second, the Delphi method was used to determine the formal research framework, and the decision-making trial and evaluation laboratory (DEMATEL) method was applied to analyze the causal relationships among the risk factors to identify the ones driving risk and those representing the outcomes of GPC. This was used to construct a causality diagram of the risks related to green certification. Finally, the analytic network process (ANP) method was used to calculate the weight of each risk factor, and the weighted prominence of each is calculated to identify the critical factors. The results showed that the working life and experience of the certification institution were the critical driving risk factors in GPC. Corresponding countermeasures were also proposed to mitigate these risk factors.
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Feng, Huirong, C. W. Lim, Liqun Chen, Xinnian Zhou, Chengjun Zhou, and Yi Lin. "Sustainable Deforestation Evaluation Model and System Dynamics Analysis." Scientific World Journal 2014 (2014): 1–14. http://dx.doi.org/10.1155/2014/106209.
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The current study used the improved fuzzy analytic hierarchy process to construct a sustainable deforestation development evaluation system and evaluation model, which has refined a diversified system to evaluate the theory of sustainable deforestation development. Leveraging the visual image of the system dynamics causal and power flow diagram, we illustrated here that sustainable forestry development is a complex system that encompasses the interaction and dynamic development of ecology, economy, and society and has reflected the time dynamic effect of sustainable forestry development from the three combined effects. We compared experimental programs to prove the direct and indirect impacts of the ecological, economic, and social effects of the corresponding deforest techniques and fully reflected the importance of developing scientific and rational ecological harvesting and transportation technologies. Experimental and theoretical results illustrated that light cableway skidding is an ecoskidding method that is beneficial for the sustainable development of resources, the environment, the economy, and society and forecasted the broad potential applications of light cableway skidding in timber production technology. Furthermore, we discussed the sustainable development countermeasures of forest ecosystems from the aspects of causality, interaction, and harmony.
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Dewi, Shanty Kartika, and Anis Fuad. "Strategi Segmenting, Targeting, dan Positioning dalam Rangka Percepatan Penurunan Stunting di Provinsi Banten." JDKP Jurnal Desentralisasi dan Kebijakan Publik 3, no. 2 (2022): 398–406. http://dx.doi.org/10.30656/jdkp.v3i2.5914.
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Indonesia, as part of the Southeast Asian region, is still experiencing a situation that cannot be separated from the problem of stunting. Every year the prevalence of stunting in Indonesia tends to experience fluctuating conditions. These fluctuating conditions indicate inconsistencies in the implementation of policy programs to reduce stunting. When referring to the WHO maximum stunting prevalence standard of 20%, most provinces in Indonesia have not been able to meet this standard. One of them is Banten Province with a stunting prevalence rate in 2019 reached 24.11%. The conceptualization of the interaction pattern of stunting problems formed from the results of systems thinking is visualized in the form of a causality diagram model. The model, built using the systems dynamics method, serves to provide an understanding of the structural dynamics of the stunting problem, based on the cause-and-effect relationships between the components that make up the problem. This became the basis for the segmenting, targeting, and positioning (STP) strategy planning process. The output of STP strategy planning is compiled into a quality document that is determined according to the level needed to accelerate stunting reduction.
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Zhang, Changlu, Liqian Tang, and Jian Zhang. "Identifying Critical Indicators in Performance Evaluation of Green Supply Chains Using Hybrid Multiple-Criteria Decision-Making." Sustainability 15, no. 7 (2023): 6095. http://dx.doi.org/10.3390/su15076095.
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Performance evaluation of green supply chains (GSC) is an important tool to improve their comprehensive management. Identifying critical indicators is crucial to evaluation. This study examines the critical indicators in performance evaluations of GPC and provides relevant suggestions for managers to improve GSCs’ performances. Firstly, we summarized 24 evaluation indicators from five dimensions—financial value, customer service-level, business processes, innovation and development, and the so-called green level. Secondly, the Delphi method was used to determine the formal research framework. The fuzzy decision-making trial and evaluation laboratory based analytic network process (fuzzy DEMATEL-based ANP) model was applied. The weighted prominence of each indicator was calculated to identify those that were critical, and a causality diagram was constructed for them. Finally, corresponding countermeasures and implications regarding those were put forward. The research results show that the critical indicators include the return rate of net assets, the growth rate of profit, the rate of service satisfaction, market share, production flexibility, and the green consensus. Among them, the green consensus, the growth rate of profit and the rate of service satisfaction form a virtuous circle, leading to the improvement of the overall performance of GSC.
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Cao, Min, and Bin Cui. "Negative Effects of Age at Menarche on Risk of Cardiometabolic Diseases in Adulthood: A Mendelian Randomization Study." Journal of Clinical Endocrinology & Metabolism 105, no. 2 (2019): 515–22. http://dx.doi.org/10.1210/clinem/dgz071.
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Abstract Context Observational studies have demonstrated that early menarche is associated with cardiometabolic diseases, but confounding factors make it difficult to infer causality. Objective We used Mendelian randomization (MR) to examine whether age at menarche (AAM) is causally associated with type 2 diabetes (T2D), coronary artery disease (CAD) and cardiometabolic traits. Design and Methods A 2-sample MR analysis was conducted using genome-wide association study (GWAS) summary statistics from the Diabetes Genetics Replication and Meta-analysis (DIAGRAM) consortium (n = 159 208) for T2D and the Coronary Artery Disease Genome-wide Replication and Meta-analysis plus the Coronary Artery Disease Genetics (CARDIoGRAMplusC4D) consortium (n = 184 305) for CAD. We used 122 instrumental variables (IVs) extracted from a published GWAS meta-analysis incorporating 182 416 women to determine the causal effect of AAM on cardiometabolic diseases, treating childhood and adult body mass index (BMI) as the confounders. Sensitivity analyses were also performed to detect the pleiotropy of the IVs. Results Employing the MR approach, we found that later AAM was associated with decreased risk of CAD (OR, 0.92 [95% CI, 0.88-0.96]; P = 2.06 × 10–4) in adults, as well as lower blood levels of log fasting insulin, log homeostatic model assessment of insulin resistance (HOMA-IR), log HOMA of β-cell function (HOMA-B), triglycerides, and diastolic blood pressure, but higher blood level of high-density lipoprotein. However, the associations were substantially attenuated after excluding BMI-related variants. MR analyses provide little evidence on the causal effect between AAM and T2D. Conclusions Our findings showed that AAM did not appear to have a causal effect on the risk of cardiometabolic diseases in adult life, as their associations observed in epidemiological studies might be largely mediated through excessive adiposity. We propose adiposity might be a primary target in future intervention strategy.
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Gan, Wei, Robert J. Clarke, Anubha Mahajan, et al. "Bone mineral density and risk of type 2 diabetes and coronary heart disease: A Mendelian randomization study." Wellcome Open Research 2 (August 22, 2017): 68. http://dx.doi.org/10.12688/wellcomeopenres.12288.1.
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Background: Observational studies have demonstrated that increased bone mineral density is associated with a higher risk of type 2 diabetes (T2D), but the relationship with risk of coronary heart disease (CHD) is less clear. Moreover, substantial uncertainty remains about the causal relevance of increased bone mineral density for T2D and CHD, which can be assessed by Mendelian randomisation studies. Methods: We identified 235 independent single nucleotide polymorphisms (SNPs) associated at p<5×10-8 with estimated heel bone mineral density (eBMD) in 116,501 individuals from the UK Biobank study, accounting for 13.9% of eBMD variance. For each eBMD-associated SNP, we extracted effect estimates from the largest available GWAS studies for T2D (DIAGRAM: n=26,676 T2D cases and 132,532 controls) and CHD (CARDIoGRAMplusC4D: n=60,801 CHD cases and 123,504 controls). A two-sample design using several Mendelian randomization approaches was used to investigate the causal relevance of eBMD for risk of T2D and CHD. In addition, we explored the relationship of eBMD, instrumented by the 235 SNPs, on 12 cardiovascular and metabolic risk factors. Finally, we conducted Mendelian randomization analysis in the reverse direction to investigate reverse causality. Results: Each one standard deviation increase in genetically instrumented eBMD (equivalent to 0.14 g/cm2) was associated with an 8% higher risk of T2D (odds ratio [OR] 1.08; 95% confidence interval [CI]: 1.02 to 1.14; p=0.012) and 5% higher risk of CHD (OR 1.05; 95%CI: 1.00 to 1.10; p=0.034). Consistent results were obtained in sensitivity analyses using several different Mendelian randomization approaches. Equivalent increases in eBMD were also associated with lower plasma levels of HDL-cholesterol and increased insulin resistance. Mendelian randomization in the reverse direction using 94 T2D SNPs or 52 CHD SNPs showed no evidence of reverse causality with eBMD. Conclusions: These findings suggest a causal relationship between elevated bone mineral density with risks of both T2D and CHD.