How difficult is inference of mammalian causal gene regulatory networks?
Directory of Open Access Journals (Sweden)
Djordje Djordjevic
Full Text Available Gene regulatory networks (GRNs play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect, which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference
How difficult is inference of mammalian causal gene regulatory networks?
Djordjevic, Djordje; Yang, Andrian; Zadoorian, Armella; Rungrugeecharoen, Kevin; Ho, Joshua W K
2014-01-01
Gene regulatory networks (GRNs) play a central role in systems biology, especially in the study of mammalian organ development. One key question remains largely unanswered: Is it possible to infer mammalian causal GRNs using observable gene co-expression patterns alone? We assembled two mouse GRN datasets (embryonic tooth and heart) and matching microarray gene expression profiles to systematically investigate the difficulties of mammalian causal GRN inference. The GRNs were assembled based on > 2,000 pieces of experimental genetic perturbation evidence from manually reading > 150 primary research articles. Each piece of perturbation evidence records the qualitative change of the expression of one gene following knock-down or over-expression of another gene. Our data have thorough annotation of tissue types and embryonic stages, as well as the type of regulation (activation, inhibition and no effect), which uniquely allows us to estimate both sensitivity and specificity of the inference of tissue specific causal GRN edges. Using these unprecedented datasets, we found that gene co-expression does not reliably distinguish true positive from false positive interactions, making inference of GRN in mammalian development very difficult. Nonetheless, if we have expression profiling data from genetic or molecular perturbation experiments, such as gene knock-out or signalling stimulation, it is possible to use the set of differentially expressed genes to recover causal regulatory relationships with good sensitivity and specificity. Our result supports the importance of using perturbation experimental data in causal network reconstruction. Furthermore, we showed that causal gene regulatory relationship can be highly cell type or developmental stage specific, suggesting the importance of employing expression profiles from homogeneous cell populations. This study provides essential datasets and empirical evidence to guide the development of new GRN inference methods for
Inferring the conservative causal core of gene regulatory networks
Directory of Open Access Journals (Sweden)
Emmert-Streib Frank
2010-09-01
Full Text Available Abstract Background Inferring gene regulatory networks from large-scale expression data is an important problem that received much attention in recent years. These networks have the potential to gain insights into causal molecular interactions of biological processes. Hence, from a methodological point of view, reliable estimation methods based on observational data are needed to approach this problem practically. Results In this paper, we introduce a novel gene regulatory network inference (GRNI algorithm, called C3NET. We compare C3NET with four well known methods, ARACNE, CLR, MRNET and RN, conducting in-depth numerical ensemble simulations and demonstrate also for biological expression data from E. coli that C3NET performs consistently better than the best known GRNI methods in the literature. In addition, it has also a low computational complexity. Since C3NET is based on estimates of mutual information values in conjunction with a maximization step, our numerical investigations demonstrate that our inference algorithm exploits causal structural information in the data efficiently. Conclusions For systems biology to succeed in the long run, it is of crucial importance to establish methods that extract large-scale gene networks from high-throughput data that reflect the underlying causal interactions among genes or gene products. Our method can contribute to this endeavor by demonstrating that an inference algorithm with a neat design permits not only a more intuitive and possibly biological interpretation of its working mechanism but can also result in superior results.
Ness, Robert O; Sachs, Karen; Vitek, Olga
2016-03-01
Causal inference, the task of uncovering regulatory relationships between components of biomolecular pathways and networks, is a primary goal of many high-throughput investigations. Statistical associations between observed protein concentrations can suggest an enticing number of hypotheses regarding the underlying causal interactions, but when do such associations reflect the underlying causal biomolecular mechanisms? The goal of this perspective is to provide suggestions for causal inference in large-scale experiments, which utilize high-throughput technologies such as mass-spectrometry-based proteomics. We describe in nontechnical terms the pitfalls of inference in large data sets and suggest methods to overcome these pitfalls and reliably find regulatory associations. PMID:26731284
Pearl, Judea
2000-03-01
Written by one of the pre-eminent researchers in the field, this book provides a comprehensive exposition of modern analysis of causation. It shows how causality has grown from a nebulous concept into a mathematical theory with significant applications in the fields of statistics, artificial intelligence, philosophy, cognitive science, and the health and social sciences. Pearl presents a unified account of the probabilistic, manipulative, counterfactual and structural approaches to causation, and devises simple mathematical tools for analyzing the relationships between causal connections, statistical associations, actions and observations. The book will open the way for including causal analysis in the standard curriculum of statistics, artifical intelligence, business, epidemiology, social science and economics. Students in these areas will find natural models, simple identification procedures, and precise mathematical definitions of causal concepts that traditional texts have tended to evade or make unduly complicated. This book will be of interest to professionals and students in a wide variety of fields. Anyone who wishes to elucidate meaningful relationships from data, predict effects of actions and policies, assess explanations of reported events, or form theories of causal understanding and causal speech will find this book stimulating and invaluable.
Prior knowledge driven Granger causality analysis on gene regulatory network discovery
Yao, Shun; Yoo, Shinjae; Yu, Dantong
2015-01-01
Background Our study focuses on discovering gene regulatory networks from time series gene expression data using the Granger causality (GC) model. However, the number of available time points (T) usually is much smaller than the number of target genes (n) in biological datasets. The widely applied pairwise GC model (PGC) and other regularization strategies can lead to a significant number of false identifications when n>>T. Results In this study, we proposed a new method, viz., CGC-2SPR (CGC ...
Directory of Open Access Journals (Sweden)
Christopher L Plaisier
2009-09-01
Full Text Available We hypothesized that a common SNP in the 3' untranslated region of the upstream transcription factor 1 (USF1, rs3737787, may affect lipid traits by influencing gene expression levels, and we investigated this possibility utilizing the Mexican population, which has a high predisposition to dyslipidemia. We first associated rs3737787 genotypes in Mexican Familial Combined Hyperlipidemia (FCHL case/control fat biopsies, with global expression patterns. To identify sets of co-expressed genes co-regulated by similar factors such as transcription factors, genetic variants, or environmental effects, we utilized weighted gene co-expression network analysis (WGCNA. Through WGCNA in the Mexican FCHL fat biopsies we identified two significant Triglyceride (TG-associated co-expression modules. One of these modules was also associated with FCHL, the other FCHL component traits, and rs3737787 genotypes. This USF1-regulated FCHL-associated (URFA module was enriched for genes involved in lipid metabolic processes. Using systems genetics procedures we identified 18 causal candidate genes in the URFA module. The FCHL causal candidate gene fatty acid desaturase 3 (FADS3 was associated with TGs in a recent Caucasian genome-wide significant association study and we replicated this association in Mexican FCHL families. Based on a USF1-regulated FCHL-associated co-expression module and SNP rs3737787, we identify a set of causal candidate genes for FCHL-related traits. We then provide evidence from two independent datasets supporting FADS3 as a causal gene for FCHL and elevated TGs in Mexicans.
US Department of Energy wind turbine candidate site program: the regulatory process
Energy Technology Data Exchange (ETDEWEB)
Greene, M.R.; York, K.R.
1982-06-01
Sites selected in 1979 as tentative sites for installation of a demonstration MOD-2 turbine are emphasized. Selection as a candidate site in this program meant that the US Department of Energy (DOE) designated the site as eligible for a DOE-purchased and installed meteorological tower. The regulatory procedures involved in the siting and installation of these meteorological towers at the majority of the candidate sites are examined. An attempt is also made, in a preliminary fashion, to identify the legal and regulatory procedures that would be required to put up a turbine at each of these candidate sites. The information provided on each of these sites comes primarily from utility representatives, supplemented by conversations with state and local officials. The major findings are summarized on the following: federal requirements, state requirements, local requirements, land ownership, wind rights, and public attitudes.
Vigorito, Elena; Kuchenbaecker, Karoline B.; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A.; Andrulis, Irene L.; Arun, Banu K.; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A.; Campbell, Ian; Chan, Salina B.; Claes, Kathleen B. M.; Cohn, David E.; Cook, Jackie; Daly, Mary B.; Damiola, Francesca; Davidson, Rosemarie; de Pauw, Antoine; Delnatte, Capucine; Diez, Orland; Domchek, Susan M.; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F.; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D. Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D.; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A.; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K.; Goldgar, David E.; Hake, Christopher R.; Hansen, Thomas V. O.; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B. L.; Houdayer, Claude; Hulick, Peter J.; Imyanitov, Evgeny N.; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M.; Vijai, Joseph; Karlan, Beth Y.; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L.; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R.; Montagna, Marco; Nathanson, Katherine L.; Neuhausen, Susan L.; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I.; Ong, Kai-ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M.; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C.; Rookus, Matti A.; Ross, Eric A.; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F.; Slavin, Thomas P.; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I.; Tea, Muy-Kheng; Teixeira, Manuel R.; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J.; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N.; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J.; Greene, Mark H.; Couch, Fergus J.; Offit, Kenneth; Pharoah, Paul D. P.; Chenevix-Trench, Georgia; Antoniou, Antonis C.
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10−16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10−6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population. PMID:27463617
Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan; Adlard, Julian; Agnarsson, Bjarni A; Andrulis, Irene L; Arun, Banu K; Barjhoux, Laure; Belotti, Muriel; Benitez, Javier; Berger, Andreas; Bojesen, Anders; Bonanni, Bernardo; Brewer, Carole; Caldes, Trinidad; Caligo, Maria A; Campbell, Ian; Chan, Salina B; Claes, Kathleen B M; Cohn, David E; Cook, Jackie; Daly, Mary B; Damiola, Francesca; Davidson, Rosemarie; Pauw, Antoine de; Delnatte, Capucine; Diez, Orland; Domchek, Susan M; Dumont, Martine; Durda, Katarzyna; Dworniczak, Bernd; Easton, Douglas F; Eccles, Diana; Edwinsdotter Ardnor, Christina; Eeles, Ros; Ejlertsen, Bent; Ellis, Steve; Evans, D Gareth; Feliubadalo, Lidia; Fostira, Florentia; Foulkes, William D; Friedman, Eitan; Frost, Debra; Gaddam, Pragna; Ganz, Patricia A; Garber, Judy; Garcia-Barberan, Vanesa; Gauthier-Villars, Marion; Gehrig, Andrea; Gerdes, Anne-Marie; Giraud, Sophie; Godwin, Andrew K; Goldgar, David E; Hake, Christopher R; Hansen, Thomas V O; Healey, Sue; Hodgson, Shirley; Hogervorst, Frans B L; Houdayer, Claude; Hulick, Peter J; Imyanitov, Evgeny N; Isaacs, Claudine; Izatt, Louise; Izquierdo, Angel; Jacobs, Lauren; Jakubowska, Anna; Janavicius, Ramunas; Jaworska-Bieniek, Katarzyna; Jensen, Uffe Birk; John, Esther M; Vijai, Joseph; Karlan, Beth Y; Kast, Karin; Investigators, KConFab; Khan, Sofia; Kwong, Ava; Laitman, Yael; Lester, Jenny; Lesueur, Fabienne; Liljegren, Annelie; Lubinski, Jan; Mai, Phuong L; Manoukian, Siranoush; Mazoyer, Sylvie; Meindl, Alfons; Mensenkamp, Arjen R; Montagna, Marco; Nathanson, Katherine L; Neuhausen, Susan L; Nevanlinna, Heli; Niederacher, Dieter; Olah, Edith; Olopade, Olufunmilayo I; Ong, Kai-Ren; Osorio, Ana; Park, Sue Kyung; Paulsson-Karlsson, Ylva; Pedersen, Inge Sokilde; Peissel, Bernard; Peterlongo, Paolo; Pfeiler, Georg; Phelan, Catherine M; Piedmonte, Marion; Poppe, Bruce; Pujana, Miquel Angel; Radice, Paolo; Rennert, Gad; Rodriguez, Gustavo C; Rookus, Matti A; Ross, Eric A; Schmutzler, Rita Katharina; Simard, Jacques; Singer, Christian F; Slavin, Thomas P; Soucy, Penny; Southey, Melissa; Steinemann, Doris; Stoppa-Lyonnet, Dominique; Sukiennicki, Grzegorz; Sutter, Christian; Szabo, Csilla I; Tea, Muy-Kheng; Teixeira, Manuel R; Teo, Soo-Hwang; Terry, Mary Beth; Thomassen, Mads; Tibiletti, Maria Grazia; Tihomirova, Laima; Tognazzo, Silvia; van Rensburg, Elizabeth J; Varesco, Liliana; Varon-Mateeva, Raymonda; Vratimos, Athanassios; Weitzel, Jeffrey N; McGuffog, Lesley; Kirk, Judy; Toland, Amanda Ewart; Hamann, Ute; Lindor, Noralane; Ramus, Susan J; Greene, Mark H; Couch, Fergus J; Offit, Kenneth; Pharoah, Paul D P; Chenevix-Trench, Georgia; Antoniou, Antonis C
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 mutation carriers. Genotype data were available for 15,252 (2,462 ovarian cancer cases) BRCA1 and 8,211 (631 ovarian cancer cases) BRCA2 mutation carriers. Following genotype imputation, ovarian cancer associations were assessed for 4,873 and 5,020 SNPs in BRCA1 and BRCA 2 mutation carriers respectively, within a retrospective cohort analytical framework. In BRCA1 mutation carriers one set of eight correlated candidate causal variants for ovarian cancer risk modification was identified (top SNP rs10124837, HR: 0.73, 95%CI: 0.68 to 0.79, p-value 2× 10-16). These variants were located up to 20 kb upstream of BNC2. In BRCA2 mutation carriers one region, up to 45 kb upstream of BNC2, and containing 100 correlated SNPs was identified as candidate causal (top SNP rs62543585, HR: 0.69, 95%CI: 0.59 to 0.80, p-value 1.0 × 10-6). The candidate causal in BRCA1 mutation carriers did not include the strongest associated variant at this locus in the general population. In sum, we identified a set of candidate causal variants in a region that encompasses the BNC2 transcription start site. The ovarian cancer association at 9p22.2 may be mediated by different variants in BRCA1 mutation carriers and in the general population. Thus, potentially different mechanisms may underlie ovarian cancer risk for mutation carriers and the general population. PMID:27463617
Guo, Hui; Fortune, Mary D; Burren, Oliver S; Schofield, Ellen; Todd, John A; Wallace, Chris
2015-06-15
The genes and cells that mediate genetic associations identified through genome-wide association studies (GWAS) are only partially understood. Several studies that have investigated the genetic regulation of gene expression have shown that disease-associated variants are over-represented amongst expression quantitative trait loci (eQTL) variants. Evidence for colocalisation of eQTL and disease causal variants can suggest causal genes and cells for these genetic associations. Here, we used colocalisation analysis to investigate whether 595 genetic associations to ten immune-mediated diseases are consistent with a causal variant that regulates, in cis, gene expression in resting B cells, and in resting and stimulated monocytes. Previously published candidate causal genes were over-represented amongst genes exhibiting colocalisation (odds ratio > 1.5), and we identified evidence for colocalisation (posterior odds > 5) between cis eQTLs in at least one cell type and at least one disease for six genes: ADAM15, RGS1, CARD9, LTBR, CTSH and SYNGR1. We identified cell-specific effects, such as for CTSH, the expression of which in monocytes, but not in B cells, may mediate type 1 diabetes and narcolepsy associations in the chromosome 15q25.1 region. Our results demonstrate the utility of integrating genetic studies of disease and gene expression for highlighting causal genes and cell types. PMID:25743184
Regulatory assessment of the competence of shift supervisor and control room operator candidates
International Nuclear Information System (INIS)
For the last few years, initiatives have been underway to obtain assurance of CANDU stations operating staff competence by evaluating the training programs in place at each station, in addition to the well established approach of direct examination of Shift Supervisor and Control Room Operator candidates. The implementation of these initiatives has benefited from a process of organized consultation with senior representatives of the three nuclear utilities. AECB staff meet regularly with these people as members of a group named the Standing Inter-Utility/Regulatory Working Group, which was itself formed through a regulatory initiative in 1990. The examinations conducted by the AECB have also undergone significant changes to improve their effectiveness, taking into account the shortcomings of the past written examination approach to assessment, the introduction of the training program evaluation activities and the developments in the utilities training programs in the last decade. The main change so far has been the introduction of regular simulator-based examinations in 1993. However, the number and overall duration of regulatory examinations have been reduced. Further changes are planned for the near future, particularly in relation to the examination of Shift Supervisor candidates. This paper provides detailed information on the regulatory initiatives that have been taken so far and those which are still planned. Particular attention will be given to the process of examination using full-scope simulators and the experience which has been acquired since its introduction. (author)
Meta-analysis on gene regulatory networks discovered by pairwise Granger causality
Tam, GHF; Hung, YS; Chang, C.
2013-01-01
Identifying regulatory genes partaking in disease development is important to medical advances. Since gene expression data of multiple experiments exist, combining results from multiple gene regulatory network discoveries offers higher sensitivity and specificity. However, data for multiple experiments on the same problem may not possess the same set of genes, and hence many existing combining methods are not applicable. In this paper, we approach this problem using a number of meta-analysis ...
DEFF Research Database (Denmark)
Vigorito, Elena; Kuchenbaecker, Karoline B; Beesley, Jonathan;
2016-01-01
Population-based genome wide association studies have identified a locus at 9p22.2 associated with ovarian cancer risk, which also modifies ovarian cancer risk in BRCA1 and BRCA2 mutation carriers. We conducted fine-scale mapping at 9p22.2 to identify potential causal variants in BRCA1 and BRCA2 ...
DEFF Research Database (Denmark)
Rasmussen, Lauge Baungaard
2006-01-01
The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method......The lecture note explains how to use the causal mapping method as well as the theoretical framework aoosciated to the method...
Chi, Do Minh
2001-01-01
We advance a famous principle - causality principle - but under a new view. This principle is a principium automatically leading to most fundamental laws of the nature. It is the inner origin of variation, rules evolutionary processes of things, and the answer of the quest for ultimate theories of the Universe.
Mirzaei, Hamid; Knijnenburg, Theo A.; Kim, Bong; Robinson, Max; Picotti, Paola; Carter, Gregory W.; Li, Song; Dilworth, David J.; Eng, Jimmy K.; Aitchison, John D.; Shmulevich, Ilya; Galitski, Timothy; Aebersold, Ruedi; Ranish, Jeffrey
2013-01-01
Regulation of gene expression involves the orchestrated interaction of a large number of proteins with transcriptional regulatory elements in the context of chromatin. Our understanding of gene regulation is limited by the lack of a protein measurement technology that can systematically detect and quantify the ensemble of proteins associated with the transcriptional regulatory elements of specific genes. Here, we introduce a set of selected reaction monitoring (SRM) assays for the systematic ...
Khursheed, Kejhal; Wilm, Thomas P; Cashman, Christine; Quinn, John P; Bubb, Vivien J; Moss, Diana J
2015-01-21
Fused-In-Sarcoma (FUS) is a candidate gene for neurological disorders including motor neurone disease and Parkinson׳s disease in addition to various types of cancer. Recently it has been reported that over expression of FUS causes motor neurone disease in mouse models hence mutations leading to changes in gene expression may contribute to the development of neurodegenerative disease. Genome evolutionary conservation was used to predict important cis-acting DNA regulators of the FUS gene promoter that direct transcription. The putative regulators identified were analysed in reporter gene assays in cells and in chick embryos. Our analysis indicated in addition to regulatory domains 5' of the transcriptional start site an important regulatory domain resides in intron 1 of the gene itself. This intronic domain functioned both in cell lines and in vivo in the neural tube of the chick embryo including developing motor neurones. Our data suggest the interaction of multiple domains including intronic domains are involved in expression of FUS. A better understanding of the regulation of expression of FUS may give insight into how its stimulus inducible expression may be associated with neurological disorders. PMID:25451114
Frisch, Mathias
2014-01-01
Much has been written on the role of causal notions and causal reasoning in the so-called 'special sciences' and in common sense. But does causal reasoning also play a role in physics? Mathias Frisch argues that, contrary to what influential philosophical arguments purport to show, the answer is yes. Time-asymmetric causal structures are as integral a part of the representational toolkit of physics as a theory's dynamical equations. Frisch develops his argument partly through a critique of anti-causal arguments and partly through a detailed examination of actual examples of causal notions in physics, including causal principles invoked in linear response theory and in representations of radiation phenomena. Offering a new perspective on the nature of scientific theories and causal reasoning, this book will be of interest to professional philosophers, graduate students, and anyone interested in the role of causal thinking in science.
Electoral Systems and Candidate Selection
Hazan, Reuven Y.; Voerman, Gerrit
2006-01-01
Electoral systems at the national level and candidate selection methods at the party level are connected, maybe not causally but they do influence each other. More precisely, the electoral system constrains and conditions the parties' menu of choices concerning candidate selection. Moreover, in ligh
Reconstructing Causal Biological Networks through Active Learning.
Cho, Hyunghoon; Berger, Bonnie; Peng, Jian
2016-01-01
Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs), which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments. PMID:26930205
Reconstructing Causal Biological Networks through Active Learning.
Directory of Open Access Journals (Sweden)
Hyunghoon Cho
Full Text Available Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are of great practical interest, especially in the study of complex biological systems and their quantitative properties. In this work, we present an efficient, information-theoretic active learning algorithm for Gaussian Bayesian networks (GBNs, which serve as important models for gene regulatory networks. In addition to providing linear-algebraic insights unique to GBNs, leading to significant runtime improvements, we demonstrate the effectiveness of our method on data simulated with GBNs and the DREAM4 network inference challenge data sets. Our method generally leads to faster recovery of underlying network structure and faster convergence to final distribution of confidence scores over candidate graph structures using the full data, in comparison to random selection of intervention experiments.
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
Humans are fundamentally primed for making causal attributions based on correlations. This implies that researchers must be careful to present their results in a manner that inhibits unwarranted causal attribution. In this paper, we present the results of an experiment that suggests regression...... models should note carefully both their models’ identifying assumptions and which causal attributions can safely be concluded from their analysis....
Chi, Do Minh
1999-01-01
We research the natural causality of the Universe. We find that the equation of causality provides very good results on physics. That is our first endeavour and success in describing a quantitative expression of the law of causality. Hence, our theoretical point suggests ideas to build other laws including the law of the Universe's evolution.
Davidson, Russell
2013-01-01
The understanding of causal chains and mechanisms is an essential part of any scientific activity that aims at better explanation of its subject matter, and better understanding of it. While any account of causality requires that a cause should precede its effect, accounts of causality inphysics are complicated by the fact that the role of time in current theoretical physics has evolved very substantially throughout the twentieth century. In this article, I review the status of time and causa...
Causality in Europeanization Research
DEFF Research Database (Denmark)
Lynggaard, Kennet
2012-01-01
Discourse analysis as a methodology is perhaps not readily associated with substantive causality claims. At the same time the study of discourses is very much the study of conceptions of causal relations among a set, or sets, of agents. Within Europeanization research we have seen endeavours to......, it suggests that discourse analysis and the study of causality are by no means opposites. The study of Europeanization discourses may even be seen as an essential step in the move towards claims of causality in Europeanization research. This chapter deals with the question of how we may move from the...
International Nuclear Information System (INIS)
A set of spatially homogeneous and isotropic cosmological geometries generated by a class of non-perfect is investigated fluids. The irreversibility if this system is studied in the context of causal thermodynamics which provides a useful mechanism to conform to the non-violation of the causal principle. (author)
Causality in Classical Electrodynamics
Savage, Craig
2012-01-01
Causality in electrodynamics is a subject of some confusion, especially regarding the application of Faraday's law and the Ampere-Maxwell law. This has led to the suggestion that we should not teach students that electric and magnetic fields can cause each other, but rather focus on charges and currents as the causal agents. In this paper I argue…
DEFF Research Database (Denmark)
Nielsen, Max; Jensen, Frank; Setälä, Jari;
2011-01-01
to fish demand. On the German market for farmed trout and substitutes, it is found that supply sources, i.e. aquaculture and fishery, are not the only determinant of causality. Storing, tightness of management and aggregation level of integrated markets might also be important. The methodological......This article focuses on causality in demand. A methodology where causality is imposed and tested within an empirical co-integrated demand model, not prespecified, is suggested. The methodology allows different causality of different products within the same demand system. The methodology is applied...... implication is that more explicit focus on causality in demand analyses provides improved information. The results suggest that frozen trout forms part of a large European whitefish market, where prices of fresh trout are formed on a relatively separate market. Redfish is a substitute on both markets. The...
Causality and Composite Structure
Joglekar, Satish D
2007-01-01
We study the question of whether a composite structure of elementary particles, with a length scale $1/\\Lambda$, can leave observable effects of non-locality and causality violation at higher energies (but $\\lesssim \\Lambda$). We formulate a model-independent approach based on Bogoliubov-Shirkov formulation of causality. We analyze the relation between the fundamental theory (of finer constituents) and the derived theory (of composite particles). We assume that the fundamental theory is causal and formulate a condition which must be fulfilled for the derived theory to be causal. We analyze the condition and exhibit possibilities which fulfil and which violate the condition. We make comments on how causality violating amplitudes can arise.
Directory of Open Access Journals (Sweden)
Thomas eWidlok
2014-11-01
Full Text Available Cognitive Scientists interested in causal cognition increasingly search for evidence from non-WEIRD people but find only very few cross-cultural studies that specifically target causal cognition. This article suggests how information about causality can be retrieved from ethnographic monographs, specifically from ethnographies that discuss agency and concepts of time. Many apparent cultural differences with regard to causal cognition dissolve when cultural extensions of agency and personhood to non-humans are taken into account. At the same time considerable variability remains when we include notions of time, linearity and sequence. The article focuses on ethnographic case studies from Africa but provides a more general perspective on the role of ethnography in research on the diversity and universality of causal cognition.
Dynamics and causality constraints
International Nuclear Information System (INIS)
The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Causality in field theory are kinematical constraints dynamically implemented via solutions of the field equation, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away with deep implications to the nature of physicals interactions. (author)
Dynamics and causality constraints
De Souza, M M
2000-01-01
The physical meaning and the geometrical interpretation of causality implementation in classical field theories are discussed. Local causality are kinematical constraints dynamically implemented via solutions of the field equations, but in a limit of zero-distance from the field sources part of these constraints carries a dynamical content that explains old problems of classical electrodynamics away and implies on deep implications to the nature of physical interactions.
Arrighi, Pablo
2016-01-01
Consider a graph having quantum systems lying at each node. Suppose that the whole thing evolves in discrete time steps, according to a global, unitary causal operator. By causal we mean that information can only propagate at a bounded speed, with respect to the distance given by the graph. Suppose, moreover, that the graph itself is subject to the evolution, and may be driven to be in a quantum superposition of graphs---in accordance to the superposition principle. We show that these unitary causal operators must decompose as a finite-depth circuit of local unitary gates. This unifies a result on Quantum Cellular Automata with another on Reversible Causal Graph Dynamics. Along the way we formalize a notion of causality which is valid in the context of quantum superpositions of time-varying graphs, and has a number of good properties. Keywords: Quantum Lattice Gas Automata, Block-representation, Curtis-Hedlund-Lyndon, No-signalling, Localizability, Quantum Gravity, Quantum Graphity, Causal Dynamical Triangula...
Causal Inference and Causal Explanation with Background Knowledge
Meek, Christopher
2013-01-01
This paper presents correct algorithms for answering the following two questions; (i) Does there exist a causal explanation consistent with a set of background knowledge which explains all of the observed independence facts in a sample? (ii) Given that there is such a causal explanation what are the causal relationships common to every such causal explanation?
Causality and the Doppler Peaks
Turok, Neil
1996-01-01
Could cosmic structure have formed by the action of causal physics within the standard hot big bang, or was a prior period of inflation required? Recently there has been some discussion of whether causal sources could reproduce the pattern of Doppler peaks of the standard scale-invariant adiabatic theory. This paper gives a rigorous definition of causality, and a causal decomposition of a general source. I present an example of a simple causal source which mimics the standard adiabatic theory...
Rideout, D
2002-01-01
The Causal Set approach to quantum gravity asserts that spacetime, at its smallest length scale, has a discrete structure. This discrete structure takes the form of a locally finite order relation, where the order, corresponding with the macroscopic notion of spacetime causality, is taken to be a fundamental aspect of nature. After an introduction to the Causal Set approach, this thesis considers a simple toy dynamics for causal sets. Numerical simulations of the model provide evidence for the existence of a continuum limit. While studying this toy dynamics, a picture arises of how the dynamics can be generalized in such a way that the theory could hope to produce more physically realistic causal sets. By thinking in terms of a stochastic growth process, and positing some fundamental principles, we are led almost uniquely to a family of dynamical laws (stochastic processes) parameterized by a countable sequence of coupling constants. This result is quite promising in that we now know how to speak of dynamics ...
Rideout, D P
2001-01-01
The Causal Set approach to quantum gravity asserts that spacetime, at its smallest length scale, has a discrete structure. This discrete structure takes the form of a locally finite order relation, where the order, corresponding with the macroscopic notion of spacetime causality, is taken to be a fundamental aspect of nature. After an introduction to the Causal Set approach, this thesis considers a simple toy dynamics for causal sets. Numerical simulations of the model provide evidence for the existence of a continuum limit. While studying this toy dynamics, a picture arises of how the dynamics can be generalized in such a way that the theory could hope to produce more physically realistic causal sets. By thinking in terms of a stochastic growth process, and positing some fundamental principles, we are led almost uniquely to a family of dynamical laws (stochastic processes) parameterized by a countable sequence of coupling constants. This result is quite promising in that we now know how to speak of dynamics ...
Biased causal inseparable game
Bhattacharya, Some Sankar
2015-01-01
Here we study the \\emph{causal inseparable} game introduced in [\\href{http://www.nature.com/ncomms/journal/v3/n10/full/ncomms2076.html}{Nat. Commun. {\\bf3}, 1092 (2012)}], but it's biased version. Two separated parties, Alice and Bob, generate biased bits (say input bit) in their respective local laboratories. Bob generates another biased bit (say decision bit) which determines their goal: whether Alice has to guess Bob's bit or vice-verse. Under the assumption that events are ordered with respect to some global causal relation, we show that the success probability of this biased causal game is upper bounded, giving rise to \\emph{biased causal inequality} (BCI). In the \\emph{process matrix} formalism, which is locally in agreement with quantum physics but assume no global causal order, we show that there exist \\emph{inseparable} process matrices that violate the BCI for arbitrary bias in the decision bit. In such scenario we also derive the maximal violation of the BCI under local operations involving tracele...
International Nuclear Information System (INIS)
We discuss the geometry of trees endowed with a causal structure using the conventional framework of equilibrium statistical mechanics. We show how this ensemble is related to popular growing network models. In particular we demonstrate that on a class of afine attachment kernels the two models are identical but they can differ substantially for other choice of weights. We show that causal trees exhibit condensation even for asymptotically linear kernels. We derive general formulae describing the degree distribution, the ancestor--descendant correlation and the probability that a randomly chosen node lives at a given geodesic distance from the root. It is shown that the Hausdorff dimension dH of the causal networks is generically infinite. (author)
Bialas, Piotr
2003-10-01
We discuss the geometry of trees endowed with a causal structure using the conventional framework of equilibrium statistical mechanics. We show how this ensemble is related to popular growing network models. In particular we demonstrate that on a class of afine attachment kernels the two models are identical but they can differ substantially for other choice of weights. We show that causal trees exhibit condensation even for asymptotically linear kernels. We derive general formulae describing the degree distribution, the ancestor--descendant correlation and the probability that a randomly chosen node lives at a given geodesic distance from the root. It is shown that the Hausdorff dimension dH of the causal networks is generically infinite.
Arrighi, Pablo
2012-01-01
We generalize the theory of Cellular Automata to arbitrary, time-varying graphs. In other words we formalize, and prove theorems about, the intuitive idea of a labelled graph which evolves in time - but under the natural constraint that information can only ever be transmitted at a bounded speed, with respect to the distance given by the graph. The notion of translation-invariance is also generalized. The definition we provide for these `causal graph dynamics' is simple and axiomatic. The theorems we provide also show that it is robust. For instance, causal graph dynamics are stable under composition and under restriction to radius one. In the finite case some fundamental facts of Cellular Automata theory carry through: causal graph dynamics admit a characterization as continuous functions and they are stable under inversion. The provided examples suggest a wide range of applications of this mathematical object, from complex systems science to theoretical physics. Keywords: Dynamical networks, Boolean network...
Causal inference in econometrics
Kreinovich, Vladik; Sriboonchitta, Songsak
2016-01-01
This book is devoted to the analysis of causal inference which is one of the most difficult tasks in data analysis: when two phenomena are observed to be related, it is often difficult to decide whether one of them causally influences the other one, or whether these two phenomena have a common cause. This analysis is the main focus of this volume. To get a good understanding of the causal inference, it is important to have models of economic phenomena which are as accurate as possible. Because of this need, this volume also contains papers that use non-traditional economic models, such as fuzzy models and models obtained by using neural networks and data mining techniques. It also contains papers that apply different econometric models to analyze real-life economic dependencies.
Brustein, Ram
2000-01-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic space-like region. This "causal entropy bound", scaling as the square root of EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various "critical" situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso's holographic bound are stronger than Bekenstein's, while naive holography is too tight, and hence typically wrong.
Brustein, R; Veneziano, G
1999-01-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic space-like region. This "causal entropy bound", scaling as the square root of EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various "critical" situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso...
Czech Academy of Sciences Publication Activity Database
Hvorecký, Juraj
2012-01-01
Roč. 19, Supp.2 (2012), s. 64-69. ISSN 1335-0668 R&D Projects: GA ČR(CZ) GAP401/12/0833 Institutional support: RVO:67985955 Keywords : conciousness * free will * determinism * causality Subject RIV: AA - Philosophy ; Religion
Tachyon Kinematics and causality
International Nuclear Information System (INIS)
The chronological order of the events along a space-like path is not invariant under Lorentz transformations, as wellknown. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stuckelberg-Feynman switching procedure (SWP) has been invoked as the suitable tool to eliminate those anomalies. The application of the SWP does eliminate the motions backwards in time, but interchanges the roles of source and dector. This fact triggered the proposal of a host of causal paradoxes. Till now, however, it has not been recognized that such paradoxes can be sensibly discussed (and completely solved, at least in microphysics) only after having properly developed the tachyon relativistic mechanics. We start by showing how to apply the SWP, both in the case of ordiry Special Relativity, and in the case with tachyons. Then, we carefully exploit the kinematics of the tachyon-exchange between to (ordinary) bodies. Being finally able to tackle the tachyon-causality problem, we successively solve the paradoxes: (i) by Tolman-Regge; (ii) by Pirani; (iii) by Edmonds; (iv) by Bell. At last, we discuss a further, new paradox associated with the transmission of signals by modulated tachyon beams
Liang, X San
2014-01-01
Given two time series, can one tell, in a rigorous and quantitative way, the cause and effect between them? Based on a recently rigorized physical notion namely information flow, we arrive at a concise formula and give this challenging question, which is of wide concern in different disciplines, a positive answer. Here causality is measured by the time rate of change of information flowing from one series, say, X2, to another, X1. The measure is asymmetric between the two parties and, particularly, if the process underlying X1 does not depend on X2, then the resulting causality from X2 to X1 vanishes. The formula is tight in form, involving only the commonly used statistics, sample covariances. It has been validated with touchstone series purportedly generated with one-way causality. It has also been applied to the investigation of real world problems; an example presented here is the cause-effect relation between two climate modes, El Ni\\~no and Indian Ocean Dipole, which have been linked to the hazards in f...
Osborn, John C
2013-01-01
ABSTRACT The Candidate is an attempt to marry elements of journalism and gaming into a format that both entertains and educates the player. The Google-AP Scholarship, a new scholarship award that is given to several journalists a year to work on projects at the threshold of technology and journalism, funded the project. The objective in this prototype version of the game is to put the player in the shoes of a congressional candidate during an off-year election, specificall...
Revisiting Causality in Markov Chains
Shojaee, Abbas
2016-01-01
Identifying causal relationships is a key premise of scientific research. The growth of observational data in different disciplines along with the availability of machine learning methods offers the possibility of using an empirical approach to identifying potential causal relationships, to deepen our understandings of causal behavior and to build theories accordingly. Conventional methods of causality inference from observational data require a considerable length of time series data to capture cause-effect relationship. We find that potential causal relationships can be inferred from the composition of one step transition rates to and from an event. Also known as Markov chain, one step transition rates are a commonly available resource in different scientific disciplines. Here we introduce a simple, effective and computationally efficient method that we termed 'Causality Inference using Composition of Transitions CICT' to reveal causal structure with high accuracy. We characterize the differences in causes,...
Quantum information causality.
Pitalúa-García, Damián
2013-05-24
How much information can a transmitted physical system fundamentally communicate? We introduce the principle of quantum information causality, which states the maximum amount of quantum information that a quantum system can communicate as a function of its dimension, independently of any previously shared quantum physical resources. We present a new quantum information task, whose success probability is upper bounded by the new principle, and show that an optimal strategy to perform it combines the quantum teleportation and superdense coding protocols with a task that has classical inputs. PMID:23745844
Inferring deterministic causal relations
Daniusis, Povilas; Janzing, Dominik; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard
2012-01-01
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the ...
Causal inference based on counterfactuals
Directory of Open Access Journals (Sweden)
Höfler M
2005-09-01
Full Text Available Abstract Background The counterfactual or potential outcome model has become increasingly standard for causal inference in epidemiological and medical studies. Discussion This paper provides an overview on the counterfactual and related approaches. A variety of conceptual as well as practical issues when estimating causal effects are reviewed. These include causal interactions, imperfect experiments, adjustment for confounding, time-varying exposures, competing risks and the probability of causation. It is argued that the counterfactual model of causal effects captures the main aspects of causality in health sciences and relates to many statistical procedures. Summary Counterfactuals are the basis of causal inference in medicine and epidemiology. Nevertheless, the estimation of counterfactual differences pose several difficulties, primarily in observational studies. These problems, however, reflect fundamental barriers only when learning from observations, and this does not invalidate the counterfactual concept.
Experimental test of nonlocal causality.
Ringbauer, Martin; Giarmatzi, Christina; Chaves, Rafael; Costa, Fabio; White, Andrew G; Fedrizzi, Alessandro
2016-08-01
Explaining observations in terms of causes and effects is central to empirical science. However, correlations between entangled quantum particles seem to defy such an explanation. This implies that some of the fundamental assumptions of causal explanations have to give way. We consider a relaxation of one of these assumptions, Bell's local causality, by allowing outcome dependence: a direct causal influence between the outcomes of measurements of remote parties. We use interventional data from a photonic experiment to bound the strength of this causal influence in a two-party Bell scenario, and observational data from a Bell-type inequality test for the considered models. Our results demonstrate the incompatibility of quantum mechanics with a broad class of nonlocal causal models, which includes Bell-local models as a special case. Recovering a classical causal picture of quantum correlations thus requires an even more radical modification of our classical notion of cause and effect. PMID:27532045
Relationship of causal effects in a causal chain and related inference
Institute of Scientific and Technical Information of China (English)
GENG; Zhi; HE; Yangbo; WANG; Xueli
2004-01-01
This paper discusses the relationship among the total causal effect and local causal effects in a causal chain and identifiability of causal effects. We show a transmission relationship of causal effects in a causal chain. According to the relationship, we give an approach to eliminating confounding bias through controlling for intermediate variables in a causal chain.
Relativistic hydrodynamics - causality and stability
Ván, P.; Biró, T. S.
2007-01-01
Causality and stability in relativistic dissipative hydrodynamics are important conceptual issues. We argue that causality is not restricted to hyperbolic set of differential equations. E.g. heat conduction equation can be causal considering the physical validity of the theory. Furthermore we propose a new concept of relativistic internal energy that clearly separates the dissipative and non-dissipative effects. We prove that with this choice we remove all known instabilities of the linear re...
Causality Statistical Perspectives and Applications
Berzuini, Carlo; Bernardinell, Luisa
2012-01-01
A state of the art volume on statistical causality Causality: Statistical Perspectives and Applications presents a wide-ranging collection of seminal contributions by renowned experts in the field, providing a thorough treatment of all aspects of statistical causality. It covers the various formalisms in current use, methods for applying them to specific problems, and the special requirements of a range of examples from medicine, biology and economics to political science. This book:Provides a clear account and comparison of formal languages, concepts and models for statistical causality. Addr
Inferring deterministic causal relations
Daniusis, Povilas; Mooij, Joris; Zscheischler, Jakob; Steudel, Bastian; Zhang, Kun; Schoelkopf, Bernhard
2012-01-01
We consider two variables that are related to each other by an invertible function. While it has previously been shown that the dependence structure of the noise can provide hints to determine which of the two variables is the cause, we presently show that even in the deterministic (noise-free) case, there are asymmetries that can be exploited for causal inference. Our method is based on the idea that if the function and the probability density of the cause are chosen independently, then the distribution of the effect will, in a certain sense, depend on the function. We provide a theoretical analysis of this method, showing that it also works in the low noise regime, and link it to information geometry. We report strong empirical results on various real-world data sets from different domains.
Causal Inference and Developmental Psychology
Foster, E. Michael
2010-01-01
Causal inference is of central importance to developmental psychology. Many key questions in the field revolve around improving the lives of children and their families. These include identifying risk factors that if manipulated in some way would foster child development. Such a task inherently involves causal inference: One wants to know whether…
Friederich, Simon
2015-01-01
There is widespread belief in a tension between quantum theory and special relativity, motivated by the idea that quantum theory violates J. S. Bell's criterion of local causality, which is meant to implement the causal structure of relativistic space-time. This paper argues that if one takes the es
Expert Causal Reasoning and Explanation.
Kuipers, Benjamin
The relationship between cognitive psychologists and researchers in artificial intelligence carries substantial benefits for both. An ongoing investigation in causal reasoning in medical problem solving systems illustrates this interaction. This paper traces a dialectic of sorts in which three different types of causal resaoning for medical…
The Visual Causality Analyst: An Interactive Interface for Causal Reasoning.
Wang, Jun; Mueller, Klaus
2016-01-01
Uncovering the causal relations that exist among variables in multivariate datasets is one of the ultimate goals in data analytics. Causation is related to correlation but correlation does not imply causation. While a number of casual discovery algorithms have been devised that eliminate spurious correlations from a network, there are no guarantees that all of the inferred causations are indeed true. Hence, bringing a domain expert into the casual reasoning loop can be of great benefit in identifying erroneous casual relationships suggested by the discovery algorithm. To address this need we present the Visual Causal Analyst-a novel visual causal reasoning framework that allows users to apply their expertise, verify and edit causal links, and collaborate with the causal discovery algorithm to identify a valid causal network. Its interface consists of both an interactive 2D graph view and a numerical presentation of salient statistical parameters, such as regression coefficients, p-values, and others. Both help users in gaining a good understanding of the landscape of causal structures particularly when the number of variables is large. Our framework is also novel in that it can handle both numerical and categorical variables within one unified model and return plausible results. We demonstrate its use via a set of case studies using multiple practical datasets. PMID:26529703
["Karoshi" and causal relationships].
Hamajima, N
1992-08-01
This paper aims to introduce a measure for use by physicians for stating the degree of probable causal relationship for "Karoshi", ie, a sudden death from cerebrovascular diseases or ischemic heart diseases under occupational stresses, as well as to give a brief description for legal procedures associated with worker's compensation and civil trial in Japan. It is a well-used measure in epidemiology, "attributable risk percent (AR%)", which can be applied to describe the extent of contribution to "Karoshi" of the excess occupational burdens the deceased worker was forced to bear. Although several standards such as average occupational burdens for the worker, average occupational burdens for an ordinary worker, burdens in a nonoccupational life, and a complete rest, might be considered for the AR% estimation, the average occupational burdens for an ordinary worker should normally be utilized as a standard for worker's compensation. The adoption of AR% could be helpful for courts to make a consistent judgement whether "Karoshi" cases are compensatable or not. PMID:1392028
Principal stratification in causal inference.
Frangakis, Constantine E; Rubin, Donald B
2002-03-01
Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential values of that posttreatment variable tinder each of the treatments being compared. Principal effects are causal effects within a principal stratum. The key property of principal strata is that they are not affected by treatment assignment and therefore can be used just as any pretreatment covariate. such as age category. As a result, the central property of our principal effects is that they are always causal effects and do not suffer from the complications of standard posttreatment-adjusted estimands. We discuss briefly that such principal causal effects are the link between three recent applications with adjustment for posttreatment variables: (i) treatment noncompliance, (ii) missing outcomes (dropout) following treatment noncompliance. and (iii) censoring by death. We then attack the problem of surrogate or biomarker endpoints, where we show, using principal causal effects, that all current definitions of surrogacy, even when perfectly true, do not generally have the desired interpretation as causal effects of treatment on outcome. We go on to forrmulate estimands based on principal stratification and principal causal effects and show their superiority. PMID:11890317
CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer
Thompson, Deborah J; O'Mara, Tracy A; Glubb, Dylan M; Painter, Jodie N; Cheng, Timothy; Folkerd, Elizabeth; Doody, Deborah; Dennis, Joe; Webb, Penelope M; Gorman, Maggie; Martin, Lynn; Hodgson, Shirley; Michailidou, Kyriaki; Tyrer, Jonathan P; Maranian, Mel J; Hall, Per; Czene, Kamila; Darabi, Hatef; Li, Jingmei; Fasching, Peter A; Hein, Alexander; Beckmann, Matthias W; Ekici, Arif B; Dörk, Thilo; Hillemanns, Peter; Dürst, Matthias; Runnebaum, Ingo; Zhao, Hui; Depreeuw, Jeroen; Schrauwen, Stefanie; Amant, Frederic; Goode, Ellen L; Fridley, Brooke L; Dowdy, Sean C; Winham, Stacey J; Salvesen, Helga B; Trovik, Jone; Njolstad, Tormund S; Werner, Henrica M J; Ashton, Katie; Proietto, Tony; Otton, Geoffrey; Carvajal-Carmona, Luis; Tham, Emma; Liu, Tao; Mints, Miriam; Scott, Rodney J; McEvoy, Mark; Attia, John; Holliday, Elizabeth G; Montgomery, Grant W; Martin, Nicholas G; Nyholt, Dale R; Henders, Anjali K; Hopper, John L; Traficante, Nadia; Ruebner, Matthias; Swerdlow, Anthony J; Burwinkel, Barbara; Brenner, Hermann; Meindl, Alfons; Brauch, Hiltrud; Lindblom, Annika; Lambrechts, Diether; Chang-Claude, Jenny; Couch, Fergus J; Giles, Graham G; Kristensen, Vessela N; Cox, Angela; Bolla, Manjeet K; Wang, Qin; Bojesen, Stig E; Shah, Mitul; Luben, Robert; Khaw, Kay-Tee; Pharoah, Paul D P; Dunning, Alison M; Tomlinson, Ian; Dowsett, Mitch; Easton, Douglas F; Spurdle, Amanda B
2016-01-01
Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E2) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37 925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8×10−11). SNP rs727479 was also among those most strongly associated with circulating E2 concentrations in 2767 post-menopausal controls (P=7.4×10−8). The observed endometrial cancer odds ratio per rs727479 A-allele (1.15, CI=1.11–1.21) is compatible with that predicted by the observed effect on E2 concentrations (1.09, CI=1.03–1.21), consistent with the hypothesis that endometrial cancer risk is driven by E2. From 28 candidate-causal SNPs, 12 co-located with three putative gene-regulatory elements and their risk alleles associated with higher CYP19A1 expression in bioinformatical analyses. For both phenotypes, the associations with rs727479 were stronger among women with a higher BMI (Pinteraction=0.034 and 0.066 respectively), suggesting a biologically plausible gene-environment interaction. PMID:26574572
Classical planning and causal implicatures
DEFF Research Database (Denmark)
Blackburn, Patrick Rowan; Benotti, Luciana
In this paper we motivate and describe a dialogue manager (called Frolog) which uses classical planning to infer causal implicatures. A causal implicature is a type of Gricean relation implicature, a highly context dependent form of inference. As we shall see, causal implicatures are important for...... generate clarification requests"; as a result we can model task-oriented dialogue as an interactive process locally structured by negotiation of the underlying task. We give several examples of Frolog-human dialog, discuss the limitations imposed by the classical planning paradigm, and indicate the...
Functional equations with causal operators
Corduneanu, C
2003-01-01
Functional equations encompass most of the equations used in applied science and engineering: ordinary differential equations, integral equations of the Volterra type, equations with delayed argument, and integro-differential equations of the Volterra type. The basic theory of functional equations includes functional differential equations with causal operators. Functional Equations with Causal Operators explains the connection between equations with causal operators and the classical types of functional equations encountered by mathematicians and engineers. It details the fundamentals of linear equations and stability theory and provides several applications and examples.
On causality of extreme events
Zanin, Massimiliano
2016-01-01
Multiple metrics have been developed to detect causality relations between data describing the elements constituting complex systems, all of them considering their evolution through time. Here we propose a metric able to detect causality within static data sets, by analysing how extreme events in one element correspond to the appearance of extreme events in a second one. The metric is able to detect both linear and non-linear causalities; to analyse both cross-sectional and longitudinal data sets; and to discriminate between real causalities and correlations caused by confounding factors. We validate the metric through synthetic data, dynamical and chaotic systems, and data representing the human brain activity in a cognitive task.
Causal reasoning with mental models
Khemlani, Sangeet S.; Barbey, Aron K.; Johnson-Laird, Philip N
2014-01-01
This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews e...
Consciousness and the "Causal Paradox"
Velmans, Max
1996-01-01
Viewed from a first-person perspective consciousness appears to be necessary for complex, novel human activity - but viewed from a third-person perspective consciousness appears to play no role in the activity of brains, producing a "causal paradox". To resolve this paradox one needs to distinguish consciousness of processing from consciousness accompanying processing or causing processing. Accounts of consciousness/brain causal interactions switch between first- and third-person perspectives...
Realist Magic : Objects, Ontology, Causality
Morton, Timothy
2013-01-01
Object-oriented ontology offers a startlingly fresh way to think about causality that takes into account developments in physics since 1900. Causality, argues, Object Oriented Ontology (OOO), is aesthetic. In this book, Timothy Morton explores what it means to say that a thing has come into being, that it is persisting, and that it has ended. Drawing from examples in physics, biology, ecology, art, literature and music, Morton demonstrates the counterintuitive yet elegant explanatory power of...
Correlation Measure Equivalence in Dynamic Causal Structures
Gyongyosi, Laszlo
2016-01-01
We prove an equivalence transformation between the correlation measure functions of the causally-unbiased quantum gravity space and the causally-biased standard space. The theory of quantum gravity fuses the dynamic (nonfixed) causal structure of general relativity and the quantum uncertainty of quantum mechanics. In a quantum gravity space, the events are causally nonseparable and all time bias vanishes, which makes it no possible to use the standard causally-biased entropy and the correlation measure functions. Since a corrected causally-unbiased entropy function leads to an undefined, obscure mathematical structure, in our approach the correction is made in the data representation of the causally-unbiased space. We prove that the standard causally-biased entropy function with a data correction can be used to identify correlations in dynamic causal structures. As a corollary, all mathematical properties of the causally-biased correlation measure functions are preserved in the causally-unbiased space. The eq...
Commutative deformations of general relativity: nonlocality, causality, and dark matter
de Vegvar, P. G. N.
2016-01-01
Hopf algebra methods are applied to study Drinfeld twists of (3+1)-diffeomorphisms and deformed general relativity on \\emph{commutative} manifolds. A classical nonlocality length scale is produced above which standard light cone causality emerges. We introduce a sector of matter fields to generate selfconsistent Abelian Drinfeld twists in a background independent manner and study their discrete and gauge symmetries. They naturally give rise to dark matter candidates, possibly including ground...
Causality, causality, causality: the view of education inputs and outputs from economics
Lisa Barrow; Cecilia Elena Rouse
2005-01-01
Educators and policy makers are increasingly intent on using scientifically-based evidence when making decisions about education policy. Thus, education research today must necessarily be focused on identifying the causal relationships between education inputs and student outcomes. In this paper we discuss methodologies for estimating the causal effect of resources on education outcomes; we also review what we believe to be the best evidence from economics on a few important inputs: spending,...
Environmental Regulations and Livestock Production Levels: What is the Direction of Causality?
Herath, Deepananda P.B.; Weersink, Alfons; Thrikawala, Sunil
2006-01-01
Fundamental to the assertion that environmental regulatory standards are strategically set by decentralized authorities and consequently firms respond to spatial differences in regulatory standards is the underline causal relationship. Establishing the cause-effect association between regulatory standard setting and industry response is essential to justify the existence of the pollution haven and the potential for a race to the bottom. In this paper using 25 years data of the livestock produ...
Causality in physiological signals.
Müller, Andreas; Kraemer, Jan F; Penzel, Thomas; Bonnemeier, Hendrik; Kurths, Jürgen; Wessel, Niels
2016-05-01
Health is one of the most important non-material assets and thus also has an enormous influence on material values, since treating and preventing diseases is expensive. The number one cause of death worldwide today originates in cardiovascular diseases. For these reasons the aim of understanding the functions and the interactions of the cardiovascular system is and has been a major research topic throughout various disciplines for more than a hundred years. The purpose of most of today's research is to get as much information as possible with the lowest possible effort and the least discomfort for the subject or patient, e.g. via non-invasive measurements. A family of tools whose importance has been growing during the last years is known under the headline of coupling measures. The rationale for this kind of analysis is to identify the structure of interactions in a system of multiple components. Important information lies for example in the coupling direction, the coupling strength, and occurring time lags. In this work, we will, after a brief general introduction covering the development of cardiovascular time series analysis, introduce, explain and review some of the most important coupling measures and classify them according to their origin and capabilities in the light of physiological analyses. We will begin with classical correlation measures, go via Granger-causality-based tools, entropy-based techniques (e.g. momentary information transfer), nonlinear prediction measures (e.g. mutual prediction) to symbolic dynamics (e.g. symbolic coupling traces). All these methods have contributed important insights into physiological interactions like cardiorespiratory coupling, neuro-cardio-coupling and many more. Furthermore, we will cover tools to detect and analyze synchronization and coordination (e.g. synchrogram and coordigram). As a last point we will address time dependent couplings as identified using a recent approach employing ensembles of time series. The
Hierarchical organisation of causal graphs
International Nuclear Information System (INIS)
This paper deals with the design of a supervision system using a hierarchy of models formed by graphs, in which the variables are the nodes and the causal relations between the variables of the arcs. To obtain a representation of the variables evolutions which contains only the relevant features of their real evolutions, the causal relations are completed with qualitative transfer functions (QTFs) which produce roughly the behaviour of the classical transfer functions. Major improvements have been made in the building of the hierarchical organization. First, the basic variables of the uppermost level and the causal relations between them are chosen. The next graph is built by adding intermediary variables to the upper graph. When the undermost graph has been built, the transfer functions parameters corresponding to its causal relations are identified. The second task consists in the upwelling of the information from the undermost graph to the uppermost one. A fusion procedure of the causal relations has been designed to compute the QFTs relevant for each level. This procedure aims to reduce the number of parameters needed to represent an evolution at a high level of abstraction. These techniques have been applied to the hierarchical modelling of nuclear process. (authors). 8 refs., 12 figs
The continuum limit of causal fermion systems from Planck scale structures to macroscopic physics
Finster, Felix
2016-01-01
This monograph introduces the basic concepts of the theory of causal fermion systems, a recent approach to the description of fundamental physics. The theory yields quantum mechanics, general relativity and quantum field theory as limiting cases and is therefore a candidate for a unified physical theory. From the mathematical perspective, causal fermion systems provide a general framework for describing and analyzing non-smooth geometries and "quantum geometries". The dynamics is described by a novel variational principle, called the causal action principle. In addition to the basics, the book provides all the necessary mathematical background and explains how the causal action principle gives rise to the interactions of the standard model plus gravity on the level of second-quantized fermionic fields coupled to classical bosonic fields. The focus is on getting a mathematically sound connection between causal fermion systems and physical systems in Minkowski space. The book is intended for graduate students e...
Causal reasoning with mental models.
Khemlani, Sangeet S; Barbey, Aron K; Johnson-Laird, Philip N
2014-01-01
This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex. PMID:25389398
Causal reasoning with mental models
Directory of Open Access Journals (Sweden)
Sangeet eKhemlani
2014-10-01
Full Text Available This paper outlines the model-based theory of causal reasoning. It postulates that the core meanings of causal assertions are deterministic and refer to temporally-ordered sets of possibilities: A causes B to occur means that given A, B occurs, whereas A enables B to occur means that given A, it is possible for B to occur. The paper shows how mental models represent such assertions, and how these models underlie deductive, inductive, and abductive reasoning yielding explanations. It reviews evidence both to corroborate the theory and to account for phenomena sometimes taken to be incompatible with it. Finally, it reviews neuroscience evidence indicating that mental models for causal inference are implemented within lateral prefrontal cortex.
Causal Models for Risk Management
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Neysis Hernández Díaz
2013-12-01
Full Text Available In this work a study about the process of risk management in major schools in the world. The project management tools worldwide highlights the need to redefine risk management processes. From the information obtained it is proposed the use of causal models for risk analysis based on information from the project or company, say risks and the influence thereof on the costs, human capital and project requirements and detect the damages of a number of tasks without tribute to the development of the project. A study on the use of causal models as knowledge representation techniques causal, among which are the Fuzzy Cognitive Maps (DCM and Bayesian networks, with the most favorable MCD technique to use because it allows modeling the risk information witho ut having a knowledge base either itemize.
On Causality in Dynamical Systems
Harnack, Daniel
2016-01-01
Identification of causal links is fundamental for the analysis of complex systems. In dynamical systems, however, nonlinear interactions may hamper separability of subsystems which poses a challenge for attempts to determine the directions and strengths of their mutual influences. We found that asymmetric causal influences between parts of a dynamical system lead to characteristic distortions in the mappings between the attractor manifolds reconstructed from respective local observables. These distortions can be measured in a model-free, data-driven manner. This approach extends basic intuitions about cause-effect relations to deterministic dynamical systems and suggests a mathematically well defined explanation of results obtained from previous methods based on state space reconstruction.
Cohomology with causally restricted supports
Khavkine, Igor
2014-01-01
De Rham cohomology with spacelike compact and timelike compact supports has recently been noticed to be of importance for understanding the structure of classical and quantum field theories on curved spacetimes. We compute these cohomology groups for globally hyperbolic spacetimes in terms of their standard de Rham cohomologies. The calculation exploits the fact that the de Rham-d'Alambert wave operator can be extended to a chain map that is homotopic to zero and that its causal Green function fits into a convenient exact sequence. This method extends also to the Calabi (or Killing-Riemann-Bianchi) complex and possibly other differential complexes. We also discuss generalized causal structures and functoriality.
On the Axioms of Causal Set Theory
Dribus, Benjamin F
2013-01-01
This paper offers suggested improvements to the causal sets program in discrete gravity, which treats spacetime geometry as an emergent manifestation of causal structure at the fundamental scale. This viewpoint, which I refer to as the causal metric hypothesis, is summarized by Rafael Sorkin's phrase, "order plus number equals geometry." Proposed improvements include recognition of a generally nontransitive causal relation more fundamental than the causal order, an improved local picture of causal structure, development and use of relation space methods, and a new background-independent version of the histories approach to quantum theory. Besides causal set theory, \\`a la Bombelli, Lee, Meyer, and Sorkin, this effort draws on Isham's topos-theoretic framework for physics, Sorkin's quantum measure theory, Finkelstein's causal nets, and Grothendieck's structural principles. This approach circumvents undesirable structural features in causal set theory, such as the permeability of maximal antichains, studied by ...
Synergy and redundancy in the Granger causal analysis of dynamical networks
International Nuclear Information System (INIS)
We analyze, by means of Granger causality (GC), the effect of synergy and redundancy in the inference (from time series data) of the information flow between subsystems of a complex network. While we show that fully conditioned GC (CGC) is not affected by synergy, the pairwise analysis fails to prove synergetic effects. In cases when the number of samples is low, thus making the fully conditioned approach unfeasible, we show that partially conditioned GC (PCGC) is an effective approach if the set of conditioning variables is properly chosen. Here we consider two different strategies (based either on informational content for the candidate driver or on selecting the variables with highest pairwise influences) for PCGC and show that, depending on the data structure, either one or the other might be equally valid. On the other hand, we observe that fully conditioned approaches do not work well in the presence of redundancy, thus suggesting the strategy of separating the pairwise links in two subsets: those corresponding to indirect connections of the CGC (which should thus be excluded) and links that can be ascribed to redundancy effects and, together with the results from the fully connected approach, provide a better description of the causality pattern in the presence of redundancy. Finally we apply these methods to two different real datasets. First, analyzing electrophysiological data from an epileptic brain, we show that synergetic effects are dominant just before seizure occurrences. Second, our analysis applied to gene expression time series from HeLa culture shows that the underlying regulatory networks are characterized by both redundancy and synergy. (paper)
Ward, Lucas D; Kellis, Manolis
2016-01-01
More than 90% of common variants associated with complex traits do not affect proteins directly, but instead the circuits that control gene expression. This has increased the urgency of understanding the regulatory genome as a key component for translating genetic results into mechanistic insights and ultimately therapeutics. To address this challenge, we developed HaploReg (http://compbio.mit.edu/HaploReg) to aid the functional dissection of genome-wide association study (GWAS) results, the prediction of putative causal variants in haplotype blocks, the prediction of likely cell types of action, and the prediction of candidate target genes by systematic mining of comparative, epigenomic and regulatory annotations. Since first launching the website in 2011, we have greatly expanded HaploReg, increasing the number of chromatin state maps to 127 reference epigenomes from ENCODE 2012 and Roadmap Epigenomics, incorporating regulator binding data, expanding regulatory motif disruption annotations, and integrating expression quantitative trait locus (eQTL) variants and their tissue-specific target genes from GTEx, Geuvadis, and other recent studies. We present these updates as HaploReg v4, and illustrate a use case of HaploReg for attention deficit hyperactivity disorder (ADHD)-associated SNPs with putative brain regulatory mechanisms. PMID:26657631
Granger Causality and Unit Roots
DEFF Research Database (Denmark)
Rodríguez-Caballero, Carlos Vladimir; Ventosa-Santaulària, Daniel
2014-01-01
The asymptotic behavior of the Granger-causality test under stochastic nonstationarity is studied. Our results confirm that the inference drawn from the test is not reliable when the series are integrated to the first order. In the presence of deterministic components, the test statistic diverges...
Causal feedbacks in climate change
Nes, van E.H.; Scheffer, M.; Brovkin, V.; Lenton, T.M.; Ye, H.; Deyle, E.; Sugihara, G.
2015-01-01
The statistical association between temperature and greenhouse gases over glacial cycles is well documented1, but causality behind this correlation remains difficult to extract directly from the data. A time lag of CO2 behind Antarctic temperature—originally thought to hint at a driving role for tem
Causal Behaviour on Carter spacetime
Blanco, Oihane F
2015-01-01
In this work we will focus on the causal character of Carter Spacetime (see B. Carter, Causal structure in space-time, Gen. Rel. Grav. 1 4 337-406, 1971). The importance of this spacetime is the following: for the causally best well behaved spacetimes (the globally hyperbolic ones), there are several characterizations or alternative definitions. In some cases, it has been shown that some of the causal properties required in these characterizations can be weakened. But Carter spacetime provides a counterexample for an impossible relaxation in one of them. We studied the possibility of Carter spacetime to be a counterexample for impossible lessening in another characterization, based on the previous results. In particular, we will prove that the time-separation or Lorentzian distance between two chosen points in Carter spacetime is infinite. Although this spacetime turned out not to be the counterexample we were looking for, the found result is interesting per se and provides ideas for alternate approaches to t...
Causality problem in Economic Science
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JOSÉ LUIS RETOLAZA
2007-12-01
Full Text Available The main point of the paper is the problem of the economy to be consider like a science in the most strict term of the concept. In the first step we are going to tackle a presentation about what we understand by science to subsequently present some of the fallacies which have bring certain scepticism about the scientific character of the investigation in economy, to know: 1 The differences between hard and weak sciences -physics and social; 2 The differences between paradigm, —positivist and phenomenological— 3 The differences between physic causalityand historic causality. In the second step we are going to talk about two fundamental problems which are questioned: 1 the confusion between ontology and gnoseology and, 2 the erroneous concept of causality that commonly is used. In the last step of the paper we are going over the recent models of «causal explanation» and we suggest the probabilistic casualty development next with a more elaborated models of causal explanation, like a way to conjugate the scientific severity with the possibility to tackle complex economic realities.
Anticipation of physical causality guides eye movements
Wende, Kim; Theunissen, Laetitia; Missal, Marcus
2016-01-01
Causality is a unique feature of human perception. We present here a behavioral investigation of the influence of physical causality during visual pursuit of object collisions. Pursuit and saccadic eye movements of human subjects were recorded during ocular pursuit of two concurrently launched targets, one that moved according to the laws of Newtonian mechanics (the causal target) and the other one that moved in a physically implausible direction (the non-causal target). We found that anticip...
Causal discovery from medical textual data.
Mani, S.; Cooper, G. F.
2000-01-01
Medical records usually incorporate investigative reports, historical notes, patient encounters or discharge summaries as textual data. This study focused on learning causal relationships from intensive care unit (ICU) discharge summaries of 1611 patients. Identification of the causal factors of clinical conditions and outcomes can help us formulate better management, prevention and control strategies for the improvement of health care. For causal discovery we applied the Local Causal Discove...
Estimating causal structure using conditional DAG models
Oates, Chris J.; Smith, Jim Q.; Mukherjee, Sach
2014-01-01
This paper considers inference of causal structure in a class of graphical models called "conditional DAGs". These are directed acyclic graph (DAG) models with two kinds of variables, primary and secondary. The secondary variables are used to aid in estimation of causal relationships between the primary variables. We give causal semantics for this model class and prove that, under certain assumptions, the direction of causal influence is identifiable from the joint observational distribution ...
Reward-Guided Learning with and without Causal Attribution.
Jocham, Gerhard; Brodersen, Kay H; Constantinescu, Alexandra O; Kahn, Martin C; Ianni, Angela M; Walton, Mark E; Rushworth, Matthew F S; Behrens, Timothy E J
2016-04-01
When an organism receives a reward, it is crucial to know which of many candidate actions caused this reward. However, recent work suggests that learning is possible even when this most fundamental assumption is not met. We used novel reward-guided learning paradigms in two fMRI studies to show that humans deploy separable learning mechanisms that operate in parallel. While behavior was dominated by precise contingent learning, it also revealed hallmarks of noncontingent learning strategies. These learning mechanisms were separable behaviorally and neurally. Lateral orbitofrontal cortex supported contingent learning and reflected contingencies between outcomes and their causal choices. Amygdala responses around reward times related to statistical patterns of learning. Time-based heuristic mechanisms were related to activity in sensorimotor corticostriatal circuitry. Our data point to the existence of several learning mechanisms in the human brain, of which only one relies on applying known rules about the causal structure of the task. PMID:26971947
Representing Personal Determinants in Causal Structures.
Bandura, Albert
1984-01-01
Responds to Staddon's critique of the author's earlier article and addresses issues raised by Staddon's (1984) alternative models of causality. The author argues that it is not the formalizability of causal processes that is the issue but whether cognitive determinants of behavior are reducible to past stimulus inputs in causal structures.…
The argumentative impact of causal relations
DEFF Research Database (Denmark)
Nielsen, Anne Ellerup
1996-01-01
causality, explanation and justification. In certain types of discourse, causal relations also imply an intentional element. This paper describes the way in which the semantic and pragmatic functions of causal markers can be accounted for in terms of linguistic and rhetorical theories of argumentation....
Expectations and Interpretations during Causal Learning
Luhmann, Christian C.; Ahn, Woo-kyoung
2011-01-01
In existing models of causal induction, 4 types of covariation information (i.e., presence/absence of an event followed by presence/absence of another event) always exert identical influences on causal strength judgments (e.g., joint presence of events always suggests a generative causal relationship). In contrast, we suggest that, due to…
Principal Stratification in Causal Inference
Frangakis, Constantine E.; Rubin, Donald B.
2002-01-01
Many scientific problems require that treatment comparisons be adjusted for posttreatment variables, but the estimands underlying standard methods are not causal effects. To address this deficiency, we propose a general framework for comparing treatments adjusting for posttreatment variables that yields principal effects based on principal stratification. Principal stratification with respect to a posttreatment variable is a cross-classification of subjects defined by the joint potential valu...
Entanglement, Holography and Causal Diamonds
de Boer, Jan; Heller, Michal P; Myers, Robert C
2016-01-01
We argue that the degrees of freedom in a d-dimensional CFT can be re-organized in an insightful way by studying observables on the moduli space of causal diamonds (or equivalently, the space of pairs of timelike separated points). This 2d-dimensional space naturally captures some of the fundamental nonlocality and causal structure inherent in the entanglement of CFT states. For any primary CFT operator, we construct an observable on this space, which is defined by smearing the associated one-point function over causal diamonds. Known examples of such quantities are the entanglement entropy of vacuum excitations and its higher spin generalizations. We show that in holographic CFTs, these observables are given by suitably defined integrals of dual bulk fields over the corresponding Ryu-Takayanagi minimal surfaces. Furthermore, we explain connections to the operator product expansion and the first law of entanglement entropy from this unifying point of view. We demonstrate that for small perturbations of the va...
The Influence of Virtual Sample Size on Confidence and Causal-Strength Judgments
Liljeholm, Mimi; Cheng, Patricia W.
2009-01-01
The authors investigated whether confidence in causal judgments varies with virtual sample size--the frequency of cases in which the outcome is (a) absent before the introduction of a generative cause or (b) present before the introduction of a preventive cause. Participants were asked to evaluate the influence of various candidate causes on an…
Finitary Spacetime Sheaves of Quantum Causal Sets Curving Quantum Causality
Mallios, A
2001-01-01
A locally finite, causal and quantal substitute for a locally Minkowskian principal fiber bundle $\\cal{P}$ of modules of Cartan differential forms $\\omg$ over a bounded region $X$ of a curved $C^{\\infty}$-smooth differential manifold spacetime $M$ with structure group ${\\bf G}$ that of orthochronous Lorentz transformations $L^{+}:=SO(1,3)^{\\uparrow}$, is presented. ${\\cal{P}}$ is the structure on which classical Lorentzian gravity, regarded as a Yang-Mills type of gauge theory of a $sl(2,\\com)$-valued connection 1-form $\\cal{A}$, is usually formulated. The mathematical structure employed to model this replacement of ${\\cal{P}}$ is a principal finitary spacetime sheaf $\\vec{\\cal{P}}_{n}$ of quantum causal sets $\\amg_{n}$ with structure group ${\\bf G}_{n}$, which is a finitary version of the group ${\\bf G}$ of local symmetries of General Relativity, and a finitary Lie algebra ${\\bf g}_{n}$-valued connection 1-form ${\\cal{A}}_{n}$ on it, which is a section of its sub-sheaf $\\amg^{1}_{n}$. ${\\cal{A}}_{n}$ is phys...
The Impossibility of Causality Testing
Conway, Roger K.; P. A. V. B. Swamy; Yanagida, John F.; Muehlen, Peter von zur
1984-01-01
Causality tests developed by Sims and Granger are fatally flawed for several reasons First, when two variables, X and Y, are uncorrelated, X has no linear predictive value for Y, but X,and Y may be nonlinearly related unless they are statistically Independent, In which case X and Y are not related at all The light-hand side variables In a regression equation are exogenous If they are mean Independent of the disturbance term Mean Independence IS stronger than uncorrelatedness The proofs for de...
Breaking the arrows of causality
DEFF Research Database (Denmark)
Valsiner, Jaan
2014-01-01
Theoretical models of catalysis have proven to bring with them major breakthroughs in chemistry and biology, from the 1830s onward. It can be argued that the scientific status of chemistry has become established through the move from causal to catalytic models. Likewise, the central explanatory...... role of cyclical models in biology has made it possible to move from the idea of genetic determination to that of epigenetic negotiation as the core of biological theory. In psychology, catalytic thinking has been outside of the realm of accepted scientific schemes, as the axiomatic dependence upon the...
The Functions of Danish Causal Conjunctions
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Rita Therkelsen
2004-01-01
Full Text Available In the article I propose an analysis of the Danish causal conjunctions fordi, siden and for based on the framework of Danish Functional Grammar. As conjunctions they relate two clauses, and their semantics have in common that it indicates a causal relationship between the clauses. The causal conjunctions are different as far as their distribution is concerned; siden conjoins a subordinate clause and a main clause, for conjoins two main clauses, and fordi is able to do both. Methodologically I have based my analysis on these distributional properties comparing siden and fordi conjoining a subordinate and a main clause, and comparing for and fordi conjoining two main clauses, following the thesis that they would establish a causal relationship between different kinds of content. My main findings are that fordi establishes a causal relationship between the events referred to by the two clauses, and the whole utterance functions as a statement of this causal relationship. Siden presupposes such a general causal relationship between the two events and puts forward the causing event as a reason for assuming or wishing or ordering the caused event, siden thus establishes a causal relationship between an event and a speech act. For equally presupposes a general causal relationship between two events and it establishes a causal relationship between speech acts, and fordi conjoining two main clauses is able to do this too, but in this position it also maintains its event-relating ability, the interpretation depending on contextual factors.
Space and time in perceptual causality
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Benjamin Straube
2010-04-01
Full Text Available Inferring causality is a fundamental feature of human cognition that allows us to theorize about and predict future states of the world. Michotte suggested that humans automatically perceive causality based on certain perceptual features of events. However, individual differences in judgments of perceptual causality cast doubt on Michotte’s view. To gain insights in the neural basis of individual difference in the perception of causality, our participants judged causal relationships in animations of a blue ball colliding with a red ball (a launching event while fMRI-data were acquired. Spatial continuity and temporal contiguity were varied parametrically in these stimuli. We did not find consistent brain activation differences between trials judged as caused and those judged as non-caused, making it unlikely that humans have universal instantiation of perceptual causality in the brain. However, participants were slower to respond to and showed greater neural activity for violations of causality, suggesting that humans are biased to expect causal relationships when moving objects appear to interact. Our participants demonstrated considerable individual differences in their sensitivity to spatial and temporal characteristics in perceiving causality. These qualitative differences in sensitivity to time or space in perceiving causality were instantiated in individual differences in activation of the left basal ganglia or right parietal lobe, respectively. Thus, the perception that the movement of one object causes the movement of another is triggered by elemental spatial and temporal sensitivities, which themselves are instantiated in specific distinct neural networks.
Probabilistic causality and radiogenic cancers
International Nuclear Information System (INIS)
A review and scrutiny of the literature on probability and probabilistic causality shows that it is possible under certain assumptions to estimate the probability that a certain type of cancer diagnosed in an individual exposed to radiation prior to diagnosis was caused by this exposure. Diagnosis of this causal relationship like diagnosis of any disease - malignant or not - requires always some subjective judgments by the diagnostician. It is, therefore, illusory to believe that tables based on actuarial data can provide objective estimates of the chance that a cancer diagnosed in an individual is radiogenic. It is argued that such tables can only provide a base from which the diagnostician(s) deviate in one direction or the other according to his (their) individual (consensual) judgment. Acceptance of a physician's diagnostic judgment by patients is commonplace. Similar widespread acceptance of expert judgment by claimants in radiation compensation cases does presently not exist. Judicious use of the present radioepidemiological tables prepared by the Working Group of the National Institutes of Health or of updated future versions of similar tables may improve the situation. 20 references
Causal relationship: a new tool for the causal characterization of Lorentzian manifolds
International Nuclear Information System (INIS)
We define and study a new kind of relation between two diffeomorphic Lorentzian manifolds called a causal relation, which is any diffeomorphism characterized by mapping every causal vector of the first manifold onto a causal vector of the second. We perform a thorough study of the mathematical properties of causal relations and prove in particular that two given Lorentzian manifolds (say V and W) may be causally related only in one direction (say from V to W, but not from W to V). This leads us to the concept of causally equivalent (or isocausal in short) Lorentzian manifolds as those mutually causally related and to a definition of causal structure over a differentiable manifold as the equivalence class formed by isocausal Lorentzian metrics upon it. Isocausality is a more general concept than the conformal relationship, because we prove the remarkable result that a conformal relation φ is characterized by the fact of being a causal relation of the particular kind in which both φ and φ-1 are causal relations. Isocausal Lorentzian manifolds are mutually causally compatible, they share some important causal properties, and there are one-to-one correspondences, which are sometimes non-trivial, between several classes of their respective future (and past) objects. A more important feature is that they satisfy the same standard causality constraints. We also introduce a partial order for the equivalence classes of isocausal Lorentzian manifolds providing a classification of all the causal structures that a given fixed manifold can have. By introducing the concept of causal extension we put forward a new definition of causal boundary for Lorentzian manifolds based on the concept of isocausality, and thereby we generalize the traditional Penrose constructions of conformal infinity, diagrams and embeddings. In particular, the concept of causal diagram is given. Many explicit clarifying examples are presented throughout the paper
FDI and growth: a causal relationship
Chowdhury, Abdur; Mavrotas, George
2005-01-01
The paper examines the causal relationship between FDI and economic growth by using an innovative econometric methodology to study the direction of causality between the two variables. We apply our methodology, based on the Toda-Yamamoto test for causality, to time-series data covering the period 1969-2000 for three developing countries, namely Chile, Malaysia and Thailand, all of them major recipients of FDI with a different history of macroeconomic episodes, policy regimes and growth patter...
Linear causal modeling with structural equations
Mulaik, Stanley A
2009-01-01
Emphasizing causation as a functional relationship between variables that describe objects, Linear Causal Modeling with Structural Equations integrates a general philosophical theory of causation with structural equation modeling (SEM) that concerns the special case of linear causal relations. In addition to describing how the functional relation concept may be generalized to treat probabilistic causation, the book reviews historical treatments of causation and explores recent developments in experimental psychology on studies of the perception of causation. It looks at how to perceive causal
The problem of causality in cultivation research
Rossmann, Constanze; Brosius, Hans-Bernd
2004-01-01
This paper offers an up-to-date review of problems in determining causal relationships in cultivation research, and considers the research rationales of various approaches with special reference to causal interpretation. It describes in turn a number of methodologies for addressing the problem and resolving it as far as this is possible. The issue of causal inference arises not only in cultivation research, however, but is basic to all media effects theories and approaches primarily at the ma...
Causal inference in economics and marketing.
Varian, Hal R
2016-07-01
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual-a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144
Causal inference in economics and marketing
Varian, Hal R.
2016-01-01
This is an elementary introduction to causal inference in economics written for readers familiar with machine learning methods. The critical step in any causal analysis is estimating the counterfactual—a prediction of what would have happened in the absence of the treatment. The powerful techniques used in machine learning may be useful for developing better estimates of the counterfactual, potentially improving causal inference. PMID:27382144
Heterogeneous Causal Effects and Sample Selection Bias
DEFF Research Database (Denmark)
Breen, Richard; Choi, Seongsoo; Holm, Anders
2015-01-01
The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how...... causal effects might vary over individuals or groups. In this paper we point out one of the under-appreciated hazards of seeking to estimate heterogeneous causal effects: conventional selection bias (that is, selection on baseline differences) can easily be mistaken for heterogeneity of causal effects...
Association analysis identifies ZNF750 regulatory variants in psoriasis
Directory of Open Access Journals (Sweden)
Birnbaum Ramon Y
2011-12-01
Full Text Available Abstract Background Mutations in the ZNF750 promoter and coding regions have been previously associated with Mendelian forms of psoriasis and psoriasiform dermatitis. ZNF750 encodes a putative zinc finger transcription factor that is highly expressed in keratinocytes and represents a candidate psoriasis gene. Methods We examined whether ZNF750 variants were associated with psoriasis in a large case-control population. We sequenced the promoter and exon regions of ZNF750 in 716 Caucasian psoriasis cases and 397 Caucasian controls. Results We identified a total of 47 variants, including 38 rare variants of which 35 were novel. Association testing identified two ZNF750 haplotypes associated with psoriasis (p ZNF750 promoter and 5' UTR variants displayed a 35-55% reduction of ZNF750 promoter activity, consistent with the promoter activity reduction seen in a Mendelian psoriasis family with a ZNF750 promoter variant. However, the rare promoter and 5' UTR variants identified in this study did not strictly segregate with the psoriasis phenotype within families. Conclusions Two haplotypes of ZNF750 and rare 5' regulatory variants of ZNF750 were found to be associated with psoriasis. These rare 5' regulatory variants, though not causal, might serve as a genetic modifier of psoriasis.
Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
Energy Technology Data Exchange (ETDEWEB)
Neelamkavil, Raphael
2014-07-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.
Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
International Nuclear Information System (INIS)
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly [non-causal] processes, something exists processually in extension-motion, between the causal and the [non-causal]. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That is, the QM world is sub-luminally, luminally and superluminally local-causal throughout, and the Law of Causality is ubiquitous in the micro-world. Thus, ''probabilistic causality'' is a merely epistemic term.
Quantum retrodiction and causality principle
International Nuclear Information System (INIS)
Quantum mechanics is factually a predictive science. But quantum retrodiction may also be needed, e.g., for the experimental verification of the validity of the Schroedinger equation for the wave function in the past if the present state is given. It is shown that in the retrodictive analog of the prediction the measurement must be replaced by another physical process called the retromeasurement. In this process, the reduction of a state vector into eigenvectors of a measured observable must proceed in the opposite direction of time as compared to the usual reduction. Examples of such processes are unknown. Moreover, they are shown to be forbidden by the causality principle stating that the later event cannot influence the earlier one. So quantum retrodiction seems to be unrealizable. It is demonstrated that the approach to the retrodiction given by S.Watanabe and F.Belinfante must be considered as an unsatisfactory ersatz of retrodicting. 20 refs., 3 figs
Comparison theorems for causal diamonds
Berthiere, Clement; Solodukhin, Sergey N
2015-01-01
We formulate certain inequalities for the geometric quantities characterizing causal diamonds in curved and Minkowski spacetimes. These inequalities involve the red-shift factor which, as we show explicitly in the spherically symmetric case, is monotonic in the radial direction and it takes its maximal value at the centre. As a byproduct of our discussion we re-derive Bishop's inequality without assuming the positivity of the spatial Ricci tensor. We then generalize our considerations to arbitrary, static and not necessarily spherically symmetric, asymptotically flat spacetimes. In the case of spacetimes with a horizon our generalization involves the so-called {\\it domain of dependence}. The respective volume, expressed in terms of the duration measured by a distant observer compared with the volume of the domain in Minkowski spacetime, exhibits behaviours which differ if $d=4$ or $d>4$. This peculiarity of four dimensions is due to the logarithmic subleading term in the asymptotic expansion of the metric nea...
The Power of Causal Beliefs and Conflicting Evidence on Causal Judgments and Decision Making
Garcia-Retamero, Rocio; Muller, Stephanie M.; Catena, Andres; Maldonado, Antonio
2009-01-01
In two experiments, we investigated the relative impact of causal beliefs and empirical evidence on both decision making and causal judgments, and whether this relative impact could be altered by previous experience. 2. Selected groups of participants in both experiments received pre-training with either causal or neutral cues, or no pre-training…
International Nuclear Information System (INIS)
This publication, compiled in 8 chapters, presents the regulatory system developed by the Nuclear Regulatory Authority (NRA) of the Argentine Republic. The following activities and developed topics in this document describe: the evolution of the nuclear regulatory activity in Argentina; the Argentine regulatory system; the nuclear regulatory laws and standards; the inspection and safeguards of nuclear facilities; the emergency systems; the environmental systems; the environmental monitoring; the analysis laboratories on physical and biological dosimetry, prenatal irradiation, internal irradiation, radiation measurements, detection techniques on nuclear testing, medical program on radiation protection; the institutional relations with national and international organization; the training courses and meeting; the technical information
Spin foam models as energetic causal sets
Cortês, Marina; Smolin, Lee
2016-04-01
Energetic causal sets are causal sets endowed by a flow of energy-momentum between causally related events. These incorporate a novel mechanism for the emergence of space-time from causal relations [M. Cortês and L. Smolin, Phys. Rev. D 90, 084007 (2014); Phys. Rev. D 90, 044035 (2014)]. Here we construct a spin foam model which is also an energetic causal set model. This model is closely related to the model introduced in parallel by Wolfgang Wieland in [Classical Quantum Gravity 32, 015016 (2015)]. What makes a spin foam model also an energetic causal set is Wieland's identification of new degrees of freedom analogous to momenta, conserved at events (or four-simplices), whose norms are not mass, but the volume of tetrahedra. This realizes the torsion constraints, which are missing in previous spin foam models, and are needed to relate the connection dynamics to those of the metric, as in general relativity. This identification makes it possible to apply the new mechanism for the emergence of space-time to a spin foam model. Our formulation also makes use of Markopoulou's causal formulation of spin foams [arXiv:gr-qc/9704013]. These are generated by evolving spin networks with dual Pachner moves. This endows the spin foam history with causal structure given by a partial ordering of the events which are dual to four-simplices.
Controlling for causally relevant third variables.
Goodie, Adam S; Williams, Cristina C; Crooks, C L
2003-10-01
In 3 experiments, the authors tested the conditions under which 3rd variables are controlled for in making causal judgments. The authors hypothesized that 3rd variables are controlled for when the 3rd variables are themselves perceived as causal. In Experiment 1, the participants predicted test performance after seeing information about wearing a lucky garment, taking a test-preparation course, and staying up late. The course (perceived as more causally relevant) was controlled for more than was the garment (perceived as less causally relevant) in assessing the effectiveness of staying up late. In Experiments 2 and 3, to obviate the many alternative accounts that arise from the realistic cover story of Experiment 1, participants predicted flowers' blooming after the presentation or nonpresentation of liquids. When one liquid was trained as causal, it was controlled for more in judging another liquid than when it was trained as neutral. Overall, stimuli perceived as causal were controlled for more when judging other stimuli. The authors concluded that the effect of perceived causal relevance on causal conditionalizing is real and normatively reasonable. PMID:14672103
Causal processes and propensities in quantum mechanics
Directory of Open Access Journals (Sweden)
Mauricio SUÁREZ
2010-01-01
Full Text Available I offer an alternative interpretation of Van Fraassen's influential arguments against causal realism in quantum mechanics. These arguments provide in fact a good guide to the different causal models available for the Einstein-Podolsky-Rosen correlations, which in turn shed light on the nature of quantum propensities.
Compact Representations of Extended Causal Models
Halpern, Joseph Y.; Hitchcock, Christopher
2013-01-01
Judea Pearl (2000) was the first to propose a definition of actual causation using causal models. A number of authors have suggested that an adequate account of actual causation must appeal not only to causal structure but also to considerations of "normality." In Halpern and Hitchcock (2011), we offer a definition of actual causation…
mediation: R Package for Causal Mediation Analysis
Directory of Open Access Journals (Sweden)
Dustin Tingley
2014-09-01
Full Text Available In this paper, we describe the R package mediation for conducting causal mediation analysis in applied empirical research. In many scientific disciplines, the goal of researchers is not only estimating causal effects of a treatment but also understanding the process in which the treatment causally affects the outcome. Causal mediation analysis is frequently used to assess potential causal mechanisms. The mediation package implements a comprehensive suite of statistical tools for conducting such an analysis. The package is organized into two distinct approaches. Using the model-based approach, researchers can estimate causal mediation effects and conduct sensitivity analysis under the standard research design. Furthermore, the design-based approach provides several analysis tools that are applicable under different experimental designs. This approach requires weaker assumptions than the model-based approach. We also implement a statistical method for dealing with multiple (causally dependent mediators, which are often encountered in practice. Finally, the package also offers a methodology for assessing causal mediation in the presence of treatment noncompliance, a common problem in randomized trials.
Causalities of the Taiwan Stock Market
Juhi-Lian Julian Ting
2003-01-01
Volatility, fitting with first order Landau expansion, stationarity, and causality of the Taiwan stock market (TAIEX) are investigated based on daily records. Instead of consensuses that consider stock market index change as a random time series we propose the market change as a dual time series consists of the index and the corresponding volume. Therefore, causalities between these two time series are investigated.
Campbell's and Rubin's Perspectives on Causal Inference
West, Stephen G.; Thoemmes, Felix
2010-01-01
Donald Campbell's approach to causal inference (D. T. Campbell, 1957; W. R. Shadish, T. D. Cook, & D. T. Campbell, 2002) is widely used in psychology and education, whereas Donald Rubin's causal model (P. W. Holland, 1986; D. B. Rubin, 1974, 2005) is widely used in economics, statistics, medicine, and public health. Campbell's approach focuses on…
Unpacking the causal chain of financial literacy
Carpena, Fenella; Cole, Shawn; Shapiro, Jeremy; Zia, Bilal
2011-01-01
A growing body of literature examines the causal impact of financial literacy on individual, household, and firm level outcomes. This paper unpacks the mechanism of impact by focusing on the first link in the causal chain. Specifically, it studies the experimental impact of financial literacy on three distinct dimensions of financial knowledge. The analysis finds that financial literacy do...
Causal random geometry from stochastic quantization
DEFF Research Database (Denmark)
Ambjørn, Jan; Loll, R.; Westra, W.; Zohren, S.
2010-01-01
in this short note we review a recently found formulation of two-dimensional causal quantum gravity defined through Causal Dynamical Triangulations and stochastic quantization. This procedure enables one to extract the nonperturbative quantum Hamiltonian of the random surface model including the...
Nuclear safety in EU candidate countries
Energy Technology Data Exchange (ETDEWEB)
NONE
2000-10-01
Nuclear safety in the candidate countries to the European Union is a major issue that needs to be addressed in the framework of the enlargement process. Therefore WENRA members considered it was their duty to offer their technical assistance to their Governments and the European Union Institutions. They decided to express their collective opinion on nuclear safety in those candidate countries having at least one nuclear power plant: Bulgaria, the Czech Republic, Hungary, Lithuania, Romania, Slovakia and Slovenia. The report is structured as follows: A foreword including background information, structure of the report and the methodology used, General conclusions of WENRA members reflecting their collective opinion, For each candidate country, an executive summary, a chapter on the status of the regulatory regime and regulatory body, and a chapter on the nuclear power plant safety status. Two annexes are added to address the generic safety characteristics and safety issues for RBMK and VVER plants. The report does not cover radiation protection and decommissioning issues, while safety aspects of spent fuel and radioactive waste management are only covered as regards on-site provisions. In order to produce this report, WENRA used different means: For the chapters on the regulatory regimes and regulatory bodies, experts from WENRA did the work. For the chapters on nuclear power plant safety status, experts from WENRA and from French and German technical support organisations did the work. Taking into account the contents of these chapters, WENRA has formulated its general conclusions in this report.
Nuclear safety in EU candidate countries
International Nuclear Information System (INIS)
Nuclear safety in the candidate countries to the European Union is a major issue that needs to be addressed in the framework of the enlargement process. Therefore WENRA members considered it was their duty to offer their technical assistance to their Governments and the European Union Institutions. They decided to express their collective opinion on nuclear safety in those candidate countries having at least one nuclear power plant: Bulgaria, the Czech Republic, Hungary, Lithuania, Romania, Slovakia and Slovenia. The report is structured as follows: A foreword including background information, structure of the report and the methodology used, General conclusions of WENRA members reflecting their collective opinion, For each candidate country, an executive summary, a chapter on the status of the regulatory regime and regulatory body, and a chapter on the nuclear power plant safety status. Two annexes are added to address the generic safety characteristics and safety issues for RBMK and VVER plants. The report does not cover radiation protection and decommissioning issues, while safety aspects of spent fuel and radioactive waste management are only covered as regards on-site provisions. In order to produce this report, WENRA used different means: For the chapters on the regulatory regimes and regulatory bodies, experts from WENRA did the work. For the chapters on nuclear power plant safety status, experts from WENRA and from French and German technical support organisations did the work. Taking into account the contents of these chapters, WENRA has formulated its general conclusions in this report
Granger causality in wall-bounded turbulence
International Nuclear Information System (INIS)
Granger causality is based on the idea that if a variable helps to predict another one, then they are probably involved in a causality relationship. This technique is based on the identification of a predictive model for causality detection. The aim of this paper is to use Granger causality to study the dynamics and the energy redistribution between scales and components in wall-bounded turbulent flows. In order to apply it on flows, Granger causality is generalized for snapshot-based observations of large size using linear-model identification methods coming from model reduction. Optimized DMD, a variant of the Dynamic Mode Decomposition, is considered for building a linear model based on snapshots. This method is used to link physical events and extract physical mechanisms associated to the bursting process in the logarithmic layer of a turbulent channel flow.
Quantum-coherent mixtures of causal relations
MacLean, Jean-Philippe W; Spekkens, Robert W; Resch, Kevin J
2016-01-01
Understanding the causal influences that hold among the parts of a system is critical both to explaining that system's natural behaviour and to controlling it through targeted interventions. In a quantum world, understanding causal relations is equally important, but the set of possibilities is far richer. The two basic ways in which a pair of time-ordered quantum systems may be causally related are by a cause-effect mechanism or by a common cause acting on both. Here, we show that it is possible to have a coherent mixture of these two possibilities. We realize such a nonclassical causal relation in a quantum optics experiment and derive a set of criteria for witnessing the coherence based on a quantum version of Berkson's paradox. The interplay of causality and quantum theory lies at the heart of challenging foundational puzzles, such as Bell's theorem and the search for quantum gravity, but could also provide a resource for novel quantum technologies.
Causal ubiquity in quantum physics a superluminal and local-causal physical ontology
Neelamkavil, Raphael
2014-01-01
A fixed highest criterial velocity (of light) in STR (special theory of relativity) is a convention for a layer of physical inquiry. QM (Quantum Mechanics) avoids action-at-a-distance using this concept, but accepts non-causality and action-at-a-distance in EPR (Einstein-Podolsky-Rosen-Paradox) entanglement experiments. Even in such allegedly non-causal processes, something exists processually in extension-motion, between the causal and the non-causal. If STR theoretically allows real-valued superluminal communication between EPR entangled particles, quantum processes become fully causal. That
Modeling parsimonious putative regulatory networks: complexity and heuristic approach
Acuña, Vicente; Aravena, Andrés; Maass, Alejandro; Siegel, Anne
2014-01-01
International audience A relevant problem in systems biology is the description of the regulatory interactions between genes. It is observed that pairs of genes have significant correlation through several experimental conditions. The question is to find causal relationships that can explain this experimental evidence. A putative regulatory network can be represented by an oriented weighted graph, where vertices represent genes, arcs represent predicted regulatory interactions and the arc ...
Ke, Juntao; Lou, Jiao; Chen, Xueqin; Li, Jiaoyuan; Liu, Cheng; Gong, Yajie; Yang, Yang; Zhu, Ying; Zhang, Yi; Gong, Jing
2015-01-01
Large-scale genome-wide association studies (GWAS) have established chromosome 5q31.1 as a susceptibility locus for colorectal cancer (CRC), which was still lack of causal genetic variants. We searched potentially regulatory single nucleotide polymorphisms (SNPs) in the overlap region between linkage disequilibrium (LD) block of 5q31.1 and regulatory elements predicted by histone modifications, then tested their association with CRC via a case-control study. Among three candidate common variants, we found rs17716310 conferred significantly (heterozygous model: OR = 1.273, 95% confidence interval (95%CI) = 1.016–1.595, P = 0.036) and marginally (dominant model: OR = 1.238, 95%CI = 1.000–1.532, P = 0.050) increase risk for CRC in a Chinese population including 695 cases and 709 controls. This variation was suggested to be regulatory altering the activity of enhancer that control PITX1 expression. Using epigenetic information such as chromatin immunoprecipitation-sequencing (ChIP-seq) data might help researchers to interpret the results of GWAS and locate causal variants for diseases in post-GWAS era. PMID:26381143
Evidence and causality assessment in environmental epidemiology: methodological aspects
International Nuclear Information System (INIS)
There are usually three major steps in the study of the possible impact of environmental factors on health: 1) to demonstrate that there is an association between exposure to the factor and the disease under study; 2) to demonstrate that this association is causal; 3) to evaluate the health benefit that could be obtained by removing the source of exposure. Statistical methods are commonly assumed to provide an objective way of achieving these three steps. This paper reviews some of the conditions that have to be met to allow proper interpretations and to avoid some of the controversies that are often found in health-environment studies. First, it should be remembered that the so-called P value which is used to qualify 'statistically significant' associations between risk factors and diseases does not give any indication of the probability that this association is actual, while far too often it is believed that it does. The probability that an association between an environmental factor and a disease is real could, however, be estimated by using Bayesian methods. These methods require that the a priori probabilities be stated, which is difficult to do in practice. Some directions to overcome this difficulty are presented. Second, the analysis of causality cannot be carried out on statistical grounds alone and the so-called 'causality criteria' are of limited practical interest. Definition of what is a cause, and upon which conditions a candidate factor of a disease can be considered as a cause, deserves much research effort, and careful consideration of the huge literature (mostly outside of the epidemiological field, for example in logic) which is devoted to this subject. Finally, the measurement of the role of a factor in a disease is very often assessed through the use of 'attributable fraction' or 'attributable mortality'. This should be done only when it is demonstrated that the considered factor is causal. Moreover, the interpretation of attributable fractions
Causal localizations in relativistic quantum mechanics
Energy Technology Data Exchange (ETDEWEB)
Castrigiano, Domenico P. L., E-mail: castrig@ma.tum.de; Leiseifer, Andreas D., E-mail: andreas.leiseifer@tum.de [Fakultät für Mathematik, TU München, Boltzmannstraße 3, 85747 Garching (Germany)
2015-07-15
Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states.
Mining Causality for Explanation Knowledge from Text
Institute of Scientific and Technical Information of China (English)
Chaveevan Pechsiri; Asanee Kawtrakul
2007-01-01
Mining causality is essential to provide a diagnosis. This research aims at extracting the causality existing within multiple sentences or EDUs (Elementary Discourse Unit). The research emphasizes the use of causality verbs because they make explicit in a certain way the consequent events of a cause, e.g., "Aphids suck the sap from rice leaves. Then leaves will shrink. Later, they will become yellow and dry.". A verb can also be the causal-verb link between cause and effect within EDU(s), e.g., "Aphids suck the sap from rice leaves causing leaves to be shrunk" ("causing" is equivalent to a causal-verb link in Thai). The research confronts two main problems: identifying the interesting causality events from documents and identifying their boundaries. Then, we propose mining on verbs by using two different machine learning techniques, Naive Bayes classifier and Support Vector Machine. The resulted mining rules will be used for the identification and the causality extraction of the multiple EDUs from text. Our multiple EDUs extraction shows 0.88 precision with 0.75 recall from Na'ive Bayes classifier and 0.89 precision with 0.76 recall from Support Vector Machine.
Causal localizations in relativistic quantum mechanics
International Nuclear Information System (INIS)
Causal localizations describe the position of quantum systems moving not faster than light. They are constructed for the systems with finite spinor dimension. At the center of interest are the massive relativistic systems. For every positive mass, there is the sequence of Dirac tensor-localizations, which provides a complete set of inequivalent irreducible causal localizations. They obey the principle of special relativity and are fully Poincaré covariant. The boosters are determined by the causal position operator and the other Poincaré generators. The localization with minimal spinor dimension is the Dirac localization. Thus, the Dirac equation is derived here as a mere consequence of the principle of causality. Moreover, the higher tensor-localizations, not known so far, follow from Dirac’s localization by a simple construction. The probability of localization for positive energy states results to be described by causal positive operator valued (PO-) localizations, which are the traces of the causal localizations on the subspaces of positive energy. These causal Poincaré covariant PO-localizations for every irreducible massive relativistic system were, all the more, not known before. They are shown to be separated. Hence, the positive energy systems can be localized within every open region by a suitable preparation as accurately as desired. Finally, the attempt is made to provide an interpretation of the PO-localization operators within the frame of conventional quantum mechanics attributing an important role to the negative energy states
Causality and momentum conservation from relative locality
Amelino-Camelia, Giovanni; Bianco, Stefano; Brighenti, Francesco; Buonocore, Riccardo Junior
2015-04-01
Theories involving curved momentum space, which recently became a topic of interest in the quantum-gravity literature, can, in general, violate many apparently robust aspects of our current description of the laws of physics, including relativistic invariance, locality, causality, and global momentum conservation. Here, we explore some aspects of the pathologies arising in generic theories involving curved momentum space for what concerns causality and momentum conservation. However, we also report results suggesting that when momentum space is maximally symmetric, and the theory is formulated relativistically, most notably including translational invariance with the associated relativity of spacetime locality, momentum is globally conserved and there is no violation of causality.
Causal localizations in relativistic quantum mechanics
International Nuclear Information System (INIS)
Sufficient and necessary conditions for causal localizations of massive relativistic systems are developed. It is proven that the Dirac- and the Dirac tensor-system are up to unitary equivalence the only irreducible causal localizations with finite spinor dimension which have a massive relativistic extension. A formula for this extension is given. The existence of arbitrarily good localized states of positive energy is shown. In the context of the causality condition a Paley-Wiener theorem for bounded measurable matrix-valued functions is proven.
The CMB in a Causal Set Universe
Zuntz, Joe
2007-01-01
We discuss Cosmic Microwave Background constraints on the causal set theory of quantum gravity, which has made testable predictions about the nature of dark energy. We flesh out previously discussed heuristic constraints by showing how the power spectrum of causal set dark energy fluctuations can be found from the overlap volumes of past light cones of points in the universe. Using a modified Boltzmann code we put constraints on the single parameter of the theory that are somewhat stronger than previous ones. We conclude that causal set theory cannot explain late-time acceleration without radical alterations to General Relativity.
Causality in 3D Massive Gravity Theories
Edelstein, Jose D; Kilicarslan, Ercan; Leoni, Matias; Tekin, Bayram
2016-01-01
We study the constraints coming from local causality requirement in various 2+1 dimensional dynamical theories of gravity. In Topologically Massive Gravity, with a single parity noninvariant massive degree of freedom, and in New Massive Gravity, with two massive spin-$2$ degrees of freedom, causality and unitarity are compatible with each other and they both require the Newton's constant to be negative. In their extensions, such as the Born-Infeld gravity and the minimal massive gravity the situation is similar and quite different from their higher dimensional counterparts, such as quadratic (e.g., Einstein-Gauss-Bonnet) or cubic theories, where causality and unitarity are in conflict.
Causality, Knowledge and Coordination in Distributed Systems
Ben-Zvi, Ido
2011-01-01
Effecting coordination across remote sites in a distributed system is an essential part of distributed computing, and also an inherent challenge. In 1978, an analysis of communication in asynchronous systems was suggested by Leslie Lamport. Lamport's analysis determines a notion of temporal precedence, a sort of weak notion of time, which is otherwise missing in asynchronous systems. This notion has been extensively utilized in various applications. Yet the analysis is limited to systems that are asynchronous. In this thesis we go beyond by investigating causality in synchronous systems. In such systems, the boundaries of causal influence are not charted out exclusively by message passing. Here time itself, passing at a uniform (or almost uniform) rate for all processes, is also a medium by which causal influence may fan out. This thesis studies, and characterizes, the combinations of time and message passing that govern causal influence in synchronous systems. It turns out that knowledge based analysis [FHMV...
Wuthrich, Christian
2015-01-01
Unlike the relativity theory it seeks to replace, causal set theory has been interpreted to leave space for a substantive, though perhaps 'localized', form of 'becoming'. The possibility of fundamental becoming is nourished by the fact that the analogue of Stein's theorem from special relativity does not hold in causal set theory. Despite this, we find that in many ways, the debate concerning becoming parallels the well-rehearsed lines it follows in the domain of relativity. We present, however, some new twists and challenges. In particular, we show that a novel and exotic notion of becoming is compatible with causal sets. In contrast to the 'localized' becoming considered compatible with the dynamics of causal set theory by its advocates, our novel kind of becoming, while not answering to the typical A-theoretic demands, is 'global' and objective.
Causality Between Urban Concentration and Environmental Quality
Directory of Open Access Journals (Sweden)
Amin Pujiati
2015-08-01
Full Text Available Population is concentrated in urban areas can cause the external diseconomies on environment if it exceeds the carrying capacity of the space and the urban economy. Otherwise the quality of the environment is getting better, led to the concentration of population in urban areas are increasingly high. This study aims to analyze the relationship of causality between the urban concentration and environmental quality in urban agglomeration areas. The data used in the study of secondary data obtained from the Central Bureau of statistics and the City Government from 2000 to 2013. The analytical method used is the Granger causality and descriptive. Granger causality study results showed no pattern of reciprocal causality, between urban concentration and the quality of the environment, but there unidirectional relationship between the urban concentration and environmental quality. This means that increasing urban concentration led to decreased environmental quality.
Granger-causality maps of diffusion processes
Wahl, Benjamin; Feudel, Ulrike; Hlinka, Jaroslav; Wächter, Matthias; Peinke, Joachim; Freund, Jan A.
2016-02-01
Granger causality is a statistical concept devised to reconstruct and quantify predictive information flow between stochastic processes. Although the general concept can be formulated model-free it is often considered in the framework of linear stochastic processes. Here we show how local linear model descriptions can be employed to extend Granger causality into the realm of nonlinear systems. This novel treatment results in maps that resolve Granger causality in regions of state space. Through examples we provide a proof of concept and illustrate the utility of these maps. Moreover, by integration we convert the local Granger causality into a global measure that yields a consistent picture for a global Ornstein-Uhlenbeck process. Finally, we recover invariance transformations known from the theory of autoregressive processes.
The Gravity Dual of Boundary Causality
Engelhardt, Netta
2016-01-01
In gauge/gravity duality, points which are not causally related on the boundary cannot be causally related through the bulk; this is the statement of boundary causality. By the Gao-Wald theorem, the averaged null energy condition in the bulk is sufficient to ensure this property. Here we proceed in the converse direction: we derive a necessary as well as sufficient condition for the preservation of boundary causality under perturbative (quantum or stringy) corrections to the bulk. The condition that we find is a (background-dependent) constraint on the amount by which light cones can "open" over all null bulk geodesics. We show that this constraint is weaker than the averaged null energy condition.
Selecting appropriate cases when tracing causal mechanisms
DEFF Research Database (Denmark)
Beach, Derek; Pedersen, Rasmus Brun
2016-01-01
, ontological determinism, causal asymmetry and causal homogeneity and the importance of context. We then develop a set of case selection guidelines that are in methodological alignment with these underlying assumptions. Section 4 develops guidelines for research where the mechanism is the primary focus......The last decade has witnessed resurgence in the interest in studying the causal mechanisms linking causes and outcomes in the social sciences. This article explores the overlooked implications for case selection when tracing mechanisms using in-depth case studies. Our argument is that existing case...... selection guidelines are appropriate for research aimed at making cross-case claims about causal relationships, where case selection is primarily used to control for other causes. However, existing guidelines are not in alignment with case-based research that aims to trace mechanisms, where the goal is to...
Quantum probability assignment limited by relativistic causality.
Han, Yeong Deok; Choi, Taeseung
2016-01-01
Quantum theory has nonlocal correlations, which bothered Einstein, but found to satisfy relativistic causality. Correlation for a shared quantum state manifests itself, in the standard quantum framework, by joint probability distributions that can be obtained by applying state reduction and probability assignment that is called Born rule. Quantum correlations, which show nonlocality when the shared state has an entanglement, can be changed if we apply different probability assignment rule. As a result, the amount of nonlocality in quantum correlation will be changed. The issue is whether the change of the rule of quantum probability assignment breaks relativistic causality. We have shown that Born rule on quantum measurement is derived by requiring relativistic causality condition. This shows how the relativistic causality limits the upper bound of quantum nonlocality through quantum probability assignment. PMID:26971717
The Temporal Logic of Causal Structures
Kleinberg, Samantha
2012-01-01
Computational analysis of time-course data with an underlying causal structure is needed in a variety of domains, including neural spike trains, stock price movements, and gene expression levels. However, it can be challenging to determine from just the numerical time course data alone what is coordinating the visible processes, to separate the underlying prima facie causes into genuine and spurious causes and to do so with a feasible computational complexity. For this purpose, we have been developing a novel algorithm based on a framework that combines notions of causality in philosophy with algorithmic approaches built on model checking and statistical techniques for multiple hypotheses testing. The causal relationships are described in terms of temporal logic formulae, reframing the inference problem in terms of model checking. The logic used, PCTL, allows description of both the time between cause and effect and the probability of this relationship being observed. We show that equipped with these causal f...
Causality and the semantics of provenance
Cheney, James
2010-01-01
Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on a causal semantics for provenance graphs.
Causality and the Semantics of Provenance
Directory of Open Access Journals (Sweden)
James Cheney
2010-06-01
Full Text Available Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on using causality to give a semantics to provenance graphs.
Causality and the Semantics of Provenance
Cheney, James
2010-01-01
Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts such as causality. We contend that mathematical models of these concepts are needed to justify and compare provenance techniques. In this paper we review a theory of causality based on structural models that has been developed in artificial intelligence, and describe work in progress on using causality to give a semantics to provenance graphs.
Ten simple rules for dynamic causal modeling.
Stephan, K.E.; Penny, W.D.; Moran, R.J.; Ouden, H.E.M. den; Daunizeau, J.; Friston, K.J.
2010-01-01
Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and
A Causal Model for Diagnostic Reasoning
Institute of Scientific and Technical Information of China (English)
PENG Guoqiang; CHENG Hu
2000-01-01
Up to now, there have been many methods for knowledge representation and reasoning in causal networks, but few of them include the research on the coactions of nodes. In practice, ignoring these coactions may influence the accuracy of reasoning and even give rise to incorrect reasoning. In this paper, based on multilayer causal networks, the definitions on coaction nodes are given to construct a new causal network called Coaction Causal Network, which serves to construct a model of neural network for diagnosis followed by fuzzy reasoning, and then the activation rules are given and neural computing methods are used to finish the diagnostic reasoning. These methods are proved in theory and a method of computing the number of solutions for the diagnostic reasoning is given. Finally, the experiments and the conclusions are presented.
Causal Structure and Birefringence in Nonlinear Electrodynamics
de Melo, C. A. M.; Medeiros, L. G.; Pompeia, P. J.(Instituto de Fomento e Coordenação Industrial, Departamento de Ciência e Tecnologia Aeroespacial, Praça Mal. Eduardo Gomes 50, 12228-901, São José dos Campos, SP , Brazil)
2014-01-01
We investigate the causal structure of general nonlinear electrodynamics and determine which Lagrangians generate an effective metric conformal to Minkowski. We also proof that there is only one analytic nonlinear electrodynamics presenting no birefringence.
The Causal Effects of Father Absence
McLanahan, Sara; TACH, LAURA; Schneider, Daniel
2013-01-01
The literature on father absence is frequently criticized for its use of cross-sectional data and methods that fail to take account of possible omitted variable bias and reverse causality. We review studies that have responded to this critique by employing a variety of innovative research designs to identify the causal effect of father absence, including studies using lagged dependent variable models, growth curve models, individual fixed effects models, sibling fixed effects models, natural ...
Inter-causal Independence and Heterogeneous Factorization
Zhang, Nevin Lianwen; Poole, David L
2013-01-01
It is well known that conditional independence can be used to factorize a joint probability into a multiplication of conditional probabilities. This paper proposes a constructive definition of inter-causal independence, which can be used to further factorize a conditional probability. An inference algorithm is developed, which makes use of both conditional independence and inter-causal independence to reduce inference complexity in Bayesian networks.
Catastrophizing and Causal Beliefs in Whiplash
Buitenhuis, J.; de Jong, P J; Jaspers, J. P. C.; Groothoff, J. W.
2008-01-01
Study Design. Prospective cohort study. Objective. This study investigates the role of pain catastrophizing and causal beliefs with regard to severity and persistence of neck complaints after motor vehicle accidents. Summary of Background Data. In previous research on low back pain, somatoform disorders and chronic fatigue syndrome, pain catastrophizing and causal beliefs were found to be related to perceived disability and prognosis. Furthermore, it has been argued with respect to whiplash t...
Causal Inference in Urban and Regional Economics
Nathaniel Baum-Snow; Fernando Ferreira
2014-01-01
Recovery of causal relationships in data is an essential part of scholarly inquiry in the social sciences. This chapter discusses strategies that have been successfully used in urban and regional economics for recovering such causal relationships. Essential to any successful empirical inquiry is careful consideration of the sources of variation in the data that identify parameters of interest. Interpretation of such parameters should take into account the potential for their heterogeneity as ...
Causal transmission in reduced-form models
Vassili Bazinas; Bent Nielsen
2015-01-01
We propose a method to explore the causal transmission of a catalyst variable through two endogenous variables of interest. The method is based on the reduced-form system formed from the conditional distribution of the two endogenous variables given the catalyst. The method combines elements from instru- mental variable analysis and Cholesky decomposition of structural vector autoregressions. We give conditions for uniqueness of the causal transmission.
Invited Commentary: Causal Diagrams and Measurement Bias
Hernán, Miguel A.; Cole, Stephen R.
2009-01-01
Causal inferences about the effect of an exposure on an outcome may be biased by errors in the measurement of either the exposure or the outcome. Measurement errors of exposure and outcome can be classified into 4 types: independent nondifferential, dependent nondifferential, independent differential, and dependent differential. Here the authors describe how causal diagrams can be used to represent these 4 types of measurement bias and discuss some problems that arise when using measured expo...
A Definition and Graphical Representation for Causality
Heckerman, David; Shachter, Ross D.
2013-01-01
We present a precise definition of cause and effect in terms of a fundamental notion called unresponsiveness. Our definition is based on Savage's (1954) formulation of decision theory and departs from the traditional view of causation in that our causal assertions are made relative to a set of decisions. An important consequence of this departure is that we can reason about cause locally, not requiring a causal explanation for every dependency. Such local reasoning can be beneficial because i...
Causales de ausencia de responsabilidad penal
Directory of Open Access Journals (Sweden)
Jaime Sandoval Fernández
2003-01-01
Full Text Available Este trabajo se ocupa de las causales de ausencia de responsabilidad penal, especialmente de aquellas que tienen efecto en el injusto. Como subtemas se delimita el concepto de responsabilidad penal y su ausencia. Se estudian las principales teorias a cerca de la relación tipicidad-antijuridicidad y su incidencia en el derecho penal colombiano. Por último contiene una propuesta acerca de cómo deberian agruparse las causales del arto 32 C. PlOO.
Sex differences in the inference and perception of causal relations within a video game
Directory of Open Access Journals (Sweden)
Michael E. Young
2014-08-01
Full Text Available The learning of immediate causation within a dynamic environment was examined. Participants encountered seven decision points in which they needed to choose which of three possible candidates was the cause of explosions in the environment. Each candidate was firing a weapon at random every few seconds, but only one of them produced an immediate effect. Some participants showed little learning, but most demonstrated increases in accuracy across time. On average, men showed higher accuracy and shorter latencies that were not explained by differences in self-reported prior video game experience. This result suggests that prior reports of sex differences in causal choice in the game are not specific to situations involving delayed or probabilistic causal relations.
Associative foundation of causal learning in rats.
Polack, Cody W; McConnell, Bridget L; Miller, Ralph R
2013-03-01
Are humans unique in their ability to interpret exogenous events as causes? We addressed this question by observing the behavior of rats for indications of causal learning. Within an operant motor-sensory preconditioning paradigm, associative surgical techniques revealed that rats attempted to control an outcome (i.e., a potential effect) by manipulating a potential exogenous cause (i.e., an intervention). Rats were able to generate an innocuous auditory stimulus. This stimulus was then paired with an aversive stimulus. The animals subsequently avoided potential generation of the predictive cue, but not if the aversive stimulus was subsequently devalued or the predictive cue was extinguished (Exp. 1). In Experiment 2, we demonstrated that the aversive stimulus we used was in fact aversive, that it was subject to devaluation, that the cue-aversive stimulus pairings did make the cue a conditioned stimulus, and that the cue was subject to extinction. In Experiments 3 and 4, we established that the decrease in leverpressing observed in Experiment 1 was goal-directed instrumental behavior rather than purely a product of Pavlovian conditioning. To the extent that interventions suggest causal reasoning, it appears that causal reasoning can be based on associations between contiguous exogenous events. Thus, contiguity appears capable of establishing causal relationships between exogenous events. Our results challenge the widely held view that causal learning is uniquely human, and suggest that causal learning is explicable in an associative framework. PMID:22562460
Commutative deformations of general relativity: nonlocality, causality, and dark matter
de Vegvar, P G N
2016-01-01
Hopf algebra methods are applied to study Drinfeld twists of (3+1)-diffeomorphisms and deformed general relativity on \\emph{commutative} manifolds. A classical nonlocality length scale is produced above which standard light cone causality emerges. We introduce a sector of matter fields to generate selfconsistent Abelian Drinfeld twists in a background independent manner and study their discrete and gauge symmetries. They naturally give rise to dark matter candidates, possibly including ground state condensates. First order deformed Maxwell equations are derived and yield negligible cosmological dispersion and produce a propagation horizon only for photons approaching Planck energies. This model incorporates dark matter without any appeal to extra dimensions, supersymmetry, strings, branes, mirror worlds, or modifications of Newtonian dynamics.
Institute of Scientific and Technical Information of China (English)
Rolf; Teschke; Albrecht; Wolff; Christian; Frenzel; Alexander; Schwarzenboeck; Johannes; Schulze; Axel; Eickhoff
2014-01-01
Causality assessment of suspected drug induced liver injury(DILI) and herb induced liver injury(HILI) is hampered by the lack of a standardized approach to be used by attending physicians and at various subsequent evaluating levels. The aim of this review was to analyze the suitability of the liver specific Council for International Organizations of Medical Sciences(CIOMS) scale as a standard tool for causality assessment in DILI and HILI cases. PubMed database was searched for the following terms: drug induced liver injury; herb induced liver injury; DILI causality assessment; and HILI causality assessment. The strength of the CIOMS lies in its potential as a standardized scale for DILI and HILI causality assessment. Other advantages include its liver specificity and its validation for hepatotoxicity with excellent sensitivity, specificity and predictive validity, based on cases with a positive reexposure test. This scale allows prospective collection of all relevant data required for a valid causality assessment. It does not require expert knowledge in hepatotoxicity and its results may subsequently be refined. Weaknesses of the CIOMS scale include the limited exclusion of alternative causes and qualitatively graded risk factors. In conclusion, CIOMS appears to be suitable as a standard scale for attending physicians, regulatory agencies, expert panels and other scientists to provide a standardized, reproducible causality assessment in suspected DILI and HILI cases, applicable primarily at all assessing levels involved. 2014 Baishideng Publishing Group Co., Limited. All rights
Causal factors guide for the evaluation of accidents in research reactors
International Nuclear Information System (INIS)
In the field of radiological and nuclear safety, the Nuclear Regulatory Authority (ARN) of Argentina controls three research reactors and three critical assemblies, by means of evaluations, audits and inspections, in order to assure the fulfillment of the requirements established in the Licenses, in the regulatory standards and in the mandatory documentation in general. rom the Nuclear Regulatory Authority point of view, within the general process of research reactors safety management, the management of operating experience plays an outstanding roll. In this aspect the ARN has established specific requisites in the Operation Licences in relation to the communication, evaluation, investigation of causes, and adoption of corrective measures, for the happened events. rom the experience collected in the analysis of the reports sent by the operators it has been verified some weakness in relation to the methodology of analysis of events and in the determination of the causal factors. n such a sense, with the purpose to establish a help for the analysts and to homogenize the treatment of the events, two reference guides were designed: a guide for the evaluation of events and another with a grid of causal factors. This paper describes the main aspects of the operating management system for research reactors and critical assemblies in Argentina, and the guides developed for the event analysis and determination of causal factors. (author)
Directory of Open Access Journals (Sweden)
Pierre-François Roux
Full Text Available In this study, we propose an approach aiming at fine-mapping adiposity QTL in chicken, integrating whole genome re-sequencing data. First, two QTL regions for adiposity were identified by performing a classical linkage analysis on 1362 offspring in 11 sire families obtained by crossing two meat-type chicken lines divergently selected for abdominal fat weight. Those regions, located on chromosome 7 and 19, contained a total of 77 and 84 genes, respectively. Then, SNPs and indels in these regions were identified by re-sequencing sires. Considering issues related to polymorphism annotations for regulatory regions, we focused on the 120 and 104 polymorphisms having an impact on protein sequence, and located in coding regions of 35 and 42 genes situated in the two QTL regions. Subsequently, a filter was applied on SNPs considering their potential impact on the protein function based on conservation criteria. For the two regions, we identified 42 and 34 functional polymorphisms carried by 18 and 24 genes, and likely to deeply impact protein, including 3 coding indels and 4 nonsense SNPs. Finally, using gene functional annotation, a short list of 17 and 4 polymorphisms in 6 and 4 functional genes has been defined. Even if we cannot exclude that the causal polymorphisms may be located in regulatory regions, this strategy gives a complete overview of the candidate polymorphisms in coding regions and prioritize them on conservation- and functional-based arguments.
Preschoolers prefer to learn causal information
Directory of Open Access Journals (Sweden)
Aubry eAlvarez
2015-02-01
Full Text Available Young children, in general, appear to have a strong drive to explore the environment in ways that reveal its underlying causal structure. But are they really attuned specifically to casual information in this quest for understanding, or do they show equal interest in other types of non-obvious information about the world? To answer this question, we introduced 20 three-year-old children to two puppets who were anxious to tell the child about a set of novel artifacts and animals. One puppet consistently described causal properties of the items while the other puppet consistently described carefully matched non-causal properties of the same items. After a familiarization period in which children learned which type of information to expect from each informant, children were given the opportunity to choose which they wanted to hear describe each of eight pictured test items. On average, children chose to hear from the informant that provided causal descriptions on 72% of the trials. This preference for causal information has important implications for explaining the role of conceptual information in supporting early learning and may suggest means for maximizing interest and motivation in young children.
Quantum causality in closed timelike curves
Korotaev, S. M.; Kiktenko, E. O.
2015-08-01
Although general relativity allows the existence of closed timelike curves (CTCs), self-consistency problems arise (the ‘grandfather paradox’ among others). It is known that quantum mechanical consideration of the matter formally removes all the paradoxes, but the questions about causal structure remain. On the other hand, the idea of postselected CTCs (P-CTC) in quantum teleportation has know been put forward and experimentally implemented. We consider these problems with the aid of quantum causal analysis, where causality is defined without invoking the time relation. It implements the Cramer principle of weak causality, which admits time reversal in entangled states. We analyze Deutsch CTCs (D-CTC) with different kinds of interactions between the chronology-violating and chronology-respecting particles, with refined inferences about mixedness, quantum/classical correlations, entanglement and thermodynamics in the D-CTC. The main result is that time reversal causality can really exist, however, the final quantum state does not place retrospective constraints on the initial state, instead the final state can influence the state inside the D-CTC. This is effectively the implementation of Novikov self-consistency principle. The P-CTC has radically different properties; in particular, if the initial state was pure, the final state is always pure too. Self-consistency is controlled by the initial state-dependent traversability of the P-CTC.
Causality, initial conditions and inflationary magnetogenesis
Tsagas, Christos G
2016-01-01
The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Technically, the latter issue can be addressed by appealing to Israel's junction conditions. Causality implies that inflationary magnetic fields dot not freeze into the matter until they have re-entered the causal horizon. The nature of cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic decay of superhorizon-sized magnetic fields throughout their post-inflationary life and thus lead to considerably stronger residual strengths. Th...
Causal Mediation Analyses for Randomized Trials.
Lynch, Kevin G; Cary, Mark; Gallop, Robert; Ten Have, Thomas R
2008-01-01
In the context of randomized intervention trials, we describe causal methods for analyzing how post-randomization factors constitute the process through which randomized baseline interventions act on outcomes. Traditionally, such mediation analyses have been undertaken with great caution, because they assume that the mediating factor is also randomly assigned to individuals in addition to the randomized baseline intervention (i.e., sequential ignorability). Because the mediating factors are typically not randomized, such analyses are unprotected from unmeasured confounders that may lead to biased inference. We review several causal approaches that attempt to reduce such bias without assuming that the mediating factor is randomized. However, these causal approaches require certain interaction assumptions that may be assessed if there is enough treatment heterogeneity with respect to the mediator. We describe available estimation procedures in the context of several examples from the literature and provide resources for software code. PMID:19484136
Bulk viscous cosmology with causal transport theory
International Nuclear Information System (INIS)
We consider cosmological scenarios originating from a single imperfect fluid with bulk viscosity and apply Eckart's and both the full and the truncated Müller-Israel-Stewart's theories as descriptions of the non-equilibrium processes. Our principal objective is to investigate if the dynamical properties of Dark Matter and Dark Energy can be described by a single viscous fluid and how such description changes when a causal theory (Müller-Israel-Stewart's, both in its full and truncated forms) is taken into account instead of Eckart's non-causal one. To this purpose, we find numerical solutions for the gravitational potential and compare its behaviour with the corresponding ΛCDM case. Eckart's and the full causal theory seem to be disfavoured, whereas the truncated theory leads to results similar to those of the ΛCDM model for a bulk viscous speed in the interval 10−11 || cb2 ∼−8
The causal meaning of Hamilton's rule.
Okasha, Samir; Martens, Johannes
2016-03-01
Hamilton's original derivation of his rule for the spread of an altruistic gene (rb>c) assumed additivity of costs and benefits. Recently, it has been argued that an exact version of the rule holds under non-additive pay-offs, so long as the cost and benefit terms are suitably defined, as partial regression coefficients. However, critics have questioned both the biological significance and the causal meaning of the resulting rule. This paper examines the causal meaning of the generalized Hamilton's rule in a simple model, by computing the effect of a hypothetical experiment to assess the cost of a social action and comparing it to the partial regression definition. The two do not agree. A possible way of salvaging the causal meaning of Hamilton's rule is explored, by appeal to R. A. Fisher's 'average effect of a gene substitution'. PMID:27069669
Causal inheritance in plane wave quotients
International Nuclear Information System (INIS)
We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general spacetime to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp-waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave spacetimes. We show that all other quotients preserve stable causality
Causal inheritence in plane wave quotients
Energy Technology Data Exchange (ETDEWEB)
Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.
2003-11-24
We investigate the appearance of closed timelike curves in quotients of plane waves along spacelike isometries. First we formulate a necessary and sufficient condition for a quotient of a general spacetime to preserve stable causality. We explicitly show that the plane waves are stably causal; in passing, we observe that some pp-waves are not even distinguishing. We then consider the classification of all quotients of the maximally supersymmetric ten-dimensional plane wave under a spacelike isometry, and show that the quotient will lead to closed timelike curves iff the isometry involves a translation along the u direction. The appearance of these closed timelike curves is thus connected to the special properties of the light cones in plane wave spacetimes. We show that all other quotients preserve stable causality.
Normalizing the causality between time series
Liang, X. San
2015-08-01
Recently, a rigorous yet concise formula was derived to evaluate information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing a Lyapunov exponent-like, one-dimensional phase-space stretching rate and a noise-to-signal ratio from the rate of information flow in the balance of the marginal entropy evolution of the flow recipient. It is verified with autoregressive models and applied to a real financial analysis problem. An unusually strong one-way causality is identified from IBM (International Business Machines Corporation) to GE (General Electric Company) in their early era, revealing to us an old story, which has almost faded into oblivion, about "Seven Dwarfs" competing with a giant for the mainframe computer market.
Hume’s understanding of causal explanation
Directory of Open Access Journals (Sweden)
Stefanović Igor
2015-01-01
Full Text Available This article deals with actuality of Hume’s positive thesis about causality, specifically in modern science. According to Dauer, Hume in his Treatise of Human Nature does not deal with scientific theory which allows us, in modern times, to come to the truth, and then necessity. Also, he claims that observation alone, without theory is useless, which is the reason why we need science to predict future events. I intend to show that all three claims are incorrect, and to show an intimate connection of causality and our intuitions.
A causally connected superluminal Warp Drive spacetime
Loup, F; Waite, D; Halerewicz, E F; Stabno, M; Kuntzman, M; Sims, R
2002-01-01
It will be shown that while horizons do not exist for warp drive spacetimes traveling at subluminal velocities horizons begin to develop when a warp drive spacetime reaches luminal velocities. However it will be shown that the control region of a warp drive ship lie within the portion of the warped region that is still causally connected to the ship even at superluminal velocities, therefore allowing a ship to slow to subluminal velocities. Further it is shown that the warped regions which are causally disconnected from a warp ship have no correlation to the ship velocity.
Causal interpretation of stochastic differential equations
DEFF Research Database (Denmark)
Sokol, Alexander; Hansen, Niels Richard
2014-01-01
We give a causal interpretation of stochastic differential equations (SDEs) by defining the postintervention SDE resulting from an intervention in an SDE. We show that under Lipschitz conditions, the solution to the postintervention SDE is equal to a uniform limit in probability of postintervention...... structural equation models based on the Euler scheme of the original SDE, thus relating our definition to mainstream causal concepts. We prove that when the driving noise in the SDE is a Lévy process, the postintervention distribution is identifiable from the generator of the SDE....
Causal Entropy Bound for a Spacelike Region
Brustein, R.; Veneziano, G.
2000-06-01
The identification of a causal-connection scale motivates us to propose a new covariant bound on entropy within a generic spacelike region. This ``causal entropy bound,'' scaling as EV, and thus lying around the geometric mean of Bekenstein's S/ER and holographic S/A bounds, is checked in various ``critical'' situations. In the case of limited gravity, Bekenstein's bound is the strongest while naive holography is the weakest. In the case of strong gravity, our bound and Bousso's holographic bound are stronger than Bekenstein's, while naive holography is too tight, and hence typically wrong.
A Causal Analysis of Observed Declines in Managed Honey Bees (Apis mellifera).
Staveley, Jane P; Law, Sheryl A; Fairbrother, Anne; Menzie, Charles A
2014-02-01
The European honey bee (Apis mellifera) is a highly valuable, semi-free-ranging managed agricultural species. While the number of managed hives has been increasing, declines in overwinter survival, and the onset of colony collapse disorder in 2006, precipitated a large amount of research on bees' health in an effort to isolate the causative factors. A workshop was convened during which bee experts were introduced to a formal causal analysis approach to compare 39 candidate causes against specified criteria to evaluate their relationship to the reduced overwinter survivability observed since 2006 of commercial bees used in the California almond industry. Candidate causes were categorized as probable, possible, or unlikely; several candidate causes were categorized as indeterminate due to lack of information. Due to time limitations, a full causal analysis was not completed at the workshop. In this article, examples are provided to illustrate the process and provide preliminary findings, using three candidate causes. Varroa mites plus viruses were judged to be a "probable cause" of the reduced survival, while nutrient deficiency was judged to be a "possible cause." Neonicotinoid pesticides were judged to be "unlikely" as the sole cause of this reduced survival, although they could possibly be a contributing factor. PMID:24363549
DEFF Research Database (Denmark)
Hoeyer, Klaus
2015-01-01
This article proposes the term “safety logics” to understand attempts within the European Union (EU) to harmonize member state legislation to ensure a safe and stable supply of human biological material for transplants and transfusions. With safety logics, I refer to assemblages of discourses, le...... arise. In short, I expose the regulatory anatomy of the policy landscape....
A Causal Construction of Diffusion Processes
Banek, Tadeusz
2010-01-01
A simple nonlinear integral equation for Ito's map is obtained. Although, it does not include stochastic integrals, it does give causal construction of diffusion processes which can be easily implemented by iteration systems. Applications in financial modelling and extension to fBm are discussed.
Causal dissipative hydrodynamics for heavy ion collisions
Chaudhuri, A K
2011-01-01
We briefly discuss the recent developments in causal dissipative hydrodynamic for relativistic heavy ion collisions. Phenomenological estimate of QGP viscosity over entropy ratio from several experimental data, e.g. STAR's $\\phi$ meson data, centrality dependence of elliptic flow, universal scaling elliptic flow etc. are discussed. QGP viscosity, extracted from hydrodynamical model analysis can have very large systematic uncertainty due to uncertain initial conditions.
Causality and analyticity in quantum fields theory
International Nuclear Information System (INIS)
This is a presentation of results on the causal and analytical structure of Green functions and on the collision amplitudes in fields theories, for massive particles of one type, with a positive mass and a zero spin value. (A.B.)
Manipulation and the causal Markov condition
Hausman, Daniel; Woodward, James
2004-01-01
This paper explores the relationship between a manipulability conception of causation and the causal Markov condition (CM). We argue that violations of CM also violate widely shared expectations—implicit in the manipulability conception—having to do with the absence of spontaneous correlations. They also violate expectations concerning the connection between independence or dependence relationships in the presence and absence of interventions.
Escaping Myopia: Teaching Students about Historical Causality
Waring, Scott M.
2010-01-01
There are so many aspects to teaching history that are vital to creating well-rounded historical thinkers, but one of the most fundamental and most overlooked elements is the idea of causality. Far too many students do not understand the idea of causation, that there are multiple reasons for why historical events occurred and transpired in the way…
Causality and Teleology in High School Biology.
Tamir, Pinchas
1985-01-01
Ability to distinguish between causal (cause-effect) and teleological (means-ends) explanations was measured in 1905 twelfth-grade biology students and found to be dependent on student knowledge. Although the inability to make these distinctions contributes to misconceptions in biology, appropriate instruction can easily remedy the problem. Sample…
Causal and Teleological Explanations in Biology
Yip, Cheng-Wai
2009-01-01
A causal explanation in biology focuses on the mechanism by which a biological process is brought about, whereas a teleological explanation considers the end result, in the context of the survival of the organism, as a reason for certain biological processes or structures. There is a tendency among students to offer a teleological explanation…
Comments: Causal Interpretations of Mediation Effects
Jo, Booil; Stuart, Elizabeth A.
2012-01-01
The authors thank Dr. Lindsay Page for providing a nice illustration of the use of the principal stratification framework to define causal effects, and a Bayesian model for effect estimation. They hope that her well-written article will help expose education researchers to these concepts and methods, and move the field of mediation analysis in…
Heterogeneous Causal Effects and Sample Selection Bias
DEFF Research Database (Denmark)
Breen, Richard; Choi, Seongsoo; Holm, Anders
2015-01-01
The role of education in the process of socioeconomic attainment is a topic of long standing interest to sociologists and economists. Recently there has been growing interest not only in estimating the average causal effect of education on outcomes such as earnings, but also in estimating how cau...
Inferring causality from noisy time series data
DEFF Research Database (Denmark)
Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian;
2016-01-01
even causality direction in synchronized time-series and in the presence of intermediate coupling. We find that the presence of noise deterministically reduces the level of cross-mapping fidelity, while the convergence rate exhibits higher levels of robustness. Finally, we propose that controlled noise...
Linear Response Laws and Causality in Electrodynamics
Yuffa, Alex J.; Scales, John A.
2012-01-01
Linear response laws and causality (the effect cannot precede the cause) are of fundamental importance in physics. In the context of classical electrodynamics, students often have a difficult time grasping these concepts because the physics is obscured by the intermingling of the time and frequency domains. In this paper, we analyse the linear…
Assessment of candidate accident management strategies
International Nuclear Information System (INIS)
A set of candidate accident management strategies, whose purpose is to prevent or mitigate in-vessel core damage, were identified from various Nuclear Regulatory Commission (NRC) and industry reports. These strategies have been grouped in this report by the challenges they are intended to meet, and assessed to provide information which may be useful to individual licensees for consideration when they perform their Individual Plant Examinations. Each assessment focused on describing and explaining the strategy, considering its relationship to existing requirements and practices as well as identifying possible associated adverse effects. 10 refs
International Nuclear Information System (INIS)
One of the simplest, yet most profound, questions we can ask about the Universe is, how much stuff is in it, and further what is that stuff composed of? Needless to say, the answer to this question has very important implications for the evolution of the Universe, determining both the ultimate fate and the course of structure formation. Remarkably, at this late date in the history of the Universe we still do not have a definitive answer to this simplest of questions---although we have some very intriguing clues. It is known with certainty that most of the material in the Universe is dark, and we have the strong suspicion that the dominant component of material in the Cosmos is not baryons, but rather is exotic relic elementary particles left over from the earliest, very hot epoch of the Universe. If true, the Dark Matter question is a most fundamental one facing both particle physics and cosmology. The leading particle dark matter candidates are: the axion, the neutralino, and a light neutrino species. All three candidates are accessible to experimental tests, and experiments are now in progress. In addition, there are several dark horse, long shot, candidates, including the superheavy magnetic monopole and soliton stars. 13 refs
The causal link between energy and output growth: Evidence from Markov switching Granger causality
International Nuclear Information System (INIS)
In this paper we empirically investigate the causal link between energy consumption and economic growth employing a Markov switching Granger causality analysis. We carry out our investigation using annual U.S. real GDP, total final energy consumption and total primary energy consumption data which cover the period between 1968 and 2010. We find that there are significant changes in the causal relation between energy consumption and economic growth over the sample period under investigation. Our results show that total final energy consumption and total primary energy consumption have significant predictive content for real economic activity in the U.S. economy. Furthermore, the causality running from energy consumption to output growth seems to be strongly apparent particularly during the periods of economic downturn and energy crisis. We also document that output growth has predictive power in explaining total energy consumption. Furthermore, the power of output growth in predicting total energy consumption is found to diminish after the mid of 1980s. - Highlights: • Total energy consumption has predictive content for real economic activity. • The causality from energy to output growth is apparent in the periods of recession. • The causality from energy to output growth is strong in the periods of energy crisis. • Output growth has predictive power in explaining total energy consumption. • The power of output growth in explaining energy diminishes after the mid of 1980s
Identification, Inference and Sensitivity Analysis for Causal Mediation Effects
Imai, Kosuke; Keele, Luke; Yamamoto, Teppei
2010-01-01
Causal mediation analysis is routinely conducted by applied researchers in a variety of disciplines. The goal of such an analysis is to investigate alternative causal mechanisms by examining the roles of intermediate variables that lie in the causal paths between the treatment and outcome variables. In this paper we first prove that under a particular version of sequential ignorability assumption, the average causal mediation effect (ACME) is nonparametrically identified. We compare our ident...
Institutional Investors and Stock Market Development: A Causality Study
Guler Aras; Alovsat Muslumov
2008-01-01
This article examines causality relationships between institutional investors and stock market development based on the panel data compiled from 23 OECD countries for the years 1982 through 2000. In order to test causality relationship, Sims’ causality test based on Granger definition of causality was used in our study. Our empirical results provide evidence that there are statistically significant positive relationship between institutional investors and stock market development. The develop...
Trimmed Granger causality between two groups of time series
Hung, Ying-Chao; Tseng, Neng-Fang; Balakrishnan, Narayanaswamy
2014-01-01
The identification of causal effects between two groups of time series has been an important topic in a wide range of applications such as economics, engineering, medicine, neuroscience, and biology. In this paper, a simplified causal relationship (called trimmed Granger causality) based on the context of Granger causality and vector autoregressive (VAR) model is introduced. The idea is to characterize a subset of “important variables” for both groups of time series so that the underlying cau...
A Bayesian Theory of Sequential Causal Learning and Abstract Transfer
Lu, Hongjing; Rojas, Randall R.; Beckers, Tom; Yuille, Alan L.
2016-01-01
Two key research issues in the field of causal learning are how people acquire causal knowledge when observing data that are presented sequentially, and the level of abstraction at which learning takes place. Does sequential causal learning solely involve the acquisition of specific cause-effect links, or do learners also acquire knowledge about…
Causality and Nonlocality as Axioms for Quantum Mechanics
Popescu, Sandu; Rohrlich, Daniel
1997-01-01
Quantum mechanics permits nonlocality - both nonlocal correlations and nonlocal equations of motion - while respecting relativistic causality. Is quantum mechanics the unique theory that reconciles nonlocality and causality? We consider two models, going beyond quantum mechanics, of nonlocality: "superquantum" correlations, and nonlocal "jamming" of correlations. These models are consistent with some definitions of nonlocality and causality.
Mind and Meaning: Piaget and Vygotsky on Causal Explanation.
Beilin, Harry
1996-01-01
Piaget's theory has been characterized as descriptive and not explanatory, not qualifying as causal explanation. Piaget was consistent in showing how his theory was both explanatory and causal. Vygotsky also endorsed causal-genetic explanation but, on the basis of knowledge of only Piaget's earliest works, he claimed that Piaget's theory was not…
Sentencing goals, causal attributions, ideology, and personality.
Carroll, J S; Perkowitz, W T; Lurigio, A J; Weaver, F M
1987-01-01
Disparity in sentencing of criminals has been related to a variety of individual difference variables. We propose a framework establishing resonances or coherent patterns among sentencing goals, causal attributions, ideology, and personality. Two studies are described, one with law and criminology students, the other with probation officers. Relations among the different types of variables reveal two resonances among both students and officers. One comprises various conservative and moralistic elements: a tough, punitive stance toward crime; belief in individual causality for crime; high scores on authoritarianism, dogmatism, and internal locus of control; lower moral stage; and political conservatism. The second comprises various liberal elements: rehabilitation, belief in economic and other external determinants of crime, higher moral stage, and belief in the powers and responsibilities of government to correct social problems. Implications of these results are discussed for individual differences in sentencing, attribution theory, and attempts to reduce disparity. PMID:3820064
An insider's guide to quantum causal histories
International Nuclear Information System (INIS)
A review is given of recent work aimed at constructing a quantum theory of cosmology in which all observables refer to information measurable by observers inside the universe. At the classical level the algebra of observables should be modified to take into account the fact that observers can only give truth values to observables that have to do with their backwards light cone. The resulting algebra is a Heyting rather than a Boolean algebra. The complement is non-trivial and contains information about horizons and topology change. Representation of such observables quantum mechanically requires a many-Hilbert space formalism, in which different observers make measurements in different Hilbert spaces. I describe such a formalism, called 'quantum causal histories'; examples include causally evolving spin networks and quantum computers
Consistence beats causality in recommender systems
Zhu, Xuzhen; Hu, Zheng; Zhang, Ping; Zhou, Tao
2015-01-01
The explosive growth of information challenges people's capability in finding out items fitting to their own interests. Recommender systems provide an efficient solution by automatically push possibly relevant items to users according to their past preferences. Recommendation algorithms usually embody the causality from what having been collected to what should be recommended. In this article, we argue that in many cases, a user's interests are stable, and thus the previous and future preferences are highly consistent. The temporal order of collections then does not necessarily imply a causality relationship. We further propose a consistence-based algorithm that outperforms the state-of-the-art recommendation algorithms in disparate real data sets, including \\textit{Netflix}, \\textit{MovieLens}, \\textit{Amazon} and \\textit{Rate Your Music}.
A New Spin on Causality Constraints
Hartman, Thomas; Kundu, Sandipan
2016-01-01
Causality in a shockwave state is related to the analytic properties of a four-point correlation function. Extending recent results for scalar probes, we show that this constrains the couplings of the stress tensor to light spinning operators in conformal field theory, and interpret these constraints in terms of the interaction with null energy. For spin-1 and spin-2 conserved currents in four dimensions, the resulting inequalities are a subset of the Hofman-Maldacena conditions for positive energy deposition. It is well known that energy conditions in holographic theories are related to causality on the gravity side; our results make a connection on the CFT side, and extend it to non-holographic theories.
Normalizing the causality between time series
Liang, X San
2015-01-01
Recently, a rigorous yet concise formula has been derived to evaluate the information flow, and hence the causality in a quantitative sense, between time series. To assess the importance of a resulting causality, it needs to be normalized. The normalization is achieved through distinguishing three types of fundamental mechanisms that govern the marginal entropy change of the flow recipient. A normalized or relative flow measures its importance relative to other mechanisms. In analyzing realistic series, both absolute and relative information flows need to be taken into account, since the normalizers for a pair of reverse flows belong to two different entropy balances; it is quite normal that two identical flows may differ a lot in relative importance in their respective balances. We have reproduced these results with several autoregressive models. We have also shown applications to a climate change problem and a financial analysis problem. For the former, reconfirmed is the role of the Indian Ocean Dipole as ...
Closed timelike curves and causality violation
Lobo, Francisco S N
2010-01-01
The conceptual definition and understanding of time, both quantitatively and qualitatively is of the utmost difficulty and importance. As time is incorporated into the proper structure of the fabric of spacetime, it is interesting to note that General Relativity is contaminated with non-trivial geometries which generate closed timelike curves. A closed timelike curve (CTC) allows time travel, in the sense that an observer that travels on a trajectory in spacetime along this curve, may return to an event before his departure. This fact apparently violates causality, therefore time travel and it's associated paradoxes have to be treated with great caution. The paradoxes fall into two broad groups, namely the consistency paradoxes and the causal loops. A great variety of solutions to the Einstein field equations containing CTCs exist and it seems that two particularly notorious features stand out. Solutions with a tipping over of the light cones due to a rotation about a cylindrically symmetric axis and solution...
An insider's guide to quantum causal histories
Markopoulou, F
2000-01-01
A review is given of recent work aimed at constructing a quantum theory of cosmology in which all observables refer to information measurable by observers inside the universe. At the classical level the algebra of observables should be modified to take into account the fact that observers can only give truth values to observables that have to do with their backwards light cone. The resulting algebra is a Heyting rather than a Boolean algebra. The complement is non-trivial and contains information about horizons and topology change. Representation of such observables quantum mechanically requires a many-Hilbert space formalism, in which different observers make measurements in different Hilbert spaces. I describe such a formalism, called "quantum causal histories"; examples include causally evolving spin networks and quantum computers.
Granger-Causality Maps of Diffusion Processes
Czech Academy of Sciences Publication Activity Database
Wahl, B.; Feudel, U.; Hlinka, Jaroslav; Wächter, M.; Peinke, J.; Freund, J.A.
2016-01-01
Roč. 93, č. 2 (2016), 022213/1-022213/9. ISSN 1539-3755 R&D Projects: GA ČR GA13-23940S; GA MZd(CZ) NV15-29835A Institutional support: RVO:67985807 Keywords : Granger causality * stochastic process * diffusion process * nonlinear dynamical systems Subject RIV: BB - Applied Statistics, Operational Research Impact factor: 2.288, year: 2014
Waves and causality in higher dimensions
Wesson, Paul S
2015-01-01
We give a new, wave-like solution of the field equations of five-dimensional relativity. In ordinary three-dimensional space, the waves resemble de Broglie or matter waves, whose puzzling behaviour can be better understood in terms of one or more extra dimensions. Causality is appropriately defined by a null higher-dimensional interval. It may be possible to test the properties of these waves in the laboratory.
Information causality as a physical principle.
Pawłowski, Marcin; Paterek, Tomasz; Kaszlikowski, Dagomir; Scarani, Valerio; Winter, Andreas; Zukowski, Marek
2009-10-22
Quantum physics has remarkable distinguishing characteristics. For example, it gives only probabilistic predictions (non-determinism) and does not allow copying of unknown states (no-cloning). Quantum correlations may be stronger than any classical ones, but information cannot be transmitted faster than light (no-signalling). However, these features do not uniquely define quantum physics. A broad class of theories exist that share such traits and allow even stronger (than quantum) correlations. Here we introduce the principle of 'information causality' and show that it is respected by classical and quantum physics but violated by all no-signalling theories with stronger than (the strongest) quantum correlations. The principle relates to the amount of information that an observer (Bob) can gain about a data set belonging to another observer (Alice), the contents of which are completely unknown to him. Using all his local resources (which may be correlated with her resources) and allowing classical communication from her, the amount of information that Bob can recover is bounded by the information volume (m) of the communication. Namely, if Alice communicates m bits to Bob, the total information obtainable by Bob cannot be greater than m. For m = 0, information causality reduces to the standard no-signalling principle. However, no-signalling theories with maximally strong correlations would allow Bob access to all the data in any m-bit subset of the whole data set held by Alice. If only one bit is sent by Alice (m = 1), this is tantamount to Bob's being able to access the value of any single bit of Alice's data (but not all of them). Information causality may therefore help to distinguish physical theories from non-physical ones. We suggest that information causality-a generalization of the no-signalling condition-might be one of the foundational properties of nature. PMID:19847260
Causal Mediation Analyses for Randomized Trials
Lynch, Kevin G.; Cary, Mark; Gallop, Robert; Ten Have, Thomas R.
2008-01-01
In the context of randomized intervention trials, we describe causal methods for analyzing how post-randomization factors constitute the process through which randomized baseline interventions act on outcomes. Traditionally, such mediation analyses have been undertaken with great caution, because they assume that the mediating factor is also randomly assigned to individuals in addition to the randomized baseline intervention (i.e., sequential ignorability). Because the mediating factors are t...
Isocausal spacetimes may have different causal boundaries
Energy Technology Data Exchange (ETDEWEB)
Flores, J L; Herrera, J [Departamento de Algebra, Geometria y Topologia, Facultad de Ciencias, Universidad de Malaga, Campus Teatinos, 29071 Malaga (Spain); Sanchez, M, E-mail: floresj@agt.cie.uma.es, E-mail: jherrera@uma.es, E-mail: sanchezm@ugr.es [Departamento de Geometria y Topologia, Facultad de Ciencias, Universidad de Granada, Avenida Fuentenueva s/n, 18071 Granada (Spain)
2011-09-07
We construct an example which shows that two isocausal spacetimes, in the sense introduced recently in GarcIa-Parrado and Senovilla (2003 Class. Quantum Grav. 20 625-64), may have c-boundaries which are not equal (more precisely, not equivalent, as no bijection between the completions can preserve all the binary relations induced by causality). This example also suggests that isocausality can be useful for the understanding and computation of the c-boundary.
Representation and reasoning: a causal model approach
Nikolic, M.
2014-01-01
How do we represent our world and how do we use these representations to reason about it? The three studies reported in this thesis explored different aspects of the answer to this question. Even though these investigations offered diverse angles, they all originated from the same psychological theory of representation and reasoning. This is the idea that people represent the world and reason about it by constructing dynamic qualitative causal networks. The first study investigated how mock j...
Reconstructing Causal Biological Networks through Active Learning
Cho, Hyunghoon; Berger, Bonnie; Peng, Jian
2016-01-01
Reverse-engineering of biological networks is a central problem in systems biology. The use of intervention data, such as gene knockouts or knockdowns, is typically used for teasing apart causal relationships among genes. Under time or resource constraints, one needs to carefully choose which intervention experiments to carry out. Previous approaches for selecting most informative interventions have largely been focused on discrete Bayesian networks. However, continuous Bayesian networks are ...
A causally connected superluminal Warp Drive spacetime
Loup, F.; Held, R.; Waite, D; Halerewicz, Jr., E.; Stabno, M.; Kuntzman, M.; Sims, R.
2002-01-01
It will be shown that while horizons do not exist for warp drive spacetimes traveling at subluminal velocities horizons begin to develop when a warp drive spacetime reaches luminal velocities. However it will be shown that the control region of a warp drive ship lie within the portion of the warped region that is still causally connected to the ship even at superluminal velocities, therefore allowing a ship to slow to subluminal velocities. Further it is shown that the warped regions which ar...
Extending Temporal Causal Graph For Diagnosis Problems
Belouaer, Lamia; Bouzid, Maroua; Mouhoub, Malek
2009-01-01
Poster International audience Abductive diagnosis (Brusoni et al. 1998) consists in finding explanations for given observations by using rules of inference based on the causal dependences of the system. Time is important for abductive diagnosis (Hamscher and Davis 1984), (Hamscher, Console, and Kleer 1992). There are few works in litterature handling temporal diagnosis (Kautz 1999). They differ in the expressiveness of the temporal knowledge. We propose a new approach for Temporal Diagn...
Imposing causality on a matrix model
International Nuclear Information System (INIS)
We introduce a new matrix model that describes Causal Dynamical Triangulations (CDT) in two dimensions. In order to do so, we introduce a new, simpler definition of 2D CDT and show it to be equivalent to the old one. The model makes use of ideas from dually weighted matrix models, combined with multi-matrix models, and can be studied by the method of character expansion.
Relativistic causality and position space renormalization
Todorov, Ivan
2016-01-01
We survey the causal position space renormalization with a special attention to the role of Raymond Stora in the development of the subject. Renormalization is effected by subtracting pole terms in analytically regularized amplitudes. Residues are identified with periods whose relation to recent development in number theory is emphasized. We demonstrate the possibility of integration over internal vertices in the case of a (massless) conformal theory and display the dilation and the conformal anomaly.
Extracting causal relationships from Chinese written text
Liu, X; Hoede, C.
2002-01-01
Expert systems form one of the most important research areas in Artificial Intelligence. The main parts in expert systems are knowledge bases and inference engines. In the knowledge bases the main knowledge is knowledge in the form of ``IF-THEN" statements. In knowledge graphs, a new form of knowledge representation, the ``IF-THEN" statements are tied up with causal operators (CAU-relations). In this paper, we picked out some Chinese operators with ``CAU" meaning, and investigated these opera...
Causality and the semantics of provenance
James Cheney
2010-01-01
Provenance, or information about the sources, derivation, custody or history of data, has been studied recently in a number of contexts, including databases, scientific workflows and the Semantic Web. Many provenance mechanisms have been developed, motivated by informal notions such as influence, dependence, explanation and causality. However, there has been little study of whether these mechanisms formally satisfy appropriate policies or even how to formalize relevant motivating concepts suc...
Ten simple rules for dynamic causal modeling
Stephan, K E; Penny, W.D.; Moran, R. J.; den Ouden, H.E.M.; Daunizeau, J.; Friston, K J
2010-01-01
Dynamic causal modeling (DCM) is a generic Bayesian framework for inferring hidden neuronal states from measurements of brain activity. It provides posterior estimates of neurobiologically interpretable quantities such as the effective strength of synaptic connections among neuronal populations and their context-dependent modulation. DCM is increasingly used in the analysis of a wide range of neuroimaging and electrophysiological data. Given the relative complexity of DCM, compared to convent...
Causality detection and turbulence in fusion plasmas
Van Milligen, B Ph; Birkenmeier, G.; Ramisch, M.; Estrada, T.; Hidalgo, C.; A. Alonso
2013-01-01
This work explores the potential of an information-theoretical causality detection method for unraveling the relation between fluctuating variables in complex nonlinear systems. The method is tested on some simple though nonlinear models, and guidelines for the choice of analysis parameters are established. Then, measurements from magnetically confined fusion plasmas are analyzed. The selected data bear relevance to the all-important spontaneous confinement transitions often observed in fusio...
York eHagmayer; Neele eEngelmann
2014-01-01
Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic...
Hagmayer, York; Engelmann, Neele
2014-01-01
Cognitive psychological research focuses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets) were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic lite...
Causality, initial conditions, and inflationary magnetogenesis
Tsagas, Christos G.
2016-05-01
The post-inflationary evolution of inflation-produced magnetic fields, conventional or not, can change dramatically when two fundamental issues are accounted for. The first is causality, which demands that local physical processes can never affect superhorizon perturbations. The second is the nature of the transition from inflation to reheating and then to the radiation era, which determine the initial conditions at the start of these epochs. Causality implies that inflationary magnetic fields do not freeze into the matter until they have re-entered the causal horizon. The nature of the cosmological transitions and the associated initial conditions, on the other hand, determine the large-scale magnetic evolution after inflation. Put together, the two can slow down the adiabatic magnetic decay on superhorizon scales throughout the Universe's post-inflationary evolution and thus lead to considerably stronger residual magnetic fields. This is "good news" for both the conventional and the nonconventional scenarios of cosmic magnetogenesis. Mechanisms operating outside standard electromagnetism, in particular, do not need to enhance their fields too much during inflation in order to produce seeds that can feed the galactic dynamo today. In fact, even conventionally produced inflationary magnetic fields might be able to sustain the dynamo.
A causal dispositional account of fitness.
Triviño, Vanessa; Nuño de la Rosa, Laura
2016-09-01
The notion of fitness is usually equated to reproductive success. However, this actualist approach presents some difficulties, mainly the explanatory circularity problem, which have lead philosophers of biology to offer alternative definitions in which fitness and reproductive success are distinguished. In this paper, we argue that none of these alternatives is satisfactory and, inspired by Mumford and Anjum's dispositional theory of causation, we offer a definition of fitness as a causal dispositional property. We argue that, under this framework, the distinctiveness that biologists usually attribute to fitness-namely, the fact that fitness is something different from both the physical traits of an organism and the number of offspring it leaves-can be explained, and the main problems associated with the concept of fitness can be solved. Firstly, we introduce Mumford and Anjum's dispositional theory of causation and present our definition of fitness as a causal disposition. We explain in detail each of the elements involved in our definition, namely: the relationship between fitness and the functional dispositions that compose it, the emergent character of fitness, and the context-sensitivity of fitness. Finally, we explain how fitness and realized fitness, as well as expected and realized fitness are distinguished in our approach to fitness as a causal disposition. PMID:27338570
Bayesian Discovery of Linear Acyclic Causal Models
Hoyer, Patrik O
2012-01-01
Methods for automated discovery of causal relationships from non-interventional data have received much attention recently. A widely used and well understood model family is given by linear acyclic causal models (recursive structural equation models). For Gaussian data both constraint-based methods (Spirtes et al., 1993; Pearl, 2000) (which output a single equivalence class) and Bayesian score-based methods (Geiger and Heckerman, 1994) (which assign relative scores to the equivalence classes) are available. On the contrary, all current methods able to utilize non-Gaussianity in the data (Shimizu et al., 2006; Hoyer et al., 2008) always return only a single graph or a single equivalence class, and so are fundamentally unable to express the degree of certainty attached to that output. In this paper we develop a Bayesian score-based approach able to take advantage of non-Gaussianity when estimating linear acyclic causal models, and we empirically demonstrate that, at least on very modest size networks, its accur...
Reliability of the Granger causality inference
International Nuclear Information System (INIS)
How to characterize information flows in physical, biological, and social systems remains a major theoretical challenge. Granger causality (GC) analysis has been widely used to investigate information flow through causal interactions. We address one of the central questions in GC analysis, that is, the reliability of the GC evaluation and its implications for the causal structures extracted by this analysis. Our work reveals that the manner in which a continuous dynamical process is projected or coarse-grained to a discrete process has a profound impact on the reliability of the GC inference, and different sampling may potentially yield completely opposite inferences. This inference hazard is present for both linear and nonlinear processes. We emphasize that there is a hazard of reaching incorrect conclusions about network topologies, even including statistical (such as small-world or scale-free) properties of the networks, when GC analysis is blindly applied to infer the network topology. We demonstrate this using a small-world network for which a drastic loss of small-world attributes occurs in the reconstructed network using the standard GC approach. We further show how to resolve the paradox that the GC analysis seemingly becomes less reliable when more information is incorporated using finer and finer sampling. Finally, we present strategies to overcome these inference artifacts in order to obtain a reliable GC result
Cohomology Methods in Causal Perturbation Theory
International Nuclear Information System (INIS)
Various problems in perturbation theory of (quantum) gauge models can be rephrased in the language of cohomology theory. This was already noticed in the functional formulation of perturbative gauge theories. Causal perturbation theory is a fully quantum approach: is works only with the chronological products which are defined as operator-valued distributions in the Fock space of the model. The use of causal perturbation theory leads to similar cohomology problems; the main difference with respect to the functional methods comes from the fact that the gauge transformation of the causal approach is, essentially, the linear part of the non-linear BRST transformation.Using these methods it is possible to give a nice determination of the interaction Lagrangians for gauge models (Yang-Mills and gravitation in the linear approximation); one obtains with this method the unicity of the interaction Lagrangian up to trivial terms. The case of quantum gravity is highly non-trivial and can be generalized with this method to the massive graviton case. Going to higher orders of perturbation theory one finds quantum anomalies. Again the cohomological methods can be used to determine the generic form of these anomalies. Finally, one can investigate the arbitrariness of the chronological products in higher orders and reduce this problem to cohomology methods also.
Particle Dark Matter Candidates
Scopel, Stefano
2007-01-01
I give a short overview on some of the favorite particle Cold Dark Matter candidates today, focusing on those having detectable interactions: the axion, the KK-photon in Universal Extra Dimensions, the heavy photon in Little Higgs and the neutralino in Supersymmetry. The neutralino is still the most popular, and today is available in different flavours: SUGRA, nuSUGRA, sub-GUT, Mirage mediation, NMSSM, effective MSSM, scenarios with CP violation. Some of these scenarios are already at the level of present sensitivities for direct DM searches.
Temporal expression profiling identifies pathways mediating effect of causal variant on phenotype.
Directory of Open Access Journals (Sweden)
Saumya Gupta
2015-06-01
Full Text Available Even with identification of multiple causal genetic variants for common human diseases, understanding the molecular processes mediating the causal variants' effect on the disease remains a challenge. This understanding is crucial for the development of therapeutic strategies to prevent and treat disease. While static profiling of gene expression is primarily used to get insights into the biological bases of diseases, it makes differentiating the causative from the correlative effects difficult, as the dynamics of the underlying biological processes are not monitored. Using yeast as a model, we studied genome-wide gene expression dynamics in the presence of a causal variant as the sole genetic determinant, and performed allele-specific functional validation to delineate the causal effects of the genetic variant on the phenotype. Here, we characterized the precise genetic effects of a functional MKT1 allelic variant in sporulation efficiency variation. A mathematical model describing meiotic landmark events and conditional activation of MKT1 expression during sporulation specified an early meiotic role of this variant. By analyzing the early meiotic genome-wide transcriptional response, we demonstrate an MKT1-dependent role of novel modulators, namely, RTG1/3, regulators of mitochondrial retrograde signaling, and DAL82, regulator of nitrogen starvation, in additively effecting sporulation efficiency. In the presence of functional MKT1 allele, better respiration during early sporulation was observed, which was dependent on the mitochondrial retrograde regulator, RTG3. Furthermore, our approach showed that MKT1 contributes to sporulation independent of Puf3, an RNA-binding protein that steady-state transcription profiling studies have suggested to mediate MKT1-pleiotropic effects during mitotic growth. These results uncover interesting regulatory links between meiosis and mitochondrial retrograde signaling. In this study, we highlight the advantage
Identifying causal variants at loci with multiple signals of association.
Hormozdiari, Farhad; Kostem, Emrah; Kang, Eun Yong; Pasaniuc, Bogdan; Eskin, Eleazar
2014-10-01
Although genome-wide association studies have successfully identified thousands of risk loci for complex traits, only a handful of the biologically causal variants, responsible for association at these loci, have been successfully identified. Current statistical methods for identifying causal variants at risk loci either use the strength of the association signal in an iterative conditioning framework or estimate probabilities for variants to be causal. A main drawback of existing methods is that they rely on the simplifying assumption of a single causal variant at each risk locus, which is typically invalid at many risk loci. In this work, we propose a new statistical framework that allows for the possibility of an arbitrary number of causal variants when estimating the posterior probability of a variant being causal. A direct benefit of our approach is that we predict a set of variants for each locus that under reasonable assumptions will contain all of the true causal variants with a high confidence level (e.g., 95%) even when the locus contains multiple causal variants. We use simulations to show that our approach provides 20-50% improvement in our ability to identify the causal variants compared to the existing methods at loci harboring multiple causal variants. We validate our approach using empirical data from an expression QTL study of CHI3L2 to identify new causal variants that affect gene expression at this locus. CAVIAR is publicly available online at http://genetics.cs.ucla.edu/caviar/. PMID:25104515
Youssofzadeh, Vahab; Prasad, Girijesh; Naeem, Muhammad; Wong-Lin, KongFatt
2016-01-01
Partial Granger causality (PGC) has been applied to analyse causal functional neural connectivity after effectively mitigating confounding influences caused by endogenous latent variables and exogenous environmental inputs. However, it is not known how this connectivity obtained from PGC evolves over time. Furthermore, PGC has yet to be tested on realistic nonlinear neural circuit models and multi-trial event-related potentials (ERPs) data. In this work, we first applied a time-domain PGC technique to evaluate simulated neural circuit models, and demonstrated that the PGC measure is more accurate and robust in detecting connectivity patterns as compared to conditional Granger causality and partial directed coherence, especially when the circuit is intrinsically nonlinear. Moreover, the connectivity in PGC settles faster into a stable and correct configuration over time. After method verification, we applied PGC to reveal the causal connections of ERP trials of a mismatch negativity auditory oddball paradigm. The PGC analysis revealed a significant bilateral but asymmetrical localised activity in the temporal lobe close to the auditory cortex, and causal influences in the frontal, parietal and cingulate cortical areas, consistent with previous studies. Interestingly, the time to reach a stable connectivity configuration (~250–300 ms) coincides with the deviation of ensemble ERPs of oddball from standard tones. Finally, using a sliding time window, we showed higher resolution dynamics of causal connectivity within an ERP trial. In summary, time-domain PGC is promising in deciphering directed functional connectivity in nonlinear and ERP trials accurately, and at a sufficiently early stage. This data-driven approach can reduce computational time, and determine the key architecture for neural circuit modeling. PMID:26470866
Lane, Helen W.; Whitson, Peggy A.; Putcha, Lakshmi; Baker, Ellen; Smith, Scott M.; Stewart, Karen; Gretebeck, Randall; Nimmagudda, R. R.; Schoeller, Dale A.; Davis-Street, Janis
1999-01-01
As noted elsewhere in this report, a central goal of the Extended Duration Orbiter Medical Project (EDOMP) was to ensure that cardiovascular and muscle function were adequate to perform an emergency egress after 16 days of spaceflight. The goals of the Regulatory Physiology component of the EDOMP were to identify and subsequently ameliorate those biochemical and nutritional factors that deplete physiological reserves or increase risk for disease, and to facilitate the development of effective muscle, exercise, and cardiovascular countermeasures. The component investigations designed to meet these goals focused on biochemical and physiological aspects of nutrition and metabolism, the risk of renal (kidney) stone formation, gastrointestinal function, and sleep in space. Investigations involved both ground-based protocols to validate proposed methods and flight studies to test those methods. Two hardware tests were also completed.
Khan, Haider
2008-01-01
The purpose of this note is to clarify how the idea of "causal depth" can play a role in finding the more "approximately true" explanation through causal comparisons. It is not an exhaustive treatment but rather focuses on a few aspects that may be the most critical in evaluating the explanatory strengths of a theory in the social sciences. It presents a general argument which is anti-Humean on the critical side and scientific realist on the positive side. It also elucidates how explanations ...
Mehrara, Mohsen
2013-01-01
This paper investigates the causal relationship between education and GDP in a panel of 11 selected oil exporting countries by using panel unit root tests and panel cointegration analysis for the period 1970-2010. A three-variable model is formulated with oil exports as the third variable. The results show a strong causality from oil revenues and economic growth to education in the oil exporting countries. Yet, education does not have any significant effects on GDP in short- and long-run. It ...
Causal Loop Analysis of coastal geomorphological systems
Payo, Andres; Hall, Jim W.; French, Jon; Sutherland, James; van Maanen, Barend; Nicholls, Robert J.; Reeve, Dominic E.
2016-03-01
As geomorphologists embrace ever more sophisticated theoretical frameworks that shift from simple notions of evolution towards single steady equilibria to recognise the possibility of multiple response pathways and outcomes, morphodynamic modellers are facing the problem of how to keep track of an ever-greater number of system feedbacks. Within coastal geomorphology, capturing these feedbacks is critically important, especially as the focus of activity shifts from reductionist models founded on sediment transport fundamentals to more synthesist ones intended to resolve emergent behaviours at decadal to centennial scales. This paper addresses the challenge of mapping the feedback structure of processes controlling geomorphic system behaviour with reference to illustrative applications of Causal Loop Analysis at two study cases: (1) the erosion-accretion behaviour of graded (mixed) sediment beds, and (2) the local alongshore sediment fluxes of sand-rich shorelines. These case study examples are chosen on account of their central role in the quantitative modelling of geomorphological futures and as they illustrate different types of causation. Causal loop diagrams, a form of directed graph, are used to distil the feedback structure to reveal, in advance of more quantitative modelling, multi-response pathways and multiple outcomes. In the case of graded sediment bed, up to three different outcomes (no response, and two disequilibrium states) can be derived from a simple qualitative stability analysis. For the sand-rich local shoreline behaviour case, two fundamentally different responses of the shoreline (diffusive and anti-diffusive), triggered by small changes of the shoreline cross-shore position, can be inferred purely through analysis of the causal pathways. Explicit depiction of feedback-structure diagrams is beneficial when developing numerical models to explore coastal morphological futures. By explicitly mapping the feedbacks included and neglected within a
77 FR 61447 - Seeks Qualified Candidates for the Advisory Committee on Reactor Safeguards
2012-10-09
... Regulatory Commission. ACTION: Request for resumes. SUMMARY: The U.S. Nuclear Regulatory Commission (NRC) seeks qualified candidates for the Advisory Committee on Reactor Safeguards (ACRS). Submit resumes to Ms... appointments will be required to disclose additional financial transactions. A resume describing...
Foundational perspectives on causality in large-scale brain networks
Mannino, Michael; Bressler, Steven L.
2015-12-01
A profusion of recent work in cognitive neuroscience has been concerned with the endeavor to uncover causal influences in large-scale brain networks. However, despite the fact that many papers give a nod to the important theoretical challenges posed by the concept of causality, this explosion of research has generally not been accompanied by a rigorous conceptual analysis of the nature of causality in the brain. This review provides both a descriptive and prescriptive account of the nature of causality as found within and between large-scale brain networks. In short, it seeks to clarify the concept of causality in large-scale brain networks both philosophically and scientifically. This is accomplished by briefly reviewing the rich philosophical history of work on causality, especially focusing on contributions by David Hume, Immanuel Kant, Bertrand Russell, and Christopher Hitchcock. We go on to discuss the impact that various interpretations of modern physics have had on our understanding of causality. Throughout all this, a central focus is the distinction between theories of deterministic causality (DC), whereby causes uniquely determine their effects, and probabilistic causality (PC), whereby causes change the probability of occurrence of their effects. We argue that, given the topological complexity of its large-scale connectivity, the brain should be considered as a complex system and its causal influences treated as probabilistic in nature. We conclude that PC is well suited for explaining causality in the brain for three reasons: (1) brain causality is often mutual; (2) connectional convergence dictates that only rarely is the activity of one neuronal population uniquely determined by another one; and (3) the causal influences exerted between neuronal populations may not have observable effects. A number of different techniques are currently available to characterize causal influence in the brain. Typically, these techniques quantify the statistical
On asymmetric causal relationships in Petropolitics
Directory of Open Access Journals (Sweden)
Balan Feyza
2016-01-01
Full Text Available The aim of this paper is to examine whether the First Law of Petropolitics denominated by Friedman in 2006 is valid for OPEC countries. To do this, this paper analyses the relationship between political risk and oil supply by applying the asymmetric panel causality test suggested by Hatemi-J (2011 to these countries for the period 1984-2014. The results show that the First Law of Petropolitics is valid for Angola, Iraq, Kuwait, Libya, Nigeria, Qatar, Saudi Arabia, and the UAE, given that positive oil supply shocks significantly lead to negative political stability shocks, and negative oil supply shocks significantly lead to positive shocks in political stability.
Rapidity Correlation Structures from Causal Hydrodynamics
Gavin, Sean; Zin, Christopher
2016-01-01
Viscous diffusion can broaden the rapidity dependence of two-particle transverse momentum fluctuations. Surprisingly, measurements at RHIC by the STAR collaboration demonstrate that this broadening is accompanied by the appearance of unanticipated structure in the rapidity distribution of these fluctuations in the most central collisions. Although a first order classical Navier-Stokes theory can roughly explain the rapidity broadening, it cannot explain the additional structure. We propose that the rapidity structure can be explained using the second order causal Israel-Stewart hydrodynamics with stochastic noise.
Causality Green functions of bilocal fields
International Nuclear Information System (INIS)
It is shown by concrete examples, that the threshold value k-1 = 0 in the field quantum theory with three universal constants c, h, k, proposed in an other work, corresponding to the local theory, constitutes the bifurcation point: the causality Green function by the k finite value bifurcates into two parts: D-tildeLC and D-tildeEC. The Euclidean space-time R4 is a natural carrier of the latter one; its continuation from R4 onto R3.1 is regular, whereas the first one is singular in the zero and on the light cone and therefore it is rejected
International Nuclear Information System (INIS)
This paper investigates the causal relationship between economic growth, urbanisation and electricity consumption in the case of Angola, while utilizing the data over the period of 1971–2009. We have applied Lee and Strazicich (2003. The Review of Economics and Statistics 63, 1082–1089; 2004. Working Paper. Department of Economics, Appalachian State University) unit root tests to examine the stationarity properties of the series. Using the Gregory–Hansen structural break cointegration procedure as a complement, we employ the ARDL bounds test to investigate long run relationships. The VECM Granger causality test is subsequently used to examine the direction of causality between economic growth, urbanisation, and electricity consumption. Our results indicate the existence of long run relationships. We further observe evidence in favour of bidirectional causality between electricity consumption and economic growth. The feedback hypothesis is also found between urbanisation and economic growth. Urbanisation and electricity consumption Granger cause each other. We conclude that Angola is energy-dependent country. Consequently, the relevant authorities should boost electricity production as one of the means of achieving sustainable economic development in the long run. - Highlights: • We consider the link between electricity consumption and economic growth in Angola. • Urbanisation is added to turn the research into a trivariate investigation. • Various time series procedures are used. • Results show that increasing electricity will improve economic growth in Angola. • Results show urbanisations reduced economic growth during civil war
Luque, David; Cobos, Pedro L.; Lopez, Francisco J.
2008-01-01
In an interference-between-cues design (IbC), the expression of a learned Cue A-Outcome 1 association has been shown to be impaired if another cue, B, is separately paired with the same outcome in a second learning phase. The present study examined whether IbC could be caused by associative mechanisms independent of causal reasoning processes.…
Causal-Explanatory Pluralism: How Intentions, Functions, and Mechanisms Influence Causal Ascriptions
Lombrozo, Tania
2010-01-01
Both philosophers and psychologists have argued for the existence of distinct kinds of explanations, including teleological explanations that cite functions or goals, and mechanistic explanations that cite causal mechanisms. Theories of causation, in contrast, have generally been unitary, with dominant theories focusing either on counterfactual…
Causal mechanisms in airfoil-circulation formation
Zhu, J. Y.; Liu, T. S.; Liu, L. Q.; Zou, S. F.; Wu, J. Z.
2015-12-01
In this paper, we trace the dynamic origin, rather than any kinematic interpretations, of lift in two-dimensional flow to the physical root of airfoil circulation. We show that the key causal process is the vorticity creation by tangent pressure gradient at the airfoil surface via no-slip condition, of which the theoretical basis has been given by Lighthill ["Introduction: Boundary layer theory," in Laminar Boundary Layers, edited by L. Rosenhead (Clarendon Press, 1963), pp. 46-113], which we further elaborate. This mechanism can be clearly revealed in terms of vorticity formulation but is hidden in conventional momentum formulation, and hence has long been missing in the history of one's efforts to understand lift. By a careful numerical simulation of the flow around a NACA-0012 airfoil, and using both Eulerian and Lagrangian descriptions, we illustrate the detailed transient process by which the airfoil gains its circulation and demonstrate the dominating role of relevant dynamical causal mechanisms at the boundary. In so doing, we find that the various statements for the establishment of Kutta condition in steady inviscid flow actually correspond to a sequence of events in unsteady viscous flow.
Introducing mechanics by tapping core causal knowledge
International Nuclear Information System (INIS)
This article concerns an outline of an introductory mechanics course. It is based on the argument that various uses of the concept of force (e.g. from Kepler, Newton and everyday life) share an explanatory strategy based on core causal knowledge. The strategy consists of (a) the idea that a force causes a deviation from how an object would move of its own accord (i.e. its force-free motion), and (b) an incentive to search, where the motion deviates from the assumed force-free motion, for recurring configurations with which such deviations can be correlated (interaction theory). Various assumptions can be made concerning both the force-free motion and the interaction theory, thus giving rise to a variety of specific explanations. Kepler's semi-implicit intuition about the force-free motion is rest, Newton's explicit assumption is uniform rectilinear motion, while in everyday explanations a diversity of pragmatic suggestions can be recognized. The idea is that the explanatory strategy, once made explicit by drawing on students' intuitive causal knowledge, can be made to function for students as an advance organizer, in the sense of a general scheme that they recognize but do not yet know how to detail for scientific purposes
Emergent Horizons and Causal Structures in Holography
Banerjee, Avik; Kundu, Sandipan
2016-01-01
The open string metric arises kinematically in studying fluctuations of open string degrees of freedom on a D-brane. An observer, living on a probe D-brane, can send signals through the spacetime by using such fluctuations on the probe, that propagate in accordance with a metric which is conformal to the open string metric. Event horizons can emerge in the open string metric when one considers a D-brane with an electric field on its worldvolume. Here, we emphasize the role of and investigate, in details, the causal structure of the resulting open string event horizon and demonstrate, among other things, its close similarities to an usual black hole event horizon in asymptotically AdS-spaces. To that end, we analyze relevant geodesics, Penrose diagrams and various causal holographic observables for a given open string metric. For analytical control, most of our calculations are performed in an asymptotically AdS$_3$-background, however, we argue that the physics is qualitatively the same in higher dimensions. ...
Diagnostic reasoning using qualitative causal models
International Nuclear Information System (INIS)
The application of expert systems to reasoning problems involving real-time data from plant measurements has been a topic of much research, but few practical systems have been deployed. One obstacle to wider use of expert systems in applications involving real-time data is the lack of adequate knowledge representation methodologies for dynamic processes. Knowledge bases composed mainly of rules have disadvantages when applied to dynamic processes and real-time data. This paper describes a methodology for the development of qualitative causal models that can be used as knowledge bases for reasoning about process dynamic behavior. These models provide a systematic method for knowledge base construction, considerably reducing the engineering effort required. They also offer much better opportunities for verification and validation of the knowledge base, thus increasing the possibility of the application of expert systems to reasoning about mission critical systems. Starting with the Signed Directed Graph (SDG) method that has been successfully applied to describe the behavior of diverse dynamic processes, the paper shows how certain non-physical behaviors that result from abstraction may be eliminated by applying causal constraint to the models. The resulting Extended Signed Directed Graph (ESDG) may then be compiled to produce a model for use in process fault diagnosis. This model based reasoning methodology is used in the MOBIAS system being developed by Duke Power Company under EPRI sponsorship. 15 refs., 4 figs
EEG oscillations: From correlation to causality.
Herrmann, Christoph S; Strüber, Daniel; Helfrich, Randolph F; Engel, Andreas K
2016-05-01
Already in his first report on the discovery of the human EEG in 1929, Berger showed great interest in further elucidating the functional roles of the alpha and beta waves for normal mental activities. Meanwhile, most cognitive processes have been linked to at least one of the traditional frequency bands in the delta, theta, alpha, beta, and gamma range. Although the existing wealth of high-quality correlative EEG data led many researchers to the conviction that brain oscillations subserve various sensory and cognitive processes, a causal role can only be demonstrated by directly modulating such oscillatory signals. In this review, we highlight several methods to selectively modulate neuronal oscillations, including EEG-neurofeedback, rhythmic sensory stimulation, repetitive transcranial magnetic stimulation (rTMS), and transcranial alternating current stimulation (tACS). In particular, we discuss tACS as the most recent technique to directly modulate oscillatory brain activity. Such studies demonstrating the effectiveness of tACS comprise reports on purely behavioral or purely electrophysiological effects, on combination of behavioral effects with offline EEG measurements or on simultaneous (online) tACS-EEG recordings. Whereas most tACS studies are designed to modulate ongoing rhythmic brain activity at a specific frequency, recent evidence suggests that tACS may also modulate cross-frequency interactions. Taken together, the modulation of neuronal oscillations allows to demonstrate causal links between brain oscillations and cognitive processes and to obtain important insights into human brain function. PMID:25659527
Evidence for online processing during causal learning.
Liu, Pei-Pei; Luhmann, Christian C
2015-03-01
Many models of learning describe both the end product of learning (e.g., causal judgments) and the cognitive mechanisms that unfold on a trial-by-trial basis. However, the methods employed in the literature typically provide only indirect evidence about the unfolding cognitive processes. Here, we utilized a simultaneous secondary task to measure cognitive processing during a straightforward causal-learning task. The results from three experiments demonstrated that covariation information is not subject to uniform cognitive processing. Instead, we observed systematic variation in the processing dedicated to individual pieces of covariation information. In particular, observations that are inconsistent with previously presented covariation information appear to elicit greater cognitive processing than do observations that are consistent with previously presented covariation information. In addition, the degree of cognitive processing appears to be driven by learning per se, rather than by nonlearning processes such as memory and attention. Overall, these findings suggest that monitoring learning processes at a finer level may provide useful psychological insights into the nature of learning. PMID:25488021
Causal Conclusions that Flip Repeatedly and Their Justification
Kelly, Kevin T
2012-01-01
Over the past two decades, several consis- tent procedures have been designed to infer causal conclusions from observational data. We prove that if the true causal network might be an arbitrary, linear Gaussian net- work or a discrete Bayes network, then every unambiguous causal conclusion produced by a consistent method from non-experimental data is subject to reversal as the sample size increases any finite number of times. That result, called the causal flipping theorem, ex- tends prior results to the effect that causal discovery cannot be reliable on a given sam- ple size. We argue that since repeated flipping of causal conclusions is unavoidable in principle for consistent methods, the best possible discovery methods are consistent methods that retract their earlier conclusions no more than necessary. A series of sim- ulations of various methods across a wide range of sample sizes illustrates concretely both the theorem and the principle of com- paring methods in terms of retractions.
Comparison Analysis: Granger Causality and New Causality and Their Applications to Motor Imagery.
Hu, Sanqing; Wang, Hui; Zhang, Jianhai; Kong, Wanzeng; Cao, Yu; Kozma, Robert
2016-07-01
In this paper we first point out a fatal drawback that the widely used Granger causality (GC) needs to estimate the autoregressive model, which is equivalent to taking a series of backward recursive operations which are infeasible in many irreversible chemical reaction models. Thus, new causality (NC) proposed by Hu et al. (2011) is theoretically shown to be more sensitive to reveal true causality than GC. We then apply GC and NC to motor imagery (MI) which is an important mental process in cognitive neuroscience and psychology and has received growing attention for a long time. We study causality flow during MI using scalp electroencephalograms from nine subjects in Brain-computer interface competition IV held in 2008. We are interested in three regions: Cz (central area of the cerebral cortex), C3 (left area of the cerebral cortex), and C4 (right area of the cerebral cortex) which are considered to be optimal locations for recognizing MI states in the literature. Our results show that: 1) there is strong directional connectivity from Cz to C3/C4 during left- and right-hand MIs based on GC and NC; 2) during left-hand MI, there is directional connectivity from C4 to C3 based on GC and NC; 3) during right-hand MI, there is strong directional connectivity from C3 to C4 which is much clearly revealed by NC than by GC, i.e., NC largely improves the classification rate; and 4) NC is demonstrated to be much more sensitive to reveal causal influence between different brain regions than GC. PMID:26099149
On the causal structure between CO2 and global temperature
Adolf Stips; Diego Macias; Clare Coughlan; Elisa Garcia-Gorriz; X. San Liang
2016-01-01
We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aeroso...
Non-parametric causal inference for bivariate time series
McCracken, James M
2015-01-01
We introduce new quantities for exploratory causal inference between bivariate time series. The quantities, called penchants and leanings, are computationally straightforward to apply, follow directly from assumptions of probabilistic causality, do not depend on any assumed models for the time series generating process, and do not rely on any embedding procedures; these features may provide a clearer interpretation of the results than those from existing time series causality tools. The penchant and leaning are computed based on a structured method for computing probabilities.
Finance and Growth: Institutional Considerations, Financial Policies and Causality
Philip Arestis; Panicos Demetriades
1999-01-01
Authors in this article suggest that country specific institutional factors and policies are likely to influence the causal nature of the relationship between financial development and economic growth. Authors conduct cointegration and causality tests using time series data for twelve representative countries. The empirical results show considerable variation of causality across countries which can be explained by institutional and policy differences, providing support to the main hypothesis.
—Causality, Unintended Consequences and Deducing Shared Causes
Steven M. Shugan
2007-01-01
Despite warnings against inferring causality from observed correlations or statistical dependence, some articles do. Observed correlation is neither necessary nor sufficient to infer causality as defined by the term's everyday usage. For example, a deterministic causal process creates pseudorandom numbers; yet, we observe no correlation between the numbers. Child height correlates with spelling ability because age causes both. Moreover, order is problematic—we hear train whistles before obser...
Dark matter perturbations and viscosity: a causal approach
Acquaviva, Giovanni; John, Anslyn; Pénin, Aurélie
2016-01-01
The inclusion of dissipative effects in cosmic fluids modifies their clustering properties and could have observable effects on the formation of large scale structures. We analyse the evolution of density perturbations of cold dark matter endowed with causal bulk viscosity. The perturbative analysis is carried out in the Newtonian approximation and the bulk viscosity is described by the causal Israel-Stewart (IS) theory. In contrast to the non-causal Eckart theory, we obtain a third order evo...
The Causality between Government Revenue and Government Expenditure in Iran
2012-01-01
The causal relationship between government revenue and government expenditure is an important subject in public economics especially to the control of budget deficit. The purpose of this study is to investigate the relationship between government revenue and government expenditure in Iran by applying the bounds testing approach to cointegration. The results of the causality test show that there is a bidirectional causal relationship between government expenditure and revenues in both long run...
Integrating Probabilistic, Taxonomic and Causal Knowledge in Abductive Diagnosis
Lin, Dekang; Goebel, Randy
2013-01-01
We propose an abductive diagnosis theory that integrates probabilistic, causal and taxonomic knowledge. Probabilistic knowledge allows us to select the most likely explanation; causal knowledge allows us to make reasonable independence assumptions; taxonomic knowledge allows causation to be modeled at different levels of detail, and allows observations be described in different levels of precision. Unlike most other approaches where a causal explanation is a hypothesis that one or more causat...
A general, multivariate definition of causal effects in epidemiology.
Flanders, W Dana; Klein, Mitchel
2015-07-01
Population causal effects are often defined as contrasts of average individual-level counterfactual outcomes, comparing different exposure levels. Common examples include causal risk difference and risk ratios. These and most other examples emphasize effects on disease onset, a reflection of the usual epidemiological interest in disease occurrence. Exposure effects on other health characteristics, such as prevalence or conditional risk of a particular disability, can be important as well, but contrasts involving these other measures may often be dismissed as non-causal. For example, an observed prevalence ratio might often viewed as an estimator of a causal incidence ratio and hence subject to bias. In this manuscript, we provide and evaluate a definition of causal effects that generalizes those previously available. A key part of the generalization is that contrasts used in the definition can involve multivariate, counterfactual outcomes, rather than only univariate outcomes. An important consequence of our generalization is that, using it, one can properly define causal effects based on a wide variety of additional measures. Examples include causal prevalence ratios and differences and causal conditional risk ratios and differences. We illustrate how these additional measures can be useful, natural, easily estimated, and of public health importance. Furthermore, we discuss conditions for valid estimation of each type of causal effect, and how improper interpretation or inferences for the wrong target population can be sources of bias. PMID:25946227
Causal topology in future and past distinguishing spacetimes
International Nuclear Information System (INIS)
The causal structure of a strongly causal spacetime is particularly well endowed. Not only does it determine the conformal spacetime geometry when the spacetime dimension n > 2, as shown by Malament and Hawking-King-McCarthy (MHKM), but also the manifold dimension. The MHKM result, however, applies more generally to spacetimes satisfying the weaker causality condition of future and past distinguishability (FPD), and it is an important question whether the causal structure of such spacetimes can determine the manifold dimension. In this work, we show that the answer to this question is in the affirmative. We investigate the properties of future or past distinguishing spacetimes and show that their causal structures determine the manifold dimension. This gives a non-trivial generalization of the MHKM theorem and suggests that there is a causal topology for FPD spacetimes which encodes manifold dimension and which is strictly finer than the Alexandrov topology. We show that such a causal topology does exist. We construct it using a convergence criterion based on sequences of 'chain intervals' which are the causal analogues of null geodesic segments. We show that when the region of strong causality violation satisfies a local achronality condition, this topology is equivalent to the manifold topology in an FPD spacetime.
Causality and stability of cosmic jets
Porth, Oliver; Komissarov, Serguei S.
2015-09-01
In stark contrast to their laboratory and terrestrial counterparts, cosmic jets appear to be very stable. They are able to penetrate vast spaces, which exceed by up to a billion times the size of their central engines. We propose that the reason behind this remarkable property is the loss of causal connectivity across these jets, caused by their rapid expansion in response to fast decline of external pressure with the distance from the `jet engine'. In atmospheres with power-law pressure distribution, pext ∝ z-κ, the total loss of causal connectivity occurs, when κ > 2 - the steepness which is expected to be quite common for many astrophysical environments. This conclusion does not seem to depend on the physical nature of jets - it applies both to relativistic and non-relativistic flows, both magnetically dominated and unmagnetized jets. In order to verify it, we have carried out numerical simulations of moderately magnetized and moderately relativistic jets. The results give strong support to our hypothesis and provide with valuable insights. In particular, we find that the z-pinched inner cores of magnetic jets expand slower than their envelopes and become susceptible to instabilities even when the whole jet is stable. This may result in local dissipation and emission without global disintegration of the flow. Cosmic jets may become globally unstable when they enter flat sections of external atmospheres. We propose that the Fanaroff-Riley (FR) morphological division of extragalactic radio sources into two classes is related to this issue. In particular, we argue that the low power FR-I jets become reconfined, causally connected and globally unstable on the scale of galactic X-ray coronas, whereas more powerful FR-II jets reconfine much further out, already on the scale of radio lobes and remain largely intact until they terminate at hotspots. Using this idea, we derived the relationship between the critical jet power and the optical luminosity of the host
Quantum causality, stochastics, trajectories and information
International Nuclear Information System (INIS)
A history of the discovery of 'new' quantum mechanics and the paradoxes of its probabilistic interpretation are briefly reviewed from the modern point of view of quantum probability and information. Modern quantum theory, which has been developed during the last 20 years for the treatment of quantum open systems including quantum noise, decoherence, quantum diffusions and spontaneous jumps occurring under continuous in time observation, is not yet a part of the standard curriculum of quantum physics. It is argued that the conventional formalism of quantum mechanics is insufficient for the description of quantum events, such as spontaneous decays say, and the new experimental phenomena related to individual quantum measurements, but they have all received an adequate mathematical treatment in quantum stochastics of open systems. Moreover, the only reasonable probabilistic interpretation of quantum mechanics put forward by Max Born was, in fact, in irreconcilable contradiction with traditional mechanical reality and causality. This led to numerous quantum paradoxes, some of them due to the great inventors of quantum theory such as Einstein and Schroedinger. They are reconsidered in this paper from the modern point of view of quantum stochastics and information. The development of quantum measurement theory, initiated by von Neumann, indicated a possibility for resolution of this interpretational crisis by divorcing the algebra of the dynamical generators and the algebra of the actual observables, or Bell's beables. It is shown that within this approach quantum causality can be rehabilitated in the form of a superselection rule for compatibility of the actual histories with the potential future. This rule, together with the self-compatibility of the measurements ensuring the consistency of the histories, is called the nondemolition, or causality principle in modern quantum theory. The application of this rule in the form of dynamical commutation relations leads to the
Candidate genes of idiopathic pulmonary fibrosis: current evidence and research
Directory of Open Access Journals (Sweden)
Zhou W
2016-02-01
Full Text Available Wei Zhou,1,2 Yaping Wang1,2 1Department of Medical Genetics, 2Jiangsu Key Laboratory of Molecular Medicine, Nanjing University School of Medicine, Nanjing, People's Republic of China Abstract: Idiopathic pulmonary fibrosis (IPF is a group of common and lethal forms of idiopathic interstitial pulmonary disease. IPF is characterized by a progressive decline in lung function with a median survival of 2–3 years after diagnosis. Although the pathogenesis of the disease remains unknown, genetic predisposition could play a causal role in IPF. A set of genes have been identified as candidate genes of IPF in the past 20 years. However, the recent technological advances that allow for the analysis of millions of polymorphisms in different subjects have deepened the understanding of the genetic complexity of IPF susceptibility. Genome-wide association studies and whole-genome sequencing continue to reveal the genetic loci associated with IPF risk. In this review, we describe candidate genes on the basis of their functions and aim to gain a better understanding of the genetic basis of IPF. The discovered candidate genes may help to clarify pivotal aspects in the diagnosis, prognosis, and therapies of IPF. Keywords: idiopathic pulmonary fibrosis, candidate genes, susceptibility
Libertad de la voluntad y poderes causales Freedom of the will and causal powers
Directory of Open Access Journals (Sweden)
JOSÉ TOMÁS ALVARADO MARAMBIO
2012-03-01
Full Text Available Este trabajo discute una objeción bien conocida a la libertad de la voluntad libertaria en un mundo no determinista. En un mundo no determinista el estado de cosas total del mundo en un instante de tiempo t es compatible con diferentes estados de cosas totales alternativos en el futuro de t. Se ha argumentado que, en cuanto son posibles diferentes alternativas a una decisión libre, es una cuestión de azar y suerte que tal decisión se ha tomado. Si una decisión libre es una cuestión de suerte, entonces el agente no puede ser considerado responsable por ella. Se argumenta que la dificultad aparece en una concepción anti-realista de la causalidad, donde los hechos causales son supervenientes a regularidades o dependencias contrafácticas. Una concepción realista de la causalidad puede, por ello, explicar cómo el agente está en control causal de la decisión libre tomada, cuando la decisión no cae bajo una regularidad o una dependencia contrafáctica. Una vez considerado cómo es que el agente está en control de la decisión, se argumenta que no se puede decir que la decisión libre es una cuestión de suerte para el agente.This paper discusses a well-known objection to libertarian free will in a non-deterministic world. In a non-deterministic world the complete state of affairs of the world in an instant of time t is compatible with different alternative complete states of affairs in the future of t. It has been argued that, in so far as different alternatives are possible to a free decision, it is a matter of chance and luck that that decision is taken. If a free decision is a matter of luck, then the agent cannot be considered responsible for it. It is argued that the difficulty appears from an anti-realist conception of causality, where causal facts are supervenient on regularities or counterfactual dependences. A realist conception of causality can, then, explain how the agent is causally in control of the free decision taken when
Causality and hyperbolicity of Lovelock theories
International Nuclear Information System (INIS)
In Lovelock theories, gravity can travel faster or slower than light. The causal structure is determined by the characteristic hypersurfaces. We generalize a recent result of Izumi to prove that any Killing horizon is a characteristic hypersurface for all gravitational degrees of freedom of a Lovelock theory. Hence gravitational signals cannot escape from the region inside such a horizon. We investigate the hyperbolicity of Lovelock theories by determining the characteristic hypersurfaces for various backgrounds. First we consider Ricci flat type N spacetimes. We show that characteristic hypersurfaces are generically all non-null and that Lovelock theories are hyperbolic in any such spacetime. Next we consider static, maximally symmetric black hole solutions of Lovelock theories. Again, characteristic surfaces are generically non-null. For some small black holes, hyperbolicity is violated near the horizon. This implies that the stability of such black holes is not a well-posed problem. (paper)
On the Causal Set-Continuum Correspondence
Saravani, Mehdi
2014-01-01
We present two results which concern certain aspects of the question: when is a causal set well approximated by a Lorentzian manifold? The first result is a theorem which shows that the number-volume correspondence, if required to hold even for arbitrarily small regions, is best realized via Poisson sprinkling. The second result concerns a family of lattices in $1+1$ dimensional Minkowski space, known as Lorentzian lattices, which we show provide a much better number-volume correspondence than Poisson sprinkling for large volumes. We argue, however, that this feature should not persist in higher dimensions. We conclude by conjecturing a form of the aforementioned theorem that holds under weaker assumptions, namely that Poisson sprinkling provides the best number-volume correspondence in $3+1$ dimensions for spacetime regions with macroscopically large volumes.
Wiretap Channel with Causal State Information
Chia, Yeow-Khiang
2010-01-01
A lower bound on the secrecy capacity of the wiretap channel with state information available causally at both the encoder and decoder is established. The lower bound is shown to be strictly larger than that for the noncausal case by Liu and Chen. Achievability is proved using block Markov coding, Shannon strategy, and key generation from common state information. The state sequence available at the end of each block is used to generate a key, which is used to enhance the transmission rate of the confidential message in the following block. An upper bound on the secrecy capacity when the state is available noncausally at the encoder and decoder is established and is shown to coincide with the lower bound for several classes of wiretap channels with state.
Causality Constraints in Conformal Field Theory
CERN. Geneva
2015-01-01
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d-dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the (∂φ)4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinni...
Equity Theory Ratios as Causal Schemas
Arvanitis, Alexios; Hantzi, Alexandra
2016-01-01
Equity theory approaches justice evaluations based on ratios of exchange inputs to exchange outcomes. Situations are evaluated as just if ratios are equal and unjust if unequal. We suggest that equity ratios serve a more fundamental cognitive function than the evaluation of justice. More particularly, we propose that they serve as causal schemas for exchange outcomes, that is, they assist in determining whether certain outcomes are caused by inputs of other people in the context of an exchange process. Equality or inequality of ratios in this sense points to an exchange process. Indeed, Study 1 shows that different exchange situations, such as disproportional or balanced proportional situations, create perceptions of give-and-take on the basis of equity ratios. Study 2 shows that perceptions of justice are based more on communicatively accepted rules of interaction than equity-based evaluations, thereby offering a distinction between an attribution and an evaluation cognitive process for exchange outcomes.
Exploring Torus Universes in Causal Dynamical Triangulations
Budd, T G
2013-01-01
Motivated by the search for new observables in nonperturbative quantum gravity, we consider Causal Dynamical Triangulations (CDT) in 2+1 dimensions with the spatial topology of a torus. This system is of particular interest, because one can study not only the global scale factor, but also global shape variables in the presence of arbitrary quantum fluctuations of the geometry. Our initial investigation focusses on the dynamics of the scale factor and uncovers a qualitatively new behaviour, which leads us to investigate a novel type of boundary conditions for the path integral. Comparing large-scale features of the emergent quantum geometry in numerical simulations with a classical minisuperspace formulation, we find partial agreement. By measuring the correlation matrix of volume fluctuations we succeed in reconstructing the effective action for the scale factor directly from the simulation data. Apart from setting the stage for the analysis of shape dynamics on the torus, the new set-up highlights the role o...
Causality constraints in conformal field theory
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan
2016-05-01
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the (∂ ϕ)4 coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning operators.
A study in cosmology and causal thermodynamics
International Nuclear Information System (INIS)
The especial relativity of thermodynamic theories for reversible and irreversible processes in continuous medium is studied. The formalism referring to equilibrium and non-equilibrium configurations, and theories which includes the presence of gravitational fields are discussed. The nebular model in contraction with dissipative processes identified by heat flux and volumetric viscosity is thermodymically analysed. This model is presented by a plane conformal metric. The temperature, pressure, entropy and entropy production within thermodynamic formalism which adopts the hypothesis of local equilibrium, is calculated. The same analysis is carried out considering a causal thermodynamics, which establishes a local entropy of non-equilibrium. Possible homogeneous and isotropic cosmological models, considering the new phenomenological equation for volumetric viscosity deriving from cause thermodynamics are investigated. The found out models have plane spatial section (K=0) and some ones do not have singularities. The energy conditions are verified and the entropy production for physically reasobable models are calculated. (M.C.K.)
Causality and local determinism versus quantum nonlocality
Kupczynski, Marian
2013-01-01
The entanglement and the violation of Bell and CHSH inequalities in spin polarization correlation experiments (SPCE) is considered to be one of the biggest mysteries of Nature and is called quantum nonlocality. In this paper we show once again that this conclusion is based on imprecise terminology and on the lack of understanding of probabilistic models used in various proofs of Bell and CHSH theorems. These models are inconsistent with experimental protocols used in SPCE. This is the only reason why Bell and CHSH inequalities are violated. A probabilistic non-signalling description of SPCE, consistent with quantum predictions, is possible and it depends explicitly on the context of each experiment. It is also deterministic in the sense that the outcome is determined by supplementary local parameters describing both a physical signals and measuring instruments. The existence of such description gives additional arguments that quantum theory is emergent from some more detailed theory respecting causality and l...
Causality Constraints in Conformal Field Theory
Hartman, Thomas; Kundu, Sandipan
2015-01-01
Causality places nontrivial constraints on QFT in Lorentzian signature, for example fixing the signs of certain terms in the low energy Lagrangian. In d-dimensional conformal field theory, we show how such constraints are encoded in crossing symmetry of Euclidean correlators, and derive analogous constraints directly from the conformal bootstrap (analytically). The bootstrap setup is a Lorentzian four-point function corresponding to propagation through a shockwave. Crossing symmetry fixes the signs of certain log terms that appear in the conformal block expansion, which constrains the interactions of low-lying operators. As an application, we use the bootstrap to rederive the well known sign constraint on the $(\\partial\\phi)^4$ coupling in effective field theory, from a dual CFT. We also find constraints on theories with higher spin conserved currents. Our analysis is restricted to scalar correlators, but we argue that similar methods should also impose nontrivial constraints on the interactions of spinning o...
The balanced survivor average causal effect.
Greene, Tom; Joffe, Marshall; Hu, Bo; Li, Liang; Boucher, Ken
2013-01-01
Statistical analysis of longitudinal outcomes is often complicated by the absence of observable values in patients who die prior to their scheduled measurement. In such cases, the longitudinal data are said to be "truncated by death" to emphasize that the longitudinal measurements are not simply missing, but are undefined after death. Recently, the truncation by death problem has been investigated using the framework of principal stratification to define the target estimand as the survivor average causal effect (SACE), which in the context of a two-group randomized clinical trial is the mean difference in the longitudinal outcome between the treatment and control groups for the principal stratum of always-survivors. The SACE is not identified without untestable assumptions. These assumptions have often been formulated in terms of a monotonicity constraint requiring that the treatment does not reduce survival in any patient, in conjunction with assumed values for mean differences in the longitudinal outcome between certain principal strata. In this paper, we introduce an alternative estimand, the balanced-SACE, which is defined as the average causal effect on the longitudinal outcome in a particular subset of the always-survivors that is balanced with respect to the potential survival times under the treatment and control. We propose a simple estimator of the balanced-SACE that compares the longitudinal outcomes between equivalent fractions of the longest surviving patients between the treatment and control groups and does not require a monotonicity assumption. We provide expressions for the large sample bias of the estimator, along with sensitivity analyses and strategies to minimize this bias. We consider statistical inference under a bootstrap resampling procedure. PMID:23658214
Recursive partitioning for heterogeneous causal effects.
Athey, Susan; Imbens, Guido
2016-07-01
In this paper we propose methods for estimating heterogeneity in causal effects in experimental and observational studies and for conducting hypothesis tests about the magnitude of differences in treatment effects across subsets of the population. We provide a data-driven approach to partition the data into subpopulations that differ in the magnitude of their treatment effects. The approach enables the construction of valid confidence intervals for treatment effects, even with many covariates relative to the sample size, and without "sparsity" assumptions. We propose an "honest" approach to estimation, whereby one sample is used to construct the partition and another to estimate treatment effects for each subpopulation. Our approach builds on regression tree methods, modified to optimize for goodness of fit in treatment effects and to account for honest estimation. Our model selection criterion anticipates that bias will be eliminated by honest estimation and also accounts for the effect of making additional splits on the variance of treatment effect estimates within each subpopulation. We address the challenge that the "ground truth" for a causal effect is not observed for any individual unit, so that standard approaches to cross-validation must be modified. Through a simulation study, we show that for our preferred method honest estimation results in nominal coverage for 90% confidence intervals, whereas coverage ranges between 74% and 84% for nonhonest approaches. Honest estimation requires estimating the model with a smaller sample size; the cost in terms of mean squared error of treatment effects for our preferred method ranges between 7-22%. PMID:27382149
World oil and agricultural commodity prices: Evidence from nonlinear causality
International Nuclear Information System (INIS)
The increasing co-movements between the world oil and agricultural commodity prices have renewed interest in determining price transmission from oil prices to those of agricultural commodities. This study extends the literature on the oil-agricultural commodity prices nexus, which particularly concentrates on nonlinear causal relationships between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). To this end, the linear causality approach of Toda-Yamamoto and the nonparametric causality method of Diks-Panchenko are applied to the weekly data spanning from 1994 to 2010. The linear causality analysis indicates that the oil prices and the agricultural commodity prices do not influence each other, which supports evidence on the neutrality hypothesis. In contrast, the nonlinear causality analysis shows that: (i) there are nonlinear feedbacks between the oil and the agricultural prices, and (ii) there is a persistent unidirectional nonlinear causality running from the oil prices to the corn and to the soybeans prices. The findings from the nonlinear causality analysis therefore provide clues for better understanding the recent dynamics of the agricultural commodity prices and some policy implications for policy makers, farmers, and global investors. This study also suggests the directions for future studies. - Research highlights: → This study determines the price transmission mechanisms between the world oil and three key agricultural commodity prices (corn, soybeans, and wheat). → The linear and nonlinear cointegration and causality methods are carried out. → The linear causality analysis supports evidence on the neutrality hypothesis. → The nonlinear causality analysis shows that there is a persistent unidirectional causality from the oil prices to the corn and to the soybeans prices.
Directory of Open Access Journals (Sweden)
Alex Clop
Full Text Available Psoriasis is an immune-mediated skin disorder that is inherited as a complex genetic trait. Although genome-wide association scans (GWAS have identified 36 disease susceptibility regions, more than 50% of the genetic variance can be attributed to a single Major Histocompatibility Complex (MHC locus, known as PSORS1. Genetic studies indicate that HLA-C is the strongest PSORS1 candidate gene, since markers tagging HLA-Cw*0602 consistently generate the most significant association signals in GWAS. However, it is unclear whether HLA-Cw*0602 is itself the causal PSORS1 allele, especially as the role of SNPs that may affect its expression has not been investigated. Here, we have undertaken an in-depth molecular characterization of the PSORS1 interval, with a view to identifying regulatory variants that may contribute to disease susceptibility. By analysing high-density SNP data, we refined PSORS1 to a 179 kb region encompassing HLA-C and the neighbouring HCG27 pseudogene. We compared multiple MHC sequences spanning this refined locus and identified 144 candidate susceptibility variants, which are unique to chromosomes bearing HLA-Cw*0602. In parallel, we investigated the epigenetic profile of the critical PSORS1 interval and uncovered three enhancer elements likely to be active in T lymphocytes. Finally we showed that nine candidate susceptibility SNPs map within a HLA-C enhancer and that three of these variants co-localise with binding sites for immune-related transcription factors. These data indicate that SNPs affecting HLA-Cw*0602 expression are likely to contribute to psoriasis susceptibility and highlight the importance of integrating multiple experimental approaches in the investigation of complex genomic regions such as the MHC.
Directory of Open Access Journals (Sweden)
Bernard N. Iyke
2014-06-01
Full Text Available This paper examines the dynamic causal relationship between electricity consumption and economic growth in Ghana within a trivariate ARDL framework, for the period 1971–2012.The paper obviates the variable omission bias, and the use of cross-sectional techniques that characterise most existing studies. The results show that there is a distinct causal flow from economic growth to electricity consumption: both in the short run and in the long run. This finding supports the growth-led electricity consumption hypothesis, as documented in the literature. The paper urges policymakers in Ghana to resort to alternative sources of electric power generation, in order to reduce any future pressures on the current sources of electricity production. Appropriate monetary policies must also be put in place, in order to accommodate potential inflation hikes stemming from excessive demands for electricity in the near future.
Productivity Analysis of Public and Private Airports: A Causal Investigation
Vasigh, Bijan; Gorjidooz, Javad
2007-01-01
Around the world, airports are being viewed as enterprises, rather than public services, which are expected to be managed efficiently and provide passengers with courteous customer services. Governments are, increasingly, turning to the private sectors for their efficiency in managing the operation, financing, and development, as well as providing security for airports. Operational and financial performance evaluation has become increasingly important to airport operators due to recent trends in airport privatization. Assessing performance allows the airport operators to plan for human resources and capital investment as efficiently as possible. Productivity measurements may be used as comparisons and guidelines in strategic planning, in the internal analysis of operational efficiency and effectiveness, and in assessing the competitive position of an airport in transportation industry. The primary purpose of this paper is to investigate the operational and financial efficiencies of 22 major airports in the United States and Europe. These airports are divided into three groups based on private ownership (7 British Airport Authority airports), public ownership (8 major United States airports), and a mix of private and public ownership (7 major European Union airports. The detail ownership structures of these airports are presented in Appendix A. Total factor productivity (TFP) model was utilized to measure airport performance in terms of financial and operational efficiencies and to develop a benchmarking tool to identify the areas of strength and weakness. A regression model was then employed to measure the relationship between TFP and ownership structure. Finally a Granger causality test was performed to determine whether ownership structure is a Granger cause of TFP. The results of the analysis presented in this paper demonstrate that there is not a significant relationship between airport TFP and ownership structure. Airport productivity and efficiency is
Attribute Exploration of Gene Regulatory Processes
Wollbold, Johannes
2012-01-01
This thesis aims at the logical analysis of discrete processes, in particular of such generated by gene regulatory networks. States, transitions and operators from temporal logics are expressed in the language of Formal Concept Analysis. By the attribute exploration algorithm, an expert or a computer program is enabled to validate a minimal and complete set of implications, e.g. by comparison of predictions derived from literature with observed data. Here, these rules represent temporal dependencies within gene regulatory networks including coexpression of genes, reachability of states, invariants or possible causal relationships. This new approach is embedded into the theory of universal coalgebras, particularly automata, Kripke structures and Labelled Transition Systems. A comparison with the temporal expressivity of Description Logics is made. The main theoretical results concern the integration of background knowledge into the successive exploration of the defined data structures (formal contexts). Applyi...
Manifest Variable Granger Causality Models for Developmental Research: A Taxonomy
von Eye, Alexander; Wiedermann, Wolfgang
2015-01-01
Granger models are popular when it comes to testing hypotheses that relate series of measures causally to each other. In this article, we propose a taxonomy of Granger causality models. The taxonomy results from crossing the four variables Order of Lag, Type of (Contemporaneous) Effect, Direction of Effect, and Segment of Dependent Series…
Child Care Subsidy Use and Child Development: Potential Causal Mechanisms
Hawkinson, Laura E.
2011-01-01
Research using an experimental design is needed to provide firm causal evidence on the impacts of child care subsidy use on child development, and on underlying causal mechanisms since subsidies can affect child development only indirectly via changes they cause in children's early experiences. However, before costly experimental research is…
Causal Propagators for the Second Order Wilson Loop
Pimentel, B. M.; Tomazelli, J. L.
1996-01-01
We evaluate the Wilson loop at second order in general non-covariant gauges by means of the causal principal-value prescription for the gauge- dependent poles in the gauge-boson propagator and show that the result agrees with the usual causal prescriptions.
Evidence for Deductive Reasoning in Blocking of Causal Judgments
Mitchell, C.J.; Lovibond, P.F.; Condoleon, M.
2005-01-01
We have recently demonstrated that pre-training of additivity (the outcome of two causal cues is larger than one causal cue) greatly enhances blocking. This manipulation could work by removing a ceiling effect on the outcome, as proposed by Cheng (1997). Alternatively, it could remove the logical ambiguity associated with blocking under…
Time Symmetric Quantum Mechanics and Causal Classical Physics
Bopp, Fritz W
2016-01-01
A two boundary quantum mechanics without time ordered causal structure is advocated as consistent theory. The apparent causal structure of usual "near future" macroscopic phenomena is attributed to a cosmological asymmetry and to rules governing the transition between microscopic to macroscopic observations. Our interest is a heuristic understanding of the resulting macroscopic physics.
Cause and Event: Supporting Causal Claims through Logistic Models
O'Connell, Ann A.; Gray, DeLeon L.
2011-01-01
Efforts to identify and support credible causal claims have received intense interest in the research community, particularly over the past few decades. In this paper, we focus on the use of statistical procedures designed to support causal claims for a treatment or intervention when the response variable of interest is dichotomous. We identify…
The causal boundary and its relations with the conformal boundary
Energy Technology Data Exchange (ETDEWEB)
Herrera, J, E-mail: jherrera@agt.cie.uma.e [Departamento de Algebra, GeometrIa y TopologIa, Facultad de Ciencias, Universidad de Malaga, Campus Teatinos, 29071 Malaga (Spain)
2010-05-01
Our aim in this note is to present the results (obtained in [2]) which ensure that, under certain regularity conditions, the conformal boundary becomes equal to the causal boundary, not only as a point set, but in a topological and chronological level. In particular, under these conditions the conformal boundary becomes a powerful tool to compute the causal one.
Causal Discourse Analyzer: Improving Automated Feedback on Academic ESL Writing
Chukharev-Hudilainen, Evgeny; Saricaoglu, Aysel
2016-01-01
Expressing causal relations plays a central role in academic writing. While it is important that writing instructors assess and provide feedback on learners' causal discourse, it could be a very time-consuming task. In this respect, automated writing evaluation (AWE) tools may be helpful. However, to date, there have been no AWE tools capable of…
Thinking Fast and Slow about Causality: Response to Palinkas
Marsh, Jeanne C.
2014-01-01
Larry Palinkas advances the developing science of social work by providing an explanation of how social science research methods, both qualitative and quantitative, can improve our capacity to draw casual inferences. Understanding causal relations and making causal inferences--with the promise of being able to predict and control outcomes--is…
From Blickets to Synapses: Inferring Temporal Causal Networks by Observation
Fernando, Chrisantha
2013-01-01
How do human infants learn the causal dependencies between events? Evidence suggests that this remarkable feat can be achieved by observation of only a handful of examples. Many computational models have been produced to explain how infants perform causal inference without explicit teaching about statistics or the scientific method. Here, we…
Temporal and Causal Reasoning in Deaf and Hearing Novice Readers
Sullivan, Susan; Oakhill, Jane; Arfé, Barbara; Boureux, Magali
2014-01-01
Temporal and causal information in text are crucial in helping the reader form a coherent representation of a narrative. Deaf novice readers are generally poor at processing linguistic markers of causal/temporal information (i.e., connectives), but what is unclear is whether this is indicative of a more general deficit in reasoning about…
Advanced Vaccine Candidates for Lassa Fever
Directory of Open Access Journals (Sweden)
Igor S. Lukashevich
2012-10-01
Full Text Available Lassa virus (LASV is the most prominent human pathogen of the Arenaviridae. The virus is transmitted to humans by a rodent reservoir, Mastomys natalensis, and is capable of causing lethal Lassa Fever (LF. LASV has the highest human impact of any of the viral hemorrhagic fevers (with the exception of Dengue Fever with an estimated several hundred thousand infections annually, resulting in thousands of deaths in Western Africa. The sizeable disease burden, numerous imported cases of LF in non-endemic countries, and the possibility that LASV can be used as an agent of biological warfare make a strong case for vaccine development. Presently there is no licensed vaccine against LF or approved treatment. Recently, several promising vaccine candidates have been developed which can potentially target different groups at risk. The purpose of this manuscript is to review the LASV pathogenesis and immune mechanisms involved in protection. The current status of pre-clinical development of the advanced vaccine candidates that have been tested in non-human primates will be discussed. Major scientific, manufacturing, and regulatory challenges will also be considered.
Advanced vaccine candidates for Lassa fever.
Lukashevich, Igor S
2012-11-01
Lassa virus (LASV) is the most prominent human pathogen of the Arenaviridae. The virus is transmitted to humans by a rodent reservoir, Mastomys natalensis, and is capable of causing lethal Lassa Fever (LF). LASV has the highest human impact of any of the viral hemorrhagic fevers (with the exception of Dengue Fever) with an estimated several hundred thousand infections annually, resulting in thousands of deaths in Western Africa. The sizeable disease burden, numerous imported cases of LF in non-endemic countries, and the possibility that LASV can be used as an agent of biological warfare make a strong case for vaccine development. Presently there is no licensed vaccine against LF or approved treatment. Recently, several promising vaccine candidates have been developed which can potentially target different groups at risk. The purpose of this manuscript is to review the LASV pathogenesis and immune mechanisms involved in protection. The current status of pre-clinical development of the advanced vaccine candidates that have been tested in non-human primates will be discussed. Major scientific, manufacturing, and regulatory challenges will also be considered. PMID:23202493
Advanced Vaccine Candidates for Lassa Fever
Lukashevich, Igor S.
2012-01-01
Lassa virus (LASV) is the most prominent human pathogen of the Arenaviridae. The virus is transmitted to humans by a rodent reservoir, Mastomys natalensis, and is capable of causing lethal Lassa Fever (LF). LASV has the highest human impact of any of the viral hemorrhagic fevers (with the exception of Dengue Fever) with an estimated several hundred thousand infections annually, resulting in thousands of deaths in Western Africa. The sizeable disease burden, numerous imported cases of LF in non-endemic countries, and the possibility that LASV can be used as an agent of biological warfare make a strong case for vaccine development. Presently there is no licensed vaccine against LF or approved treatment. Recently, several promising vaccine candidates have been developed which can potentially target different groups at risk. The purpose of this manuscript is to review the LASV pathogenesis and immune mechanisms involved in protection. The current status of pre-clinical development of the advanced vaccine candidates that have been tested in non-human primates will be discussed. Major scientific, manufacturing, and regulatory challenges will also be considered. PMID:23202493
Quantum objects as elementary units of causality and locality
Diel, Hans H
2016-01-01
The author's attempt to construct a local causal model of quantum theory (QT) that includes quantum field theory (QFT) resulted in the identification of "quantum objects" as the elementary units of causality and locality. Quantum objects are collections of particles (including single particles) whose collective dynamics and measurement results can only be described by the laws of QT and QFT. Local causal models of quantum objects' internal dynamics are not possible if a locality is understood as a space-point locality. Within quantum objects, state transitions may occur which instantly affect the whole quantum object. The identification of quantum objects as the elementary units of causality and locality has two primary implications for a causal model of quantum objects: (1) quantum objects run autonomously with system-state update frequencies based on their local proper times and with either no or minimal dependency on external parameters. (2) The laws of physics that describe global (but relativistic) inter...
A causal net approach to relativistic quantum mechanics
Bateson, R. D.
2012-05-01
In this paper we discuss a causal network approach to describing relativistic quantum mechanics. Each vertex on the causal net represents a possible point event or particle observation. By constructing the simplest causal net based on Reichenbach-like conjunctive forks in proper time we can exactly derive the 1+1 dimension Dirac equation for a relativistic fermion and correctly model quantum mechanical statistics. Symmetries of the net provide various quantum mechanical effects such as quantum uncertainty and wavefunction, phase, spin, negative energy states and the effect of a potential. The causal net can be embedded in 3+1 dimensions and is consistent with the conventional Dirac equation. In the low velocity limit the causal net approximates to the Schrodinger equation and Pauli equation for an electromagnetic field. Extending to different momentum states the net is compatible with the Feynman path integral approach to quantum mechanics that allows calculation of well known quantum phenomena such as diffraction.
A causal net approach to relativistic quantum mechanics
International Nuclear Information System (INIS)
In this paper we discuss a causal network approach to describing relativistic quantum mechanics. Each vertex on the causal net represents a possible point event or particle observation. By constructing the simplest causal net based on Reichenbach-like conjunctive forks in proper time we can exactly derive the 1+1 dimension Dirac equation for a relativistic fermion and correctly model quantum mechanical statistics. Symmetries of the net provide various quantum mechanical effects such as quantum uncertainty and wavefunction, phase, spin, negative energy states and the effect of a potential. The causal net can be embedded in 3+1 dimensions and is consistent with the conventional Dirac equation. In the low velocity limit the causal net approximates to the Schrodinger equation and Pauli equation for an electromagnetic field. Extending to different momentum states the net is compatible with the Feynman path integral approach to quantum mechanics that allows calculation of well known quantum phenomena such as diffraction.
Reinforcing the glass ceiling: The consequences of hostile sexism for female managerial candidates
Masser, Barbara; Abrams, Dominic
2004-01-01
Previous research has established that benevolent sexism is related to the negative evaluation of women who violate specific norms for behavior. Research has yet to document the causal impact of hostile sexism on evaluations of individual targets. Correlational evidence and ambivalent sexism theory led us to predict that hostile sexism would be associated with negative evaluations of a female candidate for a masculine-typed occupational role. Participants completed the ASI (P. ...
Spruce, Joseph; Hargrove, William; Norman Steve; Christie, William
2014-01-01
Near real time forest disturbance detection maps from MODIS NDVI phenology data have been produced since 2010 for the conterminous U.S., as part of the on-line ForWarn national forest threat early warning system. The latter has been used by the forest health community to identify and track many regional forest disturbances caused by multiple biotic and abiotic damage agents. Attribution of causal agents for detected disturbances has been a goal since project initiation in 2006. Combined with detailed cover type maps, geospatial pest phenology data offer a potential means for narrowing the candidate causal agents responsible for a given biotic disturbance. U.S. Aerial Detection Surveys (ADS) employ such phenology data. Historic ADS products provide general locational data on recent insect-induced forest type specific disturbances that may help in determining candidate causal agents for MODIS-based disturbance maps, especially when combined with other historic geospatial disturbance data (e.g., wildfire burn scars and drought maps). Historic ADS disturbance detection polygons can show severe and extensive regional forest disturbances, though they also can show polygons with sparsely scattered or infrequent disturbances. Examples will be discussed that use various historic disturbance data to help determine potential causes of MODIS-detected regional forest disturbance anomalies.
Propagation of genetic variation in gene regulatory networks
Plahte, Erik; Gjuvsland, Arne B; Omholt, Stig W.
2013-01-01
A future quantitative genetics theory should link genetic variation to phenotypic variation in a causally cohesive way based on how genes actually work and interact. We provide a theoretical framework for predicting and understanding the manifestation of genetic variation in haploid and diploid regulatory networks with arbitrary feedback structures and intra-locus and inter-locus functional dependencies. Using results from network and graph theory, we define propagation functions describing h...
Grouped graphical Granger modeling for gene expression regulatory networks discovery
Lozano, Aurélie C.; Abe, Naoki; Yan LIU; Rosset, Saharon
2009-01-01
We consider the problem of discovering gene regulatory networks from time-series microarray data. Recently, graphical Granger modeling has gained considerable attention as a promising direction for addressing this problem. These methods apply graphical modeling methods on time-series data and invoke the notion of ‘Granger causality’ to make assertions on causality through inference on time-lagged effects. Existing algorithms, however, have neglected an important aspect of the problem—the grou...
On the basic computational structure of gene regulatory networks
Rodriguez-Caso, Carlos; Corominas-Murtra, Bernat; Solé, Ricard V.
2009-01-01
Gene regulatory networks constitute the first layer of the cellular computation for cell adaptation and surveillance. In these webs, a set of causal relations is built up from thousands of interactions between transcription factors and their target genes. The large size of these webs and their entangled nature make difficult to achieve a global view of their internal organisation. Here, this problem has been addressed through a comparative study for {\\em Escherichia coli}, {\\em Bacillus subti...
Directory of Open Access Journals (Sweden)
York eHagmayer
2014-11-01
Full Text Available Cognitive psychological research focusses on causal learning and reasoning while cognitive anthropological and social science research tend to focus on systems of beliefs. Our aim was to explore how these two types of research can inform each other. Cognitive psychological theories (causal model theory and causal Bayes nets were used to derive predictions for systems of causal beliefs. These predictions were then applied to lay theories of depression as a specific test case. A systematic literature review on causal beliefs about depression was conducted, including original, quantitative research. Thirty-six studies investigating 13 non-Western and 32 Western cultural groups were analysed by classifying assumed causes and preferred forms of treatment into common categories. Relations between beliefs and treatment preferences were assessed. Substantial agreement between cultural groups was found with respect to the impact of observable causes. Stress was generally rated as most important. Less agreement resulted for hidden, especially supernatural causes. Causal beliefs were clearly related to treatment preferences in Western groups, while evidence was mostly lacking for non-Western groups. Overall predictions were supported, but there were considerable methodological limitations. Pointers to future research, which may combine studies on causal beliefs with experimental paradigms on causal reasoning, are given.
Dijk, van J.; Breedveld, P.C.
1991-01-01
The existence of zero-order causal paths in bond graphs of physical systems implies the set of state equations to be an implicit mixed set of Differential and Algebraic Equations (DAEs). In the block diagram expansion of such a bond graph, this type of causal path corresponds with a zero-order loop.
Sizochenko, Natalia; Gajewicz, Agnieszka; Leszczynski, Jerzy; Puzyn, Tomasz
2016-03-01
In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal analysis of multivariate data. Methods of causal discovery have been applied for broader physical insight into mechanisms of action and interpretation of the developed nano-QSAR models. Previously developed nano-QSAR models for toxicity of 17 nano-sized metal oxides towards E. coli bacteria have been validated by means of the causality criteria. Using the descriptors confirmed by the causal technique, we have developed new models consistent with the straightforward causal-reasoning account. It was proven that causal inference methods are able to provide a more robust mechanistic interpretation of the developed nano-QSAR models.In this paper, we suggest that causal inference methods could be efficiently used in Quantitative Structure-Activity Relationships (QSAR) modeling as additional validation criteria within quality evaluation of the model. Verification of the relationships between descriptors and toxicity or other activity in the QSAR model has a vital role in understanding the mechanisms of action. The well-known phrase ``correlation does not imply causation'' reflects insight statistically correlated with the endpoint descriptor may not cause the emergence of this endpoint. Hence, paradigmatic shifts must be undertaken when moving from traditional statistical correlation analysis to causal
Generalized Causal Set d'Alembertians
Aslanbeigi, Siavash; Sorkin, Rafael D
2014-01-01
We introduce a family of generalized d'Alembertian operators in D-dimensional Minkowski spacetimes which are manifestly Lorentz-invariant, retarded, and non-local, the extent of the nonlocality being governed by a single parameter $\\rho$. The prototypes of these operators arose in earlier work as averages of matrix operators meant to describe the propagation of a scalar field in a causal set. We generalize the original definitions to produce an infinite family of ''Generalized Causet Box (GCB) operators'' parametrized by certain coefficients $\\{a,b_n\\}$, and we derive the conditions on the latter needed for the usual d'Alembertian to be recovered in the infrared limit. The continuum average of a GCB operator is an integral operator, and it is these continuum operators that we mainly study. To that end, we compute their action on plane waves, or equivalently their Fourier transforms g(p) [p being the momentum-vector]. For timelike p, g(p) has an imaginary part whose sign depends on whether p is past or future-...
Causal mediation analysis with a latent mediator.
Albert, Jeffrey M; Geng, Cuiyu; Nelson, Suchitra
2016-05-01
Health researchers are often interested in assessing the direct effect of a treatment or exposure on an outcome variable, as well as its indirect (or mediation) effect through an intermediate variable (or mediator). For an outcome following a nonlinear model, the mediation formula may be used to estimate causally interpretable mediation effects. This method, like others, assumes that the mediator is observed. However, as is common in structural equations modeling, we may wish to consider a latent (unobserved) mediator. We follow a potential outcomes framework and assume a generalized structural equations model (GSEM). We provide maximum-likelihood estimation of GSEM parameters using an approximate Monte Carlo EM algorithm, coupled with a mediation formula approach to estimate natural direct and indirect effects. The method relies on an untestable sequential ignorability assumption; we assess robustness to this assumption by adapting a recently proposed method for sensitivity analysis. Simulation studies show good properties of the proposed estimators in plausible scenarios. Our method is applied to a study of the effect of mother education on occurrence of adolescent dental caries, in which we examine possible mediation through latent oral health behavior. PMID:26363769
Dynamic causal models and autopoietic systems.
David, Olivier
2007-01-01
Dynamic Causal Modelling (DCM) and the theory of autopoietic systems are two important conceptual frameworks. In this review, we suggest that they can be combined to answer important questions about self-organising systems like the brain. DCM has been developed recently by the neuroimaging community to explain, using biophysical models, the non-invasive brain imaging data are caused by neural processes. It allows one to ask mechanistic questions about the implementation of cerebral processes. In DCM the parameters of biophysical models are estimated from measured data and the evidence for each model is evaluated. This enables one to test different functional hypotheses (i.e., models) for a given data set. Autopoiesis and related formal theories of biological systems as autonomous machines represent a body of concepts with many successful applications. However, autopoiesis has remained largely theoretical and has not penetrated the empiricism of cognitive neuroscience. In this review, we try to show the connections that exist between DCM and autopoiesis. In particular, we propose a simple modification to standard formulations of DCM that includes autonomous processes. The idea is to exploit the machinery of the system identification of DCMs in neuroimaging to test the face validity of the autopoietic theory applied to neural subsystems. We illustrate the theoretical concepts and their implications for interpreting electroencephalographic signals acquired during amygdala stimulation in an epileptic patient. The results suggest that DCM represents a relevant biophysical approach to brain functional organisation, with a potential that is yet to be fully evaluated. PMID:18575681
Causality and supersymmetry in the superstring theory
International Nuclear Information System (INIS)
Reduction of the ten-dimensional, heterotic-superstring effective action S-circumflex including quartic higher-derivative terms R-circumflex4 yields a physical four-action S which is tachyon-free up to quadratic order R2 - the masses M0 and M2 of the spin-0 and spin-2 particles are both real - when the internal six-space is a Calabi-Yau metric g-barμν and N=1 supersymmetry is preserved via equation dH-bar≡tr(R-bar and R-bar)-Tr(F-bar and F-bar)/30=0, where H-barμνξ is the totally antisymmetric three-index field (while the bosonic string and type-II superstring may contain a spin-2 tachyon and a spin-0 tachyon, respectively). Here, we show that this crucial feature is independent of imposing supersymmetry, for if dH-bar≠ 0, there is an additional contribution to R2 which, however, produces no tachyons. Thus, the requirement of a stable, causal theory singles out the heterotic superstring irrespective of the requirement of N=1 supersymmetry, which is essential at high energies rather for its roles in the vanishing of the cosmological constant and the maintenance of the gauge hierarchy
Body selectivity in occipitotemporal cortex: Causal evidence.
Downing, Paul E; Peelen, Marius V
2016-03-01
Perception of others' bodies provides information that is useful for a number of important social-cognitive processes. Evidence from neuroimaging methods has identified focal cortical regions that are highly selective for perceiving bodies and body parts, including the extrastriate body area (EBA) and fusiform body area (FBA). Our understanding of the functional properties of these regions, and their causal contributions to behavior, has benefitted from the study of neuropsychological patients and particularly from investigations using transcranial magnetic stimulation (TMS). We review this evidence, focusing on TMS studies that are revealing of how (and when) activity in EBA contributes to detecting people in natural scenes; to resolving their body shape, movements, actions, individual parts, and identities; and to guiding goal-directed behavior. These findings are considered in reference to a framework for body perception in which the patterns of neural activity in EBA and FBA jointly serve to make explicit the elements of the visual scene that correspond to the body and its parts. These representations are modulated by other sources of information such as prior knowledge, and are shared with wider brain networks involved in many aspects of social cognition. PMID:26044771
DEFF Research Database (Denmark)
Staalsoe, Trine; Jensen, Anja T R; Theander, Thor G; Hviid, Lars
2002-01-01
statistically significant co-variation with protection rather than on demonstration of causal relationships. We have studied the relationship between variant surface antigen-specific antibodies and clinical protection from Plasmodium falciparum malaria in general, and from pregnancy-associated malaria (PAM) in......Malaria vaccine development has traditionally concentrated on careful molecular, biochemical, and immunological characterisation of candidate antigens. In contrast, evidence of the importance of identified antigens in immunity to human infection and disease has generally been limited to...... particular, to provide robust evidence of a causal link between the two in order to allow efficient and evidence-based identification of candidate antigens for malaria vaccine development....
Time reordered: Causal perception guides the interpretation of temporal order.
Bechlivanidis, Christos; Lagnado, David A
2016-01-01
We present a novel temporal illusion in which the perceived order of events is dictated by their perceived causal relationship. Participants view a simple Michotte-style launching sequence featuring 3 objects, in which one object starts moving before its presumed cause. Not only did participants re-order the events in a causally consistent way, thus violating the objective temporal order, but they also failed to recognise the clip they had seen, preferring a clip in which temporal and causal order matched. We show that the effect is not due to lack of attention to the presented events and we discuss the problem of determining whether causality affects temporal order at an early perceptual stage or whether it distorts an accurately perceived order during retrieval. Alternatively, we propose a mechanism by which temporal order is neither misperceived nor misremembered but inferred "on-demand" given phenomenal causality and the temporal priority principle, the assumption that causes precede their effects. Finally, we discuss how, contrary to theories of causal perception, impressions of causality can be generated from dynamic sequences with strong spatiotemporal deviations. PMID:26402648
Causality between Prices and Wages: VECM Analysis for EU-27
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Adriatik Hoxha
2010-09-01
Full Text Available The literature on causality as well as the empirical evidence clearly shows that there are two opposing groups of economists, who support different hypotheses with respect to the flow of causality in the price-wage causal relationship. The first group argues that causality runs from wages to prices, whereas the second argues that effect flows from prices to wages. Nonetheless, the literature review suggeststhat there is at least some consensus in that researcher’s conclusions may be contingent on the type of data employed, applied econometric model, or even that relationship may alter with economic cycles. This paper empirically examines theprice-wage causal relationship in EU-27, by using the OLS and VECM analysis, and it also provides robust evidence in support of a bilateral causal relationship between prices and wages, both in long-run as well as in the shortrun.Prior to designing and estimating the econometric model we have performed stationarity tests for the employed price, wage and productivity variables. Additionally, we have also specified the model taking into account the lag order as well as the rank of co-integration for the co-integrated variables. Furthermore, we have also applied respective restrictions on the parameters of estimatedVECM. The evidence resulting from model robustness checks indicates that results are statistically robust. Although far from closing the issue of causality between prices and wages, this paper at least provides some fresh evidence in the case of EU-27.
Causality between Prices and Wages: VECM Analysis for EU-12
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Adriatik HOXHA
2010-05-01
Full Text Available The literature on causality as well as the empirical evidence clearly shows that there are two opposing groups of economists, who support different hypotheses with respect to the flow of causality in the price-wage causal relationship. The first group argues that causality runs from wages to price, whereas the second argue that effect flows from prices to wages. Nonetheless, there is at least some consensus that researchers conclusions may be contingent on the type of data employed, applied econometric model, or even that the relationship may vary through economic cycles. This paper empirically examines the pricewage causal relationship in EMU, by using OLS and VECM analysis, and also it provides robust evidence in support of a bilateral causal relationship between prices and wages, both in long-run as well as in the short-run. Prior to designing and estimating the econometric model we have performed stationarity tests for the employed price, wage and productivity variables. Additionally, we have also specified the model taking into account the lag order as well as the rank of co-integration for the co-integrated variables. Furthermore, we have also applied respective restrictions on the parameters of the estimated VECM and finally model robustness checks indicate that results are statistically robust. Although far from closing the issue of causality between prices and variables, this paper at least provides some fresh evidence for the case of EMU.
A Complex Systems Approach to Causal Discovery in Psychiatry.
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Glenn N Saxe
Full Text Available Conventional research methodologies and data analytic approaches in psychiatric research are unable to reliably infer causal relations without experimental designs, or to make inferences about the functional properties of the complex systems in which psychiatric disorders are embedded. This article describes a series of studies to validate a novel hybrid computational approach--the Complex Systems-Causal Network (CS-CN method-designed to integrate causal discovery within a complex systems framework for psychiatric research. The CS-CN method was first applied to an existing dataset on psychopathology in 163 children hospitalized with injuries (validation study. Next, it was applied to a much larger dataset of traumatized children (replication study. Finally, the CS-CN method was applied in a controlled experiment using a 'gold standard' dataset for causal discovery and compared with other methods for accurately detecting causal variables (resimulation controlled experiment. The CS-CN method successfully detected a causal network of 111 variables and 167 bivariate relations in the initial validation study. This causal network had well-defined adaptive properties and a set of variables was found that disproportionally contributed to these properties. Modeling the removal of these variables resulted in significant loss of adaptive properties. The CS-CN method was successfully applied in the replication study and performed better than traditional statistical methods, and similarly to state-of-the-art causal discovery algorithms in the causal detection experiment. The CS-CN method was validated, replicated, and yielded both novel and previously validated findings related to risk factors and potential treatments of psychiatric disorders. The novel approach yields both fine-grain (micro and high-level (macro insights and thus represents a promising approach for complex systems-oriented research in psychiatry.
Causality and prediction: differences and points of contact
Directory of Open Access Journals (Sweden)
Luis Carlos Silva Ayçaguer, PhD
2014-09-01
Full Text Available This contribution presents the differences between those variables that might play a causal role in a certain process and those only valuable for predicting the outcome. Some considerations are made about the core intervention of the association and the temporal precedence and biases in both cases, the study of causality and predictive modeling. In that context, several relevant aspects related to the design of the corresponding studies are briefly reviewed and some of the mistakes that are often committed in handling both, causality and prediction, are illustrated.
Stock Market and Economic Growth in Malaysia: Causality Test
Har Wai Mun; Ee Chun Siong; Tan Chai Thing
2009-01-01
Stock market has been associated with economic growth through its role as source for new private capital. On the other hand, economic growth may be the catalyst for stock market growth. Thus, the purpose of this paper was to explore causal relationships between stock market and the economy using formal tests of causality developed by C. J. Granger and yearly Malaysia data for the period 1977-2006. Results show that stock market Granger-caused economic activity with no reverse causality obser...
Spatial Causality. An application to the Deforestation Process in Bolivia
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Javier Aliaga
2011-01-01
Full Text Available This paper analyses the causes of deforestation for a representative set of Bolivian municipalities. The literature on environmental economics insists on the importance of physical and social factors. We focus on the last group of variables. Our objective is to identify causal mechanisms between these factors of risk and the problem of deforestation. To this end, we present a testing strategy for spatial causality, based on a sequence of Lagrange Multipliers. The results that we obtain for the Bolivian case confirm only partially the traditional view of the problem of deforestation. Indeed, we only find unequivocal signs of causality in relation to the structure of property rights.
Effects of inhomogeneity on the causal entropic prediction of Λ
Phillips, Daniel; Albrecht, Andreas
2011-12-01
The causal entropic principle aims to predict the unexpectedly small value of the cosmological constant Λ using a weighting by entropy increase on causal diamonds. The original work assumed a purely isotropic and homogeneous cosmology. But even the level of inhomogeneity observed in our universe forces reconsideration of certain arguments about entropy production. In particular, we must consider an ensemble of causal diamonds associated with each background cosmology and we can no longer immediately discard entropy production in the far future of the universe. Depending on our choices for a probability measure and our treatment of black hole evaporation, the prediction for Λ may be left intact or dramatically altered.
Directory of Open Access Journals (Sweden)
Argyris Arnellos
2005-02-01
Full Text Available Initially, the analysis and development of adaptive artificial systems has been based in metaphors taken from philosophical schools as well as the disciplines of biology and cognitive science. So far, the dominant approaches exhibit many advantages in specific domains of application but there all have a certain drawback, which is their inability to produce an artificial system which will be able to internally ground its representations so as to use them to produce newer, more developed ones. The respective frameworks are studied in terms of this inability and it is concluded that the problem is traced in the purely causal treatment, function and creation of the notion of representation, wherever it is used. In the case of purely dynamic systems, where the representations seem not to be very useful, it is proposed that the incorporation of a special non-causal kind of representations would give a framework which seems promising in realizing real adaptation. The relevant architecture is analyzed and discussed mainly in terms of its functionality and its contribution to the integration of pragmatic meaning aspects in an artificial system's interaction.
Directory of Open Access Journals (Sweden)
Xudong Dai
2007-03-01
Full Text Available Uncovering pathways underlying drug-induced toxicity is a fundamental objective in the field of toxicogenomics. Developing mechanism-based toxicity biomarkers requires the identification of such novel pathways and the order of their sufficiency in causing a phenotypic response. Genome-wide RNA interference (RNAi phenotypic screening has emerged as an effective tool in unveiling the genes essential for specific cellular functions and biological activities. However, eliciting the relative contribution of and sufficiency relationships among the genes identified remains challenging. In the rodent, the most widely used animal model in preclinical studies, it is unrealistic to exhaustively examine all potential interactions by RNAi screening. Application of existing computational approaches to infer regulatory networks with biological outcomes in the rodent is limited by the requirements for a large number of targeted permutations. Therefore, we developed a two-step relay method that requires only one targeted perturbation for genome-wide de novo pathway discovery. Using expression profiles in response to small interfering RNAs (siRNAs against the gene for peroxisome proliferator-activated receptor alpha (Ppara, our method unveiled the potential causal sufficiency order network for liver hypertrophy in the rodent. The validity of the inferred 16 causal transcripts or 15 known genes for PPARalpha-induced liver hypertrophy is supported by their ability to predict non-PPARalpha-induced liver hypertrophy with 84% sensitivity and 76% specificity. Simulation shows that the probability of achieving such predictive accuracy without the inferred causal relationship is exceedingly small (p < 0.005. Five of the most sufficient causal genes have been previously disrupted in mouse models; the resulting phenotypic changes in the liver support the inferred causal roles in liver hypertrophy. Our results demonstrate the feasibility of defining pathways mediating drug
Eventos Quânticos e Reducionismo Causal
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Osvaldo Pessoa Jr.
2013-12-01
Full Text Available This paper is the first step in an investigation of whether microscopic events can be reduced to a mereological composition of elementary events, especially in biological systems. The hypothesis is made that, between events in which quanta are exchanged, there is causal flow, but strictly speaking no events take place. A causal event is characterized by the possibility of an intervention or manipulation. Thus, three types of quantum mechanical events may be found: (1 detection of a quantum of energy; (2 confinement by an apparatus in a Glauber coherent state; (3 null result measurement (without exchange of quanta. The paper explores these three types of elementary causal events, e sets forth as the next step the investigation of the causal events involved in the action of a molecular motor.
On the causal structure between CO2 and global temperature.
Stips, Adolf; Macias, Diego; Coughlan, Clare; Garcia-Gorriz, Elisa; Liang, X San
2016-01-01
We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aerosol direct and indirect forcing, and on short time periods, volcanic forcings. In contrast the causality contribution from natural forcings (solar irradiance and volcanic forcing) to the long term trend is not significant. The spatial explicit analysis reveals that the anthropogenic forcing fingerprint is significantly regionally varying in both hemispheres. On paleoclimate time scales, however, the cause-effect direction is reversed: temperature changes cause subsequent CO2/CH4 changes. PMID:26900086
Environment - Assisted Invariance, Causality, and Probabilities in Quantum Physics
Zurek, W. H.
2002-01-01
I introduce environment - assisted invariance -- a symmetry related to causality that is exhibited by correlated quantum states -- and describe how it can be used to understand the nature of ignorance and, hence, the origin of probabilities in quantum physics.
On the causal structure between CO2 and global temperature
Stips, Adolf; Macias, Diego; Coughlan, Clare; Garcia-Gorriz, Elisa; Liang, X. San
2016-02-01
We use a newly developed technique that is based on the information flow concept to investigate the causal structure between the global radiative forcing and the annual global mean surface temperature anomalies (GMTA) since 1850. Our study unambiguously shows one-way causality between the total Greenhouse Gases and GMTA. Specifically, it is confirmed that the former, especially CO2, are the main causal drivers of the recent warming. A significant but smaller information flow comes from aerosol direct and indirect forcing, and on short time periods, volcanic forcings. In contrast the causality contribution from natural forcings (solar irradiance and volcanic forcing) to the long term trend is not significant. The spatial explicit analysis reveals that the anthropogenic forcing fingerprint is significantly regionally varying in both hemispheres. On paleoclimate time scales, however, the cause-effect direction is reversed: temperature changes cause subsequent CO2/CH4 changes.
Holographic entanglement and causal information in coherent states
International Nuclear Information System (INIS)
Scalar solitons in global AdS4 are holographically dual to coherent states carrying a non-trivial condensate of a scalar operator. We study the holographic information content of these states, focusing on a particular spatial region, by examining the entanglement entropy and causal holographic information. We show generically that whenever the dimension of the condensed operator is sufficiently low (characterized by the double-trace operator becoming relevant), such coherent states have lower entanglement and causal holographic information than the vacuum state of the system, despite having greater energy. We also use these geometries to illustrate the fact that causal wedges associated with a simply-connected boundary region can have non-trivial topology even in causally trivial spacetimes
Causal association rule mining methods based on fuzzy state description
Institute of Scientific and Technical Information of China (English)
Liang Kaijian; Liang Quan; Yang Bingru
2006-01-01
Aiming at the research that using more new knowledge to develope knowledge system with dynamic accordance, and under the background of using Fuzzy language field and Fuzzy language values structure as description framework, the generalized cell Automation that can synthetically process fuzzy indeterminacy and random indeterminacy and generalized inductive logic causal model is brought forward. On this basis, a kind of the new method that can discover causal association rules is provded. According to the causal information of standard sample space and commonly sample space,through constructing its state (abnormality) relation matrix, causal association rules can be gained by using inductive reasoning mechanism. The estimate of this algorithm complexity is given,and its validity is proved through case.
Causality assessment: A brief insight into practices in pharmaceutical industry
Directory of Open Access Journals (Sweden)
R Purushotham Naidu
2013-01-01
Full Text Available Healthcare industry is flooded with multitude of drugs, and the list is increasing day by day. Consumption of medications has enormously increased due to life style changes, having safer drugs is the need of the hour. Regulators and other authorities to have a check have put in stringent regulations and pharmacovigilance system in place. Eventhough there has been increase in adverse drug reactions (ADR reporting in the last decade, causality assessment has been the greater challenge for academicians and even industry. Causality is crucial for risk benefit assessment, particularly when it involves post marketing safety signals. Pharmaceutical companies have put in efforts to have a standardized approach for causality assessment. This article will provide some insight into the approaches for causality assessment from a pharma industry perspective.
Replicating the benefits of closed timelike curves without breaking causality
Yuan, Xiao; Thompson, Jayne; Haw, Jing Yan; Vedral, Vlatko; Ralph, Timothy C; Lam, Ping Koy; Weedbrook, Christian; Gu, Mile
2014-01-01
In general relativity, closed timelike curves can break causality with remarkable and unsettling consequences. At the classical level, they induce causal paradoxes disturbing enough to motivate conjectures that explicitly prevent their existence. At the quantum level, resolving such paradoxes induce radical benefits - from cloning unknown quantum states to solving problems intractable to quantum computers. Instinctively, one expects these benefits to vanish if causality is respected. Here we show that in harnessing entanglement, we can efficiently solve NP-complete problems and clone arbitrary quantum states - even when all time-travelling systems are completely isolated from the past. Thus, the many defining benefits of closed timelike curves can still be harnessed, even when causality is preserved. Our results unveil the subtle interplay between entanglement and general relativity, and significantly improve the potential of probing the radical effects that may exist at the interface between relativity and q...
Learning Why Things Change: The Difference-Based Causality Learner
Voortman, Mark; Druzdzel, Marek J
2012-01-01
In this paper, we present the Difference- Based Causality Learner (DBCL), an algorithm for learning a class of discrete-time dynamic models that represents all causation across time by means of difference equations driving change in a system. We motivate this representation with real-world mechanical systems and prove DBCL's correctness for learning structure from time series data, an endeavour that is complicated by the existence of latent derivatives that have to be detected. We also prove that, under common assumptions for causal discovery, DBCL will identify the presence or absence of feedback loops, making the model more useful for predicting the effects of manipulating variables when the system is in equilibrium. We argue analytically and show empirically the advantages of DBCL over vector autoregression (VAR) and Granger causality models as well as modified forms of Bayesian and constraintbased structure discovery algorithms. Finally, we show that our algorithm can discover causal directions of alpha r...
Testing Regulatory Consistency
Robert Breunig; Flavio M. Menezes
2008-01-01
We undertake an analysis of regulatory consistency using a database of publicly available regulatory decisions in Australia. We propose a simple exploratory model which allows us to test for regulatory consistency across jurisdictions and industries without detailed knowledge of the regulatory process. We compare two measures using our approach--the weighted average cost of capital and the proportion of firms’ revenue requirement claims disallowed by the regulator. We advocate use of the seco...
Causality and complexity: the myth of objectivity in science.
Mikulecky, Donald C
2007-10-01
Two distinctly different worldviews dominate today's thinking in science and in the world of ideas outside of science. Using the approach advocated by Robert M. Hutchins, it is possible to see a pattern of interaction between ideas in science and in other spheres such as philosophy, religion, and politics. Instead of compartmentalizing these intellectual activities, it is worthwhile to look for common threads of mutual influence. Robert Rosen has created an approach to scientific epistemology that might seem radical to some. However, it has characteristics that resemble ideas in other fields, in particular in the writings of George Lakoff, Leo Strauss, and George Soros. Historically, the atmosphere at the University of Chicago during Hutchins' presidency gave rise to Rashevsky's relational biology, which Rosen carried forward. Strauss was writing his political philosophy there at the same time. One idea is paramount in all this, and it is Lakoff who gives us the most insight into how the worldviews differ using this idea. The central difference has to do with causality, the fundamental concept that we use to build a worldview. Causal entailment has two distinct forms in Lakoff 's analysis: direct causality and complex causality. Rosen's writings on complexity create a picture of complex causality that is extremely useful in its detail, grounding in the ideas of Aristotle. Strauss asks for a return to the ancients to put philosophy back on track. Lakoff sees the weaknesses in Western philosophy in a similar way, and Rosen provides tools for dealing with the problem. This introduction to the relationships between the thinking of these authors is meant to stimulate further discourse on the role of complex causal entailment in all areas of thought, and how it brings them together in a holistic worldview. The worldview built on complex causality is clearly distinct from that built around simple, direct causality. One important difference is that the impoverished causal
Emmert-Streib, Frank; Glazko, Galina V.; Altay, Gökmen; Matos Simoes, Ricardo de
2012-01-01
In this paper, we present a systematic and conceptual overview of methods for inferring gene regulatory networks from observational gene expression data. Further, we discuss two classic approaches to infer causal structures and compare them with contemporary methods by providing a conceptual categorization thereof. We complement the above by surveying global and local evaluation measures for assessing the performance of inference algorithms.
Causality between Electricity Consumption & Economic growth : Empirical Evidence from India
Gupta, Geetu; Sahu, Naresh Chandra
2009-01-01
In this study ,an attempt has been made to investigate causality between electricity consumption and economic growth in India by adopting Granger Engel causality model for 1960-2006 period .Test results shows that electricity consumption has positive effect on economic growth. The paper support for the reforms in power sector and indicates that electricity act as a catalyst in realizing various social and economic goals.
The role of causal links in performance measurement models
Kasperskaya, Yulia; Tayles, Michael
2013-01-01
Abstract Purpose: Several well-known managerial accounting performance measurement models rely on causal assumptions. Whilst users of the models express satisfaction and link them with improved organizational performance, academic research, of the realworld applications, shows few reliable statistical associations. This paper provides a discussion on the"problematic" of causality in a performance measurement setting. Design/methodology/approach: This is a conceptual study based on an analysis...
Sensitivity analyses for parametric causal mediation effect estimation
Albert, Jeffrey M.; Wang, Wei
2014-01-01
Causal mediation analysis uses a potential outcomes framework to estimate the direct effect of an exposure on an outcome and its indirect effect through an intermediate variable (or mediator). Causal interpretations of these effects typically rely on sequential ignorability. Because this assumption is not empirically testable, it is important to conduct sensitivity analyses. Sensitivity analyses so far offered for this situation have either focused on the case where the outcome follows a line...
The Direction of Causality between Insider Ownership and Market Valuation
Pedersen, Torben; Thomsen, Steen; Kvist, Hans Kurt
2001-01-01
The causal relationship between insider ownership and market valuation is tested on a database of the largest EU and US companies. Using a Granger causality test insider ownership (measured by the fraction of closely held shares) is found to have a negative effect on market valuation (measured as the simple Tobin's Q ratio). And market valuation is found to have a negative effect on insider ownership. Consistent with an overall non-linear relationship as hypothesised by Morck e...
The Causal Relationship between Health and Education Expenditures in Malaysia
Chor Foon TANG; Yew Wah LAI
2011-01-01
A major macroeconomic policy in generating economic growth is to encourage investments on human capital such as health and education. This is because both health and education make significant contribution to increasing productivity of the labour force which ultimately exerts a positive effect on raising output levels. A question that arises is whether investments on health and education have a causal relationship and if so, what is the directional causality? The objective o...
Causal Structure and Gravitational Waves in Brane World Cosmology
Ichiki, Kiyotomo; Nakamura, Kouji
2003-01-01
The causal structure of the flat brane universe of RSII type is re-investigated to clarify the boundary conditions for stochastic gravitational waves. In terms of the Gaussian normal coordinate of the brane, a singularity of the equation for gravitational waves appears in the bulk. We show that this singularity corresponds to the ``seam singularity'' which is a singular subspace on the brane universe. Based upon the causal structure, we discuss the boundary conditions for gravitational waves ...
A Tool for Qualitative Causal Reasoning On Complex Systems
Tahar Guerram; Ramdane Maamri; Zaidi Sahnoun
2010-01-01
A cognitive map, also called a mental map, is a representation and reasoning model on causal knowledge. It is a directed, labeled and cyclic graph whose nodes represent causes or effects and whose arcs represent causal relations between these nodes such as "increases", "decreases", "supports", and "disadvantages". A cognitive map represents beliefs (knowledge) which we lay out about a given domain of discourse and is useful as a means of decision making support. There are several types of cog...
Causal Linkages Between Domestic Terrorism and Economic Growth
Thomas Gries; Tim Krieger; Daniel Meierrieks
2009-01-01
We use the Hsiao-Granger method to test for growth-terrorism causality for seven Western European countries. In bivariate settings, the impact of economic performance on domestic terrorism is very strong. In trivariate settings, the impact of performance on terrorism diminishes. Here, we find that economic performance leads terrorist violence in robust ways only for three out of seven countries. Terrorism is almost never found to causally influence growth in bivariate and trivariate specifica...
The Causal Relationship Between Government Revenue and Expenditure in Namibia
Eita, Joel Hinaunye; Mbazima, Daisy
2008-01-01
The relationship between government revenue and government expenditure is important, given its relevance for policy especially with respect to the budget deficit. The purpose of this paper is to investigate the relationship between government revenue and government expenditure in Namibia. It investigates the causal relationship between government revenue and government expenditure using Granger causality test through cointegrated vector autoregression (VAR) methods for the period the period 1...
The causal effect of teen motherhood on worklessness
WALKER, Ian; Zhu, Yu
2009-01-01
Teen motherhood continues to be high in the US and the UK relative to most other western European countries. While recent research has clarified how effective policies to reduce teen motherhood might be (Kearney (2009)), there remains little evidence that quantifies the causal effects of teen motherhood on such mothers and their first born children. This paper provides estimates of the causal effect of teen motherhood on worklessness and does so by exploiting the availability of two sources o...
Re-assessing causal accounts of learnt behavior in rats.
Burgess, K V; Dwyer, D M; Honey, R C
2012-04-01
Rats received either a common-cause (i.e., A→B, A→food) or a causal-chain training scenario (i.e., B→A, A→food) before their tendency to approach the food magazine during the presentation of B was assessed as a function of whether it was preceded by a potential alternative cause. Causal model theory predicts that the influence of an alternative cause should be restricted to the common-cause scenario. In Experiment 1, responding to B was reduced when it occurred after pressing a novel lever during the test phase. This effect was not influenced by the type of training scenario. In Experiment 2, rats were familiarized with the lever prior to test by training it as a potential cause of B. After this treatment, the lever now failed to influence test responding to B. In Experiment 3, rats given common-cause training responded more to B when it followed a cue that had previously been trained as a predictor of B, than when it followed another stimulus. This effect was not apparent in rats that received causal-chain training. This pattern of results is the opposite of that predicted by causal model theory. Thus, in three experiments, the presence of an alternative cause failed to influence test responding in manner consistent with causal model theory. These results undermine the application of causal model theory to rats, but are consistent with associative analyses. PMID:22486754
Causal quantum theory and the collapse locality loophole
International Nuclear Information System (INIS)
Causal quantum theory is an umbrella term for ordinary quantum theory modified by two hypotheses: state vector reduction is a well-defined process, and strict local causality applies. The first of these holds in some versions of Copenhagen quantum theory and need not necessarily imply practically testable deviations from ordinary quantum theory. The second implies that measurement events which are spacelike separated have no nonlocal correlations. To test this prediction, which sharply differs from standard quantum theory, requires a precise definition of state vector reduction. Formally speaking, any precise version of causal quantum theory defines a local hidden variable theory. However, causal quantum theory is most naturally seen as a variant of standard quantum theory. For that reason it seems a more serious rival to standard quantum theory than local hidden variable models relying on the locality or detector efficiency loopholes. Some plausible versions of causal quantum theory are not refuted by any Bell experiments to date, nor is it evident that they are inconsistent with other experiments. They evade refutation via a neglected loophole in Bell experiments--the collapse locality loophole--which exists because of the possible time lag between a particle entering a measurement device and a collapse taking place. Fairly definitive tests of causal versus standard quantum theory could be made by observing entangled particles separated by ≅0.1 light seconds
CRISPLD2: a novel NSCLP candidate gene.
Chiquet, Brett T; Lidral, Andrew C; Stal, Samuel; Mulliken, John B; Moreno, Lina M; Arcos-Burgos, Mauricio; Arco-Burgos, Mauricio; Valencia-Ramirez, Consuelo; Blanton, Susan H; Hecht, Jacqueline T
2007-09-15
Non-syndromic cleft lip with or without cleft palate (NSCLP) results from the complex interaction between genes and environmental factors. Candidate gene analysis and genome scans have been employed to identify the genes contributing to NSCLP. In this study, we evaluated the 16q24.1 chromosomal region, which has been identified by multiple genome scans as an NSCLP region of interest. Two candidate genes were found in the region: interferon regulatory factor 8 (IRF8) and cysteine-rich secretory protein LCCL domain containing 2 (CRISPLD2). Initially, Caucasian and Hispanic NSCLP multiplex families and simplex parent-child trios were genotyped for single nucleotide polymorphisms (SNPs) in both IRF8 and CRISPLD2. CRISPLD2 was subsequently genotyped in a data set comprised of NSCLP families from Colombia, South America. Linkage disequilibrium analysis identified a significant association between CRISPLD2 and NSCLP in both our Caucasian and Hispanic NSCLP cohorts. SNP rs1546124 and haplotypes between rs1546124 and either rs4783099 or rs16974880 were significant in the Caucasian multiplex population (P=0.01, P=0.002 and P=0.001, respectively). An altered transmission of CRISPLD2 SNPs rs8061351 (P=0.02) and rs2326398 (P=0.06) was detected in the Hispanic population. No association was found between CRISPLD2 and our Colombian population or IRF8 and NSCLP. In situ hybridization showed that CRISPLD2 is expressed in the mandible, palate and nasopharynx regions during craniofacial development at E13.5-E17.5, respectively. Altogether, these data suggest that genetic variation in CRISPLD2 has a role in the etiology of NSCLP. PMID:17616516
Corrosion resistance of candidate transportation container materials
International Nuclear Information System (INIS)
The Department of Energy is currently remediating several sites that have been contaminated over the years with hazardous, mixed waste and radioactive materials. Regulatory guidelines require strict compliance demonstrating public safety during remediation and the transport of these hazardous, mixed waste and radioactive materials. The compatibility of the metallic transportation containers with the contents they are designed to transport is an ultimate concern that must be satisfied to ensure public safety. The transportation issue is inherently complicated due to the complex, varied, and unknown composition of the hazardous, mixed and radioactive waste that is being, considered for transport by the DOE facilities. Never before have the interactions between the waste being transported and the materials that comprise the transportation packages been more important. Therefore, evaluation of material performance when subjected to a simulated waste will ensure that all regulatory issues and requirements for transportation of hazardous, mixed, and radioactive wastes are satisfied. The tasks encompassed by this study include defining criteria for candidate material selection, defining a test matrix that will provide pertinent information on the material compatibility with the waste stimulant, and evaluation of material performance when subjected to a stimulant waste. Our goal is to provide package design engineers with a choice of materials which exhibit enhanced performance upon exposure to hazardous, mixed, and radioactive waste that is similar in composition to the waste stimulant used in this study. Due to the fact that there are many other possible waste compositions, additional work needs to be done to broaden our materials compatibility/waste stream data base
Candidate gene prioritization with Endeavour.
Tranchevent, Léon-Charles; Ardeshirdavani, Amin; ElShal, Sarah; Alcaide, Daniel; Aerts, Jan; Auboeuf, Didier; Moreau, Yves
2016-07-01
Genomic studies and high-throughput experiments often produce large lists of candidate genes among which only a small fraction are truly relevant to the disease, phenotype or biological process of interest. Gene prioritization tackles this problem by ranking candidate genes by profiling candidates across multiple genomic data sources and integrating this heterogeneous information into a global ranking. We describe an extended version of our gene prioritization method, Endeavour, now available for six species and integrating 75 data sources. The performance (Area Under the Curve) of Endeavour on cross-validation benchmarks using 'gold standard' gene sets varies from 88% (for human phenotypes) to 95% (for worm gene function). In addition, we have also validated our approach using a time-stamped benchmark derived from the Human Phenotype Ontology, which provides a setting close to prospective validation. With this benchmark, using 3854 novel gene-phenotype associations, we observe a performance of 82%. Altogether, our results indicate that this extended version of Endeavour efficiently prioritizes candidate genes. The Endeavour web server is freely available at https://endeavour.esat.kuleuven.be/. PMID:27131783
Empathy Development in Teacher Candidates
Boyer, Wanda
2010-01-01
Using a grounded theory research design, the author examined 180 reflective essays of teacher candidates who participated in a "Learning Process Project," in which they were asked to synthesize and document their discoveries about the learning process over the course of a completely new learning experience as naive learners. This study explored…
Candidate Prediction Models and Methods
DEFF Research Database (Denmark)
Nielsen, Henrik Aalborg; Nielsen, Torben Skov; Madsen, Henrik;
2005-01-01
This document lists candidate prediction models for Work Package 3 (WP3) of the PSO-project called ``Intelligent wind power prediction systems'' (FU4101). The main focus is on the models transforming numerical weather predictions into predictions of power production. The document also outlines the...
Directory of Open Access Journals (Sweden)
Ninke Stukker
2009-06-01
Full Text Available Dans une hypothèse de catégorisation linguistique, les connecteurs de cause sont pris comme des outils de catégorisation. En effet, des études sur corpus suggèrent que les connecteurs sont fortement spécialisés dans une seule catégorie de causalité spécifique, mais aussi que leur usage n'est pas limité aux catégories de causalité auxquelles ils sont prototypiquement associés. Si nous supposons que le sens des connecteurs causaux peut être adéquatement décrit en référence à des catégories conceptuelles bien définies, comment pouvons-nous expliquer qu’il y ait une variation dans leur usage réel? Nous mettons l'accent sur les relations de cohérence causale volitionnelle, qui constituent le contexte d'usage prototypique du connecteur néerlandais daarom ‘c'est pourquoi’. Un autre moyen d’expression des relations causales volitionnelles est le recours au connecteur dus ‘alors/donc’ qui est prototypiquement utilisé dans les relations de causalité épistémique. Notre hypothèse est que les relations de causalité volitionnelle exprimées par daarom vs dus diffèrent systématiquement en termes de subjectivité. Nous proposons un modèle d'analyse qui contient de multiples opérationnalisation de la notion de subjectivité et une distinction entre différents niveaux de complexité (sous-clause, clause, et discours. Nous constatons que les relations causales volitionnelles en dus contiennent plus souvent des éléments subjectifs que les relations causales volitionnelles en daarom. Nous interprétons cette distribution au sein d'un cadre théorique fondé sur l'usage (usage-based framework, et nous proposons d'analyser les cas volitionnels de dus comme des instanciations non-prototypiques du sens de dus,qui est donc intrinsèquement subjectif et prototypiquement épistémique.Under a linguistic categorization hypothesis causal connectives are taken as categorization devices. Indeed, corpus studies suggest that
Enhancing scientific reasoning by refining students' models of multivariable causality
Keselman, Alla
Inquiry learning as an educational method is gaining increasing support among elementary and middle school educators. In inquiry activities at the middle school level, students are typically asked to conduct investigations and infer causal relationships about multivariable causal systems. In these activities, students usually demonstrate significant strategic weaknesses and insufficient metastrategic understanding of task demands. Present work suggests that these weaknesses arise from students' deficient mental models of multivariable causality, in which effects of individual features are neither additive, nor constant. This study is an attempt to develop an intervention aimed at enhancing scientific reasoning by refining students' models of multivariable causality. Three groups of students engaged in a scientific investigation activity over seven weekly sessions. By creating unique combinations of five features potentially involved in earthquake mechanism and observing associated risk meter readings, students had to find out which of the features were causal, and to learn to predict earthquake risk. Additionally, students in the instructional and practice groups engaged in self-directed practice in making scientific predictions. The instructional group also participated in weekly instructional sessions on making predictions based on multivariable causality. Students in the practice and instructional conditions showed small to moderate improvement in their attention to the evidence and in their metastrategic ability to recognize effective investigative strategies in the work of other students. They also demonstrated a trend towards making a greater number of valid inferences than the control group students. Additionally, students in the instructional condition showed significant improvement in their ability to draw inferences based on multiple records. They also developed more accurate knowledge about non-causal features of the system. These gains were maintained
UMA TEORÍA CAUSAL PARA LOS CASOS FREGE
Directory of Open Access Journals (Sweden)
ABEL WAJNERMAN PAZ
2015-06-01
Full Text Available Fodor ha argumentado a favor de un par de tesis que pueden caracterizarse como constituyendo un dilema: Por un lado, si adoptamos una teoría funcional para los conceptos explicamos semánticamente los casos Frege pero caemos en el holismo semántico. Por otro lado, si adoptamos una teoría causal/informacional evitamos el holismo pero no explicamos los casos Frege semánticamente. Fodor (por ej, 1994, 1998 y 2008 intenta evitar la segunda parte del dilema argumentando que los casos de Frege pueden tener una explicación sintáctica y no semántica. En este trabajo intentaré ofrecer una salida alternativa al dilema fodoriano. Propondré una explicación semántica de los casos Frege que incorpora tanto elementos de una teoría causal como de una de rol funcional. Afirmaré que el contenido cognitivo o estrecho de un concepto (el tipo de contenido aparentemente exigido por los casos Frege es el conjunto de contenidos causales/informacionales de las representaciones que figuran en su rol funcional. Considero que individuar a las representaciones en los roles por medio de sus contenidos causales permite evitar el holismo (evitando el proceso de ramsificación típicamente empleado para individuar a los roles y que identificar el contenido cognitivo con contenidos causales/informacionales de las representaciones en los roles permite evitar el referencialismo de las propuestas causales (podemos distinguir sentido de referencia en términos causales.
General solutions and causality for a Voigt medium
Energy Technology Data Exchange (ETDEWEB)
Duren, R.E.; Heestand, R.L. [Exxon Production Co., Houston, TX (United States)
1995-01-01
A 1-D wave equation solution for a propagating seismic pulse in a Voigt medium can be obtained by using a separation of variables to find time harmonic particular solutions and then superimposing the particular solutions. This superposition is a time convolution of the boundary condition (or incident pulse) and the medium`s impulse response. Even though causality is not introduced during the solution of the wave equation, the general solution is causal since the boundary condition is causal and the medium`s impulse response can be shown to be causal. The relationship between attenuation and phase velocity as well as their dependence on frequency arise from the form chosen for the particular solutions. The arbitrary constants associated with the particular solutions are determined by the boundary condition, and the initial condition is also dependent on the boundary condition; however, the initial condition is properly determined and does not depend on times after the initial time (thereby satisfying causality). The convolutional nature of the general solution allows it to also be expressed as a time convolution of the boundary conditions`s time derivative and the medium`s step function response. This expression can be viewed as a superposition of step function responses where the step function response is a particular solution to the wave equation obtained using an approach that is similar to one recently developed for propagating electric pulses. This new solution is obtained with the initial and boundary conditions being independently introduced during the solution of the wave equation. There is no frequency dependence in this solution, and the general solution is causal since it is a superposition of causal step function responses.
The Shared Causal Pasts and Futures of Cosmological Events
Friedman, Andrew S; Gallicchio, Jason
2013-01-01
We derive criteria for whether two cosmological events can have a shared causal past or a shared causal future, assuming a Friedmann-Lemaitre-Robertson-Walker universe with best-fit \\Lambda CDM cosmological parameters from the Planck satellite. We further derive criteria for whether either cosmic event could have been in past causal contact with our own worldline since the time of the hot "big bang", which we take to be the end of early-universe inflation. We find that pairs of objects such as quasars on opposite sides of the sky with redshifts z >= 3.65 have no shared causal past with each other or with our past worldline. More complicated constraints apply if the objects are at different redshifts from each other or appear at some relative angle less than 180 degrees, as seen from Earth. We present examples of observed quasar pairs that satisfy all, some, or none of the criteria for past causal independence. Given dark energy and the recent accelerated expansion, our observable universe has a finite conform...
The causality between energy consumption and economic growth in Turkey
International Nuclear Information System (INIS)
This paper applies the causality test to examine the causal relationship between primary energy consumption (EC) and real Gross National Product (GNP) for Turkey during 1970-2006. We employ unit root tests, the augmented Dickey-Fuller (ADF) and the Philips-Perron (PP), Johansen cointegration test, and Pair-wise Granger causality test to examine relation between EC and GNP. Our empirical results indicate that the two series are found to be non-stationary. However, first differences of these series lead to stationarity. Further, the results indicate that EC and GNP are cointegrated and there is bidirectional causality running from EC to GNP and vice versa. This means that an increase in EC directly affects economic growth and that economic growth also stimulates further EC. This bidirectional causality relationship between EC and GNP determined for Turkey at 1970-2006 period is in accordance with the ones in literature reported for similar countries. Consequently, we conclude that energy is a limiting factor to economic growth in Turkey and, hence, shocks to energy supply will have a negative impact on economic growth
Causal interpretation of the modified Klein-Gordon equation
International Nuclear Information System (INIS)
A consistent causal interpretation of the Klein-Gordon equation treated as a field equation has been developed, and leads to a model of entities described by the Klein-Gordon equation, i.e., spinless, massive bosons, as objectively existing fields. The question arises, however, as to whether a causal interpretation based on a particle ontology of the Klein-Gordon equation is also possible. Our purpose in this article will be to indicate, by making what we believe is a best possible attempt at developing a particle interpretation of the Klein-Gordon equation, that such an interpretation is untenable. To resolve the nonpositive-definite probability density difficulties with the Klein-Gordon equation, we modify this equation by the introduction of an evolution parameter. We base our subsequent considerations on this modified Klein-Gordon equation. Partly to motivate the need for a relativistic causal interpretation and partly to give emphasis to aspects of the causal interpretation often overlooked, we begin our article with a brief historical survey of the causal interpretation
The Causal Relationship between Health and Education Expenditures in Malaysia
Directory of Open Access Journals (Sweden)
Chor Foon TANG
2011-08-01
Full Text Available A major macroeconomic policy in generating economic growth is to encourage investments on human capital such as health and education. This is because both health and education make significant contribution to increasing productivity of the labour force which ultimately exerts a positive effect on raising output levels. A question that arises is whether investments on health and education have a causal relationship and if so, what is the directional causality? The objective of this study is to examine the causal relationship between health and education expenditures in Malaysia. This study covered annual data from 1970 to 2007. Using Granger causality as well as Toda and Yamamoto MWALD causality approaches, this study suggests that education Granger-causes health expenditure in both the short run and long run. The findings of this study implied that the Malaysian society places preference on education expenditure rather than health. This preference is not unexpected as generally, an educated and knowledgeable society precedes a healthy one. Before a society has attained a relatively higher level of education, it is less aware of the importance of health. Thus, expenditure on education should lead expenditure on health.
Causality between public policies and exports of renewable energy technologies
International Nuclear Information System (INIS)
This article investigates the causal relationship between public policies and exports of renewable energy technologies using panel data from 18 countries for the period 1991–2007. A number of panel unit root and cointegration tests are applied. Time series data on public policies and exports are integrated and cointegrated. The dynamic OLS results indicate that in the long run, a 1% increase in government R and D expenditures (RAD) increases exports (EX) by 0.819%. EX and RAD variables respond to deviations from the long-run equilibrium in the previous period. Additionally, the Blundell–Bond system generalized methods of moments (GMM) is employed to conduct a panel causality test in a vector error-correction mechanism (VECM) setting. Evidence of a bidirectional and short-run, and strong causal relationship between EX and the contribution of renewable energy to the total energy supply (CRES) is uncovered. CRES has a negative effect on EX, whereas EX has a positive effect on CRES. We suggest some policy implications based on the results of this study. - Highlights: ► We model VECM to test the Granger causality between the policies and the export. ► Technology-push policy has a positive impact on export in the long-run. ► There are the short-run causal relationships between market-pull policy and export
Does stability of relativistic dissipative fluid dynamics imply causality?
International Nuclear Information System (INIS)
We investigate the causality and stability of relativistic dissipative fluid dynamics in the absence of conserved charges. We perform a linear stability analysis in the rest frame of the fluid and find that the equations of relativistic dissipative fluid dynamics are always stable. We then perform a linear stability analysis in a Lorentz-boosted frame. Provided that the ratio of the relaxation time for the shear stress tensor τπ to the sound attenuation length Γs=4η/3(ε+P) fulfills a certain asymptotic causality condition, the equations of motion give rise to stable solutions. Although the group velocity associated with perturbations may exceed the velocity of light in a certain finite range of wave numbers, we demonstrate that this does not violate causality, as long as the asymptotic causality condition is fulfilled. Finally, we compute the characteristic velocities and show that they remain below the velocity of light if the ratio τπ/Γs fulfills the asymptotic causality condition.
Corporate Governance and Financial Performance Nexus: Any Bidirectional Causality?
Directory of Open Access Journals (Sweden)
Alley Ibrahim S.
2016-06-01
Full Text Available Most studies on corporate governance recognize endogeneity in the nexus between corporate governance and financial performance. Little attention has, however, been paid to the direction of causality between the two phenomena, and hence the Vector Error Correction (VEC model, which allows for endogenous determination of the direction of causality, has not been widely employed. This study fills that gap by estimating the nexus and the direction of causality using the VEC model to analyze panel data on selected listed firms in Nigeria. The results agree with the findings of most previous studies that corporate governance significantly affects financial performance. Board skills, board composition and management skills enhanced financial performance indicators – return on equity (ROE, return on asset (ROA and net profit margin (NPM; in many occasions, significantly. Board size and audit committee size did not, and can actually undermine financial performance. More importantly, financial performance did not significantly affect corporate governance. On the basis of the lag structure of the VEC model, this study affirms unidirectional causality in the nexus, running from corporate governance to financial performance, nullifying the hypothesis of bidirectional causality in the nexus.
International Nuclear Information System (INIS)
This contribution investigates causal interdependence between energy consumption and economic growth in Liberia and proposes application of a bootstrap methodology. To better reflect causality, employment is incorporated as additional variable. The study demonstrates evidence of distinct bidirectional Granger causality between energy consumption and economic growth. Additionally, the results show that employment in Liberia Granger causes economic growth and apply irrespective of the short-run or long-run. Evidence from a Monte Carlo experiment reveals that the asymptotic Granger causality test suffers size distortion problem for Liberian data, suggesting that the bootstrap technique employed in this study is more appropriate. Given the empirical results, implications are that energy expansion policies like energy subsidy or low energy tariff for instance, would be necessary to cope with demand exerted as a result of economic growth in Liberia. Furthermore, Liberia might have the performance of its employment generation on the economy partly determined by adequate energy. Therefore, it seems fully justified that a quick shift towards energy production based on clean energy sources may significantly slow down economic growth in Liberia. Hence, the government’s target to implement a long-term strategy to make Liberia a carbon neutral country, and eventually less carbon dependent by 2050 is understandable. - Highlights: ► Causality between energy consumption and economic growth in Liberia investigated. ► There is bidirectional causality between energy consumption and economic growth. ► Energy expansion policies are necessary to cope with demand from economic growth. ► Asymptotic Granger causality test suffers size distortion problem for Liberian data. ► The bootstrap methodology employed in our study is more appropriate.
IAEA Director General candidates announced
International Nuclear Information System (INIS)
Full text: The IAEA today confirms receipt of the nomination of five candidates for Director General of the IAEA. Nominations of the following individuals have been received by the Chairperson of the IAEA Board of Governors, Ms. Taous Feroukhi: Mr. Jean-Pol Poncelet of Belgium; Mr. Yukiya Amano of Japan; Mr. Ernest Petric of Slovenia; Mr. Abdul Samad Minty of South Africa; and Mr. Luis Echavarri of Spain. The five candidates were nominated in line with a process approved by the Board in October 2008. IAEA Director General Mohamed ElBaradei's term of office expires on 30 November 2009. He has served as Director General since 1997 and has stated that he is not available for a fourth term of office. (IAEA)
Plaisier, Christopher L.; Steve Horvath; Adriana Huertas-Vazquez; Ivette Cruz-Bautista; Herrera, Miguel F.; Teresa Tusie-Luna; Carlos Aguilar-Salinas; Päivi Pajukanta
2009-01-01
We hypothesized that a common SNP in the 3' untranslated region of the upstream transcription factor 1 (USF1), rs3737787, may affect lipid traits by influencing gene expression levels, and we investigated this possibility utilizing the Mexican population, which has a high predisposition to dyslipidemia. We first associated rs3737787 genotypes in Mexican Familial Combined Hyperlipidemia (FCHL) case/control fat biopsies, with global expression patterns. To identify sets of co-expressed genes co...
Tetravalent DNA vaccine product as a vaccine candidate against dengue.
Porter, Kevin R; Teneza-Mora, Nimfa; Raviprakash, Kanakatte
2014-01-01
Dengue is the most important arbovirus worldwide and is the virus that causes dengue fever and the more severe dengue hemorrhagic fever. There are four serotypes of dengue with each possessing the ability to cause disease. Developing a preventive vaccine is the most efficient and effective way to prevent these diseases, and because immunity to one serotype does not protect against the other serotypes, a vaccine must provide tetravalent protection. We used DNA immunization as a platform to develop a tetravalent vaccine. In this chapter, we describe the laboratory, regulatory, and clinical methodology for evaluating a candidate tetravalent vaccine in a Phase 1 clinical trial. PMID:24715294
VALUE ORIENTATIONS OF TEACHER CANDIDATES
YAPICI, Asım; KUTLU, M.Oğuz; BİLİCAN, F.Işıl
2012-01-01
Abstract This cross-sectional, descriptive study examined the change in values in time among teacher candidates. The Schwartz Values Inventory was administered to 708 freshmen and senior students studying at Cukurova University, Education Faculty. The results have shown that the students at the department of Science Education valued power, achievement, stimulation; the department of English Teaching Education valued hedonism; and the department of Education of Religious Culture valued un...
Research and regulatory review
International Nuclear Information System (INIS)
To enable the regulatory review to be effectively undertaken by the regulatory body, there is a need for it to have ready access to information generated by research activities. Certain advantages have been seen to be gained by the regulatory body itself directly allocating and controlling some portion of these activities. The princial reasons for reaching this conclusion are summarised and a brief description of the Inspectorates directly sponsored programme outlined. (author)
From candidate gene studies to GWAS and post-GWAS analyses in breast cancer.
Fachal, Laura; Dunning, Alison M
2015-02-01
There are now more than 90 established breast cancer risk loci, with 57 new ones, revealed through genome-wide-association studies (GWAS) during the last two years. Established high, moderate and low penetrance genetic variants currently explain ∼49% of familial breast cancer risk. GWAS-discovered variants account for 14%, and it is estimated that another 1000 yet-to-be-discovered loci could contribute an additional ∼14% of familial risk. Polygenic risk scores can already be used to stratify breast cancer risk in the female population and could improve the targeting of mammographic screening programmes, which are at present largely based on age-specific risks. Fine-scale mapping and functional analyses are revealing candidate causal variants and the molecular mechanisms by which GWAS-hits may act. Better-powered GWAS and genome-wide sequencing projects are likely to continue identifying new breast cancer causal variants. PMID:25727315
Dark matter perturbations and viscosity: a causal approach
Acquaviva, Giovanni; Pénin, Aurélie
2016-01-01
The inclusion of dissipative effects in cosmic fluids modifies their clustering properties and could have observable effects on the formation of large scale structures. We analyse the evolution of density perturbations of cold dark matter endowed with causal bulk viscosity. The perturbative analysis is carried out in the Newtonian approximation and the bulk viscosity is described by the causal Israel-Stewart (IS) theory. In contrast to the non-causal Eckart theory, we obtain a third order evolution equation for the density contrast that depends on three free parameters. For certain parameter values, the density contrast and growth factor in IS mimic their behaviour in $\\Lambda$CDM when $z \\geq 1$. Interestingly, and contrary to intuition, certain sets of parameters lead to an increase of the clustering.
Causal Analysis for Performance Modeling of Computer Programs
Directory of Open Access Journals (Sweden)
Jan Lemeire
2007-01-01
Full Text Available Causal modeling and the accompanying learning algorithms provide useful extensions for in-depth statistical investigation and automation of performance modeling. We enlarged the scope of existing causal structure learning algorithms by using the form-free information-theoretic concept of mutual information and by introducing the complexity criterion for selecting direct relations among equivalent relations. The underlying probability distribution of experimental data is estimated by kernel density estimation. We then reported on the benefits of a dependency analysis and the decompositional capacities of causal models. Useful qualitative models, providing insight into the role of every performance factor, were inferred from experimental data. This paper reports on the results for a LU decomposition algorithm and on the study of the parameter sensitivity of the Kakadu implementation of the JPEG-2000 standard. Next, the analysis was used to search for generic performance characteristics of the applications.
The why of things: causality in science, medicine, and life
Rabins, Peter V.
2013-01-01
Why was there a meltdown at the Fukushima power plant? Why do some people get cancer and not others? Why is global warming happening? Why does one person get depressed in the face of life's vicissitudes while another finds resilience? Questions like these -- questions of causality -- form the basis of modern scientific inquiry, posing profound intellectual and methodological challenges for researchers in the physical, natural, biomedical, and social sciences. In this groundbreaking book, noted psychiatrist and author Peter Rabins offers a conceptual framework for analyzing daunting questions of causality. Navigating a lively intellectual voyage between the shoals of strict reductionism and relativism, Rabins maps a three-facet model of causality and applies it to a variety of questions in science, medicine, economics, and more. Throughout this book, Rabins situates his argument within relevant scientific contexts, such as quantum mechanics, cybernetics, chaos theory, and epigenetics. A renowned communicator o...
Identifiability, stratification and minimum variance estimation of causal effects.
Tong, Xingwei; Zheng, Zhongguo; Geng, Zhi
2005-10-15
The weakest sufficient condition for the identifiability of causal effects is the weakly ignorable treatment assignment, which implies that potential responses are independent of treatment assignment in each fine subpopulation stratified by a covariate. In this paper, we expand the independence that holds in fine subpopulations to the case that the independence may also hold in several coarse subpopulations, each of which consists of several fine subpopulations and may have overlaps with other coarse subpopulations. We first show that the identifiability of causal effects occurs if and only if the coarse subpopulations partition the whole population. We then propose a principle, called minimum variance principle, which says that the estimator possessing the minimum variance is preferred, in dealing with the stratification and the estimation of the causal effects. The simulation results with the detail programming and a practical example demonstrate that it is a feasible and reasonable way to achieve our goals. PMID:16149123
Capturing connectivity and causality in complex industrial processes
Yang, Fan; Shah, Sirish L; Chen, Tongwen
2014-01-01
This brief reviews concepts of inter-relationship in modern industrial processes, biological and social systems. Specifically ideas of connectivity and causality within and between elements of a complex system are treated; these ideas are of great importance in analysing and influencing mechanisms, structural properties and their dynamic behaviour, especially for fault diagnosis and hazard analysis. Fault detection and isolation for industrial processes being concerned with root causes and fault propagation, the brief shows that, process connectivity and causality information can be captured in two ways: · from process knowledge: structural modeling based on first-principles structural models can be merged with adjacency/reachability matrices or topology models obtained from process flow-sheets described in standard formats; and · from process data: cross-correlation analysis, Granger causality and its extensions, frequency domain methods, information-theoretical methods, and Bayesian ne...
Quantum causal histories in the light of quantum information
Livine, E R; Livine, Etera R.; Terno, Daniel R.
2006-01-01
We use techniques of quantum information theory to analyze the quantum causal histories approach to quantum gravity. We show that while it is consistent to introduce closed timelike curves (CTCs), they cannot generically carry independent degrees of freedom. Moreover, if the effective dynamics of the chronology-respecting part of the system is linear, it should be completely decoupled from the CTCs. In the absence of a CTC not all causal structures admit the introduction of quantum mechanics. It is possible for those and only for those causal structures that can be represented as quantum computational networks. The dynamics of the subsystems should not be unitary or even completely positive. However, we show that other commonly maid assumptions ensure the complete positivity of the reduced dynamics.
Informational and Causal Architecture of Discrete-Time Renewal Processes
Directory of Open Access Journals (Sweden)
Sarah E. Marzen
2015-07-01
Full Text Available Renewal processes are broadly used to model stochastic behavior consisting of isolated events separated by periods of quiescence, whose durations are specified by a given probability law. Here, we identify the minimal sufficient statistic for their prediction (the set of causal states, calculate the historical memory capacity required to store those states (statistical complexity, delineate what information is predictable (excess entropy, and decompose the entropy of a single measurement into that shared with the past, future, or both. The causal state equivalence relation defines a new subclass of renewal processes with a finite number of causal states despite having an unbounded interevent count distribution. We use the resulting formulae to analyze the output of the parametrized Simple Nonunifilar Source, generated by a simple two-state hidden Markov model, but with an infinite-state ϵ-machine presentation. All in all, the results lay the groundwork for analyzing more complex processes with infinite statistical complexity and infinite excess entropy.
A Taxonomy of Causality-Based Biological Properties
Bodei, Chiara; Chiarugi, Davide; Gori, Roberta; 10.4204/EPTCS.19.8
2010-01-01
We formally characterize a set of causality-based properties of metabolic networks. This set of properties aims at making precise several notions on the production of metabolites, which are familiar in the biologists' terminology. From a theoretical point of view, biochemical reactions are abstractly represented as causal implications and the produced metabolites as causal consequences of the implication representing the corresponding reaction. The fact that a reactant is produced is represented by means of the chain of reactions that have made it exist. Such representation abstracts away from quantities, stoichiometric and thermodynamic parameters and constitutes the basis for the characterization of our properties. Moreover, we propose an effective method for verifying our properties based on an abstract model of system dynamics. This consists of a new abstract semantics for the system seen as a concurrent network and expressed using the Chemical Ground Form calculus. We illustrate an application of this fr...
Mirmohseni, Mahtab; Aref, Mohammad Reza
2012-01-01
In this paper, taking into account the effect of link delays, we investigate the capacity region of the Cognitive Interference Channel (C-IFC), where cognition can be obtained from either causal or non-causal generalized feedback. For this purpose, we introduce the Causal Cognitive Interference Channel With Delay (CC-IFC-WD) in which the cognitive user's transmission can depend on $L$ future received symbols as well as the past ones. We show that the CC-IFC-WD model is equivalent to a classical Causal C-IFC (CC-IFC) with link delays. Moreover, CC-IFC-WD extends both genie-aided and causal cognitive radio channels and bridges the gap between them. First, we derive an outer bound on the capacity region for the arbitrary value of $L$ and specialize this general outer bound to the strong interference case. Then, under strong interference conditions, we tighten the outer bound. To derive the achievable rate regions, we concentrate on three special cases: 1) Classical CC-IFC (L=0), 2) CC-IFC without delay (L=1), an...
Bayesian detection of causal rare variants under posterior consistency.
Liang, Faming
2013-07-26
Identification of causal rare variants that are associated with complex traits poses a central challenge on genome-wide association studies. However, most current research focuses only on testing the global association whether the rare variants in a given genomic region are collectively associated with the trait. Although some recent work, e.g., the Bayesian risk index method, have tried to address this problem, it is unclear whether the causal rare variants can be consistently identified by them in the small-n-large-P situation. We develop a new Bayesian method, the so-called Bayesian Rare Variant Detector (BRVD), to tackle this problem. The new method simultaneously addresses two issues: (i) (Global association test) Are there any of the variants associated with the disease, and (ii) (Causal variant detection) Which variants, if any, are driving the association. The BRVD ensures the causal rare variants to be consistently identified in the small-n-large-P situation by imposing some appropriate prior distributions on the model and model specific parameters. The numerical results indicate that the BRVD is more powerful for testing the global association than the existing methods, such as the combined multivariate and collapsing test, weighted sum statistic test, RARECOVER, sequence kernel association test, and Bayesian risk index, and also more powerful for identification of causal rare variants than the Bayesian risk index method. The BRVD has also been successfully applied to the Early-Onset Myocardial Infarction (EOMI) Exome Sequence Data. It identified a few causal rare variants that have been verified in the literature.
Bayesian detection of causal rare variants under posterior consistency.
Directory of Open Access Journals (Sweden)
Faming Liang
Full Text Available Identification of causal rare variants that are associated with complex traits poses a central challenge on genome-wide association studies. However, most current research focuses only on testing the global association whether the rare variants in a given genomic region are collectively associated with the trait. Although some recent work, e.g., the Bayesian risk index method, have tried to address this problem, it is unclear whether the causal rare variants can be consistently identified by them in the small-n-large-P situation. We develop a new Bayesian method, the so-called Bayesian Rare Variant Detector (BRVD, to tackle this problem. The new method simultaneously addresses two issues: (i (Global association test Are there any of the variants associated with the disease, and (ii (Causal variant detection Which variants, if any, are driving the association. The BRVD ensures the causal rare variants to be consistently identified in the small-n-large-P situation by imposing some appropriate prior distributions on the model and model specific parameters. The numerical results indicate that the BRVD is more powerful for testing the global association than the existing methods, such as the combined multivariate and collapsing test, weighted sum statistic test, RARECOVER, sequence kernel association test, and Bayesian risk index, and also more powerful for identification of causal rare variants than the Bayesian risk index method. The BRVD has also been successfully applied to the Early-Onset Myocardial Infarction (EOMI Exome Sequence Data. It identified a few causal rare variants that have been verified in the literature.
Temporal sequence in observational studies to establish causality
Directory of Open Access Journals (Sweden)
Luis Carlos Silva Ayçaguer, PhD
2014-05-01
Full Text Available The article includes a brief summary on the scope of the notions of causality and risk and considers some operational difficulties that arise when dealing with problems associated with them. It underscores the vital importance of timing and its link with the most commonly used observational research designs that address causal relationships. The article describes in detail the need to record the order in which the relevant events occur and how to consider this in the analysis. A detailed example of errors that are usually incurred in and their effect is provided.
Towards a definition of locality in a manifoldlike causal set
DEFF Research Database (Denmark)
Glaser, Lisa; Surya, Sumati
2013-01-01
It is a common misconception that spacetime discreteness necessarily implies a violation of local Lorentz invariance. In fact, in the causal set approach to quantum gravity, Lorentz invariance follows from the specific implementation of the discreteness hypothesis. However, this comes at the cost...... of locality. In particular, it is difficult to define a "local" region in a manifoldlike causal set, i.e., one that corresponds to an approximately flat spacetime region. Following up on suggestions from previous work, we bridge this lacuna by proposing a definition of locality based on the abundance...
High frequency statistical arbitrage via the optimal thermal causal path
Chinthalapati, V. L. Raju
2011-01-01
We consider the problem of identifying similarities and causality relationships in a given set of ﬁnancial time series data streams. We develop further the “Optimal Thermal Causal Path” method, which is a non-parametric method proposed by Sornette et al. The method considers the mismatch between a given pair of time series in order to identify the expected minimum energy path lead-lag structure between the pair. Traders may ﬁnd this a useful tool for directional trading, to spot arbitrage opp...
Information–theoretic implications of quantum causal structures
DEFF Research Database (Denmark)
Chaves, Rafael; Majenz, Christian; Gross, David
2015-01-01
. However, no systematic method is known for treating such problems in a way that generalizes to quantum systems. Here, we describe a general algorithm for computing information–theoretic constraints on the correlations that can arise from a given causal structure, where we allow for quantum systems as well...... as classical random variables. The general technique is applied to two relevant cases: first, we show that the principle of information causality appears naturally in our framework and go on to generalize and strengthen it. Second, we derive bounds on the correlations that can occur in a networked...... architecture, where a set of few-body quantum systems is distributed among some parties....
Causal relationship between obesity and vitamin D status
DEFF Research Database (Denmark)
Vimaleswaran, Karani S; Berry, Diane J; Lu, Chen;
2013-01-01
Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi-directional ......Obesity is associated with vitamin D deficiency, and both are areas of active public health concern. We explored the causality and direction of the relationship between body mass index (BMI) and 25-hydroxyvitamin D [25(OH)D] using genetic markers as instrumental variables (IVs) in bi...
The Framework, Causal and Co-compact Structure of Space-time
Kovár, Martin
2013-01-01
We introduce a canonical, compact topology, which we call weakly causal, naturally generated by the causal site of J. D. Christensen and L. Crane, a pointless algebraic structure motivated by certain problems of quantum gravity. We show that for every four-dimensional globally hyperbolic Lorentzian manifold there exists an associated causal site, whose weakly causal topology is co-compact with respect to the manifold topology and vice versa. Thus, the causal site has the full information about the topology of space-time, represented by the Lorentzian manifold. In addition, we show that there exist also non-Lorentzian causal sites (whose causal relation is not a continuous poset) and so the weakly causal topology and its de Groot dual extends the usual manifold topology of space-time beyond topologies generated by the traditional, smooth model. As a source of inspiration in topologizing the studied causal structures, we use some methods and constructions of general topology and formal concept analysis.
International Nuclear Information System (INIS)
The NRC Regulatory Agenda is a compilation of all rules on which the NRC has recently completed action or has proposed, or is considering action and all petitions for rulemaking which have been received by the Commission and are pending disposition by the Commission. The Regulatory Agenda is updated and issued each quarter
International Nuclear Information System (INIS)
The NRC Regulatory Agenda is a compilation of all rules on which the NRC has recently completed action, or has proposed action, or is considering action, and all petitions for rulemaking which have been received by the Commission and are pending disposition by the Commission. The Regulatory Agenda is updated and issued each quarter
International Nuclear Information System (INIS)
The NRC Regulatory Agenda is a compilation of all rules on which the NRC has proposed or is considering action and all petitions for rulemaking which have been received by the Commission and are pending disposition by the Commission. The Regulatory Agenda is updated and issued each quarter
Nuclear Regulatory legislation
International Nuclear Information System (INIS)
This compilation of statutes and material pertaining to nuclear regulatory legislation through the 97th Congress, 2nd Session, has been prepared by the Office of the Executive Legal Director, U.S. Nuclear Regulatory Commission, with the assistance of staff, for use as an internal resource document
International Nuclear Information System (INIS)
The NRC Regulatory Agenda is a compilation of all rules on which the NRC has recently completed action, or has proposed action, or is considering action, and all petitions for rulemaking which have been received by the Commission and are pending disposition by the Commission. The Regulatory Agenda is updated and issued each quarter
International Nuclear Information System (INIS)
The NRC Regulatory Agenda is a compilation of all rules on which the NRC has recently completed action or has proposed, or is considering action and all petitions for rulemaking which have been received by the commission and are pending disposition by the Commission. The Regulatory Agenda is updated and issued each quarter
Enhancer scanning to locate regulatory regions in genomic loci.
Buckley, Melissa; Gjyshi, Anxhela; Mendoza-Fandiño, Gustavo; Baskin, Rebekah; Carvalho, Renato S; Carvalho, Marcelo A; Woods, Nicholas T; Monteiro, Alvaro N A
2016-01-01
This protocol provides a rapid, streamlined and scalable strategy to systematically scan genomic regions for the presence of transcriptional regulatory regions that are active in a specific cell type. It creates genomic tiles spanning a region of interest that are subsequently cloned by recombination into a luciferase reporter vector containing the simian virus 40 promoter. Tiling clones are transfected into specific cell types to test for the presence of transcriptional regulatory regions. The protocol includes testing of different single-nucleotide polymorphism (SNP) alleles to determine their effect on regulatory activity. This procedure provides a systematic framework for identifying candidate functional SNPs within a locus during functional analysis of genome-wide association studies. This protocol adapts and combines previous well-established molecular biology methods to provide a streamlined strategy, based on automated primer design and recombinational cloning, allowing one to rapidly go from a genomic locus to a set of candidate functional SNPs in 8 weeks. PMID:26658467
PERKINS Edward; Antczak, Philipp; Burgoon, Lyle; Falciani, Francesco; GARCIA-REYERO Natalia; GUTSELL Steve; HODGES Geoff; KIENZLER AUDE; Knapen, Dries; McBride, Mary; Willett, Catherine
2015-01-01
Adverse outcome pathways (AOPs) offer a pathway-based toxicological framework to support hazard assessment and regulatory decision-making. However, little has been discussed about the scientific confidence needed, or how complete a pathway should be, before use in a specific regulatory application. Here we review four case studies to explore the degree of scientific confidence and extent of completeness (in terms of causal events) that is required for an AOP to be useful for a spe...
Smith, Andrew J. P.; Howard, Philip; Shah, Sonia; Eriksson, Per; Stender, Stefan; Giambartolomei, Claudia; Folkersen, Lasse; Tybjærg-Hansen, Anne; Kumari, Meena; Palmen, Jutta; Hingorani, Aroon D.; Talmud, Philippa J; Humphries, Steve E.
2012-01-01
Following the widespread use of genome-wide association studies (GWAS), focus is turning towards identification of causal variants rather than simply genetic markers of diseases and traits. As a step towards a high-throughput method to identify genome-wide, non-coding, functional regulatory variants, we describe the technique of allele-specific FAIRE, utilising large-scale genotyping technology (FAIRE-gen) to determine allelic effects on chromatin accessibility and regulatory potential. FAIRE...
van Dijk; Breedveld, P.C.
1991-01-01
The existence of zero-order causal paths in bond graphs of physical systems implies the set of state equations to be an implicit mixed set of Differential and Algebraic Equations (DAEs). In the block diagram expansion of such a bond graph, this type of causal path corresponds with a zero-order loop. In this paper the numerical solution of the DAEs by methods commonly used for solving stiff systems of Ordinary Differential Equations (ODEs) is discussed. Apart from a description of the numerica...
Causal efficacy and the normative notion of sustainability science
Directory of Open Access Journals (Sweden)
Lin-Shu Wang
2011-10-01
Full Text Available Sustainability science requires both a descriptive understanding and a normative approach. Modern science, however, began as purely descriptive knowledge, the core of which is that matter is dynamically inert and without purpose. The British philosopher David Hume concluded that the only type of causation in the material world is “efficient causation,” which supported this purposeless view of a deterministic world “governed” by the causal laws of dynamics. But Hume did not argue against the existence of efficacious causation, only the error of humans projecting the mind’s efficacy to objects. Though dynamically inert, a material object away from equilibrium can be thermodynamically reactive, suggesting the possibility of the object being efficaciously managed for a purpose. Furthermore, quantum physics has replaced classical physics as the fundamental theory of the material world. Its basic equation, the Schrödinger wave-equation, is deterministic but causally inert—it cannot govern, leaving the determinism door unlocked. This causal gap, according to the von Neumann-Stapp quantum measurement/activation theory, necessitates the pragmatic existence in an irreversible universe of the causal efficacy of mental effort and information management. The resulting “bigger” empirical science has room for “descriptive determinism” and “normative action,” both of which are utterly essential in formulating sustainability science as an integral discipline.
What can causal networks tell us about metabolic pathways?
Directory of Open Access Journals (Sweden)
Rachael Hageman Blair
Full Text Available Graphical models describe the linear correlation structure of data and have been used to establish causal relationships among phenotypes in genetic mapping populations. Data are typically collected at a single point in time. Biological processes on the other hand are often non-linear and display time varying dynamics. The extent to which graphical models can recapitulate the architecture of an underlying biological processes is not well understood. We consider metabolic networks with known stoichiometry to address the fundamental question: "What can causal networks tell us about metabolic pathways?". Using data from an Arabidopsis Bay[Formula: see text]Sha population and simulated data from dynamic models of pathway motifs, we assess our ability to reconstruct metabolic pathways using graphical models. Our results highlight the necessity of non-genetic residual biological variation for reliable inference. Recovery of the ordering within a pathway is possible, but should not be expected. Causal inference is sensitive to subtle patterns in the correlation structure that may be driven by a variety of factors, which may not emphasize the substrate-product relationship. We illustrate the effects of metabolic pathway architecture, epistasis and stochastic variation on correlation structure and graphical model-derived networks. We conclude that graphical models should be interpreted cautiously, especially if the implied causal relationships are to be used in the design of intervention strategies.
Energy consumption and GDP in Tunisia: Cointegration and causality analysis
International Nuclear Information System (INIS)
In this paper, the Johansen cointegration technique is used to examine the causal relationship between per capita energy consumption (PCEC) and per capita gross domestic product (PCGDP) for Tunisia during the 1971-2004 period. In order to test for Granger causality in the presence of cointegration among the variables, a vector error correction model (VECM) is used instead of a vector autoregressive (VAR) model. Our estimation results indicate that the PCGDP and PCEC for Tunisia are related by one cointegrating vector and that there is a long-run bi-directional causal relationship between the two series and a short-run unidirectional causality from energy to gross domestic product (GDP). The source of causation in the long-run is found to be the error-correction terms in both directions. Hence, an important policy implication resulting from this analysis is that energy can be considered as a limiting factor to GDP growth in Tunisia. Conclusions for Tunisia may also be relevant for a number of countries that have to go through a similar development path of increasing pressure on already scarce energy resources.
Fostering Deeper Critical Inquiry with Causal Layered Analysis
Haigh, Martin
2016-01-01
Causal layered analysis (CLA) is a technique that enables deeper critical inquiry through a structured exploration of four layers of causation. CLA's layers reach down from the surface litany of media understanding, through the layer of systemic causes identified by conventional research, to underpinning worldviews, ideologies and philosophies,…
Temperature has a causal effect on avian timing of reproduction
Visser, M.E.; Holleman, L.J.M.; Caro, S.P.
2009-01-01
Many bird species reproduce earlier in years with high spring temperatures, but little is known about the causal effect of temperature. Temperature may have a direct effect on timing of reproduction but the correlation may also be indirect, for instance via food phenology. As climate change has led
Ratoon stunting disease of sugarcane: isolation of the causal bacterium.
Davis, M J; Gillaspie, A G; Harris, R W; Lawson, R H
1980-12-19
A small coryneform bacterium was consistently isolated from sugarcane with ratoon stunting disease and shown to be the causal agent. A similar bacterium was isolated from Bermuda grass. Both strains multiplied in sugarcane and Bermuda grass, but the Bermuda grass strain did not incite the symptoms of ratoon stunting disease in sugarcane. Shoot growth in Bermuda grass was retarded by both strains. PMID:17817853
Inferring Causality: Coupling Assymetry Tested using Surrogate Data
Czech Academy of Sciences Publication Activity Database
Paluš, Milan
Berlin : European Physical Society, 2005 - (Schöll, E.; Lüdge, K.). s. 132-133 ISBN 2-914771-26-6. [Dynamics Days Europe 2005 /25./. 25.07.2005-28.07.2005, Berlin] Institutional research plan: CEZ:AV0Z10300504 Keywords : inference * causality * surrogate data Subject RIV: BA - General Mathematics
Emergence of a 4D world from causal quantum gravity
Ambjørn, J.; Jurkiewicz, J.(Faculty of Physics, Astronomy and Applied Computer Science, Jagiellonian University, ul. prof. Stanislawa Lojasiewicza 11, Krakow, PL 30-348, Poland); Loll, R
2006-01-01
Causal Dynamical Triangulations in four dimensions provide a background- independent definition of the sum over geometries in nonperturbative quantum gravity, with a positive cosmological constant. We present evidence that a macro- scopic four-dimensional world emerges from this theory dynamically.
The Development of Causal and Logical Connectives in Children
Lawton, J. T.
1977-01-01
Children's use of causal and logical connectives was examined before and after treatments based on advance organizers with social studies lessons. In samples of 120 children from age-levels 6 and 10 years a diminution in the use of syncretic reasoning and understanding followed the experimental treatment. (Editor)
Heart-rate monitoring by air pressure and causal analysis
Tsuchiya, Naoki; Nakajima, Hiroshi; Hata, Yutaka
2011-06-01
Among lots of vital signals, heart-rate (HR) is an important index for diagnose human's health condition. For instance, HR provides an early stage of cardiac disease, autonomic nerve behavior, and so forth. However, currently, HR is measured only in medical checkups and clinical diagnosis during the rested state by using electrocardiograph (ECG). Thus, some serious cardiac events in daily life could be lost. Therefore, a continuous HR monitoring during 24 hours is desired. Considering the use in daily life, the monitoring should be noninvasive and low intrusive. Thus, in this paper, an HR monitoring in sleep by using air pressure sensors is proposed. The HR monitoring is realized by employing the causal analysis among air pressure and HR. The causality is described by employing fuzzy logic. According to the experiment on 7 males at age 22-25 (23 on average), the correlation coefficient against ECG is 0.73-0.97 (0.85 on average). In addition, the cause-effect structure for HR monitoring is arranged by employing causal decomposition, and the arranged causality is applied to HR monitoring in a setting posture. According to the additional experiment on 6 males, the correlation coefficient is 0.66-0.86 (0.76 on average). Therefore, the proposed method is suggested to have enough accuracy and robustness for some daily use cases.
Testing Dark Energy and Cardassian Expansion for Causality
De Leon, J P
2004-01-01
Causality principle is a powerful criterion that allows us to discriminate between what is possible or not. In this paper we study the transition from decelerated to accelerated expansion in the context of Cardassian and dark energy models. We distinguish two important events during the transition. The first one is the end of the matter-dominated phase, which occurs at some time $t_{eq}$. The second one is the actual crossover from deceleration to acceleration, which occurs at some $t_{T}$. Causality requires $t_{T} \\geq t_{eq}$. We demonstrate that dark energy models, with constant $w$, and Cardassian expansion, are compatible with causality only if $(\\Omega_{M} - \\bar{q}) \\leq 1/2$. However, observational data indicate that the most probable option is $(\\Omega_{M} - \\bar{q}) > 1/2$. Consequently, the transition from deceleration to acceleration in dark energy and Cardassian models occurs before the matter-dominated epoch comes to an end, i.e., $t_{eq} > t_{T}$. Which contradicts causality principle.
Testing Information Causality for General Quantum Communication Protocols
Yu, I-Ching
2015-01-01
Information causality was proposed as a physical principle to put upper bound on the accessible information gain in a physical bi-partite communication scheme. Intuitively, the information gain cannot be larger than the amount of classical communication to avoid violation of causality. Moreover, it was shown that this bound is consistent with the Tsirelson bound for the binary quantum systems. In this paper, we test the information causality for the more general (non-binary) quantum communication schemes. In order to apply the semi-definite programming method to find the maximal information gain, we only consider the schemes in which the information gain is monotonically related to the Bell-type functions, i.e., the generalization of CHSH functions for Bell inequalities in a binary schemes. We determine these Bell-type functions by using the signal decay theorem. Our results support the proposal of information causality. We also find the maximal information gain by numerical brute-force method for the most ge...
Intimate Partner Violence and Welfare Participation: A Longitudinal Causal Analysis
Cheng, Tyrone C.
2013-01-01
This longitudinal study examined the temporal-ordered causal relationship between intimate partner violence (IPV), five mental disorders (depression, generalized anxiety disorder, social phobia, panic attack, posttraumatic stress disorder [PTSD]), alcohol abuse/dependence, drug abuse/ dependence, treatment seeking (from physician, counselor, and…
Causality and Conjugate Points in General Plane Waves
Flores, J L
2003-01-01
Let $M = M_0 x R^2$ be a pp--wave type spacetime endowed with the metric $ds^2 = + 2 du dv + H(x,u) du^2$, where $(M_0, $ is any Riemannian manifold and $H(x,u)$ an arbitrary function. We show that the behaviour of $H(x,u)$ at spatial infinity determines the causality of $M$, concretely: (a) if $-H(x,u)$ behaves subquadratically at spatial infinity then the spacetime $M_0$ is strongly causal, (b) it is globally hyperbolic if, additionally, the spatial part $(M_0, )$ is complete, and (c) $M$ is always causal, but there are (superquadratic) non-distinguishing examples with $H(x,u)$ arbitrarily close to a quadratic spatial behavior. Therefore, the classical exact model $M_0 = \\R^2$, $H(x,u) = h_{ij}(u) x_i x_j$, which is known to be strongly causal but not globally hyperbolic, lies in the critical quadratic situation with complete $M_0$. This must be taken into account for realistic applications. The relation of these results with the notion of astigmatic conjugacy and the existence of conjugate points is also ...
Microscopic formula for transport coefficients of causal hydrodynamics
Koide, T.
2007-01-01
The Green-Kubo-Nakano formula should be modified in relativistic hydrodynamics because of the problem of acausality and the breaking of sum rules. In this work, we propose a formula to calculate the transport coefficients of causal hydrodynamics based on the projection operator method. As concrete examples, we derive the expressions for the diffusion coefficient, the shear viscosity coefficient, and corresponding relaxation times.
Remarks on the correspondence of the relativity and causality principles
Kholmetskii, Alexander L.
2002-01-01
A particular problem about special kind of two light pulses propagation has been considered in cases of inertial motion, constant homogeneous gravitation field and progressive non-inertial motion with constant acceleration. A contradiction between the causality principle and relativity theory has been revealed.
Psychology and evolutionary biology; Causal analysis, evidence, and nomothetic laws
Van Hezewijk, René
2008-01-01
Published as a chapter in Van Hezewijk, R. (2003). Psychology and evolutionary biology; Causal analysis, evidence, and nomothetic laws. In N. Stephenson, L. Radtke, R. Jorna & H. J. Stam (Eds.), Theoretical psychology; Critical contributions (pp. 405-415). Concord, Ontario: Captus Press.
Moral asymmetries in judgments of agency withstand ludicrous causal deviance
Sousa, Paulo; Holbrook, Colin; Swiney, Lauren
2015-01-01
Americans have been shown to attribute greater intentionality to immoral than to amoral actions in cases of causal deviance, that is, cases where a goal is satisfied in a way that deviates from initially planned means (e.g., a gunman wants to hit a target and his hand slips, but the bullet ricochets off a rock into the target). However, past research has yet to assess whether this asymmetry persists in cases of extreme causal deviance. Here, we manipulated the level of mild to extreme causal deviance of an immoral versus amoral act. The asymmetry in attributions of intentionality was observed at all but the most extreme level of causal deviance, and, as we hypothesized, was mediated by attributions of blame/credit and judgments of action performance. These findings are discussed as they support a multiple-concepts interpretation of the asymmetry, wherein blame renders a naïve concept of intentional action (the outcome matches the intention) more salient than a composite concept (the outcome matches the intention and was brought about by planned means), and in terms of their implications for cross-cultural research on judgments of agency. PMID:26441755
Children's Causal Inferences from Conflicting Testimony and Observations
Bridgers, Sophie; Buchsbaum, Daphna; Seiver, Elizabeth; Griffiths, Thomas L.; Gopnik, Alison
2016-01-01
Preschoolers use both direct observation of statistical data and informant testimony to learn causal relationships. Can children integrate information from these sources, especially when source reliability is uncertain? We investigate how children handle a conflict between what they hear and what they see. In Experiment 1, 4-year-olds were…
What is causal about individual differences? : A comment on Weinberger
D. Borsboom
2015-01-01
Weinberger (2015) claims that if a latent variable is a cause, it must be a within-subject cause. In addition, Weinberger suggests that this fact refutes the conclusion of Borsboom, Mellenbergh, and Van Heerden (2003), who stated that standard psychometric models have a causal interpretation that is
The Special Status of Actions in Causal Reasoning in Rats
Leising, Kenneth J.; Wong, Jared; Waldmann, Michael R.; Blaisdell, Aaron P.
2008-01-01
A. P. Blaisdell, K. Sawa, K. J. Leising, and M. R. Waldmann (2006) reported evidence for causal reasoning in rats. After learning through Pavlovian observation that Event A (a light) was a common cause of Events X (an auditory stimulus) and F (food), rats predicted F in the test phase when they observed Event X as a cue but not when they generated…
Music and Spatial Task Performance: A Causal Relationship.
Rauscher, Frances H.; And Others
This research paper reports on testing the hypothesis that music and spatial task performance are causally related. Two complementary studies are presented that replicate and explore previous findings. One study of college students showed that listening to a Mozart sonata induces subsequent short-term spatial reasoning facilitation and tested the…
The TETRAD Project: Constraint Based Aids to Causal Model Specification.
Scheines, Richard; Spirtes, Peter; Glymour, Clark; Meek, Christopher; Richardson, Thomas
1998-01-01
The TETRAD for constraint-based aids to causal model specification project and related work in computer science aims to apply standards of rigor and precision to the problem of using data and background knowledge to make inferences about a model's specifications. Several algorithms that are implemented in the TETRAD II program are presented. (SLD)
Second-Order Conditioning of Human Causal Learning
Jara, Elvia; Vila, Javier; Maldonado, Antonio
2006-01-01
This article provides the first demonstration of a reliable second-order conditioning (SOC) effect in human causal learning tasks. It demonstrates the human ability to infer relationships between a cause and an effect that were never paired together during training. Experiments 1a and 1b showed a clear and reliable SOC effect, while Experiments 2a…
Causality in Psychiatry: A Hybrid Symptom Network Construct Model.
Young, Gerald
2015-01-01
Causality or etiology in psychiatry is marked by standard biomedical, reductionistic models (symptoms reflect the construct involved) that inform approaches to nosology, or classification, such as in the DSM-5 [Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition; (1)]. However, network approaches to symptom interaction [i.e., symptoms are formative of the construct; e.g., (2), for posttraumatic stress disorder (PTSD)] are being developed that speak to bottom-up processes in mental disorder, in contrast to the typical top-down psychological construct approach. The present article presents a hybrid top-down, bottom-up model of the relationship between symptoms and mental disorder, viewing symptom expression and their causal complex as a reciprocally dynamic system with multiple levels, from lower-order symptoms in interaction to higher-order constructs affecting them. The hybrid model hinges on good understanding of systems theory in which it is embedded, so that the article reviews in depth non-linear dynamical systems theory (NLDST). The article applies the concept of emergent circular causality (3) to symptom development, as well. Conclusions consider that symptoms vary over several dimensions, including: subjectivity; objectivity; conscious motivation effort; and unconscious influences, and the degree to which individual (e.g., meaning) and universal (e.g., causal) processes are involved. The opposition between science and skepticism is a complex one that the article addresses in final comments. PMID:26635639
Causal Temperature Profiles in Horizon-free Collapse
Indian Academy of Sciences (India)
N. F. Naidu; M. Govender
2007-12-01
We investigate the causal temperature profiles in a recent model of a radiating star undergoing dissipative gravitational collapse without the formation of a horizon. It is shown that this simple exact model provides physically reasonable behaviour for the temperature profile within the framework of extended irreversible thermodynamics.
Causality between the Amplitude and Frequency of Cardiac Oscillations
Czech Academy of Sciences Publication Activity Database
Paluš, Milan; Stefanovska, A.; Veber, M.
2004-01-01
Roč. 4, č. 2 (2004), s. 127-132. ISSN 1567-8822 Institutional research plan: CEZ:AV0Z1030915 Keywords : causality * cardiac frequency * systolic pressure * information theory * mutual information * synchronization * direction of driving Subject RIV: BB - Applied Statistics, Operational Research
Effects of Perceived Causality on Perceptions of Persons Who Stutter
Boyle, Michael P.; Blood, Gordon W.; Blood, Ingrid M.
2009-01-01
This study examined the effects of the perceived cause of stuttering on perceptions of persons who stutter (PWS) using a 7-item social distance scale, a 25-item adjective pair scale and a 2-item visual analogue scale. Two hundred and four university students rated vignettes which varied on describing a PWS with different causalities for stuttering…
Quantum superluminal communication does not result in the causal loop
Shan, Gao
1999-01-01
We show that the quantum superluminal communication based on the quantum nonlocal influence, if exists, will not result in the causal loop, this conclusion is essentially determined by the peculiarity of the quantum nonlocal influence itself, according to which there must exist a preferred Lorentz frame for consistently describing the quantum nonlocal process.
Causal Attributions and Recovery from Rape: Implications for Counseling.
Frazier, Patricia A.; Schauben, Laura J.
One factor related to postrape trauma is the survivor's belief about the cause of the rape. Most research to date on the relation between causal attributions and postrape recovery has been guided by a theoretical model which proposes that certain types of self-blame can be adaptive for survivors. Specifically, behavioral self-blame is thought to…
The Importance of Qualitative Research for Causal Explanation in Education
Maxwell, Joseph A.
2012-01-01
The concept of causation has long been controversial in qualitative research, and many qualitative researchers have rejected causal explanation as incompatible with an interpretivist or constructivist approach. This rejection conflates causation with the positivist "theory" of causation, and ignores an alternative understanding of causation,…
Causal Model Progressions as a Foundation for Intelligent Learning Environments.
White, Barbara Y.; Frederiksen, John R.
This paper describes the theoretical underpinnings and architecture of a new type of learning environment that incorporates features of microworlds and of intelligent tutoring systems. The environment is based on a progression of increasingly sophisticated causal models that simulate domain phenomena, generate explanations, and serve as student…
The relativistic causal Newton gravity law vs general relativity
Zinoviev, Yury M.
2013-01-01
The equations of the relativistic causal Newton gravity law for the planets of the solar system are studied in the approximation when the Sun rests at the coordinate origin and the planets do not interact between each other. The planet orbits of general relativity are also studied in the same approximation.
Geometric Time and Causal Time in Relativistic Lagrangian Mechanics
Brunet, Olivier
2016-01-01
In this article, we argue that two distinct types of time should be taken into account in relativistic physics: a geometric time, which emanates from the structure of spacetime and its metrics, and a causal time, indicating the flow from the past to the future. A particularity of causal times is that its values have no intrinsic meaning, as their evolution alone is meaningful. In the context of relativistic Lagrangian mechanics, causal times corresponds to admissible parameterizations of paths, and we show that in order for a langragian to not depend on any particular causal time (as its values have no intrinsic meaning), it has to be homogeneous in its velocity argument. We illustrate this property with the example of a free particle in a potential. Then, using a geometric Lagrangian (i.e. a parameterization independent Lagrangian which is also manifestly covariant), we introduce the notion of ageodesicity of a path which measures to what extent a path is far from being a geodesic, and show how the notion ca...
Development and Coherence of Beliefs Regarding Disease Causality and Prevention
Sigelman, Carol K.
2014-01-01
Guided by a naïve theories perspective on the development of thinking about disease, this study of 188 children aged 6 to 18 examined knowledge of HIV/AIDS causality and prevention using parallel measures derived from open-ended and structured interviews. Knowledge of both risk factors and prevention rules, as well as conceptual understanding of…
Promising new cryogenic seal candidate
International Nuclear Information System (INIS)
Of the five seal candidates considered for the main propellant system of the Space Shuttle, only one candidate, the fluoroplastic Halar, satisfied all tests including the critical LO2 impact test and the cryogenic compression sealability test. Radiation-cross-linked Halar is a tough, strong thermoplastic that not only endured one hundred 2200 N compression cycles at 83 K while mounted in a standard military O-ring gland without cracking or deforming, but improved in sealability as a result of this cycling. Although these Halar O-rings require much higher sealing forces (approximately 500 N) at room temperature than rubber O-rings, on cooling to cryogenic temperatures the required sealing force only doubles, whereas the sealing force for rubber O-rings increases eightfold. Although these Halar O-rings were inadequately cross-linked, they still exhibited promise as LO2-compatible cryogenic seals. It is expected that their high-temperature properties can be greatly improved by higher degrees of cross-linking (e.g., by 20 mrad of radiation) without compromising their already excellent low-temperature properties. A direct comparison should then be obtained between the best of the cross-linked Halar compounds and the current commercial cryogenic seal materials, filled Teflon and Kel-F
Understanding Complexity: Pattern Recognitions, Emergent Phenomena and Causal Coupling
Raia, F.
2010-12-01
In teaching and learning complex systems we face a fundamental issue: Simultaneity of causal interactions -where effects are at the same time causes of systems’ behavior. Complex systems’ behavior and evolution are controlled by negative and positive feedback processes, continually changing boundary conditions and complex interaction between systems levels (emergence). These processes cannot be described and understood in a mechanistic framework where causality is conceived of being mostly of cause-effect nature or a linear chain of causes and effects. Mechanist causality by definition is characterized by the assumption that an earlier phenomenon A has a causal effect on the development of a phenomenon B. Since this concept also assumes unidirectional time, B cannot have an effect on A. Since students study science mostly in the lingering mechanistic framework, they have problems understanding complex systems. Specifically, our research on students understanding of complexity indicates that our students seem to have great difficulties in explaining mechanisms underlying natural processes within the current paradigm. Students tend to utilize simple linear model of causality and establish a one-to-one correspondence between cause and effect describing phenomena such as emergence and self-organization as being mechanistically caused. Contrary to experts, when presented with data distribution -spatial and/or temporal-, students first consider or search for a unique cause without describing the distribution or a recognized pattern. Our research suggests that students do not consider a pattern observed as an emergent phenomenon and therefore a causal determinant influencing and controlling the evolution of the system. Changes in reasoning have been observed when students 1) are iteratively asked to recognize and describe patterns in data distribution and 2) subsequently learn to identify these patterns as emergent phenomena and as fundamental causal controls over
Developing a Causal Model from Liver Function Test Data
Inada, Masanori; Terano, Takao
As Active Mining is a new concept among data mining and/or knowledge discovery in databases communities, in order to validate the effectiveness, it is important to carry out empirical studies using practical data. Based on the concept of Active User Reaction, this paper develops a causal model from liver function test data in a medical domain. To develop the model, we have set a problem to predict the values of ICG (indocyanine green) test from given observation data and experts' background knowledge. We therefore employ a framework of meta-learning and structural equation modeling. In this paper meta-learning means learning about mined results from multiple data-mining techniques. Structural equation modeling enables us to describe flexible models from background knowledge. The construction of the causal model contains two phases: meta-learning and the model building. The meta-learning phase utilizes both the linear regression and the neural network as data mining techniques, then examines the predictability on the given data set. Mining models are n-folded learned from the training data set. Each of the prediction accuracy of the mining models is compared using with the testing data. On the model building phase, we use structural equation modeling to develop a causal model based on results of meta-learning and background knowledge. We again compare the accuracy of the causal model with each of the mining models. Consequently we have developed the causal model, which is comprehensible and have good predictive performance, via the meta-learning phase. Through the empirical study, we have got the conclusion that the framework of meta-learning is effective in data mining in a difficult medical domain.
Causal discovery via reproducing kernel Hilbert space embeddings.
Chen, Zhitang; Zhang, Kun; Chan, Laiwan; Schölkopf, Bernhard
2014-07-01
Causal discovery via the asymmetry between the cause and the effect has proved to be a promising way to infer the causal direction from observations. The basic idea is to assume that the mechanism generating the cause distribution p(x) and that generating the conditional distribution p(y|x) correspond to two independent natural processes and thus p(x) and p(y|x) fulfill some sort of independence condition. However, in many situations, the independence condition does not hold for the anticausal direction; if we consider p(x, y) as generated via p(y)p(x|y), then there are usually some contrived mutual adjustments between p(y) and p(x|y). This kind of asymmetry can be exploited to identify the causal direction. Based on this postulate, in this letter, we define an uncorrelatedness criterion between p(x) and p(y|x) and, based on this uncorrelatedness, show asymmetry between the cause and the effect in terms that a certain complexity metric on p(x) and p(y|x) is less than the complexity metric on p(y) and p(x|y). We propose a Hilbert space embedding-based method EMD (an abbreviation for EMbeDding) to calculate the complexity metric and show that this method preserves the relative magnitude of the complexity metric. Based on the complexity metric, we propose an efficient kernel-based algorithm for causal discovery. The contribution of this letter is threefold. It allows a general transformation from the cause to the effect involving the noise effect and is applicable to both one-dimensional and high-dimensional data. Furthermore it can be used to infer the causal ordering for multiple variables. Extensive experiments on simulated and real-world data are conducted to show the effectiveness of the proposed method. PMID:24708374
Energy Technology Data Exchange (ETDEWEB)
NONE
1994-05-01
The Office of Civilian Radioactive Waste Management (OCRWM) Program Management System Manual requires preparation of the OCRWM Regulatory Guidance Document (RGD) that addresses licensing, environmental compliance, and safety and health compliance. The document provides: regulatory compliance policy; guidance to OCRWM organizational elements to ensure a consistent approach when complying with regulatory requirements; strategies to achieve policy objectives; organizational responsibilities for regulatory compliance; guidance with regard to Program compliance oversight; and guidance on the contents of a project-level Regulatory Compliance Plan. The scope of the RGD includes site suitability evaluation, licensing, environmental compliance, and safety and health compliance, in accordance with the direction provided by Section 4.6.3 of the PMS Manual. Site suitability evaluation and regulatory compliance during site characterization are significant activities, particularly with regard to the YW MSA. OCRWM`s evaluation of whether the Yucca Mountain site is suitable for repository development must precede its submittal of a license application to the Nuclear Regulatory Commission (NRC). Accordingly, site suitability evaluation is discussed in Chapter 4, and the general statements of policy regarding site suitability evaluation are discussed in Section 2.1. Although much of the data and analyses may initially be similar, the licensing process is discussed separately in Chapter 5. Environmental compliance is discussed in Chapter 6. Safety and Health compliance is discussed in Chapter 7.
International Nuclear Information System (INIS)
The Office of Civilian Radioactive Waste Management (OCRWM) Program Management System Manual requires preparation of the OCRWM Regulatory Guidance Document (RGD) that addresses licensing, environmental compliance, and safety and health compliance. The document provides: regulatory compliance policy; guidance to OCRWM organizational elements to ensure a consistent approach when complying with regulatory requirements; strategies to achieve policy objectives; organizational responsibilities for regulatory compliance; guidance with regard to Program compliance oversight; and guidance on the contents of a project-level Regulatory Compliance Plan. The scope of the RGD includes site suitability evaluation, licensing, environmental compliance, and safety and health compliance, in accordance with the direction provided by Section 4.6.3 of the PMS Manual. Site suitability evaluation and regulatory compliance during site characterization are significant activities, particularly with regard to the YW MSA. OCRWM's evaluation of whether the Yucca Mountain site is suitable for repository development must precede its submittal of a license application to the Nuclear Regulatory Commission (NRC). Accordingly, site suitability evaluation is discussed in Chapter 4, and the general statements of policy regarding site suitability evaluation are discussed in Section 2.1. Although much of the data and analyses may initially be similar, the licensing process is discussed separately in Chapter 5. Environmental compliance is discussed in Chapter 6. Safety and Health compliance is discussed in Chapter 7
Candidate genes for drought tolerance and improved productivity in rice (Oryza sativa L.)
Indian Academy of Sciences (India)
M S Vinod; Naveen Sharma; K Manjunatha; Adnan Kanbar; N B Prakash; H E Shashidhar
2006-03-01
Candidate genes are sequenced genes of known biological action involved in the development or physiology of a trait. Twenty-one putative candidate genes were designed after an exhaustive search in the public databases along with an elaborate literature survey for candidate gene products and/or regulatory sequences associated with enhanced drought resistance. The downloaded sequences were then used to design primers considering the flanking sequences as well. Polymerase chain reaction (PCR) performed on 10 diverse cultivars that involved Japonica, Indica and local accessions, revealed 12 polymorphic candidate genes. Seven polymorphic candidate genes were then utilized to genotype 148 individuals of CT9993 × IR62266 doubled haploid (DH) mapping population. The segregation data were tested for deviation from the expected Mendelian ratio (1:1) using a Chi-square test (<1%). Based on this, four candidate genes were assessed to be significant and the remaining three, as non-significant. All the significant candidate genes were biased towards CT9993, the female parent in the DH mapping population. Single-marker analysis strongly associated ( < 1%) them to different traits under both well-watered and low-moisture stress conditions. Two candidate genes, EXP15 and EXP13, were found to be associated with root number and silicon content in the stem respectively, under both well-watered and low-moisture stress conditions.
Managing Regulatory Body Competence
International Nuclear Information System (INIS)
In 2001, the IAEA published TECDOC 1254, which examined the way in which the recognized functions of a regulatory body for nuclear facilities results in competence needs. Using the systematic approach to training (SAT), TECDOC 1254 provided a framework for regulatory bodies for managing training and developing and their maintaining their competence. It has been successfully used by many regulators. The IAEA has also introduced a methodology and an assessment tool - Guidelines for Systematic Assessment of Regulatory Competence Needs (SARCoN) - which provides practical guidance on analysing the training and development needs of a regulatory body and, through a gap analysis, guidance on establishing competence needs and how to meet them. In 2009, the IAEA established a steering committee (supported by a bureau) with the mission to advise the IAEA on how it could best assist Member States to develop suitable competence management systems for their regulatory bodies. The committee recommended the development of a safety report on managing staff competence as an integral part of a regulatory body's management system. This Safety Report was developed in response to this request. It supersedes TECDOC 1254, broadens its application to regulatory bodies for all facilities and activities, and builds upon the experience gained through the application of TECDOC 1254 and SARCoN and the feedback received from Member States. This Safety Report applies to the management of adequate competence as needs change, and as such is equally applicable to the needs of States 'embarking' on a nuclear power programme. It also deals with the special case of building up the competence of regulatory bodies as part of the overall process of establishing an 'embarking' State's regulatory system
DEFF Research Database (Denmark)
Smith, Frank Andrew; Howard, Philip; Shah, Sonia;
2012-01-01
Following the widespread use of genome-wide association studies (GWAS), focus is turning towards identification of causal variants rather than simply genetic markers of diseases and traits. As a step towards a high-throughput method to identify genome-wide, non-coding, functional regulatory varia...
Energy consumption and income in Chinese provinces: Heterogeneous panel causality analysis
International Nuclear Information System (INIS)
Highlights: ► We examine the Granger causality between GDP and energy use for Chinese provinces. ► We use panel causality techniques and take into consideration panel heterogeneity. ► Homogeneous causality tests fail and we test for panel heterogeneous causality. ► Causality holds for 19 provinces from GDP to energy and in the opposite direction for 14 provinces. ► The results point to the importance of the government’s recent energy-saving policies. -- Abstract: Recently, energy production in China fell behind energy consumption. This poses important challenges for the rapidly growing Chinese economy. As a consequence, the causal relationship between energy consumption and GDP is an important empirical issue. This paper examines Granger causality between energy consumption and GDP in China using province-level data. The current paper extends the Granger causality analysis employed in previous studies by taking into account panel heterogeneity. Specifically, four different causal relationships are examined: homogeneous non-causality (HNC), homogeneous causality (HC), heterogeneous non-causality (HENC), and heterogeneous causality (HEC). HC and HNC hypotheses are rejected for causality in either direction, from GDP to energy or from energy to GDP, which implies that the panel made up of Chinese provinces is not homogeneous. Then, heterogeneous causality tests (HEC ad HENC) are conducted for each province. For the causality running from GDP to energy, 19 provinces exhibit HEC and 11 provinces exhibit HENC. For the causality running from energy to GDP, 14 provinces exhibit HEC and 16 provinces exhibit HENC. The results suggest that the Chinese government should incorporate a regional perspective while formulating and implementing energy policies.
Guarnera, Enrico; Berezovsky, Igor N
2016-03-01
Allostery is one of the pervasive mechanisms through which proteins in living systems carry out enzymatic activity, cell signaling, and metabolism control. Effective modeling of the protein function regulation requires a synthesis of the thermodynamic and structural views of allostery. We present here a structure-based statistical mechanical model of allostery, allowing one to observe causality of communication between regulatory and functional sites, and to estimate per residue free energy changes. Based on the consideration of ligand free and ligand bound systems in the context of a harmonic model, corresponding sets of characteristic normal modes are obtained and used as inputs for an allosteric potential. This potential quantifies the mean work exerted on a residue due to the local motion of its neighbors. Subsequently, in a statistical mechanical framework the entropic contribution to allosteric free energy of a residue is directly calculated from the comparison of conformational ensembles in the ligand free and ligand bound systems. As a result, this method provides a systematic approach for analyzing the energetics of allosteric communication based on a single structure. The feasibility of the approach was tested on a variety of allosteric proteins, heterogeneous in terms of size, topology and degree of oligomerization. The allosteric free energy calculations show the diversity of ways and complexity of scenarios existing in the phenomenology of allosteric causality and communication. The presented model is a step forward in developing the computational techniques aimed at detecting allosteric sites and obtaining the discriminative power between agonistic and antagonistic effectors, which are among the major goals in allosteric drug design. PMID:26939022
Testing causal relationships between wholesale electricity prices and primary energy prices
International Nuclear Information System (INIS)
We apply the lag-augmented vector autoregression technique to test the Granger-causal relationships among wholesale electricity prices, natural gas prices, and crude oil prices. In addition, by adopting a cross-correlation function approach, we test not only the causality in mean but also the causality in variance between the variables. The results of tests using both techniques show that gas prices Granger-cause electricity prices in mean. We find no Granger-causality in variance among these variables. -- Highlights: •We test the Granger-causality among wholesale electricity and primary energy prices. •We test not only the causality in mean but also the causality in variance. •The results show that gas prices Granger-cause electricity prices in mean. •We find no Granger-causality in variance among these variables
K-causal structure of space-time in general relativity
Indian Academy of Sciences (India)
Sujatha Janardhan; R V Saraykar
2008-04-01
Using K-causal relation introduced by Sorkin and Woolgar [1], we generalize results of Garcia-Parrado and Senovilla [2,3] on causal maps. We also introduce causality conditions with respect to K-causality which are analogous to those in classical causality theory and prove their inter-relationships. We introduce a new causality condition following the work of Bombelli and Noldus [4] and show that this condition lies in between global hyperbolicity and causal simplicity. This approach is simpler and more general as compared to traditional causal approach [5,6] and it has been used by Penrose et al [7] in giving a new proof of positivity of mass theorem. 0-space-time structures arise in many mathematical and physical situations like conical singularities, discontinuous matter distributions, phenomena of topology-change in quantum field theory etc.
75 FR 58374 - 2010 Release of CADDIS (Causal Analysis/Diagnosis Decision Information System)
2010-09-24
... AGENCY 2010 Release of CADDIS (Causal Analysis/Diagnosis Decision Information System) AGENCY... Decision Information System (CADDIS). This Web site was developed to help scientists find, develop, organize, and use environmental information to improve causal assessments of biological impairment....
International Nuclear Information System (INIS)
The Regulatory Agenda is a quarterly compilation of all rules on which the NRC has recently completed action or has proposed, or is considering action and of all petitions for rulemaking that the NRC has received that are pending disposition
Goal orientations in sport: a causal model Orientaciones de Meta en el deporte: un modelo causal
Directory of Open Access Journals (Sweden)
Francisco P. Holgado
2010-05-01
Full Text Available The study is based on research work relating goal orientation in sport with contextual variables and personal variables. The sample was 511 professional athletes. A “causal” model is proposed in which task and goal ego orientations are the dependent variables. A hypothetical model is obtained using structural equations modelling, supporting that: a athletes who find satisfaction experimenting mastery, who perceive a motivational climate that rewards hard work and who believe that success depends on their effort, develop task goal orientation; and b athletes who get satisfaction demonstrating greater capacity than the rest, who live a motivational climate that leads them to be better than the others and that only rewards the best players, and whose main motive for practising sport is to achieve certain social status and popularity, will have an ego goal orientation. Este trabajo parte de las investigaciones que relacionan las orientaciones de meta en el deporte con variables contextuales, como el clima motivacional percibido, y con variables personales, tales como la satisfacción con los resultados deportivos, las creencias relacionadas con los factores implicados en la obtención del éxito y los motivos por lo que se practica deporte. La muestra está compuesta por 511 deportistas profesionales. Se llevan a cabo análisis de regresión múltiple y se propone un modelo causal en el que las variables a predecir son las orientaciones de meta, a la tarea y al ego. Con ecuaciones estructurales se contrasta un modelo hipotético, que presenta un ajuste adecuado, y que defiende que: a el deportista que encuentra la satisfacción experimentando maestría, que percibe un clima motivacional que premia el trabajo duro y que cree que el éxito depende de su esfuerzo, desarrolla una orientación de meta a la tarea: y b que el deportista que obtiene satisfacción demostrando mayor capacidad que los demás, que vive un clima motivacional que le conduce a
Regulatory unbundling in telecommunications
Knieps, Günter
2011-01-01
Due to its dynamic nature, and the increasing importance of competitive sub-parts, the telecommunications sector provides particularly interesting insights for studying regulatory unbundling. Based on the theory of monopolistic bottle-necks the fallacies of overregulation by undue unbundling obligations are indicated. Neither the promotion of infrastructure competition by mandatory un-bundling of competitive subparts of telecommunications infrastructure, nor regulatory induced network fragmen...
Energy Technology Data Exchange (ETDEWEB)
Johnson, T.C. [Nuclear Regulatory Commission (United States)
1989-11-01
The US Nuclear Regulatory Commission (NRC) is addressing several low-level waste disposal issues that will be important to waste generators and to States and Compacts developing new disposal capacity. These issues include Greater-Than-Class C (GTCC) waste, mixed waste, below regulatory concern (BRC) waste, and the low-level waste data base. This paper discusses these issues and their current status.
Global properties of causal wedges in asymptotically AdS spacetimes
Hubeny, Veronika E; Tonni, Erik
2013-01-01
We examine general features of causal wedges in asymptotically AdS spacetimes and show that in a wide variety of cases they have non-trivial topology. We also prove some general results regarding minimal area surfaces on the causal wedge boundary and thereby derive constraints on the causal holographic information. We go on to demonstrate that certain properties of the causal wedge impact significantly on features of extremal surfaces which are relevant for computation of holographic entanglement entropy.
Pairwise Measures of Causal Direction in the Epidemiology of Sleep Problems and Depression
Rosenström, Tom; Jokela, Markus; Puttonen, Sampsa; Hintsanen, Mirka; Pulkki-Råback, Laura; Viikari, Jorma S.; Raitakari, Olli T.; Keltikangas-Järvinen, Liisa
2012-01-01
Depressive mood is often preceded by sleep problems, suggesting that they increase the risk of depression. Sleep problems can also reflect prodromal symptom of depression, thus temporal precedence alone is insufficient to confirm causality. The authors applied recently introduced statistical causal-discovery algorithms that can estimate causality from cross-sectional samples in order to infer the direction of causality between the two sets of symptoms from a novel perspective. Two common-popu...
Danish Ahmed SIDDIQUI; Ahmed, Qazi Masood
2009-01-01
This paper investigates relationship between institutional quality and economic performance in Pakistan using the Johansen-Juselius cointegration technique and the Granger causality test. The study results indicate that Institutions and growth are cointegrated and thus exhibit a reliable long run relationship. The Granger causality test findings indicate that the causality between Institutions and growth is uni-directional. However, there is no short run causality from Institutions to growth...
The Causality Relation Between Consumer Confidence and Stock Prices: Case of Turkey
Topuz, Yusuf Volkan
2010-01-01
In this study, the causality relation between consumer confidence and stock price is discussed. This study is based on the assumption of potential bi-directional casuality which is from stock prices towards consumer confidence as there might also be causality from consumer confidence towards stock prices. To this end, in this study the causality relation between consumer confidence index and ISE-100 index during the terms of 2004:01-2009:01 is examined by using Granger Causality test. One-dir...
An Algorithm for Deciding if a Set of Observed Independencies Has a Causal Explanation
Verma, Tom S.; Pearl, Judea
2013-01-01
In a previous paper [Pearl and Verma, 1991] we presented an algorithm for extracting causal influences from independence information, where a causal influence was defined as the existence of a directed arc in all minimal causal models consistent with the data. In this paper we address the question of deciding whether there exists a causal model that explains ALL the observed dependencies and independencies. Formally, given a list M of conditional independence statements, it is required to dec...
Causal Mediation in Educational Research: An Illustration Using International Assessment Data
Caro, Daniel H.
2015-01-01
This paper applies the causal mediation framework proposed by Kosuke Imai and colleagues (Imai, Keele, & Tingley, 2010) to educational research by examining the causal mediating role of early literacy activities in parental education influences on reading performance. The paper argues that the study of causal mediation is particularly relevant…
Change, Self-Organization and the Search for Causality in Educational Research and Practice
Koopmans, Matthijs
2014-01-01
Causality is an inextricable part of the educational process, as our understanding of what works in education depends on our ability to make causal attributions. Yet, the research and policy literature in education tends to define causality narrowly as the attribution of educational outcomes to intervention effects in a randomized control trial…
Causal Reasoning in Economics: A Selective Exploration of Semantic, Epistemic and Dynamical Aspects
F. Claveau (Francois)
2012-01-01
textabstractEconomists reason causally. Like many other scientists, they aim at formulating justified causal claims about their object of study. This thesis contributes to our understanding of how causal reasoning proceeds in economics. By using the research on the causes of unemployment as a case s
Using Propensity Score Analysis for Making Causal Claims in Research Articles
Bai, Haiyan
2011-01-01
The central role of the propensity score analysis (PSA) in observational studies is for causal inference; as such, PSA is often used for making causal claims in research articles. However, there are still some issues for researchers to consider when making claims of causality using PSA results. This summary first briefly reviews PSA, followed by…
Causality and Truth [Cauzalitate şi adevăr
Dinga Emil
2014-01-01
The paper aims to discuss the concept of truth in its relation with causality. More exactly, the relation of causality between… causality and truth recognition is exposed and debated. The three types of truth are presented and examined in the light of the paper purpose, commenting on the consequences of the concordance-truth type, as well as crucial questions in knowledge and praxeology.
AnneSchlottmann
2013-01-01
Humans, even babies, perceive causality when one shape moves briefly and linearly after another. Motion timing is crucial in this and causal impressions disappear with short delays between motions. However, the role of temporal information is more complex: It is both a cue to causality and a factor that constrains processing. It affects ability to distinguish causality from non-causality, and social from mechanical causality. Here we study both issues with 3- to 7-year-olds and adults who saw...
Static- and Stationary-complete Spacetimes: Algebraic and Causal Structures
Harris, Steven G
2014-01-01
This is intended as an analysis of the global properties of static and stationary spacetimes with complete (timelike) Killing field, with particular attention to quotients by group actions. This is presented in terms of algebraic structures which are fairly simple for the static case and more involved for the stationary case; the most important tool, the fundamental cocycle, is a cohomological class for static spacetimes but of somewhat looser structure in the stationary case. In particular: (1) A new measurement, similar to the spacetime interval in Minkowski space, is devised for detecting whether two points are causally related in a stationary spacetime; this proves very useful for analysis. (2) All stationary spacetimes are categorized by how they behave with respect to the fundamental cocycle; this enables a complete characterization of global causality properties. (3) It is shown how these tools determine whether global hyperbolicity of a stationary spacetime is inherited by its quotients. (4) Examples ...
Causality between regional stock markets: A frequency domain approach
Directory of Open Access Journals (Sweden)
Gradojević Nikola
2013-01-01
Full Text Available Using a data set from five regional stock exchanges (Serbia, Croatia, Slovenia, Hungary and Germany, this paper presents a frequency domain analysis of a causal relationship between the returns on the CROBEX, SBITOP, CETOP and DAX indices, and the return on the major Serbian stock exchange index, BELEX 15. We find evidence of a somewhat dominant effect of the CROBEX and CETOP stock indices on the BELEX 15 stock index across a range of frequencies. The results also indicate that the BELEX 15 index and the SBITOP index interact in a bi-directional causal fashion. Finally, the DAX index movements consistently drive the BELEX 15 index returns for cycle lengths between 3 and 11 days without any feedback effect.
On a renormalization group scheme for causal dynamical triangulations
Cooperman, Joshua H.
2016-03-01
The causal dynamical triangulations approach aims to construct a quantum theory of gravity as the continuum limit of a lattice-regularized model of dynamical geometry. A renormalization group scheme—in concert with finite size scaling analysis—is essential to this aim. Formulating and implementing such a scheme in the present context raises novel and notable conceptual and technical problems. I explored these problems, and, building on standard techniques, suggested potential solutions in a previous paper (Cooperman, arXiv:gr-qc/1410.0026). As an application of these solutions, I now propose a renormalization group scheme for causal dynamical triangulations. This scheme differs significantly from that studied recently by Ambjørn, Görlich, Jurkiewicz, Kreienbuehl, and Loll.
Renormalization group approach to causal bulk viscous cosmological models
Energy Technology Data Exchange (ETDEWEB)
Belinchon, J A [Grupo Inter-Universitario de Analisis Dimensional, Dept. Fisica ETS Arquitectura UPM, Av. Juan de Herrera 4, Madrid (Spain); Harko, T [Department of Physics, University of Hong Kong, Pokfulam Road, Hong Kong (China); Mak, M K [Department of Physics, Hong Kong University of Science and Technology, Clear Water Bay, Hong Kong (China)
2002-06-07
The renormalization group method is applied to the study of homogeneous and flat Friedmann-Robertson-Walker type universes, filled with a causal bulk viscous cosmological fluid. The starting point of the study is the consideration of the scaling properties of the gravitational field equations, the causal evolution equation of the bulk viscous pressure and the equations of state. The requirement of scale invariance imposes strong constraints on the temporal evolution of the bulk viscosity coefficient, temperature and relaxation time, thus leading to the possibility of obtaining the bulk viscosity coefficient-energy density dependence. For a cosmological model with bulk viscosity coefficient proportional to the Hubble parameter, we perform the analysis of the renormalization group flow around the scale-invariant fixed point, thereby obtaining the long-time behaviour of the scale factor.
A review of causal estimation of effects in mediation analyses.
Ten Have, Thomas R; Joffe, Marshall M
2012-02-01
We describe causal mediation methods for analysing the mechanistic factors through which interventions act on outcomes. A number of different mediation approaches have been presented in the biomedical, social science and statistical literature with an emphasis on different aspects of mediation. We review the different sets of assumptions that allow identification and estimation of effects in the simple case of a single intervention, a temporally subsequent mediator and outcome. These assumptions include various no confounding assumptions including sequential ignorability assumptions and also interaction assumptions involving the treatment and mediator. The understanding of such assumptions is crucial since some can be assessed under certain conditions (e.g. treatment-mediator interactions), whereas others cannot (sequential ignorability). These issues become more complex with multiple mediators and longitudinal outcomes. In addressing these assumptions, we review several causal approaches to mediation analyses. PMID:21163849
Causal evidence for frontal cortex organization for perceptual decision making.
Rahnev, Dobromir; Nee, Derek Evan; Riddle, Justin; Larson, Alina Sue; D'Esposito, Mark
2016-05-24
Although recent research has shown that the frontal cortex has a critical role in perceptual decision making, an overarching theory of frontal functional organization for perception has yet to emerge. Perceptual decision making is temporally organized such that it requires the processes of selection, criterion setting, and evaluation. We hypothesized that exploring this temporal structure would reveal a large-scale frontal organization for perception. A causal intervention with transcranial magnetic stimulation revealed clear specialization along the rostrocaudal axis such that the control of successive stages of perceptual decision making was selectively affected by perturbation of successively rostral areas. Simulations with a dynamic model of decision making suggested distinct computational contributions of each region. Finally, the emergent frontal gradient was further corroborated by functional MRI. These causal results provide an organizational principle for the role of frontal cortex in the control of perceptual decision making and suggest specific mechanistic contributions for its different subregions. PMID:27162349
Renormalization group approach to causal bulk viscous cosmological models
International Nuclear Information System (INIS)
The renormalization group method is applied to the study of homogeneous and flat Friedmann-Robertson-Walker type universes, filled with a causal bulk viscous cosmological fluid. The starting point of the study is the consideration of the scaling properties of the gravitational field equations, the causal evolution equation of the bulk viscous pressure and the equations of state. The requirement of scale invariance imposes strong constraints on the temporal evolution of the bulk viscosity coefficient, temperature and relaxation time, thus leading to the possibility of obtaining the bulk viscosity coefficient-energy density dependence. For a cosmological model with bulk viscosity coefficient proportional to the Hubble parameter, we perform the analysis of the renormalization group flow around the scale-invariant fixed point, thereby obtaining the long-time behaviour of the scale factor
Scale-dependent homogeneity measures for causal dynamical triangulations
Cooperman, Joshua H
2014-01-01
I propose two scale-dependent measures of the homogeneity of the quantum geometry determined by an ensemble of causal triangulations. The first measure is volumetric, probing the growth of volume with graph geodesic distance. The second measure is spectral, probing the return probability of a random walk with diffusion time. Both of these measures, particularly the first, are closely related to those used to assess the homogeneity of our own universe on the basis of galaxy redshift surveys. I employ these measures to quantify the quantum spacetime homogeneity as well as the temporal evolution of quantum spatial homogeneity of ensembles of causal triangulations in the well-known physical phase. According to these measures, the quantum spacetime geometry exhibits some degree of inhomogeneity on sufficiently small scales and a high degree of homogeneity on sufficiently large scales. This inhomogeneity appears unrelated to the phenomenon of dynamical dimensional reduction. I also uncover evidence for power-law sc...
Causal diagrams, the placebo effect, and the expectation effect
Directory of Open Access Journals (Sweden)
Shahar E
2013-09-01
Full Text Available Eyal Shahar,1 Doron J Shahar2 1Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, 2Department of Mathematics, College of Science, University of Arizona, Tucson, AZ, USA Abstract: Using causal diagrams, a formal research methodology, we analyzed several definitions of placebo and the placebo effect. We conclude that placebo is an ambiguous, redundant term and that the so-called placebo effect conceals far more interesting effects that are attributed to the patient's expectation. Biomedical research will benefit from abandoning the term placebo effect and focusing instead on a deeper understanding of the expectation variable, including its causes, effects, and effect modifiers. This avenue of research should be pursued by observational cohorts that are nested within clinical trials. Keywords: causal diagrams, effect modification, placebo, expectation
Convergence Rate of the Causal Jacobi Derivative Estimator
Liu, Da-Yan; Perruquetti, Wilfrid
2011-01-01
Numerical causal derivative estimators from noisy data are essential for real time applications especially for control applications or fluid simulation so as to address the new paradigms in solid modeling and video compression. By using an analytical point of view due to Lanczos \\cite{C. Lanczos} to this causal case, we revisit $n^{th}$\\ order derivative estimators originally introduced within an algebraic framework by Mboup, Fliess and Join in \\cite{num,num0}. Thanks to a given noise level $\\delta$ and a well-suitable integration length window, we show that the derivative estimator error can be $\\mathcal{O}(\\delta ^{\\frac{q+1}{n+1+q}})$ where $q$\\ is the order of truncation of the Jacobi polynomial series expansion used. This so obtained bound helps us to choose the values of our parameter estimators. We show the efficiency of our method on some examples.
Regge behavior saves string theory from causality violations
DEFF Research Database (Denmark)
di Vecchia, Paolo; Giuseppe, D'Appollonio; Russo, Rodolfo;
2015-01-01
Higher-derivative corrections to the Einstein-Hilbert action are present in bosonic string theory leading to the potential causality violations recently pointed out by Camanho et al. [1]. We analyze in detail this question by considering high-energy string-brane collisions at impact parameters b...... violations are instead neatly avoided when the full structure of string theory — and in particular its Regge behavior — is taken into account....... ≤ l s (the string-length parameter) with l s ≫ R p (the characteristic scale of the Dp-brane geometry). If we keep only the contribution of the massless states causality is violated for a set of initial states whose polarization is suitably chosen with respect to the impact parameter vector. Such...
Regge behavior saves String Theory from causality violations
D'Appollonio, Giuseppe; Russo, Rodolfo; Veneziano, Gabriele
2015-01-01
Higher-derivative corrections to the Einstein-Hilbert action are present in bosonic string theory leading to the potential causality violations recently pointed out by Camanho et al. We analyze in detail this question by considering high-energy string-brane collisions at impact parameters $b \\le l_s$ (the string-length parameter) with $l_s \\gg R_p$ (the characteristic scale of the D$p$-brane geometry). If we keep only the contribution of the massless states causality is violated for a set of initial states whose polarization is suitably chosen with respect to the impact parameter vector. Such violations are instead neatly avoided when the full structure of string theory - and in particular its Regge behavior - is taken into account.
Causal explanation, intentionality, and prediction: Evaluating the Criticism of "Deductivism"
DEFF Research Database (Denmark)
Koch, Carsten Allan
2001-01-01
In a number of influential contributions, Tony Lawson has attacked a view of science that he refers to as deductivism, and criticized economists for implicitly using it in their research. Lawson argues that deductivism is simply the covering-law model, also known as the causal model of scientific...... critisizes the use of universal laws in social science, especially in economics. This view cannot be as easily dismissed as his general criticism of causal explanation. We argue that a number of arguments often used against the existence of (correct) universal laws in the social sciences can be put into...... question. First, it is argued that entities need not be identical, or even remotely alike, to be applicable to the same law. What is necessary is that they have common properties, e.g. mass in physics, and that the law relates to that property (section 6). Second, one might take the so-called model of...
Probing the Cultural Constitution of Causal Cognition - A Research Program.
Bender, Andrea; Beller, Sieghard
2016-01-01
To what extent is the way people perceive, represent, and reason about causal relationships dependent on culture? While there have been sporadic attempts to explore this question, a systematic investigation is still lacking. Here, we propose that human causal cognition is not only superficially affected by cultural background, but that it is co-constituted by the cultural nature of the human species. To this end, we take stock of on-going research, with a particular focus on the methodological approaches taken: cross-species comparisons, archeological accounts, developmental studies, cross-cultural, and cross-linguistic experiments, as well as in-depth within-culture analyses of cognitive concepts, processes, and changes over time. We argue that only a combination of these approaches will allow us to integrate different components of cognition, levels of analysis, and points of view-the key requirements for a comprehensive, interdisciplinary research program to advance this field. PMID:26941695
Causal inference and the data-fusion problem.
Bareinboim, Elias; Pearl, Judea
2016-07-01
We review concepts, principles, and tools that unify current approaches to causal analysis and attend to new challenges presented by big data. In particular, we address the problem of data fusion-piecing together multiple datasets collected under heterogeneous conditions (i.e., different populations, regimes, and sampling methods) to obtain valid answers to queries of interest. The availability of multiple heterogeneous datasets presents new opportunities to big data analysts, because the knowledge that can be acquired from combined data would not be possible from any individual source alone. However, the biases that emerge in heterogeneous environments require new analytical tools. Some of these biases, including confounding, sampling selection, and cross-population biases, have been addressed in isolation, largely in restricted parametric models. We here present a general, nonparametric framework for handling these biases and, ultimately, a theoretical solution to the problem of data fusion in causal inference tasks. PMID:27382148
Dark matter perturbations and viscosity: A causal approach
Acquaviva, Giovanni; John, Anslyn; Pénin, Aurélie
2016-08-01
The inclusion of dissipative effects in cosmic fluids modifies their clustering properties and could have observable effects on the formation of large-scale structures. We analyze the evolution of density perturbations of cold dark matter endowed with causal bulk viscosity. The perturbative analysis is carried out in the Newtonian approximation and the bulk viscosity is described by the causal Israel-Stewart (IS) theory. In contrast to the noncausal Eckart theory, we obtain a third-order evolution equation for the density contrast that depends on three free parameters. For certain parameter values, the density contrast and growth factor in IS mimic their behavior in Λ CDM when z ≥1 . Interestingly, and contrary to intuition, certain sets of parameters lead to an increase of the clustering.
Causal Evolutions of Bulk Local Excitations from CFT
Goto, Kanato; Takayanagi, Tadashi
2016-01-01
Bulk localized excited states in an AdS spacetime can be constructed from Ishibashi states with respect to the global conformal symmetry in the dual CFT. We study boundary two point functions of primary operators in the presence of bulk localized excitations in two dimensional CFTs. From two point functions in holographic CFTs, we observe causal propagations of radiations when the mass of dual bulk scalar field is close to the BF bound. This behavior for holographic CFTs is consistent with the locality and causality in classical gravity duals. We also show that this cannot be seen in free fermion CFTs. Moreover, we find that the short distance behavior of two point functions is universal and obeys the relation which generalizes the first law of entanglement entropy.
On the conceptual distinction of general causality orientations
DEFF Research Database (Denmark)
Olesen, Martin Hammershøj
This study investigates the conceptual overlap and distinction between individual differences in the Five-Factor Model and Self-determination theory. Participants were 223 adults (age mean=43.74; 60.09% women), who originated in a Danish national probability sample. The participants completed...... electronic questionnaires of dispositional personality traits (NEO-FFI) and general causality orientations (GCOS). Proposed separate latent models and alternative shared latent models of the underlying individual differences constructs had been developed in a previous exploratory study (Olesen, Thomsen......, Schnieber & Tønnesvang, under review). The models were tested using confirmatory factor analyses. Results showed that all three causality orientations were distinct from but closely related to personality traits. Hence, integrative efforts are suggested in relation to comprehensive personality frameworks...
Rule Versus the Causality Rule in Insurance Law
DEFF Research Database (Denmark)
Lando, Henrik
When the Buyer of insurance has negligently kept silent or misrepresented a (material) fact to the Seller, one of two rules will determine the extent to which cover will consequently be reduced. The pro-rata rule lowers cover in proportion to how much the Seller would have increased the premium had...... he been correctly informed; the causality rule provides either zero cover if the omitted fact has caused the insurance event, or full cover if the event would have occurred regardless of the fact. This article explores which rule is more efficient. Using the framework proposed by Picard and Dixit......'s true type. On the other hand, when the risk of unintentional misrepresentation is small, when verification is costly, and when the Buyer is sufficiently risk averse, the Buyer conceivably may be more effectively deterred from intentional misrepresentation under the causality rule. It is argued that the...
Altered cortical causality after remifentanil administration in healthy volunteers
DEFF Research Database (Denmark)
Khodayari-Rostamabad, Ahmad; Graversen, Carina; Olesen, Soren S;
2014-01-01
Alterations in cortical causality information flow induced by remifentanil infusion in healthy volunteers was investigated in a placebo-controlled double-blind cross-over study. For each of the 21 enrolled male subjects, 2.5 minutes of resting electroencephalography (EEG) data were collected before...... features being reproducible between the two baseline recordings, several PSI features were altered by remifentanil administration in comparison to placebo. Furthermore, several of the PSI features altered by remifentanil were correlated to changes in both CRT and pain scores. The results indicate that...... remifentanil administration influence the information flow between several brain areas. Hence, the EEG causality approach offers the potential to assist in deciphering the cortical effects of remifentanil administration....
The Causal Relationship between Private and Public Investment in Zimbabwe
Muyambiri, Brian; Chiwira, Oscar; Enowbi Batuo, Michael; Chiranga, Ngonidzashe
2010-01-01
The study examines the relationship between private and public investment in Zimbabwe utilizing yearly time series data for the period 1970 to 2007. Emphasis is placed on the direction of causality and the effect of the two types of investment on each other. The paper constructs empirical models for both private and public investment, based on the flexible accelerator theory. Private investment is found to be cointegrated with public investment. A cointergration approach and VEC model are em...
Causality between Malaysian Islamic Stock Market and Macroeconomic Variables
Naseri, Marjan; Masih, Mansur
2013-01-01
This paper makes an attempt to analyse the causality between Islamic stock market and three macroeconomic variables in the case of Malaysia. Although there are numerous studies investigating relationship between conventional stock market and macroeconomic fundamentals, there is a certain gap in the literature pertaining to the relationship between Islamic indices and macroeconomic variables which are becoming an interesting area of research due to fast growing force of Islamic finance. Thus, ...
Learning strategies and causal attributions in second language learning
Sorić, Izabela; Ančić, Jadranka
2008-01-01
Although in itself “motivation to learn” is a complex multifaceted construct, according to Dornyei (2001), the picture becomes even more complex when the motivation to learn a foreign/second language is concerned. It seems that a better understanding of the dynamic relationship between learners’ use of language learning strategies and the causal attributions they make for their achievement in language learning is necessary in order to direct and improve learners’ motivation. The present study...
Identifying Causal Marketing Mix Effects Using a Regression Discontinuity Design
Wesley Hartmann; Harikesh S. Nair; Sridhar Narayanan
2011-01-01
We discuss how regression discontinuity designs arise naturally in settings where firms target marketing activity at consumers, and we illustrate how this aspect may be exploited for econometric inference of causal effects of marketing effort. Our main insight is to use commonly observed discontinuities and kinks in the heuristics by which firms target such marketing activity to consumers for nonparametric identification. Such kinks, along with continuity restrictions that are typically satis...
Export and Economic Growth in India: Causal Interpretation
Pandey, Alok Kumar
2006-01-01
The relationship between export and economic growth has been an important issue of discussion among scholars and economist throughout the world. The existence of nexus in between export and economic growth can be examined in several ways like growth rates relating to GDP and export, proportion of export to growth, several policies relating to accelerate economic growth and export etc. The effective way to explore nexus in export and economic growth would be the causal analysis between two var...
Causal Inference from Longitudinal Studies with Baseline Randomization
2008-01-01
We describe analytic approaches for study designs that, like large simple trials, can be better characterized as longitudinal studies with baseline randomization than as either a pure randomized experiment or a purely observational study. We (i) discuss the intention-to-treat effect as an effect measure for randomized studies, (ii) provide a formal definition of causal effect for longitudinal studies, (iii) describe several methods -- based on inverse probability weighting and g-estimation --...
Variational multi-fluid dynamics and causal heat conductivity
Andersson, N.; Comer, G. L.
2009-01-01
We discuss heat conductivity from the point of view of a variational multi-fluid model, treating entropy as a dynamical entity. We demonstrate that a two-fluid model with a massive fluid component and a massless entropy can reproduce a number of key results from extended irreversible thermodynamics. In particular, we show that the entropy entrainment is intimately linked to the thermal relaxation time that is required to make heat propagation in solids causal. We also discuss non-local terms ...
The Causal Impacts of Child Labor Law in Brazil
Piza, Caio; Portela Souza, André
2015-01-01
This paper investigates the causal impact of the change in Brazil’s child labor law of December 1998. The change increased the minimum legal age of entry into the labor force from 14 to 16 years. The analysis uses a difference-in-differences approach to estimate the impact of this change in the law on labor force participation rates as a whole, as well as for the formal and informal sectors ...
Causal models for performance evaluation of added-value operations
Zuñiga Alcaraz, Catya Atziry
2012-01-01
The present PhD thesis report has been elaborated as a compendium of publications, in which diverse Causal Models have been developed to assist in the decision making process using a cause-effect relationship approach inherent in the system. A brief description of the items included in the doctoral thesis. The document is organized in four different parts. First, the Chapter called “Basic Notions” introduces the basic notions and a general perspective on the systems approach. Particular in...
Semiparametric and Robust Methods for Complex Parameters in Causal Inference
Zheng, Wenjing
2014-01-01
This dissertation focuses on developing robust semiparametric methods for complex parameters that emerge at the interface of causal inference and biostatistics, with applications to epidemiological and medical research. Specifically, it address three important topics: Part I (chapter 1) presents a framework to construct and analyze group sequential covariate-adjusted response-adaptive (CARA) randomized controlled trials (RCTs) that admits the use of data-adaptive approaches in constructing th...
Impact of topology in causal dynamical triangulations quantum gravity
Ambjorn, Jan; Drogosz, Zbigniew; Gizbert-Studnicki, Jakub; Goerlich, Andrzej; Jurkiewicz, Jerzy; Nemeth, Daniel
2016-01-01
We investigate the impact of spatial topology in 3+1 dimensional causal dynamical triangulations (CDT) by performing numerical simulations with toroidal spatial topology instead of the previously used spherical topology. In the case of spherical spatial topology we observed in the so-called phase C an average spatial volume distribution n(t) which after a suitable time redefinition could be identified as the spatial volume distribution of the four-sphere. Imposing toroidal spatial topology we...