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Relevant bibliographies by topics / Causal relationship models

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Academic literature on the topic 'Causal relationship models'

Author: Grafiati

Published: 6 September 2023

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Journal articles on the topic "Causal relationship models"

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Belevich, M. "Relationship between standard and causal fluid models." Acta Mechanica 180, no. 1-4 (2005): 83–106. http://dx.doi.org/10.1007/s00707-005-0262-y.

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Ranstam, J., and J. A. Cook. "Causal relationship and confounding in statistical models." British Journal of Surgery 103, no. 11 (2016): 1445–46. http://dx.doi.org/10.1002/bjs.10241.

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Baetu, Tudor M. "Do Biopsychosocial Causal Models Rule Out Physicalism?" Journal of Consciousness Studies 29, no. 1 (2022): 6–29. http://dx.doi.org/10.53765/20512201.29.1.006.

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Donald Price and James Barrell, two eminent pain researchers, argue that every time an experiment demonstrates that a biological variable is causally relevant to a psychological outcome, we are entitled to further rule out a possible mind–brain identity or supervenience relationship. As experimental evidence for two-way causal links between biological and psychological variables accumulates, more and more identity and supervenience relationships are ruled out, suggesting that psychophysicalism is empirically better supported than physicalism. I raise an objection to this line of argumentation

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Malina, Stephen, Daniel Cizin, and David A. Knowles. "Deep mendelian randomization: Investigating the causal knowledge of genomic deep learning models." PLOS Computational Biology 18, no. 10 (2022): e1009880. http://dx.doi.org/10.1371/journal.pcbi.1009880.

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Multi-task deep learning (DL) models can accurately predict diverse genomic marks from sequence, but whether these models learn the causal relationships between genomic marks is unknown. Here, we describe Deep Mendelian Randomization (DeepMR), a method for estimating causal relationships between genomic marks learned by genomic DL models. By combining Mendelian randomization with in silico mutagenesis, DeepMR obtains local (locus specific) and global estimates of (an assumed) linear causal relationship between marks. In a simulation designed to test recovery of pairwise causal relations betwee

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Chvykov, Pavel, and Erik Hoel. "Causal Geometry." Entropy 23, no. 1 (2020): 24. http://dx.doi.org/10.3390/e23010024.

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Information geometry has offered a way to formally study the efficacy of scientific models by quantifying the impact of model parameters on the predicted effects. However, there has been little formal investigation of causation in this framework, despite causal models being a fundamental part of science and explanation. Here, we introduce causal geometry, which formalizes not only how outcomes are impacted by parameters, but also how the parameters of a model can be intervened upon. Therefore, we introduce a geometric version of “effective information”—a known measure of the informativeness of

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Haynes, Stephen N. "Causal models and the assessment-treatment relationship in behavior therapy." Journal of Psychopathology and Behavioral Assessment 10, no. 2 (1988): 171–83. http://dx.doi.org/10.1007/bf00962642.

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HALPERN, JOSEPH Y. "FROM CAUSAL MODELS TO COUNTERFACTUAL STRUCTURES." Review of Symbolic Logic 6, no. 2 (2012): 305–22. http://dx.doi.org/10.1017/s1755020312000305.

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AbstractGalles & Pearl (l998) claimed that “for recursive models, the causal model framework does not add any restrictions to counterfactuals, beyond those imposed by Lewis’s [possible-worlds] framework.” This claim is examined carefully, with the goal of clarifying the exact relationship between causal models and Lewis’s framework. Recursive models are shown to correspond precisely to a subclass of (possible-world) counterfactual structures. On the other hand, a slight generalization of recursive models, models where all equations have unique solutions, is shown to be incomparable in expr

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Guo, Guang, and Leah K. VanWey. "Sibship Size and Intellectual Development: Is the Relationship Causal?" American Sociological Review 64, no. 2 (1999): 169–87. http://dx.doi.org/10.1177/000312249906400202.

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Previous research has consistently found a negative statistical relationship between sibship size and children's intellectual development. Two explanations have been offered for this finding. The prevailing explanation is that the relationship is causal, suggesting that limiting family size would lead to more intelligent children. A second explanation maintains that the relationship is spurious—that one or more undetermined factors correlated with family size are causally related to intellectual development. Using data on children from the National Longitudinal Survey of Youth, we reexamine th

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Yen, Chi-Hsien (Eric), Haocong Cheng, Grace Yu-Chun Yen, Brian P. Bailey, and Yun Huang. "Narratives + Diagrams: An Integrated Approach for Externalizing and Sharing People's Causal Beliefs." Proceedings of the ACM on Human-Computer Interaction 5, CSCW2 (2021): 1–27. http://dx.doi.org/10.1145/3479588.

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Causal knowledge is of interest in many areas, such as statistics and machine learning, as it allows people and algorithms to predict outcomes and make data-driven decisions. Researchers in CSCW have proposed tools and workflows to externalize causal knowledge or beliefs from a group of people; however, most of the generated causal diagrams lack a deeper understanding of the causal mechanisms or could not capture diverse beliefs. By integrating narratives with causal diagrams, we implemented an interactive system that allows users to 1) write narratives to rationalize their perceived causal re

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CHU, BEI-TSENG B. "DIAGNOSIS WITH CONTINUOUS AND DISCRETE CAUSAL RELATIONSHIPS: KNOWLEDGE REPRESENTATION." International Journal of Pattern Recognition and Artificial Intelligence 06, no. 04 (1992): 731–51. http://dx.doi.org/10.1142/s0218001492000370.

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Most present research on diagnostic reasoning has dealt with discrete causal relationships. However, continuous causal relationships are frequently encountered in many applications, particularly in equipment/instrument diagnostic applications. This paper offers an integrated model of discrete and continuous causal relationships based on probability theory. Four types of continuous and discrete causal relationships are identified. For each type of causal relationship the following issues are addressed: its semantics and causation strength based on probability theory, and how causation strength

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Dissertations / Theses on the topic "Causal relationship models"

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Hagerty, Nicholas L. "Bayesian Network Modeling of Causal Relationships in Polymer Models." Miami University / OhioLINK, 2021. http://rave.ohiolink.edu/etdc/view?acc_num=miami1619009432971036.

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Tringides, Constantinos A. "Alternative formulations of joint model systems of departure time choice and mode choice for non-work trips." [Tampa, Fla.] : University of South Florida, 2004. http://purl.fcla.edu/fcla/etd/SFE0000240.

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Kasperskaya, Yulia. "Essays on causal performance measurement models." Doctoral thesis, Universitat Pompeu Fabra, 2007. http://hdl.handle.net/10803/7348.

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La tesis trata de los modelos de gestión modernos de naturaleza causal, entre los que destaca el Cuadro de Mando Integral (CMI). En primer lugar, se presenta un análisis conceptual su supuesto central, las relaciones causa-efecto. En segundo lugar, se ofrece un análisis estadístico de los supuestos del CMI. En tercer lugar, a partir dos casos de estudio de ayuntamientos, se compara y analiza la implementación del CMI en las organizaciones. El análisis conceptual indica que la complejidad, la incertidumbre y el carácter dinámico del entorno pueden obstaculizar la elaboración de modelos válidos

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Ye, Xin. "Development of models for understanding causal relationships among activity and travel variables." [Tampa, Fla] : University of South Florida, 2006. http://purl.fcla.edu/usf/dc/et/SFE0001842.

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Dobransky, Nicole Denise. "OPTIMIZING LEARNING THROUGH TEACHER-STUDENT RELATIONSHIPS: A TEST OF THE CAUSAL PROCESS STUDENT UNDERSTANDING MODEL." Lexington, Ky. : [University of Kentucky Libraries], 2008. http://hdl.handle.net/10225/959.

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Thesis (Ph. D.)--University of Kentucky, 2008.<br>Title from document title page (viewed on January 26, 2009). Document formatted into pages; contains: vii, 99 p. : ill. Includes abstract and vita. Includes bibliographical references (p. 87-96).

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Campbell, Lucy Jane. "Statistical models for time to event outcomes and determination of causal relationships in an observational HIV/TB study." Thesis, University of Cape Town, 2012. http://hdl.handle.net/11427/6570.

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Lamberts, Monique. "The relationship between stress levels and job satisfaction amongst high school educators in De Aar (Northern Cape)." Thesis, University of the Western Cape, 2011. http://etd.uwc.ac.za/index.php?module=etd&action=viewtitle&id=gen8Srv25Nme4_2086_1363786447.

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<p>A large number of studies show that educators are exposed to workloads that result particularly in stress. According to Olivier and Venter (2003), stress is considered to be the main factor contributing to job-related illnesses, early retirement, job dissatisfaction and absenteeism. Teaching, has without a doubt become a more demanding and stressful job. The lack of discipline in schools, abolishment of corporal punishment, large pupilteacher ratios and a new curriculum approach all contribute to raising the stress levels of teachers (Ngidi &amp<br>Sibaya, 2002). Stanton, Bachiochi, Robie,

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Lance, Charles E. "Evaluation of competing models of the causal relationships among job satisfaction and organizational commitment as precursors to voluntary employee turnover." Diss., Georgia Institute of Technology, 1985. http://hdl.handle.net/1853/29210.

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Brunelli, Renata Trevisan. "Análise do impacto de perturbações sobre medidas de qualidade de ajuste para modelos de equações estruturais." Universidade de São Paulo, 2012. http://www.teses.usp.br/teses/disponiveis/45/45133/tde-24032013-123415/.

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A Modelagem de Equações Estruturais (SEM, do inglês Structural Equation Modeling) é uma metodologia multivariada que permite estudar relações de causa/efeito e correlação entre um conjunto de variáveis (podendo ser elas observadas ou latentes), simultaneamente. A técnica vem se difundindo cada vez mais nos últimos anos, em diferentes áreas do conhecimento. Uma de suas principais aplicações é na conrmação de modelos teóricos propostos pelo pesquisador (Análise Fatorial Conrmatória). Existem diversas medidas sugeridas pela literatura que servem para avaliar o quão bom está o ajuste de um modelo

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Islam, Muhammad Saiful. "Modelling cost overrun risks in power plant projects." Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/125508/1/Muhammad%20Saiful_Islam_Thesis.pdf.

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Cost overruns in power plant projects frequently occur, and this very alarming phenomenon requires proper risk assessment and management in the early phase of power plant project development. A modified fuzzy group decision-making approach (FGDMA) was developed and the critical risks in different phases of thermal power plant project were identified. Further, a novel fuzzy canonical model (FCM) was developed and the complex causal risk-networks were modelled to understand the root causes of cost overruns. The benefits of this research to practitioners are such that it provides greater understa

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Books on the topic "Causal relationship models"

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Fell, John P. C. In search of a causal relationship between industrial output and employment in Ireland. Central Bank of Ireland, 1989.

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Varlamov, Oleg. Mivar databases and rules. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in th

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Varlamov, Oleg. 18 examples of mivar expert systems. INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1248446.

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Many years of research on mivar technologies of logical artificial intelligence have allowed us to create a new powerful, versatile and fast tool, which is called "multidimensional open gnoseological active net" — "multidimensional open gnoseological active net: MOGAN". This tool allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format, and it can be used to model cause-and-effect relationships in different subject areas and create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert system

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Goul, Pauline, and Usher, eds. Early Modern Écologies. Amsterdam University Press, 2020. http://dx.doi.org/10.5117/9789462985971.

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Early Modern Écologies is the first collective volume to offer perspectives on the relationship between contemporary ecological thought and early modern French literature. If Descartes spoke of humans as being ‘masters and possessors of Nature’ in the seventeenth century, the writers taken up in this volume arguably demonstrated a more complex and urgent understanding of the human relationship to our shared planet. Opening up a rich archive of literary and non-literary texts produced by Montaigne and his contemporaries, this volume foregrounds not how ecocriticism renews our understanding of a

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Paolella, Christopher. Human Trafficking in Medieval Europe. Amsterdam University Press, 2020. http://dx.doi.org/10.5117/9789463723336.

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Human trafficking has become a global concern over the last twenty years, but its violence has terrorized and traumatized its victims and survivors for millennia. This study examines the deep history of human trafficking from Late Antiquity to the Early Modern Period. It traces the evolution of trafficking patterns: the growth and decline of trafficking routes, the everchanging relationships between traffickers and authorities, and it examines the underlying causes that lead to vulnerability and thus to exploitation. As the reader will discover, the conditions that lead to human trafficking in

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Isakov, Vladimir. Speak the language of schemes. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1860649.

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Schematization and visualization are the necessary means to ensure the activity of a modern specialist. Schematization allows you to highlight the main thing in an object, to discover its constituent elements, to show their relationship, gives impetus to the construction of conceptual approaches. Visualization "dresses" schematic concepts in a bright, expressive artistic and graphic form. The handbook provides descriptions of the most popular means of analytical graphics - maps, graphs, tables, graphs, diagrams, flowcharts (algorithms), chronolents, maps, methodological schemes, etc. The ways

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Le Pelley, Mike E., Oren Griffiths, and Tom Beesley. Associative Accounts of Causal Cognition. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.2.

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Humans are clearly sensitive to causal structures—we can describe and understand causal mechanisms and make predictions based on them. But this chapter asks: Is causal learning always causal? Or might seemingly causal behavior sometimes be based on associations that merely encode the information that two events “go together,” not that one causes the other? This associative view supposes that people often (mis)interpret associations as supporting the existence of a causal relationship between events; they make the everyday mistake of confusing correlation with causation. To assess the validity

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Sutton, Margaret Rose. THE RELATIONSHIP AND PREDICTABILITY OF FIVE PSYCHOSOCIAL FACTORS IN CANCER PATIENTS' COPING PROCESSES: A TEST OF TWO PROPOSED CAUSAL MODELS. 1990.

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NANDE-VÁZQUEZ, Edgard Alfredo, Teodoro REYES-FONG, and Omar Alejandro PÉREZ-CRUZ. The Generalized Least Squares Method (GMM) as a tool for causal analysis of spending, budget management and electoral results. ECORFAN, 2021. http://dx.doi.org/10.35429/b.2021.8.1.130.

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In the different fields of science, many times, there is a need to estimate the associations between variables, as an approach to understanding the interaction of one as a function of the others. It is usually done by applying restrictive models, such as analysis of variance and linear regression. This type of analysis requires that the dependent variable be continuous, have a normal and constant distribution of the mean and variance. However, when the dependent variable is discrete or categorical, the linear model is not viable. Faced with this impediment, the theory of linear models arises a

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Holyoak, Keith J., and Hee Seung Lee. Inferring Causal Relations by Analogy. Edited by Michael R. Waldmann. Oxford University Press, 2017. http://dx.doi.org/10.1093/oxfordhb/9780199399550.013.25.

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When two situations share a common pattern of relationships among their constituent elements, people often draw an analogy between a familiar source analog and a novel target analog. This chapter reviews major subprocesses of analogical reasoning and discusses how analogical inference is guided by causal relations. Psychological evidence suggests that analogical inference often involves constructing and then running a causal model. It also provides some examples of analogies and models that have been used as tools in science education to foster understanding of critical causal relations. A Bay

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Book chapters on the topic "Causal relationship models"

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von Eckardstein, Arnold. "High Density Lipoproteins: Is There a Comeback as a Therapeutic Target?" In Prevention and Treatment of Atherosclerosis. Springer International Publishing, 2021. http://dx.doi.org/10.1007/164_2021_536.

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AbstractLow plasma levels of High Density Lipoprotein (HDL) cholesterol (HDL-C) are associated with increased risks of atherosclerotic cardiovascular disease (ASCVD). In cell culture and animal models, HDL particles exert multiple potentially anti-atherogenic effects. However, drugs increasing HDL-C have failed to prevent cardiovascular endpoints. Mendelian Randomization studies neither found any genetic causality for the associations of HDL-C levels with differences in cardiovascular risk. Therefore, the causal role and, hence, utility as a therapeutic target of HDL has been questioned. However, the biomarker “HDL-C” as well as the interpretation of previous data has several important limitations: First, the inverse relationship of HDL-C with risk of ASCVD is neither linear nor continuous. Hence, neither the-higher-the-better strategies of previous drug developments nor previous linear cause-effect relationships assuming Mendelian randomization approaches appear appropriate. Second, most of the drugs previously tested do not target HDL metabolism specifically so that the futile trials question the clinical utility of the investigated drugs rather than the causal role of HDL in ASCVD. Third, the cholesterol of HDL measured as HDL-C neither exerts nor reports any HDL function. Comprehensive knowledge of structure-function-disease relationships of HDL particles and associated molecules will be a pre-requisite, to test them for their physiological and pathogenic relevance and exploit them for the diagnostic and therapeutic management of individuals at HDL-associated risk of ASCVD but also other diseases, for example diabetes, chronic kidney disease, infections, autoimmune and neurodegenerative diseases.

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Cleophas, Ton J., and Aeilko H. Zwinderman. "Bayes and Causal Relationships." In Modern Bayesian Statistics in Clinical Research. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-92747-3_13.

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de Jong, Gjalt, and Bart Nooteboom. "The Theoretical Model." In The Causal Structure of Long-Term Supply Relationships. Springer US, 2000. http://dx.doi.org/10.1007/978-1-4615-4525-5_3.

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Esposito, Floriana, Donato Malerba, and Giovanni Semeraro. "Discovering Probabilistic Causal Relationships: A Comparison Between Two Methods." In Selecting Models from Data. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4612-2660-4_24.

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Gudlaugsson, Bjarnhedinn, Huda Dawood, Gobind Pillai, and Michael Short. "First Step Towards a System Dynamic Sustainability Assessment Model for Urban Energy Transition." In Springer Proceedings in Energy. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-63916-7_28.

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AbstractThis paper presents a conceptual model that describes the correlation between an urban energy system and sustainability. The model captures the complexity of the urban energy transition, and the task of achieving sustainable development needs to embrace all aspects of sustainability. This paper portrays the aspects of sustainability as four-dimensional—Environment, Economic, Society, and Technology. The relationship between these four dimensions and the urban energy system is presented in a simplified and aggregated-qualitative based causal-loop diagram. The causal-loop diagram illustrates the causal and interconnective relationships between the four dimensions and their different variables. The causal-loop diagram describes the complex dynamic relationships within a simple urban energy system. The paper also provides a brief description of balancing and reinforcing loops, with the causal-loop diagram present. The conceptual model along with the causal-loop diagrams visually illustrate the dynamic relationship between the four dimensions as well as highlights the complexity and challenging problems that decision-makers are facing today when it comes energy planning and energy system development.

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Entner, Doris, and Patrik O. Hoyer. "Discovering Unconfounded Causal Relationships Using Linear Non-Gaussian Models." In New Frontiers in Artificial Intelligence. Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-25655-4_17.

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Bakker, Bram, and Paul den Dulk. "Causal Relationships and Relationships between Levels: The Modes of Description Perspective." In Proceedings of the Twenty First Annual Conference of the Cognitive Science Society. Psychology Press, 2020. http://dx.doi.org/10.4324/9781410603494-13.

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Wake, Akira, and Herbert R. Morgan. "Human Disease Caused by Yersinia." In Host-Parasite Relationships and the Yersinia Model. Springer Berlin Heidelberg, 1986. http://dx.doi.org/10.1007/978-3-642-71344-6_20.

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Hair, Joseph F., G. Tomas M. Hult, Christian M. Ringle, Marko Sarstedt, Nicholas P. Danks, and Soumya Ray. "An Introduction to Structural Equation Modeling." In Classroom Companion: Business. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-80519-7_1.

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AbstractStructural equation modeling is a multivariate data analysis method for analyzing complex relationships among constructs and indicators. To estimate structural equation models, researchers generally draw on two methods: covariance-based SEM (CB-SEM) and partial least squares SEM (PLS-SEM). Whereas CB-SEM is primarily used to confirm theories, PLS represents a causal–predictive approach to SEM that emphasizes prediction in estimating models, whose structures are designed to provide causal explanations. PLS-SEM is also useful for confirming measurement models. This chapter offers a concise overview of PLS-SEM’s key characteristics and discusses the main differences compared to CB-SEM. The chapter also describes considerations when using PLS-SEM and highlights situations that favor its use compared to CB-SEM.

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Gao, Ya, Shaoxiong Ji, Tongxuan Zhang, Prayag Tiwari, and Pekka Marttinen. "Contextualized Graph Embeddings for Adverse Drug Event Detection." In Machine Learning and Knowledge Discovery in Databases. Springer International Publishing, 2023. http://dx.doi.org/10.1007/978-3-031-26390-3_35.

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AbstractAn adverse drug event (ADE) is defined as an adverse reaction resulting from improper drug use, reported in various documents such as biomedical literature, drug reviews, and user posts on social media. The recent advances in natural language processing techniques have facilitated automated ADE detection from documents. However, the contextualized information and relations among text pieces are less explored. This paper investigates contextualized language models and heterogeneous graph representations. It builds a contextualized graph embedding model for adverse drug event detection. We employ different convolutional graph neural networks and pre-trained contextualized embeddings as the building blocks. Experimental results show that our methods can improve the performance by comparing recent ADE detection models, suggesting that a text graph can capture causal relationships and dependency between different entities in a document.

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Conference papers on the topic "Causal relationship models"

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Perçin, Selçuk, Aykut Karakaya, and Seymur Ağazade. "The Relationship between Export and Innovation in Turkish Manufacturing Industry." In International Conference on Eurasian Economies. Eurasian Economists Association, 2015. http://dx.doi.org/10.36880/c06.01408.

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Posner’s (1961) “technological gap theory” and Vernon’s (1966) “product life cycle theory” predicts that innovation causes market power and facilitates export. In other side export encourages firms and provides more affirmative environment for innovative processes. These theoretical approaches have different predictions regarding the direction of causality between export and innovation. Using Two-Step System Generalized Moments of Method this study investigates causality relationship between export intensity and R&D intensity for the period 2008-2013 in Turkish Manufacturing Industry. Caus

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Sun, Schyler C., Bailu Jin, Zhuangkun Wei, and Weisi Guo. "Revealing the Excitation Causality between Climate and Political Violence via a Neural Forward-Intensity Poisson Process." In Thirty-First International Joint Conference on Artificial Intelligence {IJCAI-22}. International Joint Conferences on Artificial Intelligence Organization, 2022. http://dx.doi.org/10.24963/ijcai.2022/718.

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The causal mechanism between climate and political violence is fraught with complex mechanisms. Current quantitative causal models rely on one or more assumptions: (1) the climate drivers persistently generate conflict, (2) the causal mechanisms have a linear relationship with the conflict generation parameter, and/or (3) there is sufficient data to inform the prior distribution. Yet, we know conflict drivers often excite a social transformation process which leads to violence (e.g., drought forces agricultural producers to join urban militia), but further climate effects do not necessarily co

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Purmalis, Ritvars. "Cēloņsakarības konstatēšana mākslīgā intelekta darbībā." In Latvijas Universitātes 80. starptautiskā zinātniskā konference. LU Akadēmiskais apgāds, 2022. http://dx.doi.org/10.22364/juzk.80.14.

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While there is still a debate at European Union level as to which of the known models of civil liability should be used to determine a person’s civil liability for damage caused by an artificial intelligence-driven system, particular attention should be directed at the issues relating to the “transparency” and “explainability” of the operation of artificial intelligence-driven system. The purpose of this article is to provide a brief insight into the importance of establishing the causal relationship between the way in which the inputs (various datasets) available for the artificial intelligen

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Elmas, Bekir, and Ömer Esen. "Determining a Dynamic Relationship Between Stock Prices and Exchange Rates: An Empirical Study on Eurasia." In International Conference on Eurasian Economies. Eurasian Economists Association, 2010. http://dx.doi.org/10.36880/c01.00168.

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The stock price has a close relationship with some macroeconomic variables. As examples of the main macroeconomic variables can be shown that exchange rates, inflation, interest rate, growth rates. This paper empirically examined the relationship between the local stock market indexes and exchange rate (USD) in six Eurasian countries namely Turkey, Germany, France, Netherlands, Russia, France and India. The paper set out by testing existence of a long-term relationship between considered two variables using the Engle-Granger (1987), Johansen (1988, 1995) and Johansen-Juselius (1990) cointegrat

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Vilcu, Adrian, Ion Verzea, Mihaela Cojan, and Adrian Vilcu. "EDUCATIONAL SOFTWARE FOR THE OPTIMIZATION OF SAFETY IN OPERATION IN THE TEXTILE PROCESSES." In eLSE 2017. Carol I National Defence University Publishing House, 2017. http://dx.doi.org/10.12753/2066-026x-17-243.

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One of the present challenges of the textile production management consists in correlating the production- quality policies corroborated with the need to control and optimize the manufacturing process from the standpoint of the times of good operation and maintenance respectively. The studies undertaken until now have proved the necessity of a new approach of the causal relationship between safety in operation and production strategies, based on mathematical and neuronal modelling. The objective of our research consists in the determination of reliability/ maintainability relationship for a ma

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Catania, Giuseppe, and Silvio Sorrentino. "Experimental Identification of a Fractional Derivative Linear Model for Viscoelastic Materials." In ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2005. http://dx.doi.org/10.1115/detc2005-85725.

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Non integer, fractional order derivative rheological models are known to be very effective in describing the linear viscoelastic dynamic behaviour of mechanical structures made of polymers [1]. The application of fractional calculus to viscoelasticity can be physically consistent [2][3][4] and the resulting non integer order differential stress-strain constitutive relation provides good curve fitting properties, requires only a few parameters and leads to causal behaviour [5]. When using such models the solution of direct problems, i.e. the evaluation of time or frequency response from a known

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Dalte, Olha. "HYPER-HYPONYMIC RELATIONSHIPS BETWEEN PARONYMIC TERMS «CAUSAL» AND «CAUSATIVE»: CORPORA-BASED VERIFICATION." In Modern Science: Processes of Globalisation and Transformation. Publishing House “Baltija Publishing”, 2023. http://dx.doi.org/10.30525/978-9934-26-309-5-36.

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Meredith, David. "A CAUSAL RELATIONSHIP MODEL OF UNDERGRADUATE STUDENTS’ WILLINGNESS TO COMMUNICATE ENGLISH." In 35th International Academic Conference, Barcelona. International Institute of Social and Economic Sciences, 2018. http://dx.doi.org/10.20472/iac.2018.935.029.

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Li, Shuang, Si-Ze Hou, Yutong Yao, Yongqi Sun, and Bin Ding. "MMINN: Management-Model Informed Neural Network with Interpretability and Causal Relationship." In 2022 5th International Conference on Pattern Recognition and Artificial Intelligence (PRAI). IEEE, 2022. http://dx.doi.org/10.1109/prai55851.2022.9904239.

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Guo, Zhenghao, Verity M. McClelland, and Zoran Cvetkovic. "Unravelling Causal Relationships Between Cortex and Muscle with Errors-in-variables Models." In 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE, 2021. http://dx.doi.org/10.1109/embc46164.2021.9630485.

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Reports on the topic "Causal relationship models"

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Khvostina, Inesa, Serhiy Semerikov, Oleh Yatsiuk, Nadiia Daliak, Olha Romanko, and Ekaterina Shmeltser. Casual analysis of financial and operational risks of oil and gas companies in condition of emergent economy. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4120.

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The need to control the risk that accompanies businesses in their day- to-day operations, and at the same time changing economic conditions make risk management an almost indispensable element of economic life. Selection of the main aspects of the selected phases of the risk management process: risk identification and risk assessment are related to their direct relationship with the subject matter (risk identification to be managed; risk analysis leading to the establishment of a risk hierarchy, and, consequently, the definition of risk control’ methods) and its purpose (bringing the risk to a

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Rizzo, Tesalia. Shaping political trust through participatory governance in Lat in America. Inter-American Development Bank, 2021. http://dx.doi.org/10.18235/0003601.

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This paper critically assesses research that examines the link between participatory institutions and political trust in the context of developing countries, with a focus on Latin America. A significant limitation in the systematic accumulation of knowledge in this field is inattention to identifying a clear causal chain through which citizen participation shapes political, economic, and attitudinal outcomes such as political trust. This is particularly important in the Latin American case where constitutionally stated objectives of participatory governance include the improvement of citizen w

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Kneale, Dylan, James Thomas, Mukdarut Bangpan, Hugh Waddington, and David Gough. Causal chain analysis in systematic reviews of international development interventions. Centre for Excellence and Development Impact and Learning (CEDIL), 2018. http://dx.doi.org/10.51744/cip4.

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Understanding the extent to which an intervention ‘works’ can provide compelling evidence to decision-makers, although without an accompanying explanation of how an intervention works, this evidence can be difficult to apply in other settings, ultimately impeding its usefulness in making judicious and evidence-informed decisions. In this paper, we describe causal chain analysis as involving the development of a logic model, which outlines graphically a hypothesis of how an intervention leads to a change in an outcome. This logic model is then used to anchor subsequent decisions in the systemat

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Acosta, Karina. Locked up? The development and internal migration nexus in Colombia. Banco de la República, 2022. http://dx.doi.org/10.32468/dtseru.304.

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Although a sizable number of studies have been exploring the migration development nexus in international settings, there is still a reduced number on internal contexts in recent years. This research aims to estimate the causal effect of origin economic conditions on internal population migration using a time series of the Colombian states between 2012 and 2019. This analysis provides a macro perspective of associations and causation between population dynamics and development in the current changes observed using spatial interaction models. Likewise, it analyses the current portray of interna

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Montville, Thomas J., and Roni Shapira. Molecular Engineering of Pediocin A to Establish Structure/Function Relationships for Mechanistic Control of Foodborne Pathogens. United States Department of Agriculture, 1993. http://dx.doi.org/10.32747/1993.7568088.bard.

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This project relates the structure of the bacteriocin molecule (which is genetically determined) to its antimicrobial function. We have sequenced the 19,542 bp pediocin plasmid pMD136 and developed a genetic transfer system for pediococci. The pediocin A operon is complex, containing putative structural, immunity, processing, and transport genes. The deduced sequence of the pediocin A molecule contains 44 amino acids and has a predicted PI of 9.45. Mechanistic studies compared the interaction of pediocin PA-1 and nisin with Listeria monocytgenes cells and model lipid systems. While significant

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Ruvinsky, Alicia, Maria Seale, R. Salter, and Natàlia Garcia-Reyero. An ontology for an epigenetics approach to prognostics and health management. Engineer Research and Development Center (U.S.), 2023. http://dx.doi.org/10.21079/11681/46632.

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Techniques in prognostics and health management have advanced considerably in the last few decades, enabled by breakthroughs in computational methods and supporting technologies. These predictive models, whether data-driven or physics-based, target the modeling of a system’s aggregate performance. As such, they generalize assumptions about the modelled system’s components, and are thus limited in their ability to represent individual components and the dynamic environmental factors that affect composite system health. To address this deficiency, we have developed an epigenetics-inspired knowle

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Foeken, van, and Gresnigt. L51809 Buckling and Collapse of UOE Manufactured Steel Pipes. Pipeline Research Council International, Inc. (PRCI), 1998. http://dx.doi.org/10.55274/r0010236.

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In the past 20 years, much research has been conducted into buckling and collapse of pipelines under external pressure, bending or tension and combinations. Also many finite element analyses have been performed into the behavior of pipelines under these loads. The available test results show considerable scatter, which is considered to be caused by variations in the stress-strain relationship, the anisotropy of the steel, the Bauschinger effect, the geometrical deviations, the residual stresses, the test conditions, etc. The manufacturing method (seamless, UO, UOE) has a considerable influence

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Lawrence, David. UK trade and the war in Ukraine. Royal Institute of International Affairs, 2022. http://dx.doi.org/10.55317/9781784135379.

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- The UK is less exposed to the direct effects of Russia’s invasion of Ukraine than its European neighbours. However, the indirect and longer-term effects of the war on UK trade could still be significant. - Inflationary pressure worldwide will contribute to price rises in the UK, particularly for food and energy. The ongoing effects of both Brexit – which has caused cross-border supply frictions and worker shortages – and the COVID-19 pandemic – which led to pent-up domestic demand and further reduced the labour force – will only increase this upward pressure. - The war has prompted increased

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Watkins, Chris B., Susan Lurie, Amnon Lers, and Patricia L. Conklin. Involvement of Antioxidant Enzymes and Genes in the Resistance Mechanism to Postharvest Superficial Scald Development. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7586539.bard.

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The objective of this research project was to evaluate the involvement of antioxidant enzymes and genes in the resistance mechanism to postharvest superficial scald development using two primary systems: 1. Resistant and susceptible progenies of an apple cross between a scald resistant crab apple, ‘White Angel’ and a scald susceptible cultivar, ‘Rome Beauty’; 2. Heat-treatment of ‘Granny Smith’, which is known to reduce scald development in this cultivar. In 2002 we asked for, and received (October 14), permission to revise our initial objectives. The US side decided to expand their results to

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Zhang, Renduo, and David Russo. Scale-dependency and spatial variability of soil hydraulic properties. United States Department of Agriculture, 2004. http://dx.doi.org/10.32747/2004.7587220.bard.

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Water resources assessment and protection requires quantitative descriptions of field-scale water flow and contaminant transport through the subsurface, which, in turn, require reliable information about soil hydraulic properties. However, much is still unknown concerning hydraulic properties and flow behavior in heterogeneous soils. Especially, relationships of hydraulic properties changing with measured scales are poorly understood. Soil hydraulic properties are usually measured at a small scale and used for quantifying flow and transport in large scales, which causes misleading results. The

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