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Ivan Herman Fischer
2009-09-01
Full Text Available Este trabalho visou caracterizar quanto a critérios morfológicos e fisiológicos isolados de Streptomyces causadores de sarna comum profunda em batata; avaliar o comportamento de cultivares em relação à doença e a variação na agressividade entre os isolados da bactéria. Os isolados de Streptomyces apresentaram coloração cinza em meio extrato de levedura e malte e cadeias de esporos espiraladas, produzidas sobre um micélio aéreo. Ocorreu produção de melanina em meio de tirosina-ágar e a utilização de oito fontes de carbono recomendadas, propriedades estas que correspondem às descritas para S. scabies. Batatas-semente sadias de seis cultivares foram plantadas em substrato infestado com seis isolados de S. scabies separadamente e as plantas cultivadas em vasos e ambiente aberto. A severidade da doença foi estimada com auxílio de uma escala diagramática e avaliou-se o rendimento de tubérculos (g/planta. As cvs. Mondial e Jaete Bintje foram as mais resistentes à sarna comum com severidade média nos dois experimentos de 10,5% e 14,0%, respectivamente, seguidas por Asterix (17,4%, Ágata (21,8%, Monalisa (23,0% e Cupido (23,3%. A agressividade dos isolados variou quantitativamente, com severidade maior para o isolado M4 (34,7% e menor para o isolado M1 (6,2%. Redução da produção de tubérculos foi verificada na cv. Jaete Bintje, no primeiro experimento, e quando as cultivares foram infectadas pelos isolados A1, M2 e M3, no primeiro experimento, e pelo isolado M4, no segundo experimento.This work aimed to characterize the isolates of Streptomyces, responsible for deep common scab symptoms in potato, according to morphological and physiological criteria; to evaluate the resistance of potato cultivars to the disease and the aggressiveness of bacterium isolates. The Streptomyces isolates presented gray coloration on yeast extract and malt medium and spiral spore chains, produced on aerial hyphae. Production of melanina occurred
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Oscar Arnaldo Batista Neto e Silva
2011-12-01
Full Text Available Em monitoramentos de pragas realizados na cultura da macieira foram observadas maiores infestações da mariposa oriental (Grapholita molesta em frutos provenientes de pomares com maior incidência de lesões causadas pela sarna-da-macieira (Venturia inaequalis. Para validar esta observação, conduziu-se um experimento em laboratório com o objetivo de verificar a influência de lesões da sarna da macieira em frutos, na capacidade de infestação por G. molesta. Foram utilizados frutos (n=200 de macieira da variedade Gala com sintomas da sarna (n=100 e frutos sadios (n=100. Uma lagarta recém-eclodida foi inoculada em cada fruto e a avaliação foi realizada 10 dias após a infestação, determinando-se o número de lagartas que conseguiram penetrar nos frutos. Houve diferença significativa na capacidade de penetração das lagartas associado a presença de lesões da sarna (87% quando comparado com frutos sadios (61%. Conclui-se que frutos de maçã da cv. Gala atacados por Venturia inaequalis são mais infestados por lagartas de primeiro ínstar de Grapholita molesta.
Eficácia da ivermectina comprimido no tratamento da sarna sarcóptica em cães naturalmente infestados
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Gisele Maria de Andrade
Full Text Available RESUMO: O objetivo deste trabalho foi avaliar a eficácia da ivermectina comprimido administrada por via oral no tratamento de Sarcoptes scabiei em cães naturalmente infestados. Foram selecionados 14 cães com raspados cutâneos positivos para o ácaro S. scabiei, idade de 1-5 anos, sem raça definida, distribuídos na mesma proporção de ambos os sexos, em dois grupos experimentais, compondo 7 animais por grupo. Todos os animais foram tratados a cada 7 dias, totalizando quatro tratamentos em cada cão (Dias 0,7,14 e 21. No grupo I foi administrada a ivermectina5 comprimido na dosagem de 0,2mg/kg e no grupo controle positivo (Grupo II foi administrado um produto comercial a base de ivermectina comprimido na mesma dosagem do grupo I. Raspados cutâneos, avaliações clinicas e laboratoriais complementares dos cães foram realizadas durante o período de estudo. Clinicamente, não houve diferença significativa entre as avaliações antes e após o tratamento entre os dois grupos. Raspados negativos foram observados em ambos os grupos a partir do dia D+14, mantendo-se negativos até o final do período experimental. As lesões dermatológicas iniciais observadas no acompanhamento clínico regrediram e a partir do dia D+14 a melhora clínica era evidente em ambos os grupos. A ivermectina (Ivermectan Pet, UCBVET Saúde Animal administrada por via oral foi eficaz no tratamento de S. scabiei em cães naturalmente infestados.
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Sávio Freire Bruno
2008-08-01
Full Text Available A sarna knemidocóptica ocasionada pelo ácaro Knemidokoptes sp. pode ser considerada uma enfermidade de caráter relevante na rotina clínica aviária. Este trabalho tem como objetivo relatar a ocorrência da sarna knemidocóptica em aves de companhia atendidas no Setor de Animais Selvagens da Faculdade de Veterinária da Universidade Federal Fluminense (UFF, ressaltando as principais espécies acometidas e a eficácia do tratamento clínico estabelecido. No período entre janeiro de 2000 e junho de 2006, 374 aves foram atendidas no Setor; 25 delas eram portadoras de ectoparasitos, das quais 68% (n=17 com diagnóstico de sarna knemidocóptica. As lesões associadas à presença do Knemidokoptes sp. ocorreram principalmente na região dos pés em 14 aves (82,4%, sendo os Passeriformes (Serinus canarius os mais acometidos com 14 casos (82,4%, seguidos de três casos (17,7% em Psitaciformes (Melopsittacus undulatus. Os sinais clínicos constituíram-se de lesões hiperqueratosas e deformidade de dígitos. A confirmação do diagnóstico foi realizada por meio, da identificação microscópica do ácaro a partir de raspado cutâneo da área infestada. Em 15 pacientes portadores da sarna knemidocóptica, entre Passeriformes e Psitaciformes, administrou-se pomada composta por sulfureto de potássio 3g 100g-1 e carbonato de potássio 3g 100g-1 associados uma vez ao dia, em dias alternados, por quatorze dias. Apenas dois pacientes (11,8% foram tratados com aplicação tópica de solução à base de benzoato de benzila 25%, na mesma freqüência e duração do tratamento anterior. Foi intercalado o uso de óleo mineral puro 100%, aplicado topicamente duas vezes ao dia, em ambos os tratamentos. Nos casos mais graves (três pacientes, associou-se ao tratamento 0,06ml de ivermectina 1% pour on em dose única. Os pacientes submetidos a esses tratamentos obtiveram em sua totalidade a cura clínica.Knemidocoptic mange caused by Knemidokoptes sp. can be
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.
JOHN SEARLE SOBRE A IDENTIDADE E A EFICÁCIA CAUSAL DA CONSCIÊNCIA
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Tárik de Athayde Prata
2010-01-01
Full Text Available O texto discute os problemas em que se envolve o naturalismo biológico deJohn Searle ao defender (a a eficácia causal da consciência, (b a identidade dascapacidades causais da consciência e das capacidades causais dos processos cerebrais e(c a irredutibilidade ontológica da consciência. Essas três teses parecem implicar que aconsciência é e não é idêntica à atividade cerebral. Uma solução poderia ser encontradase o autor discutisse mais cuidadosamente a noção de identidade.
Sarna Devī: feste di primavera, folklore e sostenibilità nelle tradizioni del Jharkhand
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Stefano Beggiora
2014-12-01
Full Text Available In the Chota Nagpur plateau, in India, the worship of Sarna Devi (sarnaism seems today to unite in a sort of brotherhood many indigenous ethnic groups of the state of Jharkhand. Guardian of the boundaries of villages, Sarna is the goddess of the sacred grove and preside over the good harvest. The present work consists in an ethnographical analysis of the major spring festivals - and related rituals - widespread among the most populous indigenous peoples (ādivāsī of Jharkhand, with particular reference to Santals and Oraons. By reconstructing a comprehensive overview of the cultural relations among the ethnic groups, I emphasize how religious prescriptions and local shamanism share a common message of sustainability and equilibrium between man and the nature. The essay includes translations of verses, sacred liturgies, songs, employed in the celebration of the goddess and her environment.
El daño y el nexo causal en la perdida de oportunidad
Herrera Montañez, Diego Alejandro
2016-01-01
El presente escrito se ocupa de estudiar el nexo de causalidad como elemento estructural de la responsabilidad cuando éste es difuso. Para ello, se pretende abordar la pérdida de la oportunidad como una teoría especial de causalidad que tiene lugar cuando el nexo causal no resulta claro, lo cual contradice la tesis preponderante de la doctrina y la jurisprudencia tradicional según la cual, la pérdida de la oportunidad es un criterio autónomo del daño. En su contenido se realiza una explic...
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Maria Isabel de Souza
2009-12-01
Full Text Available
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Diorvania Ribeiro Giaretta
2010-04-01
Full Text Available Several diseases have affected apple production, among them there is Glomerella leaf spot (GLS caused by Colletotrichum spp. The first report of this disease in apple was in plants nearby citrus orchards in São Paulo State, Brazil. The origin of this disease is still not clear, and studies based on the molecular phylogeny could relate the organisms evolutionarily and characterize possible mechanisms of divergent evolution. The amplification of 5.8S-ITS (Internal Transcribed Spacer of rDNA of 51 pathogenic Colletotrichum spp. isolates from apples, pineapple guava and citrus produced one fragment of approximately 600 bases pairs (bp for all the isolates analyzed. The amplified fragments were cleaved with restriction enzymes, and fragments from 90 to 500bp were obtained. The sequencing of this region allowed the generation of a phylogenetic tree, regardless of their hosts, and 5 isolated groups were obtained. From the "in silico" comparison, it was possible to verify a variation from 93 to 100% of similarity between the sequences studied and the Genbank data base. The causal agent of GLS is nearly related (clustered to isolates of pineapple guava and to the citrus isolates used as control.A produção de maçã vem sendo comprometida pela ocorrência de muitas doenças, entre as quais se destaca a Mancha Foliar de Glomerella (MFG, causada por Colletotrichum spp. O primeiro relato dessa doença em maçã foi registrado em plantas próximas a pomares de citrus no Estado de São Paulo, Brasil. A origem da MFG ainda não está bem clara, e estudos baseados na filogenia permitirão relacionar o organismo evolutivamente, possibilitando caracterizar possíveis mecanismos divergentes de evolução. A amplificação da região 5.8S-ITS (espaçador interno transcrito do rDNA de 51 isolados de Colletotrichum patogênicos em de maçã, goiabeira serrana e citrus produziu um fragmento de aproximadamente 600 pares de bases (pb para todos os isolados analisados
Cavero, Poholl Adan Sagratzki
2011-01-01
O principal problema fitossanitário da cultura da bananeira no Brasil e também em outros países é a sigatoka-negra, causada pelo fungo Micosphaerella fijiensis Morelet, que pode ocasionar perdas de até 100% da produção. A medida mundialmente mais utilizada no controle deste problema em bananais comerciais têm sido pulverizações com fungicidas. Na Amazônia, o uso de fungicidas para o controle da sigatoka-negra torna-se econômica e ecologicamente inviável, face aos custos e aos impactos ambient...
Ellis, George FR; Pabjan, Tadeusz
2013-01-01
Written by philosophers, cosmologists, and physicists, this collection of essays deals with causality, which is a core issue for both science and philosophy. Readers will learn about different types of causality in complex systems and about new perspectives on this issue based on physical and cosmological considerations. In addition, the book includes essays pertaining to the problem of causality in ancient Greek philosophy, and to the problem of God's relation to the causal structures of nature viewed in the light of contemporary physics and cosmology.
Causal and causally separable processes
Oreshkov, Ognyan; Giarmatzi, Christina
2016-09-01
The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B, either A is in the causal past of B, B is in the causal past of A, or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B, an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and
Causal and causally separable processes
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Oreshkov, Ognyan; Giarmatzi, Christina
2016-01-01
The idea that events are equipped with a partial causal order is central to our understanding of physics in the tested regimes: given two pointlike events A and B , either A is in the causal past of B , B is in the causal past of A , or A and B are space-like separated. Operationally, the meaning of these order relations corresponds to constraints on the possible correlations between experiments performed in the vicinities of the respective events: if A is in the causal past of B , an experimenter at A could signal to an experimenter at B but not the other way around, while if A and B are space-like separated, no signaling is possible in either direction. In the context of a concrete physical theory, the correlations compatible with a given causal configuration may obey further constraints. For instance, space-like correlations in quantum mechanics arise from local measurements on joint quantum states, while time-like correlations are established via quantum channels. Similarly to other variables, however, the causal order of a set of events could be random, and little is understood about the constraints that causality implies in this case. A main difficulty concerns the fact that the order of events can now generally depend on the operations performed at the locations of these events, since, for instance, an operation at A could influence the order in which B and C occur in A ’s future. So far, no formal theory of causality compatible with such dynamical causal order has been developed. Apart from being of fundamental interest in the context of inferring causal relations, such a theory is imperative for understanding recent suggestions that the causal order of events in quantum mechanics can be indefinite. Here, we develop such a theory in the general multipartite case. Starting from a background-independent definition of causality, we derive an iteratively formulated canonical decomposition of multipartite causal correlations. For a fixed number of settings and
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I.M.R.S. Serra
2011-03-01
Full Text Available O presente trabalho teve como objetivo estudar a diversidade fenotípica e patogênica de 40 isolados de Colletotrichum obtidos de mangueira no Nordeste do Brasil e identificar diferentes espécies desse fitopatógeno, agente causal de antracnose, através da análise da seqüência da região ITS do rDNA. Quanto à caracterização morfológica e cultural, as colônias dos isolados apresentaram diversidade em relação à cor e aspecto, sendo mais comum à cor branco-cinza, característica de Colletotrichum gloeosporioides. Não foram observadas variações expressivas na morfologia dos 40 isolados. Os conídios apresentaram-se, predominantemente, hialinos e unicelulares, com formato variando de bastonete para cilíndrico. Todos os isolados produziram apressórios variados em formato e quantidade e apenas 10 isolados apresentaram setas. Para efeito do crescimento micelial e taxa de crescimento foi possível classificar os isolados em sete grupos. Vinte e dois isolados exibiram taxa de crescimento >10mm/dia, considerada típica da espécie C. gloeosporioides. Os isolados foram patogênicos em folhas destacadas de mangueira, induzindo sintomas de antracnose, na forma de manchas escuras levemente deprimidas, e apresentando variações quanto à agressividade. Na identificação específica, baseada na análise da seqüência ITS do DNA ribossomal, 36 isolados amplificaram com o oligonucleotídeos CgInt, específico para C. gloeosporioides e o ITS4, Os isolados CM1, CM4, CM5 e CM10, não amplificaram produtos para nenhum dos oligonucleotídeos específicos, sendo identificados como Colletotrichum spp. Os resultados desse trabalho demonstraram que isolados de Colletotrichum, obtidos de mangueira, apresentam ampla variabilidade morfofisiológica e patogênica. E que, possivelmente, existe mais de uma espécie de Colletotrichum que causa antracnose em mangueira no Nordeste do Brasil.
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Elaine Spindola Mantovani
2006-06-01
Full Text Available Falsa estria vermelha (FEV, uma nova doença causada por Xanthomonas sp., é diferente diferente de todas as outras doenças já descritas em cana-de-açúcar. Ela está distribuída por toda as principais regiões canavieiras do centro-sul do Brasil, mas ainda não foi detectada no norte e nordeste do Brasil nem em qualquer outro país. O presente estudo determinou a gama de culturas e plantas daninhas hospedeiras da bactéria dentre espécies pertencentes às gramíneas, através de inoculação por injeção e pulverização de suspensão bacteriana. Além da cana-de-açúcar, entre as 31 diferentes espécies estudadas, apenas sorgo, milho e aveia apresentaram sintomas, 15 dias após a inoculação. Em sorgo, no ponto de inoculação, apareceram estrias avermelhadas coalescentes. As folhas apresentaram típicas estrias vermelhas finas (1 mm, longas e paralelas às nervuras, com presença de exsudato bacteriano. Até mesmo as inflorescências apresentaram pontuações avermelhadas. Plantas de milho inoculadas com seringa apresentaram sintomas de anasarca e descoloração de tecidos ao redor do ponto de inoculação e estrias cloróticas (2-3 mm no limbo foliar; porém, sem exsudato de bactéria. Apenas folhas de cevada apresentaram sintomas quando inoculadas por pulverização. As lesões iniciais eram estrias e manchas de cor palha, evoluindo para uma necrose total das folhas, causando a morte das plantas. A partir de folhas sintomáticas de cana-de-açúcar, sorgo, milho e aveia, realizaram-se re-isolamentos, obtendo-se culturas puras de Xanthomonas sp. cuja identidade foi comprovada através de testes sorológicos e por Rep-PCR. Diante desses resultados, surge a necessidade de realização de inspeções e campos de cultivo de sorgo, milho e aveia para verificar a presença da bactéria da FEV e determinar se o patógeno pode infectar essas culturas naturalmente.False Red Stripe (FRS, a new disease caused by Xanthomonas sp., is different
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Luisa Moraes Abreu Ferreira
2011-06-01
Full Text Available Este artigo discute uma pesquisa empírica apresentada em 2009 como Trabalho de Conclusão de Curso na Direito GV sobre a definição da causalidade para responsabilização criminal nos tribunais de justiça. Foram analisadas 84 apelações criminais julgadas entre 2007 e 2008 e extraídos resultados quantitativos e qualitativos relacionados aos dados do processo, ao resultado da decisão e à argumentação. A análise desses resultados levou a cinco principais constatações: (1 a discussão sobre nexo causal ocorre quase exclusivamente em casos de crimes culposos; (2 muitas vezes, apesar de discutido pelas partes, a existência de nexo causal não é afirmada no acórdão; (3 o nexo causal é frequentemente afirmado com pouca fundamentação e, em geral, com menos argumentos do que a afirmação de culpa; (4 a teoria mais utilizada pelos tribunais é a da equivalência das condições; e (5 o nexo causal é frequentemente afirmado como decorrência da culpa.This paper reports empirical research presented in 2009 as final dissertation for graduation as bachelor of laws at direito gv about the definition of causation to attribute criminal liability in the brazilian state supreme Courts. A total of 84 criminal appeals, ruled between 2007 and 2008, were analyzed and quantitative and qualitative results related to procedure data, results of the decision and reasoning were extracted. Analysis of these results led to five major findings: (1 discussion of causation occurs almost exclusively in cases of willful crimes, (2 often, though discussed by the parties, a causal relationship is not asserted in the decision, (3 causal relationship is often stated with little reasoning and, generally, with fewer arguments than the statement of negligence, (a the causal theory most used by the courts is that cause is every necessary condition for the event, and (5j causal relationship is often asserted as a result of negligence.
Morabia, Alfredo
2005-01-01
Epidemiological methods, which combine population thinking and group comparisons, can primarily identify causes of disease in populations. There is therefore a tension between our intuitive notion of a cause, which we want to be deterministic and invariant at the individual level, and the epidemiological notion of causes, which are invariant only at the population level. Epidemiologists have given heretofore a pragmatic solution to this tension. Causal inference in epidemiology consists in checking the logical coherence of a causality statement and determining whether what has been found grossly contradicts what we think we already know: how strong is the association? Is there a dose-response relationship? Does the cause precede the effect? Is the effect biologically plausible? Etc. This approach to causal inference can be traced back to the English philosophers David Hume and John Stuart Mill. On the other hand, the mode of establishing causality, devised by Jakob Henle and Robert Koch, which has been fruitful in bacteriology, requires that in every instance the effect invariably follows the cause (e.g., inoculation of Koch bacillus and tuberculosis). This is incompatible with epidemiological causality which has to deal with probabilistic effects (e.g., smoking and lung cancer), and is therefore invariant only for the population.
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Denise Oliveira e Silva
2008-08-01
Full Text Available OBJETIVO: Trata-se da descrição de resultados baseados na elaboração de um modelo de determinação causal de forma participativa e abrangente, realizada em seis comunidades quilombolas no município de Santarém, no Estado do Pará, sobre a rede de causalidade da insegurança alimentar e nutricional com a abertura da Rodovia BR-163. MÉTODOS: O processo investigativo utilizou métodos de abordagem sócio-antropológica tendo como base o desenvolvimento de um modelo de causalidade construído por meio da realização de grupos focais com representantes da comunidade. RESULTADOS: Os resultados do estudo demonstraram que a utilização de abordagens participativas estimula a auto-estima da comunidade e o empoderamento sobre os fatores que determinam seus problemas. O modelo causal construído revela que a insegurança alimentar e nutricional, para as comunidades, estabelece que fatores históricos relacionados à posse da terra e ao seu uso atual baseado em práticas predatórias, são os aspectos fundamentais na compreensão da rede de determinação causal da insegurança alimentar e nutricional. CONCLUSÃO: O racismo e suas nuances sociais têm contribuído para a invisibilidade social dessas comunidades nas políticas públicas brasileiras. As comunidades quilombolas se consideram em insegurança alimentar e nutricional e indicam que a abertura da Rodovia BR-163 pode ser uma ameaça ao etno-desenvolvimento sustentável na região. E referem que o desenvolvimento econômico esperado com a abertura desta rodovia, se não for realizado com base na participação da comunidade, pode aumentar a fome, a miséria e o racismo.OBJECTIVE: This work describes results based on the participative and encompassing development of a model of causal determination done in six quilombola communities of Santarém, Pará State, regarding the causality of food and nutrition insecurity with the construction of the BR-163 highway. METHODS: The research process
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Paulo Roberto Gagliardi
2009-07-01
Full Text Available O raquitismo-da-soqueira (RSD, causado pela bactéria Leifsonia xyli subsp. xyli, é uma das mais importantes doenças da cana-de-açúcar nas regiões produtoras do mundo. O presente trabalho teve como objetivo avaliar o grau de resistência de 10 variedades comerciais RB de cana-de-açúcar mais a variedade CB 49-260, a qual foi incluída como padrão suscetível. O trabalho visou avaliar os danos amostrados em campo pelo peso das parcelas em função da relação entre a produtividade de parcelas inoculadas e não inoculadas artificialmente com a bactéria. Os resultados mostraram que as variedades RB 72 454, RB 83 5486, RB 86 7515, RB 92 5211, RB 92 5268, RB 92 5345, RB 92 8064 e a variedade padrão CB 49-260 comportaram-se como variedades suscetíveis. A variedade RB 85 5156 comportou-se como de resistência intermediária e apenas as variedades RB 85 5453 e RB 85 5536 comportaram-se como tolerantes.Ratoon stunting disease (RSD caused by bacteria Leifsonia xyli subsp. xyli is one of the most economically important disease of sugarcane worldwide. The present survey had objective to evaluate the resistance of 10 RB commercial cultivars of sugarcane including CB 49-260 as a susceptible standard. The study evaluated the correlating the damages presented for overhauls productivity of inoculate and non inoculate parcels with the bacteria. The results showed that varieties RB 72 454, RB 83 5486, RB 86 7515, RB 92 8064, RB 92 5211, RB 92 5345 and RB 92 5268 were susceptible. RB 85 5156 had a intermediary resistance and varieties RB 85 5453 and RB 85 5536 both showed tolerant behavior.
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Taís Ferreira Almeida
2009-09-01
Full Text Available A flor preta do morangueiro, causada por Colletotrichum acutatum, acarreta sérios problemas à cultura. Com o objetivo de verificar a utilização de extratos vegetais no controle da doença, testes "in vitro" foram realizados com 11 extratos vegetais hidroalcoólicos produzidos de plantas utilizadas na medicina popular. Os extratos foram preparados a partir de diferentes partes da planta, de acordo com a espécie, utilizando água e álcool no processo de extração por maceração. Foi verificada a influência dos extratos no crescimento micelial, esporulação e germinaç��o de esporos de C. acutatum, e também no controle do patógeno em folhas e frutos destacados. De acordo com a metodologia utilizada, os extratos vegetais que apresentaram maior eficiência foram os de folha e ramos de Ruta graveolens, Artemisia absinthium e bulbos de Allium sativum, indicando ter essas plantas potencial fungitóxico para o controle de C. acutatum.The black spot of strawberry plants caused by Colletotrichum acutatum, causes serious problems to the culture. To control the disease and minimize the use of fungicides, in vitro assays were accomplished with 11 different plant hydroalcoholic extract from plants species used in the popular medicine. The extracts were produced from plant parts (according to the species using water and alcohol in the extraction process for infusion. The influence of the extracts was verified in the micelial growth, esporulation and germination of the pathogen, besides a test with leaves and outstanding fruits. In agreement with the methodology used in this study, the extracts that showed the highest efficiency were the ones from Ruta graveolens, Artemisia absinthium and Allium sativum, which indicate such plants as potential fungitoxics for the control of C. acutatum.
Causally nonseparable processes admitting a causal model
International Nuclear Information System (INIS)
Feix, Adrien; Araújo, Mateus; Brukner, Caslav
2016-01-01
A recent framework of quantum theory with no global causal order predicts the existence of ‘causally nonseparable’ processes. Some of these processes produce correlations incompatible with any causal order (they violate so-called ‘causal inequalities’ analogous to Bell inequalities ) while others do not (they admit a ‘causal model’ analogous to a local model ). Here we show for the first time that bipartite causally nonseparable processes with a causal model exist, and give evidence that they have no clear physical interpretation. We also provide an algorithm to generate processes of this kind and show that they have nonzero measure in the set of all processes. We demonstrate the existence of processes which stop violating causal inequalities but are still causally nonseparable when mixed with a certain amount of ‘white noise’. This is reminiscent of the behavior of Werner states in the context of entanglement and nonlocality. Finally, we provide numerical evidence for the existence of causally nonseparable processes which have a causal model even when extended with an entangled state shared among the parties. (paper)
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Katia Cristina Kupper
2009-12-01
Full Text Available A queda prematura dos frutos cítricos (QPFC, causada por Colletotrichum acutatum, dados os grandes prejuízos que têm causado aos produtores, constitui-se numa doença de grande importância econômica. O controle da doença é feito predominantemente mediante uso de fungicidas, que eleva o custo de produção e afeta negativamente o meio ambiente. Diante disso, este trabalho teve por objetivo buscar um método alternativo de controle da QPFC, mediante o uso de agentes de biocontrole ou de biofertilizantes. Diferentes concentrações de biofertilizantes (originários de duas fontes distintas e denominados de Bio1 e Bio 2; três isolados de Bacillus subtilis (ACB-69; 72 e 77 e três isolados de Trichoderma spp. (ACB-14; 37 e 39 foram testados, isoladamente ou em combinação, sob condições de laboratório, quanto à capacidade inibitória da germinação de conídios de C. acutatum. Estudaram-se, ainda, a produção de metabólitos termoestáveis por B. subtilis e o efeito sobre a germinação do patógeno. Quinze isolados de B. subtilis foram testados quanto à capacidade de prevenir a infecção por C. acutatum em flores destacadas de lima- ácida 'Tahiti' e, no campo, foram instalados dois experimentos, visando a testar ACBs e biofertilizantes no controle da doença. Verificou-se que o isolado ACB-72 (B. subtilis e ACB-37 (T. pseudokoningii foram os que mais inibiram a germinação do patógeno. Quanto à produção de metabólitos termoestáveis, ACB-69 e 77 foram os mais eficientes em produzir substâncias antifúngicas, e em quantidades suficientes para inibirem a germinação do patógeno. A mistura dos quatro isolados de Bacillus (ACBs: 69; 72; 77 e AP3 foi o que apresentou maior porcentagem de inibição (73%. Os biofertilizantes (Bio1 e Bio2, em concentrações acima de 10% e, quando em associação com isolados de Trichoderma spp., promoveram maiores inibições na germinação de C. acutatum. Em testes com flores destacadas
Lorentzon, Karin; Gustafsson, Victor
2017-01-01
Denna studie handlar om hur ett sponsrat blogginlägg av en influencer inkodas och hur läsarna i kommentarerna avkodar meddelandet och reagerar på inlägget. Studiens syfte är att öka förståelsen för hur läsare avkodar sponsrade blogginlägg. Vi antog innan genomförandet att fler skulle avkoda meddelandena på ett sätt som skulle vara mer kritiskt gentemot samarbetet, därför har det gjorts en teoriprövande studie av Stuart Halls teori om inkodning och avkodning. För uppnå vårt syfte har vi använt...
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.
Jones, Robert
2010-03-01
There are a wide range of views on causality. To some (e.g. Karl Popper) causality is superfluous. Bertrand Russell said ``In advanced science the word cause never occurs. Causality is a relic of a bygone age.'' At the other extreme Rafael Sorkin and L. Bombelli suggest that space and time do not exist but are only an approximation to a reality that is simply a discrete ordered set, a ``causal set.'' For them causality IS reality. Others, like Judea Pearl and Nancy Cartwright are seaking to build a complex fundamental theory of causality (Causality, Cambridge Univ. Press, 2000) Or perhaps a theory of causality is simply the theory of functions. This is more or less my take on causality.
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Cristina Puente Águeda
2011-10-01
Full Text Available Causality is a fundamental notion in every field of science. Since the times of Aristotle, causal relationships have been a matter of study as a way to generate knowledge and provide for explanations. In this paper I review the notion of causality through different scientific areas such as physics, biology, engineering, etc. In the scientific area, causality is usually seen as a precise relation: the same cause provokes always the same effect. But in the everyday world, the links between cause and effect are frequently imprecise or imperfect in nature. Fuzzy logic offers an adequate framework for dealing with imperfect causality, so a few notions of fuzzy causality are introduced.
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Ricardo Porto Tedesco
2004-12-01
Full Text Available OBJETIVO: conhecer as expectativas de primigestas com relação à via de parto, bem como os motivos de sua escolha, procurando melhorar a qualidade do relacionamento médico-paciente. MÉTODOS: foi realizado estudo do tipo qualitativo por meio da análise do sujeito coletivo, incluindo primigestas atendidas de setembro a novembro de 2003 nos pronto-socorros dos serviços da Faculdade de Medicina de Jundiaí. Foi aplicado questionário especialmente elaborado para responder aos objetivos propostos pela pesquisa o questionário é baseado nas dúvidas apresentadas por pacientes que freqüentaram o serviço meses antes da elaboração do projeto. O consentimento livre e esclarecido, assinado pela gestante e por um dos pesquisadores responsáveis. Foi obtido para fins de padronização da amostra a seleção das pacientes seguiu critérios de inclusão: idade maior que 16 anos, primigestas, que estivessem recebendo assistência pré-natal e consentimento pós-informado lido e esclarecido. Foram considerados critérios de exclusão pacientes mentalmente incapacitadas e gestantes de alto risco com doenças que pudessem interferir na escolha da paciente. RESULTADOS: a população estudada teve como perfil mais prevalente mulheres com mais de 21 anos, brancas, casadas, com segundo grau completo e que estavam no terceiro trimestre da gestação. A via de parto de preferência da maioria das mulheres (90% foi o parto vaginal normal, sendo que as principais justificativas foram: a praticidade para sua realização (94% e o medo do sofrimento e dor no pós-parto causados pela cesárea. Encontramos relação entre a preferência pelo parto vaginal com mulheres de maior idade, casadas, não havendo diferença significativa entre as raças. CONCLUSÃO: estes resultados nos mostram enorme contraste entre a preferência das mulheres e os altos índices de cesárea no Brasil. Concluímos que deve haver falha de informação, falta de diálogo entre os
Rehder, Bob
2017-01-01
This article assesses how people reason with categories whose features are related in causal cycles. Whereas models based on causal graphical models (CGMs) have enjoyed success modeling category-based judgments as well as a number of other cognitive phenomena, CGMs are only able to represent causal structures that are acyclic. A number of new…
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Ribeiro Luiz Fernando
1999-01-01
Full Text Available Extratos aquosos foram obtidos a partir de bulbilhos de alho, folhas de hortelã e mamona e frutos de pimenta. Após a incorporação destes extratos em BDA, obtendo-se concentrações de 100, 200, 500, 1000, 5000 e 10000 ppm, foi avaliado o crescimento e a produção de conídios de um isolado de Colletotrichum gloeosporioides, agente de podridão em frutos de mamoeiro. Os resultados demonstraram o efeito inibitório dos diferentes extratos a partir da concentração de 200 ppm. O extrato de alho inibiu o crescimento micelial, em porcentagens variáveis de 5,3 a 67,6%, porém não atuou de modo expressivo sobre a produção de conídios. Em contraposição, os extratos de hortelã, mamona e pimenta promoveram inibição menos acentuada do crescimento de micélio, porém reduziram drasticamente a produção de conídios em níveis variáveis de 41 a 84%, de acordo com as concentrações crescentes dos mesmos. As propriedades fungitóxicas detectadas nos extratos utilizados no ensaio evidenciaram o uso potencial dos mesmos como alternativa aos métodos físicos e químicos convencionalmente usados para o controle da doença.
Causal imprinting in causal structure learning.
Taylor, Eric G; Ahn, Woo-Kyoung
2012-11-01
Suppose one observes a correlation between two events, B and C, and infers that B causes C. Later one discovers that event A explains away the correlation between B and C. Normatively, one should now dismiss or weaken the belief that B causes C. Nonetheless, participants in the current study who observed a positive contingency between B and C followed by evidence that B and C were independent given A, persisted in believing that B causes C. The authors term this difficulty in revising initially learned causal structures "causal imprinting." Throughout four experiments, causal imprinting was obtained using multiple dependent measures and control conditions. A Bayesian analysis showed that causal imprinting may be normative under some conditions, but causal imprinting also occurred in the current study when it was clearly non-normative. It is suggested that causal imprinting occurs due to the influence of prior knowledge on how reasoners interpret later evidence. Consistent with this view, when participants first viewed the evidence showing that B and C are independent given A, later evidence with only B and C did not lead to the belief that B causes C. Copyright © 2012 Elsevier Inc. All rights reserved.
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Elizabeth Gilchrist
2009-06-01
Full Text Available El protozoario Spongospora subterranea f. sp. subterranea es un parásito obligado que replica en raíces y tubérculos de papa causando la sarna polvosa. Esta enfermedad se ha difundido a escala global debido al comercio de tubérculos-semilla infectados y a la ausencia de tratamientos efectivos. En este trabajo se investigó la influencia sobre la sarna polvosa de cuatro aislamientos de Trichoderma asperellum en tres tipos de suelo: Andisol, Entisol e Inceptisol. Tubérculos de Solanum tuberosum variedad Diacol Capiro fueron plantados en parcelas infectadas con 1942 ± 226 quistosoros por gramo de suelo. No se observaron diferencias entre las plantas tratadas y no tratadas con T. asperellum. La superficie de raíz ocupada por agallas fue en promedio 2,2%, sin encontrarse diferencias significativas (PThe protozoan Spongospora subterranea f. sp. subterranea is an obligate parasite that replicates in roots and tubers of potato causing the powdery scab. This disease has disseminated on a global scale, because the commercial traffic of infected tubers used as seed and the absence of effective treatments. The present work investigated the effects of four isolates of Trichoderma asperellum in three soil types: Andisol, Entisol and Inceptisol. The soils were infected with 1942 ± 226 cystosori per gram of soil. It was used Solanum tuberosum variety Diacol Capiro. No differences were observed between treated and non treated plants with T. asperellum. The root surface affected by galls was an average of 2.2 %, and no significant differences (p<0.05 were observed among the soils. The reduction of plant growth was of 41, 32 and 28 % for the Andisol, Entisol and Inceptisol, respectively. The reduction in tubers production was of 40, 28 and 0,1% for the Andisol, Entisol and Inceptisol, respectively. Similar percent of root surface covered with galls resulted in production reduction of 40%, but also of 0,1%, indicating the necessity of other methods to
Repeated causal decision making.
Hagmayer, York; Meder, Björn
2013-01-01
Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in such situations and how they use their knowledge to adapt to changes in the decision context. Our studies show that decision makers' behavior is strongly contingent on their causal beliefs and that people exploit their causal knowledge to assess the consequences of changes in the decision problem. A high consistency between hypotheses about causal structure, causally expected values, and actual choices was observed. The experiments show that (a) existing causal hypotheses guide the interpretation of decision feedback, (b) consequences of decisions are used to revise existing causal beliefs, and (c) decision makers use the experienced feedback to induce a causal model of the choice situation even when they have no initial causal hypotheses, which (d) enables them to adapt their choices to changes of the decision problem. (PsycINFO Database Record (c) 2013 APA, all rights reserved).
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Adalmir Marquetti
2009-12-01
Full Text Available O objetivo deste trabalho é testar a hipótese clássico-marxiana de ligação causal entre a taxa de lucro e a taxa de acumulação de capital para um conjunto de 20 países da OCDE. A metodologia utilizada baseia-se no procedimento proposto por Toda e Yamamoto (1995 para testar a hipótese de não causalidade de Granger. A especificação de teste empregada, derivada a partir da equação de Cambridge, envolve três variáveis: a taxa de lucro, a taxa de acumulação e a taxa de investimento. A consideração da variável investimento permite comparações entre as tradições clássico-marxiana e pós-keynesianas. Os resultados para a Austrália, a Dinamarca, os eua, a Finlândia e a Irlanda são consistentes com a concepção clássico-marxiana. Por outro lado, os resultados para o Canadá, a Coreia do Sul, a Grécia e a Suécia são parcialmente consistentes com a tradição pós-keynesiana.The purpose of this paper is to test the classical-Marxian hypothesis of causal linkages between profit rate and the accumulation of capital for a dataset of 20 OECD countries. The procedure proposed by Toda and Yamamoto (1995 to test for the Granger non-causality hypotheses is employed in the statistical procedure. The test specification, derived from the Cambridge equation, involve three variables: profit rate, accumulation of capital and investment rate. The consideration of the investment rate allows a comparison between the classical-Marxian and the post-Keynesian traditions. For the cases of Australia, Denmark, usa, Finland and Ireland, the results provide empirical support for the classical-Marxian conception. On the other hand, in the cases of Canada, South Korea, Greece and Sweden, the results support the post-Keynesian tradition.
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Juliana Paiva Carnaúba
2006-04-01
Full Text Available O mamoeiro (Carica papaya é uma das mais importantes fruteiras tropicais, e seus frutos contribuem com uma produção de 1,65 milhão de toneladas por ano para o Brasil. Um isolado de Phytophthora sp. obtido de frutos de mamoeiro da cultivar Havaí, em Alagoas, foi caracterizado morfologicamente e sua patogenicidade foi confirmada em frutos e mudas deste hospedeiro. Em meio suco V-8, os esporangióforos apresentaram-se delgados, simples ou pouco ramificados, enquanto os esporângios se apresentaram ovóides a elipsóides, proeminentemente papilados e um pedicelo curto na porção basal, medindo em média 37,68 x 27,52 mm. Através das características apresentadas pelo isolado e os sintomas induzidos, o agente causal foi identificado como Phytophthora palmivora. Apesar de essa doença já ocorrer em outros estados, como Bahia, Espírito Santo, São Paulo, Pernambuco e Pará, este é o primeiro relato de Phytophthora palmivora em mamoeiro no Estado de Alagoas.The papaya (Carica papaya is one of the most important tropical fruit crops and its fruit contribute with a production of 1.65 millions tons/year in Brazil. An isolated of Phytophthora sp. gotten from papaya fruits cv. Hawaii, in the state of Alagoas, was characterized morphologically and its pathogenicity to this fruits and seedling was confirmed. In a V-8 medium, the sporangiophores presented to be slim, simple or little ramified, while the sporangia presented ovoid to ellipsoid, prominently papillae and one short pedicel in the basal portion, measuring in average 37,68 x 27,52 (m. Through the characteristics presented by the isolated and the induced symptoms, the causal agent was identified as Phytophthora palmivora. Despite of this disease already occurring in other states like in Bahia, Espirito Santo, São Paulo, Pernambuco and Pará, this is the first report of Phytophthora palmivora on papaya in the state of Alagoas, Brazil.
Repeated Causal Decision Making
Hagmayer, York; Meder, Bjorn
2013-01-01
Many of our decisions refer to actions that have a causal impact on the external environment. Such actions may not only allow for the mere learning of expected values or utilities but also for acquiring knowledge about the causal structure of our world. We used a repeated decision-making paradigm to examine what kind of knowledge people acquire in…
International Nuclear Information System (INIS)
Novello, M.; Salim, J.M.; Torres, J.; Oliveira, H.P. de
1989-01-01
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) [pt
Causal Analysis After Haavelmo
Heckman, James; Pinto, Rodrigo
2014-01-01
Haavelmo's seminal 1943 and 1944 papers are the first rigorous treatment of causality. In them, he distinguished the definition of causal parameters from their identification. He showed that causal parameters are defined using hypothetical models that assign variation to some of the inputs determining outcomes while holding all other inputs fixed. He thus formalized and made operational Marshall's (1890) ceteris paribus analysis. We embed Haavelmo's framework into the recursive framework of Directed Acyclic Graphs (DAGs) used in one influential recent approach to causality (Pearl, 2000) and in the related literature on Bayesian nets (Lauritzen, 1996). We compare the simplicity of an analysis of causality based on Haavelmo's methodology with the complex and nonintuitive approach used in the causal literature of DAGs—the “do-calculus” of Pearl (2009). We discuss the severe limitations of DAGs and in particular of the do-calculus of Pearl in securing identification of economic models. We extend our framework to consider models for simultaneous causality, a central contribution of Haavelmo. In general cases, DAGs cannot be used to analyze models for simultaneous causality, but Haavelmo's approach naturally generalizes to cover them. PMID:25729123
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…
Causality in Europeanization Research
DEFF Research Database (Denmark)
Lynggaard, Kennet
2012-01-01
to develop discursive institutional analytical frameworks and something that comes close to the formulation of hypothesis on the effects of European Union (EU) policies and institutions on domestic change. Even if these efforts so far do not necessarily amount to substantive theories or claims of causality......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......, 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 study...
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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.
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Ämin Baumeler
2017-07-01
Full Text Available Computation models such as circuits describe sequences of computation steps that are carried out one after the other. In other words, algorithm design is traditionally subject to the restriction imposed by a fixed causal order. We address a novel computing paradigm beyond quantum computing, replacing this assumption by mere logical consistency: We study non-causal circuits, where a fixed time structure within a gate is locally assumed whilst the global causal structure between the gates is dropped. We present examples of logically consistent non-causal circuits outperforming all causal ones; they imply that suppressing loops entirely is more restrictive than just avoiding the contradictions they can give rise to. That fact is already known for correlations as well as for communication, and we here extend it to computation.
Causality and headache triggers
Turner, Dana P.; Smitherman, Todd A.; Martin, Vincent T.; Penzien, Donald B.; Houle, Timothy T.
2013-01-01
Objective The objective of this study was to explore the conditions necessary to assign causal status to headache triggers. Background The term “headache trigger” is commonly used to label any stimulus that is assumed to cause headaches. However, the assumptions required for determining if a given stimulus in fact has a causal-type relationship in eliciting headaches have not been explicated. Methods A synthesis and application of Rubin’s Causal Model is applied to the context of headache causes. From this application the conditions necessary to infer that one event (trigger) causes another (headache) are outlined using basic assumptions and examples from relevant literature. Results Although many conditions must be satisfied for a causal attribution, three basic assumptions are identified for determining causality in headache triggers: 1) constancy of the sufferer; 2) constancy of the trigger effect; and 3) constancy of the trigger presentation. A valid evaluation of a potential trigger’s effect can only be undertaken once these three basic assumptions are satisfied during formal or informal studies of headache triggers. Conclusions Evaluating these assumptions is extremely difficult or infeasible in clinical practice, and satisfying them during natural experimentation is unlikely. Researchers, practitioners, and headache sufferers are encouraged to avoid natural experimentation to determine the causal effects of headache triggers. Instead, formal experimental designs or retrospective diary studies using advanced statistical modeling techniques provide the best approaches to satisfy the required assumptions and inform causal statements about headache triggers. PMID:23534872
D'Ariano, Giacomo Mauro
2018-07-13
Causality has never gained the status of a 'law' or 'principle' in physics. Some recent literature has even popularized the false idea that causality is a notion that should be banned from theory. Such misconception relies on an alleged universality of the reversibility of the laws of physics, based either on the determinism of classical theory, or on the multiverse interpretation of quantum theory, in both cases motivated by mere interpretational requirements for realism of the theory. Here, I will show that a properly defined unambiguous notion of causality is a theorem of quantum theory, which is also a falsifiable proposition of the theory. Such a notion of causality appeared in the literature within the framework of operational probabilistic theories. It is a genuinely theoretical notion, corresponding to establishing a definite partial order among events, in the same way as we do by using the future causal cone on Minkowski space. The notion of causality is logically completely independent of the misidentified concept of 'determinism', and, being a consequence of quantum theory, is ubiquitous in physics. In addition, as classical theory can be regarded as a restriction of quantum theory, causality holds also in the classical case, although the determinism of the theory trivializes it. I then conclude by arguing that causality naturally establishes an arrow of time. This implies that the scenario of the 'block Universe' and the connected 'past hypothesis' are incompatible with causality, and thus with quantum theory: they are both doomed to remain mere interpretations and, as such, are not falsifiable, similar to the hypothesis of 'super-determinism'.This article is part of a discussion meeting issue 'Foundations of quantum mechanics and their impact on contemporary society'. © 2018 The Author(s).
International Nuclear Information System (INIS)
Maund, J.B.
1979-01-01
Although the existence of tachyons is not ruled out by special relativity, it appears that causal paradoxes will arise if there are tachyons. The usual solutions to these paradoxes employ some form of the reinterpretation principle. In this paper it is argued first that, the principle is incoherent, second, that even if it is not, some causal paradoxes remain, and third, the most plausible ''solution,'' which appeals to boundary conditions of the universe, will conflict with special relativity
Dynamics and causality constraints
International Nuclear Information System (INIS)
Sousa, Manoelito M. de
2001-04-01
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)
Causality discovery technology
Chen, M.; Ertl, T.; Jirotka, M.; Trefethen, A.; Schmidt, A.; Coecke, B.; Bañares-Alcántara, R.
2012-11-01
Causality is the fabric of our dynamic world. We all make frequent attempts to reason causation relationships of everyday events (e.g., what was the cause of my headache, or what has upset Alice?). We attempt to manage causality all the time through planning and scheduling. The greatest scientific discoveries are usually about causality (e.g., Newton found the cause for an apple to fall, and Darwin discovered natural selection). Meanwhile, we continue to seek a comprehensive understanding about the causes of numerous complex phenomena, such as social divisions, economic crisis, global warming, home-grown terrorism, etc. Humans analyse and reason causality based on observation, experimentation and acquired a priori knowledge. Today's technologies enable us to make observations and carry out experiments in an unprecedented scale that has created data mountains everywhere. Whereas there are exciting opportunities to discover new causation relationships, there are also unparalleled challenges to benefit from such data mountains. In this article, we present a case for developing a new piece of ICT, called Causality Discovery Technology. We reason about the necessity, feasibility and potential impact of such a technology.
A quantum causal discovery algorithm
Giarmatzi, Christina; Costa, Fabio
2018-03-01
Finding a causal model for a set of classical variables is now a well-established task—but what about the quantum equivalent? Even the notion of a quantum causal model is controversial. Here, we present a causal discovery algorithm for quantum systems. The input to the algorithm is a process matrix describing correlations between quantum events. Its output consists of different levels of information about the underlying causal model. Our algorithm determines whether the process is causally ordered by grouping the events into causally ordered non-signaling sets. It detects if all relevant common causes are included in the process, which we label Markovian, or alternatively if some causal relations are mediated through some external memory. For a Markovian process, it outputs a causal model, namely the causal relations and the corresponding mechanisms, represented as quantum states and channels. Our algorithm opens the route to more general quantum causal discovery methods.
Olafsson, Gestur; Helgason, Sigurdur
1996-01-01
This book is intended to introduce researchers and graduate students to the concepts of causal symmetric spaces. To date, results of recent studies considered standard by specialists have not been widely published. This book seeks to bring this information to students and researchers in geometry and analysis on causal symmetric spaces.Includes the newest results in harmonic analysis including Spherical functions on ordered symmetric space and the holmorphic discrete series and Hardy spaces on compactly casual symmetric spacesDeals with the infinitesimal situation, coverings of symmetric spaces, classification of causal symmetric pairs and invariant cone fieldsPresents basic geometric properties of semi-simple symmetric spacesIncludes appendices on Lie algebras and Lie groups, Bounded symmetric domains (Cayley transforms), Antiholomorphic Involutions on Bounded Domains and Para-Hermitian Symmetric Spaces
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.
Maximally causal quantum mechanics
International Nuclear Information System (INIS)
Roy, S.M.
1998-01-01
We present a new causal quantum mechanics in one and two dimensions developed recently at TIFR by this author and V. Singh. In this theory both position and momentum for a system point have Hamiltonian evolution in such a way that the ensemble of system points leads to position and momentum probability densities agreeing exactly with ordinary quantum mechanics. (author)
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...
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
Explaining through causal mechanisms
Biesbroek, Robbert; Dupuis, Johann; Wellstead, Adam
2017-01-01
This paper synthesizes and builds on recent critiques of the resilience literature; namely that the field has largely been unsuccessful in capturing the complexity of governance processes, in particular cause–effects relationships. We demonstrate that absence of a causal model is reflected in the
Optimal causal inference: estimating stored information and approximating causal architecture.
Still, Susanne; Crutchfield, James P; Ellison, Christopher J
2010-09-01
We introduce an approach to inferring the causal architecture of stochastic dynamical systems that extends rate-distortion theory to use causal shielding--a natural principle of learning. We study two distinct cases of causal inference: optimal causal filtering and optimal causal estimation. Filtering corresponds to the ideal case in which the probability distribution of measurement sequences is known, giving a principled method to approximate a system's causal structure at a desired level of representation. We show that in the limit in which a model-complexity constraint is relaxed, filtering finds the exact causal architecture of a stochastic dynamical system, known as the causal-state partition. From this, one can estimate the amount of historical information the process stores. More generally, causal filtering finds a graded model-complexity hierarchy of approximations to the causal architecture. Abrupt changes in the hierarchy, as a function of approximation, capture distinct scales of structural organization. For nonideal cases with finite data, we show how the correct number of the underlying causal states can be found by optimal causal estimation. A previously derived model-complexity control term allows us to correct for the effect of statistical fluctuations in probability estimates and thereby avoid overfitting.
Operator ordering and causality
Plimak, L. I.; Stenholm, S. T.
2011-01-01
It is shown that causality violations [M. de Haan, Physica 132A, 375, 397 (1985)], emerging when the conventional definition of the time-normal operator ordering [P.L.Kelley and W.H.Kleiner, Phys.Rev. 136, A316 (1964)] is taken outside the rotating wave approximation, disappear when the amended definition [L.P. and S.S., Annals of Physics, 323, 1989 (2008)] of this ordering is used.
International Nuclear Information System (INIS)
Lucas, J.R.
1984-01-01
Originating from lectures given to first year undergraduates reading physics and philosophy or mathematics and philosophy, formal logic is applied to issues and the elucidation of problems in space, time and causality. No special knowledge of relativity theory or quantum mechanics is needed. The text is interspersed with exercises and each chapter is preceded by a suggested 'preliminary reading' and followed by 'further reading' references. (U.K.)
Fukuda, Takashi; Dahalan, Jauhari
2011-01-01
This paper attempts to explore a new dimension of India’s ‘financegrowth- crisis’ nexus. For this end, the summary indicators of financial development, financial crisis and financial repression are created through the principal component approach, and we perform the cointegration and Granger causality analysis employing the methods of vector error correction model (VECM) and autoregressive distributed lag (ARDL). The element of structural break is also taken into assessment while specifying t...
Causal events enter awareness faster than non-causal events
Directory of Open Access Journals (Sweden)
Pieter Moors
2017-01-01
Full Text Available Philosophers have long argued that causality cannot be directly observed but requires a conscious inference (Hume, 1967. Albert Michotte however developed numerous visual phenomena in which people seemed to perceive causality akin to primary visual properties like colour or motion (Michotte, 1946. Michotte claimed that the perception of causality did not require a conscious, deliberate inference but, working over 70 years ago, he did not have access to the experimental methods to test this claim. Here we employ Continuous Flash Suppression (CFS—an interocular suppression technique to render stimuli invisible (Tsuchiya & Koch, 2005—to test whether causal events enter awareness faster than non-causal events. We presented observers with ‘causal’ and ‘non-causal’ events, and found consistent evidence that participants become aware of causal events more rapidly than non-causal events. Our results suggest that, whilst causality must be inferred from sensory evidence, this inference might be computed at low levels of perceptual processing, and does not depend on a deliberative conscious evaluation of the stimulus. This work therefore supports Michotte’s contention that, like colour or motion, causality is an immediate property of our perception of the world.
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.
Causal inference in public health.
Glass, Thomas A; Goodman, Steven N; Hernán, Miguel A; Samet, Jonathan M
2013-01-01
Causal inference has a central role in public health; the determination that an association is causal indicates the possibility for intervention. We review and comment on the long-used guidelines for interpreting evidence as supporting a causal association and contrast them with the potential outcomes framework that encourages thinking in terms of causes that are interventions. We argue that in public health this framework is more suitable, providing an estimate of an action's consequences rather than the less precise notion of a risk factor's causal effect. A variety of modern statistical methods adopt this approach. When an intervention cannot be specified, causal relations can still exist, but how to intervene to change the outcome will be unclear. In application, the often-complex structure of causal processes needs to be acknowledged and appropriate data collected to study them. These newer approaches need to be brought to bear on the increasingly complex public health challenges of our globalized world.
Causal Diagrams for Empirical Research
Pearl, Judea
1994-01-01
The primary aim of this paper is to show how graphical models can be used as a mathematical language for integrating statistical and subject-matter information. In particular, the paper develops a principled, nonparametric framework for causal inference, in which diagrams are queried to determine if the assumptions available are sufficient for identifiying causal effects from non-experimental data. If so the diagrams can be queried to produce mathematical expressions for causal effects in ter...
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
Causal electromagnetic interaction equations
International Nuclear Information System (INIS)
Zinoviev, Yury M.
2011-01-01
For the electromagnetic interaction of two particles the relativistic causal quantum mechanics equations are proposed. These equations are solved for the case when the second particle moves freely. The initial wave functions are supposed to be smooth and rapidly decreasing at the infinity. This condition is important for the convergence of the integrals similar to the integrals of quantum electrodynamics. We also consider the singular initial wave functions in the particular case when the second particle mass is equal to zero. The discrete energy spectrum of the first particle wave function is defined by the initial wave function of the free-moving second particle. Choosing the initial wave functions of the free-moving second particle it is possible to obtain a practically arbitrary discrete energy spectrum.
Structural Equations and Causal Explanations: Some Challenges for Causal SEM
Markus, Keith A.
2010-01-01
One common application of structural equation modeling (SEM) involves expressing and empirically investigating causal explanations. Nonetheless, several aspects of causal explanation that have an impact on behavioral science methodology remain poorly understood. It remains unclear whether applications of SEM should attempt to provide complete…
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…
Friederich, Simon
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
Covariation in Natural Causal Induction.
Cheng, Patricia W.; Novick, Laura R.
1991-01-01
Biases and models usually offered by cognitive and social psychology and by philosophy to explain causal induction are evaluated with respect to focal sets (contextually determined sets of events over which covariation is computed). A probabilistic contrast model is proposed as underlying covariation computation in natural causal induction. (SLD)
Paradoxical Behavior of Granger Causality
Witt, Annette; Battaglia, Demian; Gail, Alexander
2013-03-01
Granger causality is a standard tool for the description of directed interaction of network components and is popular in many scientific fields including econometrics, neuroscience and climate science. For time series that can be modeled as bivariate auto-regressive processes we analytically derive an expression for spectrally decomposed Granger Causality (SDGC) and show that this quantity depends only on two out of four groups of model parameters. Then we present examples of such processes whose SDGC expose paradoxical behavior in the sense that causality is high for frequency ranges with low spectral power. For avoiding misinterpretations of Granger causality analysis we propose to complement it by partial spectral analysis. Our findings are illustrated by an example from brain electrophysiology. Finally, we draw implications for the conventional definition of Granger causality. Bernstein Center for Computational Neuroscience Goettingen
On causality of extreme events
Directory of Open Access Journals (Sweden)
Massimiliano Zanin
2016-06-01
Full Text Available 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 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. We further show how the proposed metric is able to outperform classical causality metrics, provided non-linear relationships are present and large enough data sets are available.
Neural Correlates of Causal Power Judgments
Directory of Open Access Journals (Sweden)
Denise Dellarosa Cummins
2014-12-01
Full Text Available Causal inference is a fundamental component of cognition and perception. Probabilistic theories of causal judgment (most notably causal Bayes networks derive causal judgments using metrics that integrate contingency information. But human estimates typically diverge from these normative predictions. This is because human causal power judgments are typically strongly influenced by beliefs concerning underlying causal mechanisms, and because of the way knowledge is retrieved from human memory during the judgment process. Neuroimaging studies indicate that the brain distinguishes causal events from mere covariation, and between perceived and inferred causality. Areas involved in error prediction are also activated, implying automatic activation of possible exception cases during causal decision-making.
Energy Technology Data Exchange (ETDEWEB)
Steinberg, Aephraim M. [Institute for Experimental Physics, University of Vienna, Vienna (Austria)
2003-12-01
Experiment confirms that information cannot be transmitted faster than the speed of light. Ever since Einstein stated that nothing can travel faster than light, physicists have delighted in finding exceptions. One after another, observations of such 'superluminal' propagation have been made. However, while some image or pattern- such as the motion of a spotlight projected on a distant wall - might have appeared to travel faster than light, it seemed that there was no way to use the superluminal effect to transmit energy or information. In recent years, the superluminal propagation of light pulses through certain media has led to renewed controversy. In 1995, for example, Guenther Nimtz of the University of Cologne encoded Mozart's 40th Symphony on a microwave beam, which he claimed to have transmitted at a speed faster than light. Others maintain that such a violation of Einstein's speed limit would wreak havoc on our most fundamental ideas about causality, allowing an effect to precede its cause. Relativity teaches us that sending a signal faster than light would be equivalent to sending it backwards in time. (U.K.)
Directory of Open Access Journals (Sweden)
A. Jackson Stenner
2013-08-01
Full Text Available Rasch’s unidimensional models for measurement show how to connect object measures (e.g., reader abilities, measurement mechanisms (e.g., machine-generated cloze reading items, and observational outcomes (e.g., counts correct on reading instruments. Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct. We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained.
Stenner, A Jackson; Fisher, William P; Stone, Mark H; Burdick, Donald S
2013-01-01
Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained.
Stenner, A. Jackson; Fisher, William P.; Stone, Mark H.; Burdick, Donald S.
2013-01-01
Rasch's unidimensional models for measurement show how to connect object measures (e.g., reader abilities), measurement mechanisms (e.g., machine-generated cloze reading items), and observational outcomes (e.g., counts correct on reading instruments). Substantive theory shows what interventions or manipulations to the measurement mechanism can be traded off against a change to the object measure to hold the observed outcome constant. A Rasch model integrated with a substantive theory dictates the form and substance of permissible interventions. Rasch analysis, absent construct theory and an associated specification equation, is a black box in which understanding may be more illusory than not. Finally, the quantitative hypothesis can be tested by comparing theory-based trade-off relations with observed trade-off relations. Only quantitative variables (as measured) support such trade-offs. Note that to test the quantitative hypothesis requires more than manipulation of the algebraic equivalencies in the Rasch model or descriptively fitting data to the model. A causal Rasch model involves experimental intervention/manipulation on either reader ability or text complexity or a conjoint intervention on both simultaneously to yield a successful prediction of the resultant observed outcome (count correct). We conjecture that when this type of manipulation is introduced for individual reader text encounters and model predictions are consistent with observations, the quantitative hypothesis is sustained. PMID:23986726
International Nuclear Information System (INIS)
Crawford, G.N.
1981-01-01
The analysis is directed at a causal description of photon diffraction, which is explained in terms of a wave exerting real forces and providing actual guidance to each quantum of energy. An undulatory PSI wave is associated with each photon, and this wave is assumed to imply more than an informative probability function, so that it actually carries real energy, in much the same way as does an electro-magnetic wave. Whether or not it may be in some way related to the electromagnetic wave is left as a matter of on-going concern. A novel application of the concept of a minimum energy configuration is utilized; that is, a system of energy quanta seeks out relative positions and orientations of least mutual energy, much as an electron seeks its Bohr radius as a position of least mutual energy. Thus the concept implies more a guiding interaction of the PSI waves than an interfering cancellation of these waves. Similar concepts have been suggested by L. de Broglie and D. Bohm
["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.
Structure and Strength in Causal Induction
Griffiths, Thomas L.; Tenenbaum, Joshua B.
2005-01-01
We present a framework for the rational analysis of elemental causal induction--learning about the existence of a relationship between a single cause and effect--based upon causal graphical models. This framework makes precise the distinction between causal structure and causal strength: the difference between asking whether a causal relationship…
Dynamics of Quantum Causal Structures
Castro-Ruiz, Esteban; Giacomini, Flaminia; Brukner, Časlav
2018-01-01
It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B ). Here, we develop a framework for "dynamics of causal structures," i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B , via superposition of causal orders, to a channel from B to A . We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.
Dynamics of Quantum Causal Structures
Directory of Open Access Journals (Sweden)
Esteban Castro-Ruiz
2018-03-01
Full Text Available It was recently suggested that causal structures are both dynamical, because of general relativity, and indefinite, because of quantum theory. The process matrix formalism furnishes a framework for quantum mechanics on indefinite causal structures, where the order between operations of local laboratories is not definite (e.g., one cannot say whether operation in laboratory A occurs before or after operation in laboratory B. Here, we develop a framework for “dynamics of causal structures,” i.e., for transformations of process matrices into process matrices. We show that, under continuous and reversible transformations, the causal order between operations is always preserved. However, the causal order between a subset of operations can be changed under continuous yet nonreversible transformations. An explicit example is that of the quantum switch, where a party in the past affects the causal order of operations of future parties, leading to a transition from a channel from A to B, via superposition of causal orders, to a channel from B to A. We generalize our framework to construct a hierarchy of quantum maps based on transformations of process matrices and transformations thereof.
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.
Discrete causal theory emergent spacetime and the causal metric hypothesis
Dribus, Benjamin F
2017-01-01
This book evaluates and suggests potentially critical improvements to causal set theory, one of the best-motivated approaches to the outstanding problems of fundamental physics. Spacetime structure is of central importance to physics beyond general relativity and the standard model. The causal metric hypothesis treats causal relations as the basis of this structure. The book develops the consequences of this hypothesis under the assumption of a fundamental scale, with smooth spacetime geometry viewed as emergent. This approach resembles causal set theory, but differs in important ways; for example, the relative viewpoint, emphasizing relations between pairs of events, and relationships between pairs of histories, is central. The book culminates in a dynamical law for quantum spacetime, derived via generalized path summation.
Causal boundary for stably causal space-times
International Nuclear Information System (INIS)
Racz, I.
1987-12-01
The usual boundary constructions for space-times often yield an unsatisfactory boundary set. This problem is reviewed and a new solution is proposed. An explicit identification rule is given on the set of the ideal points of the space-time. This construction leads to a satisfactory boundary point set structure for stably causal space-times. The topological properties of the resulting causal boundary construction are examined. For the stably causal space-times each causal curve has a unique endpoint on the boundary set according to the extended Alexandrov topology. The extension of the space-time through the boundary is discussed. To describe the singularities the defined boundary sets have to be separated into two disjoint sets. (D.Gy.) 8 refs
Causal boundary for strongly causal spacetimes: Pt. 1
International Nuclear Information System (INIS)
Szabados, L.B.
1989-01-01
In a previous paper an analysis of the general structure of the causal boundary constructions and a new explicit identification rule, built up from elementary TIP-TIF gluings, were presented. In the present paper we complete our identification by incorporating TIP-TIP and TIF-TIF gluings as well. An asymptotic causality condition is found which, for physically important cases, ensures the uniqueness of the endpoints of the non-spacelike curves in the completed spacetime. (author)
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...... to 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...
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.
Causal Modelling in Evaluation Research.
Winteler, Adolf
1983-01-01
A study applied path analysis methods, using new techniques of causal analysis, to the problem of predicting the achievement, dropout rate, and satisfaction of university students. Besides providing explanations, the technique indicates possible remedial measures. (MSE)
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...
Regression to Causality : Regression-style presentation influences causal attribution
DEFF Research Database (Denmark)
Bordacconi, Mats Joe; Larsen, Martin Vinæs
2014-01-01
of equivalent results presented as either regression models or as a test of two sample means. Our experiment shows that the subjects who were presented with results as estimates from a regression model were more inclined to interpret these results causally. Our experiment implies that scholars using regression...... models – one of the primary vehicles for analyzing statistical results in political science – encourage causal interpretation. Specifically, we demonstrate that presenting observational results in a regression model, rather than as a simple comparison of means, makes causal interpretation of the results...... more likely. Our experiment drew on a sample of 235 university students from three different social science degree programs (political science, sociology and economics), all of whom had received substantial training in statistics. The subjects were asked to compare and evaluate the validity...
Putting a cap on causality violations in causal dynamical triangulations
International Nuclear Information System (INIS)
Ambjoern, Jan; Loll, Renate; Westra, Willem; Zohren, Stefan
2007-01-01
The formalism of causal dynamical triangulations (CDT) provides us with a non-perturbatively defined model of quantum gravity, where the sum over histories includes only causal space-time histories. Path integrals of CDT and their continuum limits have been studied in two, three and four dimensions. Here we investigate a generalization of the two-dimensional CDT model, where the causality constraint is partially lifted by introducing branching points with a weight g s , and demonstrate that the system can be solved analytically in the genus-zero sector. The solution is analytic in a neighborhood around weight g s = 0 and cannot be analytically continued to g s = ∞, where the branching is entirely geometric and where one would formally recover standard Euclidean two-dimensional quantum gravity defined via dynamical triangulations or Liouville theory
Bayesian networks improve causal environmental ...
Rule-based weight of evidence approaches to ecological risk assessment may not account for uncertainties and generally lack probabilistic integration of lines of evidence. Bayesian networks allow causal inferences to be made from evidence by including causal knowledge about the problem, using this knowledge with probabilistic calculus to combine multiple lines of evidence, and minimizing biases in predicting or diagnosing causal relationships. Too often, sources of uncertainty in conventional weight of evidence approaches are ignored that can be accounted for with Bayesian networks. Specifying and propagating uncertainties improve the ability of models to incorporate strength of the evidence in the risk management phase of an assessment. Probabilistic inference from a Bayesian network allows evaluation of changes in uncertainty for variables from the evidence. The network structure and probabilistic framework of a Bayesian approach provide advantages over qualitative approaches in weight of evidence for capturing the impacts of multiple sources of quantifiable uncertainty on predictions of ecological risk. Bayesian networks can facilitate the development of evidence-based policy under conditions of uncertainty by incorporating analytical inaccuracies or the implications of imperfect information, structuring and communicating causal issues through qualitative directed graph formulations, and quantitatively comparing the causal power of multiple stressors on value
Causality and analyticity in optics
International Nuclear Information System (INIS)
Nussenzveig, H.M.
In order to provide an overall picture of the broad range of optical phenomena that are directly linked with the concepts of causality and analyticity, the following topics are briefly reviewed, emphasizing recent developments: 1) Derivation of dispersion relations for the optical constants of general linear media from causality. Application to the theory of natural optical activity. 2) Derivation of sum rules for the optical constants from causality and from the short-time response function (asymptotic high-frequency behavior). Average spectral behavior of optical media. Applications. 3) Role of spectral conditions. Analytic properties of coherence functions in quantum optics. Reconstruction theorem.4) Phase retrieval problems. 5) Inverse scattering problems. 6) Solution of nonlinear evolution equations in optics by inverse scattering methods. Application to self-induced transparency. Causality in nonlinear wave propagation. 7) Analytic continuation in frequency and angular momentum. Complex singularities. Resonances and natural-mode expansions. Regge poles. 8) Wigner's causal inequality. Time delay. Spatial displacements in total reflection. 9) Analyticity in diffraction theory. Complex angular momentum theory of Mie scattering. Diffraction as a barrier tunnelling effect. Complex trajectories in optics. (Author) [pt
Hierarchical organisation of causal graphs
International Nuclear Information System (INIS)
Dziopa, P.
1993-01-01
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
Entropy for theories with indefinite causal structure
International Nuclear Information System (INIS)
Markes, Sonia; Hardy, Lucien
2011-01-01
Any theory with definite causal structure has a defined past and future, be it defined by light cones or an absolute time scale. Entropy is a concept that has traditionally been reliant on a definite notion of causality. However, without a definite notion of causality, the concept of entropy is not all lost. Indefinite causal structure results from combining probabilistic predictions and dynamical space-time. The causaloid framework lays the mathematical groundwork to be able to treat indefinite causal structure. In this paper, we build on the causaloid mathematics and define a causally-unbiased entropy for an indefinite causal structure. In defining a causally-unbiased entropy, there comes about an emergent idea of causality in the form of a measure of causal connectedness, termed the Q factor.
mediation: R package for causal mediation analysis
Tingley, Dustin; Yamamoto, Teppei; Hirose, Kentaro; Keele, Luke; Imai, Kosuke
2012-01-01
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 su...
Directory of Open Access Journals (Sweden)
José Tomás Alvarado
2009-08-01
Full Text Available This work presents a causal conception of metaphysical modality in which a state of affairs is metaphysically possible if and only if it can be caused (in the past, the present or the future by current entities. The conception is contrasted with what is called the “combinatorial” conception of modality, in which everything can co-exist with anything else. This work explains how the notion of ‘causality’ should be construed in the causal theory, what difference exists between modalities thus defined from nomological modality, how accessibility relations between possible worlds should be interpreted, and what is the relation between the causal conception and the necessity of origin.
Introductive remarks on causal inference
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Silvana A. Romio
2013-05-01
Full Text Available One of the more challenging issues in epidemiological research is being able to provide an unbiased estimate of the causal exposure-disease effect, to assess the possible etiological mechanisms and the implication for public health. A major source of bias is confounding, which can spuriously create or mask the causal relationship. In the last ten years, methodological research has been developed to better de_ne the concept of causation in epidemiology and some important achievements have resulted in new statistical models. In this review, we aim to show how a technique the well known by statisticians, i.e. standardization, can be seen as a method to estimate causal e_ects, equivalent under certain conditions to the inverse probability treatment weight procedure.
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.
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.
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.
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......, eventually rejecting the null hypothesis, even when the series are independent of each other. Moreover, controlling for these deterministic elements (in the auxiliary regressions of the test) does not preclude the possibility of drawing erroneous inferences. Granger-causality tests should not be used under...
Quantum theory and local causality
Hofer-Szabó, Gábor
2018-01-01
This book summarizes the results of research the authors have pursued in the past years on the problem of implementing Bell's notion of local causality in local physical theories and relating it to other important concepts and principles in the foundations of physics such as the Common Cause Principle, Bell's inequalities, the EPR (Einstein-Podolsky-Rosen) scenario, and various other locality and causality concepts. The book is intended for philosophers of science with an interest in the formal background of sciences, philosophers of physics and physicists working in foundation of physics.
[Causal analysis approaches in epidemiology].
Dumas, O; Siroux, V; Le Moual, N; Varraso, R
2014-02-01
Epidemiological research is mostly based on observational studies. Whether such studies can provide evidence of causation remains discussed. Several causal analysis methods have been developed in epidemiology. This paper aims at presenting an overview of these methods: graphical models, path analysis and its extensions, and models based on the counterfactual approach, with a special emphasis on marginal structural models. Graphical approaches have been developed to allow synthetic representations of supposed causal relationships in a given problem. They serve as qualitative support in the study of causal relationships. The sufficient-component cause model has been developed to deal with the issue of multicausality raised by the emergence of chronic multifactorial diseases. Directed acyclic graphs are mostly used as a visual tool to identify possible confounding sources in a study. Structural equations models, the main extension of path analysis, combine a system of equations and a path diagram, representing a set of possible causal relationships. They allow quantifying direct and indirect effects in a general model in which several relationships can be tested simultaneously. Dynamic path analysis further takes into account the role of time. The counterfactual approach defines causality by comparing the observed event and the counterfactual event (the event that would have been observed if, contrary to the fact, the subject had received a different exposure than the one he actually received). This theoretical approach has shown limits of traditional methods to address some causality questions. In particular, in longitudinal studies, when there is time-varying confounding, classical methods (regressions) may be biased. Marginal structural models have been developed to address this issue. In conclusion, "causal models", though they were developed partly independently, are based on equivalent logical foundations. A crucial step in the application of these models is the
USO DA DORAMECTINA NO TRATAMENTO DA DEMODICOSE CANINA: RELATO DE CASO
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Lívia Silva JACOMINE
2017-12-01
Full Text Available A demodicose ou sarna demodécica é uma dermatoparasitose não contagiosa e ocasionada por uma reação cutânea inflamatória relacionada à multiplicação excessiva do ácaro Demodex canis. As causas da doença não estão totalmente definidas, entretanto, a baixa imunidade é um fator que predispõe a doença. A classificação da demodicose baseia-se na localização corpórea do animal, sendo localizada ou generalizada. O prognóstico é variável. Os sinais clínicos são alopecia, eritema, descamação, hiperpigmentação, liquenificação, febre e linfoadenopatia. O diagnóstico é realizado através de raspado cutâneo, impressão em fita de acetato, tricograma ou biópsia de pele. O tratamento há décadas foi realizado através do uso do amitraz, porém, além da toxicidade, o uso inadequado desse fármaco ocasionou em desenvolvimento de resistência. Atualmente, as lactonas macrocíclicas, tais como ivermectina, doramectina, milbemicina oxima e moxidectina vêm sendo empregadas com sucesso em cães. Entretanto, cães das raças dolicocéfalas, tais como Collie e Pastor Alemão, dentre outras, manifestam reações tóxicas graves com o uso da ivermectina. Assim, o objetivo desse trabalho foi relatar um caso do uso da doramectina na dose de 0,6 mg/kg, via oral a cada 72 horas, durante 60 dias no tratamento da demodicose generalizada em um cão da raça Pastor Alemão. Os resultados obtidos demostraram a melhora clínica do animal e nenhum efeito adverso foi clinicamente observado. Concluindo, não obstante a demodicose ser uma doença clínica desafiadora, o uso da doramectina demostrou vantagens pelo maior intervalo de administração, redução na duração do tratamento e a ausência de reações adversas, comuns as avermectinas quando usadas em animais dolicocéfalos.
Causal Reasoning with Mental Models
2014-08-08
The initial rubric is equivalent to an exclusive disjunction between the two causal assertions. It 488 yields the following two mental models: 489...are 575 important, whereas the functions of artifacts are important (Ahn, 1998). A genetic code is 576 accordingly more critical to being a goat than
Identity, causality, and pronoun ambiguity.
Sagi, Eyal; Rips, Lance J
2014-10-01
This article looks at the way people determine the antecedent of a pronoun in sentence pairs, such as: Albert invited Ron to dinner. He spent hours cleaning the house. The experiment reported here is motivated by the idea that such judgments depend on reasoning about identity (e.g., the identity of the he who cleaned the house). Because the identity of an individual over time depends on the causal-historical path connecting the stages of the individual, the correct antecedent will also depend on causal connections. The experiment varied how likely it is that the event of the first sentence (e.g., the invitation) would cause the event of the second (the house cleaning) for each of the two individuals (the likelihood that if Albert invited Ron to dinner, this would cause Albert to clean the house, versus cause Ron to clean the house). Decisions about the antecedent followed causal likelihood. A mathematical model of causal identity accounted for most of the key aspects of the data from the individual sentence pairs. Copyright © 2014 Cognitive Science Society, Inc.
Charged singularities: the causality violation
Energy Technology Data Exchange (ETDEWEB)
De Felice, F; Nobili, L [Padua Univ. (Italy). Ist. di Fisica; Calvani, M [Padua Univ. (Italy). Ist. di Astronomia
1980-12-01
A search is made for examples of particle trajectories which, approaching a naked singularity from infinity, make up for lost time before going back to infinity. In the Kerr-Newman metric a whole family of such trajectories is found showing that the causality violation is indeed a non-avoidable pathology.
Entanglement, holography and causal diamonds
de Boer, Jan; Haehl, Felix M.; Heller, Michal P.; Myers, Robert C.
2016-08-01
We argue that the degrees of freedom in a d-dimensional CFT can be reorganized 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 2 d-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 entanglemententropy from this unifying point of view. We demonstrate that for small perturbations of the vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.
Entanglement, holography and causal diamonds
Energy Technology Data Exchange (ETDEWEB)
Boer, Jan de [Institute of Physics, Universiteit van Amsterdam,Science Park 904, 1090 GL Amsterdam (Netherlands); Haehl, Felix M. [Centre for Particle Theory & Department of Mathematical Sciences, Durham University,South Road, Durham DH1 3LE (United Kingdom); Heller, Michal P.; Myers, Robert C. [Perimeter Institute for Theoretical Physics,31 Caroline Street North, Waterloo, Ontario N2L 2Y5 (Canada)
2016-08-29
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 vacuum, our observables obey linear two-derivative equations of motion on the space of causal diamonds. In two dimensions, the latter is given by a product of two copies of a two-dimensional de Sitter space. For a class of universal states, we show that the entanglement entropy and its spin-three generalization obey nonlinear equations of motion with local interactions on this moduli space, which can be identified with Liouville and Toda equations, respectively. This suggests the possibility of extending the definition of our new observables beyond the linear level more generally and in such a way that they give rise to new dynamically interacting theories on the moduli space of causal diamonds. Various challenges one has to face in order to implement this idea are discussed.
The argumentative impact of causal relations
DEFF Research Database (Denmark)
Nielsen, Anne Ellerup
1996-01-01
such as 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.......The semantic relations between and within utterances are marked by the use of connectors and adverbials. One type of semantic relations is causal relations expressed by causal markers such as because, therefore, so, for, etc. Some of these markers cover different types of causal relations...
Spectral dimension in causal set quantum gravity
International Nuclear Information System (INIS)
Eichhorn, Astrid; Mizera, Sebastian
2014-01-01
We evaluate the spectral dimension in causal set quantum gravity by simulating random walks on causal sets. In contrast to other approaches to quantum gravity, we find an increasing spectral dimension at small scales. This observation can be connected to the nonlocality of causal set theory that is deeply rooted in its fundamentally Lorentzian nature. Based on its large-scale behaviour, we conjecture that the spectral dimension can serve as a tool to distinguish causal sets that approximate manifolds from those that do not. As a new tool to probe quantum spacetime in different quantum gravity approaches, we introduce a novel dimensional estimator, the causal spectral dimension, based on the meeting probability of two random walkers, which respect the causal structure of the quantum spacetime. We discuss a causal-set example, where the spectral dimension and the causal spectral dimension differ, due to the existence of a preferred foliation. (paper)
On causal nonrelativistic classical electrodynamics
International Nuclear Information System (INIS)
Goedecke, G.H.
1984-01-01
The differential-difference (DD) motion equations of the causal nonrelativistic classical electrodynamics developed by the author in 1975 are shown to possess only nonrunaway, causal solutions with no discontinuities in particle velocity or position. As an example, the DD equation solution for the problem of an electromagnetic shock incident on an initially stationary charged particle is contrasted with the standard Abraham-Lorentz equation solution. The general Cauchy problem for these DD motion equations is discussed. In general, in order to uniquely determine a solution, the initial data must be more detailed than the standard Cauchy data of initial position and velocity. Conditions are given under which the standard Cauchy data will determine the DD equation solutions to sufficient practical accuracy
Quantum mechanics, relativity and causality
International Nuclear Information System (INIS)
Tati, Takao.
1975-07-01
In quantum mechanics, the state is prepared by a measurement on a space-like surface sigma. What is that determines the surface sigma on which the measurement prepares the state It is considered either a mechanism proper to the measuring process (apparatus) or a universal property of space-time. In the former case, problems arise, concerning causality or conservation of probability due to that the velocity of reduction of wave-packet is considered to exceed the light velocity. The theory of finite degree of freedom proposed previously belongs to the latter case. In this theory, the surface sigma is restricted to the hyper-plane perpendicular to a universal time-like vector governing causal relations. We propose an experiment to discriminate between the above-mentioned two cases and to test the existence of the universal time-like vector. (auth.)
Causal Set Generator and Action Computer
Cunningham, William; Krioukov, Dmitri
2017-01-01
The causal set approach to quantum gravity has gained traction over the past three decades, but numerical experiments involving causal sets have been limited to relatively small scales. The software suite presented here provides a new framework for the generation and study of causal sets. Its efficiency surpasses previous implementations by several orders of magnitude. We highlight several important features of the code, including the compact data structures, the $O(N^2)$ causal set generatio...
Modeling of causality with metamaterials
International Nuclear Information System (INIS)
Smolyaninov, Igor I
2013-01-01
Hyperbolic metamaterials may be used to model a 2 + 1-dimensional Minkowski space–time in which the role of time is played by one of the spatial coordinates. When a metamaterial is built and illuminated with a coherent extraordinary laser beam, the stationary pattern of light propagation inside the metamaterial may be treated as a collection of particle world lines, which represents a complete ‘history’ of this 2 + 1-dimensional space–time. While this model may be used to build interesting space–time analogs, such as metamaterial ‘black holes’ and a metamaterial ‘big bang’, it lacks causality: since light inside the metamaterial may propagate back and forth along the ‘timelike’ spatial coordinate, events in the ‘future’ may affect events in the ‘past’. Here we demonstrate that a more sophisticated metamaterial model may fix this deficiency via breaking the mirror and temporal (PT) symmetries of the original model and producing one-way propagation along the ‘timelike’ spatial coordinate. The resulting 2 + 1-dimensional Minkowski space–time appears to be causal. This scenario may be considered as a metamaterial model of the Wheeler–Feynman absorber theory of causality. (paper)
THE CAUSAL ANALYSIS / DIAGNOSIS DECISION ...
CADDIS is an on-line decision support system that helps investigators in the regions, states and tribes find, access, organize, use and share information to produce causal evaluations in aquatic systems. It is based on the US EPA's Stressor Identification process which is a formal method for identifying causes of impairments in aquatic systems. CADDIS 2007 increases access to relevant information useful for causal analysis and provides methods and tools that practitioners can use to analyze their own data. The new Candidate Cause section provides overviews of commonly encountered causes of impairments to aquatic systems: metals, sediments, nutrients, flow alteration, temperature, ionic strength, and low dissolved oxygen. CADDIS includes new Conceptual Models that illustrate the relationships from sources to stressors to biological effects. An Interactive Conceptual Model for phosphorus links the diagram with supporting literature citations. The new Analyzing Data section helps practitioners analyze their data sets and interpret and use those results as evidence within the USEPA causal assessment process. Downloadable tools include a graphical user interface statistical package (CADStat), and programs for use with the freeware R statistical package, and a Microsoft Excel template. These tools can be used to quantify associations between causes and biological impairments using innovative methods such as species-sensitivity distributions, biological inferenc
Causal structure of analogue spacetimes
International Nuclear Information System (INIS)
Barcelo, Carlos; Liberati, Stefano; Sonego, Sebastiano; Visser, Matt
2004-01-01
The so-called 'analogue models of general relativity' provide a number of specific physical systems, well outside the traditional realm of general relativity, that nevertheless are well-described by the differential geometry of curved spacetime. Specifically, the propagation of perturbations in these condensed matter systems is described by 'effective metrics' that carry with them notions of 'causal structure' as determined by an exchange of quasi-particles. These quasi-particle-induced causal structures serve as specific examples of what can be done in the presence of a Lorentzian metric without having recourse to the Einstein equations of general relativity. (After all, the underlying analogue model is governed by its own specific physics, not necessarily by the Einstein equations.) In this paper we take a careful look at what can be said about the causal structure of analogue spacetimes, focusing on those containing quasi-particle horizons, both with a view to seeing what is different from standard general relativity, and what the similarities might be. For definiteness, and because the physics is particularly simple to understand, we will phrase much of the discussion in terms of acoustic disturbances in moving fluids, where the underlying physics is ordinary fluid mechanics, governed by the equations of traditional hydrodynamics, and the relevant quasi-particles are the phonons. It must however be emphasized that this choice of example is only for the sake of pedagogical simplicity and that our considerations apply generically to wide classes of analogue spacetimes
Obesity and infection: reciprocal causality.
Hainer, V; Zamrazilová, H; Kunešová, M; Bendlová, B; Aldhoon-Hainerová, I
2015-01-01
Associations between different infectious agents and obesity have been reported in humans for over thirty years. In many cases, as in nosocomial infections, this relationship reflects the greater susceptibility of obese individuals to infection due to impaired immunity. In such cases, the infection is not related to obesity as a causal factor but represents a complication of obesity. In contrast, several infections have been suggested as potential causal factors in human obesity. However, evidence of a causal linkage to human obesity has only been provided for adenovirus 36 (Adv36). This virus activates lipogenic and proinflammatory pathways in adipose tissue, improves insulin sensitivity, lipid profile and hepatic steatosis. The E4orf1 gene of Adv36 exerts insulin senzitizing effects, but is devoid of its pro-inflammatory modalities. The development of a vaccine to prevent Adv36-induced obesity or the use of E4orf1 as a ligand for novel antidiabetic drugs could open new horizons in the prophylaxis and treatment of obesity and diabetes. More experimental and clinical studies are needed to elucidate the mutual relations between infection and obesity, identify additional infectious agents causing human obesity, as well as define the conditions that predispose obese individuals to specific infections.
Behavioural Pattern of Causality Parameter of Autoregressive ...
African Journals Online (AJOL)
In this paper, a causal form of Autoregressive Moving Average process, ARMA (p, q) of various orders and behaviour of the causality parameter of ARMA model is investigated. It is deduced that the behaviour of causality parameter ψi depends on positive and negative values of autoregressive parameter φ and moving ...
Exploring Individual Differences in Preschoolers' Causal Stance
Alvarez, Aubry; Booth, Amy E.
2016-01-01
Preschoolers, as a group, are highly attuned to causality, and this attunement is known to facilitate memory, learning, and problem solving. However, recent work reveals substantial individual variability in the strength of children's "causal stance," as demonstrated by their curiosity about and preference for new causal information. In…
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.…
Causal inference in economics and marketing.
Varian, Hal R
2016-07-05
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.
Causal knowledge and reasoning in decision making
Hagmayer, Y.; Witteman, C.L.M.
2017-01-01
Normative causal decision theories argue that people should use their causal knowledge in decision making. Based on these ideas, we argue that causal knowledge and reasoning may support and thereby potentially improve decision making based on expected outcomes, narratives, and even cues. We will
Directory of Open Access Journals (Sweden)
Andrés Felipe Restrepo Duque
2009-12-01
Full Text Available Se evaluaron los efectos de dos biocontroladores potenciales, un consorcio de micorrizas y viruta de pino sobre el control de Spongospora subterranea f. sp. subterranea en papa Diacol Capiro muy susceptible a la sarna polvosa. El estudio se realizó en el Centro Agropecuario Paysandú, corregimiento de Santa Elena Medellín a 2.550 msnm, temperatura media de 14 ºC y precipitación promedio anual de 2.500 mm. Se utilizó un diseño completamente al azar con cuatro repeticiones y cinco tratamientos (Trichoderma harzianum; Producto comercial de micorrizas “Mikorhyze lote C7”; Pseudomonas fluorescents, viruta de pino y Testigo sin control. Se encontraron porcentajes de incidencia de la enfermedad en raíces (32% para el tratamiento testigo (sin control, aunque el porcentaje de severidad tanto del testigo como de los demás tratamientos fue bajo, el cual no superó el 0,23%. La expresión de síntomas en tubérculos mostró diferencias estadísticamente significativas entre el tratamiento testigo y la aplicación de T. harzianum, micorrizas y P. fluorescents a los tubérculos, al igual que la adición de la viruta de pino al suelo. Estos tratamientos redujeron la incidencia y severidad de la sarna polvosa en las raíces y tubérculos. Las variables fisiológicas peso seco de raíces, peso de tubérculos y peso seco de la parte aérea, no presentaron incrementos positivos ni diferencias significativas entre los tratamientos evaluados.The effect of two potential microorganism, mycorhize and pine wood shavings for management of Spongospora subterranea f. sp. subterranea in potato cultivar DIACOL Capiro were evaluated. This research was established at the Agricultural Center of Paysandú (Santa Elena - Medellín to 2,550 masL, average temperature of 14 ºC and average annual rainfall of 2,500 mm. A field experiment was established using a randomized complete design with four replications and five treatments (Trichoderma harzianum; Comercial product
A theory of causal learning in children: causal maps and Bayes nets.
Gopnik, Alison; Glymour, Clark; Sobel, David M; Schulz, Laura E; Kushnir, Tamar; Danks, David
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computations similar to those for learning causal Bayes nets and for predicting with them. Experimental results suggest that 2- to 4-year-old children construct new causal maps and that their learning is consistent with the Bayes net formalism.
Norms and customs: causally important or causally impotent?
Jones, Todd
2010-01-01
In this article, I argue that norms and customs, despite frequently being described as being causes of behavior in the social sciences and ordinary conversation, cannot really cause behavior. Terms like "norms" and the like seem to refer to philosophically disreputable disjunctive properties. More problematically, even if they do not, or even if there can be disjunctive properties after all, I argue that norms and customs still cannot cause behavior. The social sciences would be better off without referring to properties like norms and customs as if they could be causal.
A theory of causal learning in children: Causal maps and Bayes nets
Gopnik, A; Glymour, C; Sobel, D M; Schulz, L E; Kushnir, T; Danks, D
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously understood in terms of the formalism of directed graphical causal models, or Bayes nets. Children's causal learning and inference may involve computatio...
Causal mediation analysis with multiple causally non-ordered mediators.
Taguri, Masataka; Featherstone, John; Cheng, Jing
2018-01-01
In many health studies, researchers are interested in estimating the treatment effects on the outcome around and through an intermediate variable. Such causal mediation analyses aim to understand the mechanisms that explain the treatment effect. Although multiple mediators are often involved in real studies, most of the literature considered mediation analyses with one mediator at a time. In this article, we consider mediation analyses when there are causally non-ordered multiple mediators. Even if the mediators do not affect each other, the sum of two indirect effects through the two mediators considered separately may diverge from the joint natural indirect effect when there are additive interactions between the effects of the two mediators on the outcome. Therefore, we derive an equation for the joint natural indirect effect based on the individual mediation effects and their interactive effect, which helps us understand how the mediation effect works through the two mediators and relative contributions of the mediators and their interaction. We also discuss an extension for three mediators. The proposed method is illustrated using data from a randomized trial on the prevention of dental caries.
The Functions of Danish Causal Conjunctions
Directory of Open Access Journals (Sweden)
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.
Causal diagrams in systems epidemiology
Directory of Open Access Journals (Sweden)
Joffe Michael
2012-03-01
Full Text Available Abstract Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s. Transmitted causes ("causes of causes" tend not to be systematically analysed. The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties. The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets. Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.
Causal diagrams in systems epidemiology.
Joffe, Michael; Gambhir, Manoj; Chadeau-Hyam, Marc; Vineis, Paolo
2012-03-19
Methods of diagrammatic modelling have been greatly developed in the past two decades. Outside the context of infectious diseases, systematic use of diagrams in epidemiology has been mainly confined to the analysis of a single link: that between a disease outcome and its proximal determinant(s). Transmitted causes ("causes of causes") tend not to be systematically analysed.The infectious disease epidemiology modelling tradition models the human population in its environment, typically with the exposure-health relationship and the determinants of exposure being considered at individual and group/ecological levels, respectively. Some properties of the resulting systems are quite general, and are seen in unrelated contexts such as biochemical pathways. Confining analysis to a single link misses the opportunity to discover such properties.The structure of a causal diagram is derived from knowledge about how the world works, as well as from statistical evidence. A single diagram can be used to characterise a whole research area, not just a single analysis - although this depends on the degree of consistency of the causal relationships between different populations - and can therefore be used to integrate multiple datasets.Additional advantages of system-wide models include: the use of instrumental variables - now emerging as an important technique in epidemiology in the context of mendelian randomisation, but under-used in the exploitation of "natural experiments"; the explicit use of change models, which have advantages with respect to inferring causation; and in the detection and elucidation of feedback.
Probabilistic causality and radiogenic cancers
International Nuclear Information System (INIS)
Groeer, P.G.
1986-01-01
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
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
Causal relationship: a new tool for the causal characterization of Lorentzian manifolds
International Nuclear Information System (INIS)
Garcia-Parrado, Alfonso; Senovilla, Jose M M
2003-01-01
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
International Nuclear Information System (INIS)
Bombelli, L.; Lee, J.; Meyer, D.; Sorkin, R.D.
1987-01-01
We propose that space-time at the smallest scales is in reality a causal set: a locally finite set of elements endowed with a partial order corresponding to the macroscopic relation that defines past and future. We explore how a Lorentzian manifold can approximate a causal set, noting in particular that the thereby defined effective dimensionality of a given causal set can vary with length scale. Finally, we speculate briefly on the quantum dynamics of causal sets, indicating why an appropriate choice of action can reproduce general relativity in the classical limit
Amodal causal capture in the tunnel effect.
Bae, Gi Yeul; Flombaum, Jonathan I
2011-01-01
In addition to identifying individual objects in the world, the visual system must also characterize the relationships between objects, for instance when objects occlude one another or cause one another to move. Here we explored the relationship between perceived causality and occlusion. Can one perceive causality in an occluded location? In several experiments, observers judged whether a centrally presented event involved a single object passing behind an occluder, or one object causally launching another (out of view and behind the occluder). With no additional context, the centrally presented event was typically judged as a non-causal pass, even when the occluding and disoccluding objects were different colors--an illusion known as the 'tunnel effect' that results from spatiotemporal continuity. However, when a synchronized context event involved an unambiguous causal launch, participants perceived a causal launch behind the occluder. This percept of an occluded causal interaction could also be driven by grouping and synchrony cues in the absence of any explicitly causal interaction. These results reinforce the hypothesis that causality is an aspect of perception. It is among the interpretations of the world that are independently available to vision when resolving ambiguity, and that the visual system can 'fill in' amodally.
Electromagnetic pulses, localized and causal
Lekner, John
2018-01-01
We show that pulse solutions of the wave equation can be expressed as time Fourier superpositions of scalar monochromatic beam wave functions (solutions of the Helmholtz equation). This formulation is shown to be equivalent to Bateman's integral expression for solutions of the wave equation, for axially symmetric solutions. A closed-form one-parameter solution of the wave equation, containing no backward-propagating parts, is constructed from a beam which is the tight-focus limit of two families of beams. Application is made to transverse electric and transverse magnetic pulses, with evaluation of the energy, momentum and angular momentum for a pulse based on the general localized and causal form. Such pulses can be represented as superpositions of photons. Explicit total energy and total momentum values are given for the one-parameter closed-form pulse.
Quantum retrodiction and causality principle
International Nuclear Information System (INIS)
Shirokov, M.I.
1994-01-01
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
Causal ubiquity in quantum physics. A superluminal and local-causal physical ontology
International Nuclear Information System (INIS)
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 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
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.
A Theory of Causal Learning in Children: Causal Maps and Bayes Nets
Gopnik, Alison; Glymour, Clark; Sobel, David M.; Schulz, Laura E.; Kushnir, Tamar; Danks, David
2004-01-01
The authors outline a cognitive and computational account of causal learning in children. They propose that children use specialized cognitive systems that allow them to recover an accurate "causal map" of the world: an abstract, coherent, learned representation of the causal relations among events. This kind of knowledge can be perspicuously…
International Nuclear Information System (INIS)
Garcia-Parrado, Alfonso; Sanchez, Miguel
2005-01-01
Recently (Garcia-Parrado and Senovilla 2003 Class. Quantum Grav. 20 625-64) the concept of causal mapping between spacetimes, essentially equivalent in this context to the chronological map defined in abstract chronological spaces, and the related notion of causal structure, have been introduced as new tools to study causality in Lorentzian geometry. In the present paper, these tools are further developed in several directions such as (i) causal mappings-and, thus, abstract chronological ones-do not preserve two levels of the standard hierarchy of causality conditions (however, they preserve the remaining levels as shown in the above reference), (ii) even though global hyperbolicity is a stable property (in the set of all time-oriented Lorentzian metrics on a fixed manifold), the causal structure of a globally hyperbolic spacetime can be unstable against perturbations; in fact, we show that the causal structures of Minkowski and Einstein static spacetimes remain stable, whereas that of de Sitter becomes unstable, (iii) general criteria allow us to discriminate different causal structures in some general spacetimes (e.g. globally hyperbolic, stationary standard); in particular, there are infinitely many different globally hyperbolic causal structures (and thus, different conformal ones) on R 2 (iv) plane waves with the same number of positive eigenvalues in the frequency matrix share the same causal structure and, thus, they have equal causal extensions and causal boundaries
Directory of Open Access Journals (Sweden)
Edgar Beltrán Sánchez
2009-12-01
Full Text Available La sarna polvosa es una enfermedad que decrece la producción de papa. Es causada por el parásito obligado Spongospora subterranea f. sp. subterranea, el cual produce grupos de zoosporas enquistadas llamados quistosoros. Cuando las zoosporas están activas pueden infectar raíces y tubérculos iniciando un nuevo ciclo reproductivo. Para estudiar la influencia de las condiciones de incubación sobre la activación de las zoosporas, suspensiones acuosas de quistosoros fueron incubadas bajo diferentes condiciones. Los quistosoros y las zoosporas activas fueron diariamente contados utilizando microscopio óptico. El mayor número de zoosporas activas se encontró al cuarto día de incubación, mientras que el menor número de quistosoros se registró al quinto día de incubación. Esto sugiere que las zoosporas permanecen activas por un corto periodo. El número de zoosporas activas por quistosoro fue significativamente (PThe powdery scab is a disease that decreases potato production. It is caused by Spongospora subterranea f. sp. subterranea. This obligate parasite produces cystosori, which are groups of encysted zoospores. When these zoospores are active, they can infect roots and tubers initiating a new replication cycle. To investigate the influence of the incubation conditions on the zoospore activation, suspensions of cystosori in water were incubated under different conditions. The cystosori and the active zoospores were daily counted under microscope. The higher number of active zoospores was found after four days of incubation, meanwhile the lower number of cystosori was found after five days of incubation. This suggests that zoospores are active for a short period. The number of active zoospores per cystosorus was significantly (P<0.05 higher in tap water than in distillated water, and in presence of light than in dark. More zoospores per cystosorus were activated at 19 °C than at 5 °C, but potato roots did not have a significant (P<0
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…
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.
Causal Mediation Analysis: Warning! Assumptions Ahead
Keele, Luke
2015-01-01
In policy evaluations, interest may focus on why a particular treatment works. One tool for understanding why treatments work is causal mediation analysis. In this essay, I focus on the assumptions needed to estimate mediation effects. I show that there is no "gold standard" method for the identification of causal mediation effects. In…
A General Approach to Causal Mediation Analysis
Imai, Kosuke; Keele, Luke; Tingley, Dustin
2010-01-01
Traditionally in the social sciences, causal mediation analysis has been formulated, understood, and implemented within the framework of linear structural equation models. We argue and demonstrate that this is problematic for 3 reasons: the lack of a general definition of causal mediation effects independent of a particular statistical model, the…
A Causal Model of Faculty Research Productivity.
Bean, John P.
A causal model of faculty research productivity was developed through a survey of the literature. Models of organizational behavior, organizational effectiveness, and motivation were synthesized into a causal model of productivity. Two general types of variables were assumed to affect individual research productivity: institutional variables and…
Counterfactual overdetermination vs. the causal exclusion problem.
Sparber, Georg
2005-01-01
This paper aims to show that a counterfactual approach to causation is not sufficient to provide a solution to the causal exclusion problem in the form of systematic overdetermination. Taking into account the truthmakers of causal counterfactuals provides a strong argument in favour of the identity of causes in situations of translevel, causation.
Causal Indicators Can Help to Interpret Factors
Bentler, Peter M.
2016-01-01
The latent factor in a causal indicator model is no more than the latent factor of the factor part of the model. However, if the causal indicator variables are well-understood and help to improve the prediction of individuals' factor scores, they can help to interpret the meaning of the latent factor. Aguirre-Urreta, Rönkkö, and Marakas (2016)…
Quasi-Experimental Designs for Causal Inference
Kim, Yongnam; Steiner, Peter
2016-01-01
When randomized experiments are infeasible, quasi-experimental designs can be exploited to evaluate causal treatment effects. The strongest quasi-experimental designs for causal inference are regression discontinuity designs, instrumental variable designs, matching and propensity score designs, and comparative interrupted time series designs. This…
Determining Directional Dependency in Causal Associations
Pornprasertmanit, Sunthud; Little, Todd D.
2012-01-01
Directional dependency is a method to determine the likely causal direction of effect between two variables. This article aims to critique and improve upon the use of directional dependency as a technique to infer causal associations. We comment on several issues raised by von Eye and DeShon (2012), including: encouraging the use of the signs of…
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....... This might lead us to find heterogeneous effects when the true effect is homogenous, or to wrongly estimate not only the magnitude but also the sign of heterogeneous effects. We apply a test for the robustness of heterogeneous causal effects in the face of varying degrees and patterns of selection bias...
Repair of Partly Misspecified Causal Diagrams.
Oates, Chris J; Kasza, Jessica; Simpson, Julie A; Forbes, Andrew B
2017-07-01
Errors in causal diagrams elicited from experts can lead to the omission of important confounding variables from adjustment sets and render causal inferences invalid. In this report, a novel method is presented that repairs a misspecified causal diagram through the addition of edges. These edges are determined using a data-driven approach designed to provide improved statistical efficiency relative to de novo structure learning methods. Our main assumption is that the expert is "directionally informed," meaning that "false" edges provided by the expert would not create cycles if added to the "true" causal diagram. The overall procedure is cast as a preprocessing technique that is agnostic to subsequent causal inferences. Results based on simulated data and data derived from an observational cohort illustrate the potential for data-assisted elicitation in epidemiologic applications. See video abstract at, http://links.lww.com/EDE/B208.
Causality, spin, and equal-time commutators
International Nuclear Information System (INIS)
Abdel-Rahman, A.M.
1975-01-01
We study the causality constraints on the structure of the Lorentz-antisymmetric component of the commutator of two conserved isovector currents between fermion states of equal momenta. We discuss the sum rules that follow from causality and scaling, using the recently introduced refined infinite-momentum technique. The complete set of sum rules is found to include the spin-dependent fixed-mass sum rules obtained from light-cone commutators. The causality and scaling restrictions on the structure of the electromagnetic equal-time commutators are discussed, and it is found, in particular, that causality requires the spin-dependent part of the matrix element for the time-space electromagnetic equal-time commutator to vanish identically. It is also shown, in comparison with the electromagnetic case, that the corresponding matrix element for the time-space isovector current equal-time commutator is required, by causality, to have isospin-antisymmetric tensor and scalar operator Schwinger terms
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
Causality violations in Lovelock theories
Brustein, Ram; Sherf, Yotam
2018-04-01
Higher-derivative gravity theories, such as Lovelock theories, generalize Einstein's general relativity (GR). Modifications to GR are expected when curvatures are near Planckian and appear in string theory or supergravity. But can such theories describe gravity on length scales much larger than the Planck cutoff length scale? Here we find causality constraints on Lovelock theories that arise from the requirement that the equations of motion (EOM) of perturbations be hyperbolic. We find a general expression for the "effective metric" in field space when Lovelock theories are perturbed around some symmetric background solution. In particular, we calculate explicitly the effective metric for a general Lovelock theory perturbed around cosmological Friedman-Robertson-Walker backgrounds and for some specific cases when perturbed around Schwarzschild-like solutions. For the EOM to be hyperbolic, the effective metric needs to be Lorentzian. We find that, unlike for GR, the effective metric is generically not Lorentzian when the Lovelock modifications are significant. So, we conclude that Lovelock theories can only be considered as perturbative extensions of GR and not as truly modified theories of gravity. We compare our results to those in the literature and find that they agree with and reproduce the results of previous studies.
Causal localizations in relativistic quantum mechanics
Castrigiano, Domenico P. L.; Leiseifer, Andreas D.
2015-07-01
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.
Causal inference, probability theory, and graphical insights.
Baker, Stuart G
2013-11-10
Causal inference from observational studies is a fundamental topic in biostatistics. The causal graph literature typically views probability theory as insufficient to express causal concepts in observational studies. In contrast, the view here is that probability theory is a desirable and sufficient basis for many topics in causal inference for the following two reasons. First, probability theory is generally more flexible than causal graphs: Besides explaining such causal graph topics as M-bias (adjusting for a collider) and bias amplification and attenuation (when adjusting for instrumental variable), probability theory is also the foundation of the paired availability design for historical controls, which does not fit into a causal graph framework. Second, probability theory is the basis for insightful graphical displays including the BK-Plot for understanding Simpson's paradox with a binary confounder, the BK2-Plot for understanding bias amplification and attenuation in the presence of an unobserved binary confounder, and the PAD-Plot for understanding the principal stratification component of the paired availability design. Published 2013. This article is a US Government work and is in the public domain in the USA.
Can chance cause cancer? A causal consideration.
Stensrud, Mats Julius; Strohmaier, Susanne; Valberg, Morten; Aalen, Odd Olai
2017-04-01
The role of randomness, environment and genetics in cancer development is debated. We approach the discussion by using the potential outcomes framework for causal inference. By briefly considering the underlying assumptions, we suggest that the antagonising views arise due to estimation of substantially different causal effects. These effects may be hard to interpret, and the results cannot be immediately compared. Indeed, it is not clear whether it is possible to define a causal effect of chance at all. Copyright © 2017 Elsevier Ltd. All rights reserved.
Dual Causality and the Autonomy of Biology.
Bock, Walter J
2017-03-01
Ernst Mayr's concept of dual causality in biology with the two forms of causes (proximate and ultimate) continues to provide an essential foundation for the philosophy of biology. They are equivalent to functional (=proximate) and evolutionary (=ultimate) causes with both required for full biological explanations. The natural sciences can be classified into nomological, historical nomological and historical dual causality, the last including only biology. Because evolutionary causality is unique to biology and must be included for all complete biological explanations, biology is autonomous from the physical sciences.
Mathematical implications of Einstein-Weyl causality
International Nuclear Information System (INIS)
Borchers, H.J.; Sen, R.N.
2006-01-01
The present work is the first systematic attempt at answering the following fundamental question: what mathematical structures does Einstein-Weyl causality impose on a point-set that has no other previous structure defined on it? The authors propose an axiomatization of Einstein-Weyl causality (inspired by physics), and investigate the topological and uniform structures that it implies. Their final result is that a causal space is densely embedded in one that is locally a differentiable manifold. The mathematical level required of the reader is that of the graduate student in mathematical physics. (orig.)
The mistake of the causal relationship
Directory of Open Access Journals (Sweden)
О. Д. Комаров
2015-03-01
Full Text Available The article deals with issues of the mistake of the causal relationship. The modern criminal law science approaches to the content of the mistake of the causal relationship and its significance to the qualification of the crime are described. It is proved that in cases of dolus generalis different mental attitude of the guilty person to two separate acts of his conduct exist. Consequently, in mentioned above cases mistake of the causal relationship does not have place. The rules of qualification of the crimes commited with the mistake of causation and in cases of dolus generalis are proposed .
Assessing students' beliefs, emotions and causal attribution ...
African Journals Online (AJOL)
Keywords: academic emotion; belief; causal attribution; statistical validation; students' conceptions of learning ... Sadi & Lee, 2015), through their effect on motivation and learning strategies .... to understand why they may or may not be doing.
Granger Causality Testing with Intensive Longitudinal Data.
Molenaar, Peter C M
2018-06-01
The availability of intensive longitudinal data obtained by means of ambulatory assessment opens up new prospects for prevention research in that it allows the derivation of subject-specific dynamic networks of interacting variables by means of vector autoregressive (VAR) modeling. The dynamic networks thus obtained can be subjected to Granger causality testing in order to identify causal relations among the observed time-dependent variables. VARs have two equivalent representations: standard and structural. Results obtained with Granger causality testing depend upon which representation is chosen, yet no criteria exist on which this important choice can be based. A new equivalent representation is introduced called hybrid VARs with which the best representation can be chosen in a data-driven way. Partial directed coherence, a frequency-domain statistic for Granger causality testing, is shown to perform optimally when based on hybrid VARs. An application to real data is provided.
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.
Selecting appropriate cases when tracing causal mechanisms
DEFF Research Database (Denmark)
Beach, Derek; Pedersen, Rasmus Brun
2016-01-01
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 unpack the causal mechanism between X and Y, enabling causal inferences to be made because empirical evidence is provided for how the mechanism actually operated in a particular case. The in-depth, within-case tracing of how mechanisms operate in particular cases produces what can be termed mechanistic...
Rate-Agnostic (Causal) Structure Learning.
Plis, Sergey; Danks, David; Freeman, Cynthia; Calhoun, Vince
2015-12-01
Causal structure learning from time series data is a major scientific challenge. Extant algorithms assume that measurements occur sufficiently quickly; more precisely, they assume approximately equal system and measurement timescales. In many domains, however, measurements occur at a significantly slower rate than the underlying system changes, but the size of the timescale mismatch is often unknown. This paper develops three causal structure learning algorithms, each of which discovers all dynamic causal graphs that explain the observed measurement data, perhaps given undersampling. That is, these algorithms all learn causal structure in a "rate-agnostic" manner: they do not assume any particular relation between the measurement and system timescales. We apply these algorithms to data from simulations to gain insight into the challenge of undersampling.
K-causality and degenerate spacetimes
Dowker, H. F.; Garcia, R. S.; Surya, S.
2000-11-01
The causal relation K+ was introduced by Sorkin and Woolgar to extend the standard causal analysis of C2 spacetimes to those that are only C0. Most of their results also hold true in the case of metrics with degeneracies which are C0 but vanish at isolated points. In this paper we seek to examine K+ explicitly in the case of topology-changing `Morse histories' which contain degeneracies. We first demonstrate some interesting features of this relation in globally Lorentzian spacetimes. In particular, we show that K+ is robust and the Hawking and Sachs characterization of causal continuity translates into a natural condition in terms of K+. We then examine K+ in topology-changing Morse spacetimes with the degenerate points excised and then for the Morse histories in which the degenerate points are reinstated. We find further characterizations of causal continuity in these cases.
Efficient nonparametric estimation of causal mediation effects
Chan, K. C. G.; Imai, K.; Yam, S. C. P.; Zhang, Z.
2016-01-01
An essential goal of program evaluation and scientific research is the investigation of causal mechanisms. Over the past several decades, causal mediation analysis has been used in medical and social sciences to decompose the treatment effect into the natural direct and indirect effects. However, all of the existing mediation analysis methods rely on parametric modeling assumptions in one way or another, typically requiring researchers to specify multiple regression models involving the treat...
Inference of Boundaries in Causal Sets
Cunningham, William
2017-01-01
We investigate the extrinsic geometry of causal sets in $(1+1)$-dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons-Hawking-York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space...
The Continuum Limit of Causal Fermion Systems
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...
Causal strength induction from time series data.
Soo, Kevin W; Rottman, Benjamin M
2018-04-01
One challenge when inferring the strength of cause-effect relations from time series data is that the cause and/or effect can exhibit temporal trends. If temporal trends are not accounted for, a learner could infer that a causal relation exists when it does not, or even infer that there is a positive causal relation when the relation is negative, or vice versa. We propose that learners use a simple heuristic to control for temporal trends-that they focus not on the states of the cause and effect at a given instant, but on how the cause and effect change from one observation to the next, which we call transitions. Six experiments were conducted to understand how people infer causal strength from time series data. We found that participants indeed use transitions in addition to states, which helps them to reach more accurate causal judgments (Experiments 1A and 1B). Participants use transitions more when the stimuli are presented in a naturalistic visual format than a numerical format (Experiment 2), and the effect of transitions is not driven by primacy or recency effects (Experiment 3). Finally, we found that participants primarily use the direction in which variables change rather than the magnitude of the change for estimating causal strength (Experiments 4 and 5). Collectively, these studies provide evidence that people often use a simple yet effective heuristic for inferring causal strength from time series data. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Kant on causal laws and powers.
Henschen, Tobias
2014-12-01
The aim of the paper is threefold. Its first aim is to defend Eric Watkins's claim that for Kant, a cause is not an event but a causal power: a power that is borne by a substance, and that, when active, brings about its effect, i.e. a change of the states of another substance, by generating a continuous flow of intermediate states of that substance. The second aim of the paper is to argue against Watkins that the Kantian concept of causal power is not the pre-critical concept of real ground but the category of causality, and that Kant holds with Hume that causal laws cannot be inferred non-inductively (that he accordingly has no intention to show in the Second analogy or elsewhere that events fall under causal laws). The third aim of the paper is to compare the Kantian position on causality with central tenets of contemporary powers ontology: it argues that unlike the variants endorsed by contemporary powers theorists, the Kantian variants of these tenets are resistant to objections that neo-Humeans raise to these tenets.
Causality violation, gravitational shockwaves and UV completion
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Hollowood, Timothy J.; Shore, Graham M. [Department of Physics, Swansea University,Swansea, SA2 8PP (United Kingdom)
2016-03-18
The effective actions describing the low-energy dynamics of QFTs involving gravity generically exhibit causality violations. These may take the form of superluminal propagation or Shapiro time advances and allow the construction of “time machines”, i.e. spacetimes admitting closed non-spacelike curves. Here, we discuss critically whether such causality violations may be used as a criterion to identify unphysical effective actions or whether, and how, causality problems may be resolved by embedding the action in a fundamental, UV complete QFT. We study in detail the case of photon scattering in an Aichelburg-Sexl gravitational shockwave background and calculate the phase shifts in QED for all energies, demonstrating their smooth interpolation from the causality-violating effective action values at low-energy to their manifestly causal high-energy limits. At low energies, these phase shifts may be interpreted as backwards-in-time coordinate jumps as the photon encounters the shock wavefront, and we illustrate how the resulting causality problems emerge and are resolved in a two-shockwave time machine scenario. The implications of our results for ultra-high (Planck) energy scattering, in which graviton exchange is modelled by the shockwave background, are highlighted.
Illness causal beliefs in Turkish immigrants
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Klimidis Steven
2007-07-01
Full Text Available Abstract Background People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Methods Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Results Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Conclusion Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes
Illness causal beliefs in Turkish immigrants.
Minas, Harry; Klimidis, Steven; Tuncer, Can
2007-07-24
People hold a wide variety of beliefs concerning the causes of illness. Such beliefs vary across cultures and, among immigrants, may be influenced by many factors, including level of acculturation, gender, level of education, and experience of illness and treatment. This study examines illness causal beliefs in Turkish-immigrants in Australia. Causal beliefs about somatic and mental illness were examined in a sample of 444 members of the Turkish population of Melbourne. The socio-demographic characteristics of the sample were broadly similar to those of the Melbourne Turkish community. Five issues were examined: the structure of causal beliefs; the relative frequency of natural, supernatural and metaphysical beliefs; ascription of somatic, mental, or both somatic and mental conditions to the various causes; the correlations of belief types with socio-demographic, modernizing and acculturation variables; and the relationship between causal beliefs and current illness. Principal components analysis revealed two broad factors, accounting for 58 percent of the variation in scores on illness belief scales, distinctly interpretable as natural and supernatural beliefs. Second, beliefs in natural causes were more frequent than beliefs in supernatural causes. Third, some causal beliefs were commonly linked to both somatic and mental conditions while others were regarded as more specific to either somatic or mental disorders. Last, there was a range of correlations between endorsement of belief types and factors defining heterogeneity within the community, including with demographic factors, indicators of modernizing and acculturative processes, and the current presence of illness. Results supported the classification of causal beliefs proposed by Murdock, Wilson & Frederick, with a division into natural and supernatural causes. While belief in natural causes is more common, belief in supernatural causes persists despite modernizing and acculturative influences. Different
Entanglement entropy in causal set theory
Sorkin, Rafael D.; Yazdi, Yasaman K.
2018-04-01
Entanglement entropy is now widely accepted as having deep connections with quantum gravity. It is therefore desirable to understand it in the context of causal sets, especially since they provide in a natural manner the UV cutoff needed to render entanglement entropy finite. Formulating a notion of entanglement entropy in a causal set is not straightforward because the type of canonical hypersurface-data on which its definition typically relies is not available. Instead, we appeal to the more global expression given in Sorkin (2012 (arXiv:1205.2953)) which, for a Gaussian scalar field, expresses the entropy of a spacetime region in terms of the field’s correlation function within that region (its ‘Wightman function’ W(x, x') ). Carrying this formula over to the causal set, one obtains an entropy which is both finite and of a Lorentz invariant nature. We evaluate this global entropy-expression numerically for certain regions (primarily order-intervals or ‘causal diamonds’) within causal sets of 1 + 1 dimensions. For the causal-set counterpart of the entanglement entropy, we obtain, in the first instance, a result that follows a (spacetime) volume law instead of the expected (spatial) area law. We find, however, that one obtains an area law if one truncates the commutator function (‘Pauli–Jordan operator’) and the Wightman function by projecting out the eigenmodes of the Pauli–Jordan operator whose eigenvalues are too close to zero according to a geometrical criterion which we describe more fully below. In connection with these results and the questions they raise, we also study the ‘entropy of coarse-graining’ generated by thinning out the causal set, and we compare it with what one obtains by similarly thinning out a chain of harmonic oscillators, finding the same, ‘universal’ behaviour in both cases.
The Relevance of Causal Social Construction
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Marques Teresa
2017-02-01
Full Text Available Social constructionist claims are surprising and interesting when they entail that presumably natural kinds are in fact socially constructed. The claims are interesting because of their theoretical and political importance. Authors like Díaz-León argue that constitutive social construction is more relevant for achieving social justice than causal social construction. This paper challenges this claim. Assuming there are socially salient groups that are discriminated against, the paper presents a dilemma: if there were no constitutively constructed social kinds, the causes of the discrimination of existing social groups would have to be addressed, and understanding causal social construction would be relevant to achieve social justice. On the other hand, not all possible constitutively socially constructed kinds are actual social kinds. If an existing social group is constitutively constructed as a social kind K, the fact that it actually exists as a K has social causes. Again, causal social construction is relevant. The paper argues that (i for any actual social kind X, if X is constitutively socially constructed as K, then it is also causally socially constructed; and (ii causal social construction is at least as relevant as constitutive social construction for concerns of social justice. For illustration, I draw upon two phenomena that are presumed to contribute towards the discrimination of women: (i the poor performance effects of stereotype threat, and (ii the silencing effects of gendered language use.
Preschoolers prefer to learn causal information
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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.
Gravity and matter in causal set theory
International Nuclear Information System (INIS)
Sverdlov, Roman; Bombelli, Luca
2009-01-01
The goal of this paper is to propose an approach to the formulation of dynamics for causal sets and coupled matter fields. We start from the continuum version of the action for a Klein-Gordon field coupled to gravity, and rewrite it first using quantities that have a direct correspondent in the case of a causal set, namely volumes, causal relations and timelike lengths, as variables to describe the geometry. In this step, the local Lagrangian density L(f;x) for a set of fields f is recast into a quasilocal expression L 0 (f;p,q) that depends on pairs of causally related points pprq and is a function of the values of f in the Alexandrov set defined by those points, and whose limit as p and q approach a common point x is L(f;x). We then describe how to discretize L 0 (f;p,q) and use it to define a causal-set-based action.
A frequency domain subspace algorithm for mixed causal, anti-causal LTI systems
Fraanje, Rufus; Verhaegen, Michel; Verdult, Vincent; Pintelon, Rik
2003-01-01
The paper extends the subspacc identification method to estimate state-space models from frequency response function (FRF) samples, proposed by McKelvey et al. (1996) for mixed causal/anti-causal systems, and shows that other frequency domain subspace algorithms can be extended similarly. The method
Causal inheritance in plane wave quotients
International Nuclear Information System (INIS)
Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.
2003-01-01
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
Inference of boundaries in causal sets
Cunningham, William J.
2018-05-01
We investigate the extrinsic geometry of causal sets in (1+1) -dimensional Minkowski spacetime. The properties of boundaries in an embedding space can be used not only to measure observables, but also to supplement the discrete action in the partition function via discretized Gibbons–Hawking–York boundary terms. We define several ways to represent a causal set using overlapping subsets, which then allows us to distinguish between null and non-null bounding hypersurfaces in an embedding space. We discuss algorithms to differentiate between different types of regions, consider when these distinctions are possible, and then apply the algorithms to several spacetime regions. Numerical results indicate the volumes of timelike boundaries can be measured to within 0.5% accuracy for flat boundaries and within 10% accuracy for highly curved boundaries for medium-sized causal sets with N = 214 spacetime elements.
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.
Spatial hypersurfaces in causal set cosmology
International Nuclear Information System (INIS)
Major, Seth A; Rideout, David; Surya, Sumati
2006-01-01
Within the causal set approach to quantum gravity, a discrete analogue of a spacelike region is a set of unrelated elements, or an antichain. In the continuum approximation of the theory, a moment-of-time hypersurface is well represented by an inextendible antichain. We construct a richer structure corresponding to a thickening of this antichain containing non-trivial geometric and topological information. We find that covariant observables can be associated with such thickened antichains and transitions between them, in classical sequential growth models of causal sets. This construction highlights the difference between the covariant measure on causal set cosmology and the standard sum-over-histories approach: the measure is assigned to completed histories rather than to histories on a restricted spacetime region. The resulting re-phrasing of the sum-over-histories may be fruitful in other approaches to quantum gravity
Testing the causal theory of reference.
Domaneschi, Filippo; Vignolo, Massimiliano; Di Paola, Simona
2017-04-01
Theories of reference are a crucial research topic in analytic philosophy. Since the publication of Kripke's Naming and Necessity, most philosophers have endorsed the causal/historical theory of reference. The goal of this paper is twofold: (i) to discuss a method for testing experimentally the causal theory of reference for proper names by investigating linguistic usage and (ii) to present the results from two experiments conducted with that method. Data collected in our experiments confirm the causal theory of reference for people proper names and for geographical proper names. A secondary but interesting result is that the semantic domain affects reference assignment: while with people proper names speakers tend to assign the semantic reference, with geographical proper names they are prompted to assign the speaker's reference. Copyright © 2016 Elsevier B.V. All rights reserved.
Bulk viscous cosmology with causal transport theory
International Nuclear Information System (INIS)
Piattella, Oliver F.; Fabris, Júlio C.; Zimdahl, Winfried
2011-01-01
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 || cb 2 ∼ −8
Causal inheritance in plane wave quotients
Hubeny, Veronika E.; Rangamani, Mukund; Ross, Simon F.
2004-01-01
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 space-time 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 space-times. We show that all other quotients preserve stable causality.
Neural correlates of continuous causal word generation.
Wende, Kim C; Straube, Benjamin; Stratmann, Mirjam; Sommer, Jens; Kircher, Tilo; Nagels, Arne
2012-09-01
Causality provides a natural structure for organizing our experience and language. Causal reasoning during speech production is a distinct aspect of verbal communication, whose related brain processes are yet unknown. The aim of the current study was to investigate the neural mechanisms underlying the continuous generation of cause-and-effect coherences during overt word production. During fMRI data acquisition participants performed three verbal fluency tasks on identical cue words: A novel causal verbal fluency task (CVF), requiring the production of multiple reasons to a given cue word (e.g. reasons for heat are fire, sun etc.), a semantic (free association, FA, e.g. associations with heat are sweat, shower etc.) and a phonological control task (phonological verbal fluency, PVF, e.g. rhymes with heat are meat, wheat etc.). We found that, in contrast to PVF, both CVF and FA activated a left lateralized network encompassing inferior frontal, inferior parietal and angular regions, with further bilateral activation in middle and inferior as well as superior temporal gyri and the cerebellum. For CVF contrasted against FA, we found greater bold responses only in the left middle frontal cortex. Large overlaps in the neural activations during free association and causal verbal fluency indicate that the access to causal relationships between verbal concepts is at least partly based on the semantic neural network. The selective activation in the left middle frontal cortex for causal verbal fluency suggests that distinct neural processes related to cause-and-effect-relations are associated with the recruitment of middle frontal brain areas. Copyright © 2012 Elsevier Inc. All rights reserved.
BOLD Granger causality reflects vascular anatomy.
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J Taylor Webb
Full Text Available A number of studies have tried to exploit subtle phase differences in BOLD time series to resolve the order of sequential activation of brain regions, or more generally the ability of signal in one region to predict subsequent signal in another region. More recently, such lag-based measures have been applied to investigate directed functional connectivity, although this application has been controversial. We attempted to use large publicly available datasets (FCON 1000, ADHD 200, Human Connectome Project to determine whether consistent spatial patterns of Granger Causality are observed in typical fMRI data. For BOLD datasets from 1,240 typically developing subjects ages 7-40, we measured Granger causality between time series for every pair of 7,266 spherical ROIs covering the gray matter and 264 seed ROIs at hubs of the brain's functional network architecture. Granger causality estimates were strongly reproducible for connections in a test and replication sample (n=620 subjects for each group, as well as in data from a single subject scanned repeatedly, both during resting and passive video viewing. The same effect was even stronger in high temporal resolution fMRI data from the Human Connectome Project, and was observed independently in data collected during performance of 7 task paradigms. The spatial distribution of Granger causality reflected vascular anatomy with a progression from Granger causality sources, in Circle of Willis arterial inflow distributions, to sinks, near large venous vascular structures such as dural venous sinuses and at the periphery of the brain. Attempts to resolve BOLD phase differences with Granger causality should consider the possibility of reproducible vascular confounds, a problem that is independent of the known regional variability of the hemodynamic response.
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....
Morse theory on timelike and causal curves
International Nuclear Information System (INIS)
Everson, J.; Talbot, C.J.
1976-01-01
It is shown that the set of timelike curves in a globally hyperbolic space-time manifold can be given the structure of a Hilbert manifold under a suitable definition of 'timelike.' The causal curves are the topological closure of this manifold. The Lorentzian energy (corresponding to Milnor's energy, except that the Lorentzian inner product is used) is shown to be a Morse function for the space of causal curves. A fixed end point index theorem is obtained in which a lower bound for the index of the Hessian of the Lorentzian energy is given in terms of the sum of the orders of the conjugate points between the end points. (author)
Inferring causality from noisy time series data
DEFF Research Database (Denmark)
Mønster, Dan; Fusaroli, Riccardo; Tylén, Kristian
2016-01-01
Convergent Cross-Mapping (CCM) has shown high potential to perform causal inference in the absence of models. We assess the strengths and weaknesses of the method by varying coupling strength and noise levels in coupled logistic maps. We find that CCM fails to infer accurate coupling strength...... and 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...
Ocorrência da ferrugem da videira em Minas Gerais
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Adelica Aparecida Xavier
2012-03-01
Full Text Available A ferrugem da videira causada por Phakopsora euvitis Ono constitui-se numa ameaça às regiões produtoras de uva em função do potencial destrutivo da planta. A doença foi detectada no Brasil, pela primeira vez, em 2001. Atualmente, ela ocorre no Paraná, Mato Grosso do Sul, São Paulo, Rio Grande do Sul, Mato Grosso, Roraima, Espírito Santo e Santa Catarina. Em abril de 2010, observaram-se na estação experimental da Unimontes, Janaúba, Minas Gerais, plantas da cv. Niágara rosada com sintomas típicos da doença. A análise dos sintomas e a caracterização dos urediniósporos sésseis, levemente equinulados, com formato oval, ou elipsoide formado em urédias subepidérmicas na origem, inrompentes e com paráfises circundantes dorsalmente, levaram à diagnose de Phakopsora euvitis como o agente causal da doença. Este é o primeiro relato da doença no Estado de Minas Gerais.
Causal Meta-Analysis : Methodology and Applications
Bax, L.J.
2009-01-01
Meta-analysis is a statistical method to summarize research data from multiple studies in a quantitative manner. This dissertation addresses a number of methodological topics in causal meta-analysis and reports the development and validation of meta-analysis software. In the first (methodological)
Information-causality and extremal tripartite correlations
International Nuclear Information System (INIS)
Yang, Tzyh Haur; Cavalcanti, Daniel; Almeida, Mafalda L; Teo, Colin; Scarani, Valerio
2012-01-01
We study the principle of information-causality (IC) in the presence of extremal no-signaling correlations on a tripartite scenario. We prove that all, except one, of the non-local correlations lead to violation of IC. The remaining non-quantum correlation is shown to satisfy any bipartite physical principle. (paper)
The causal structure of utility conditionals.
Bonnefon, Jean-François; Sloman, Steven A
2013-01-01
The psychology of reasoning is increasingly considering agents' values and preferences, achieving greater integration with judgment and decision making, social cognition, and moral reasoning. Some of this research investigates utility conditionals, ''if p then q'' statements where the realization of p or q or both is valued by some agents. Various approaches to utility conditionals share the assumption that reasoners make inferences from utility conditionals based on the comparison between the utility of p and the expected utility of q. This article introduces a new parameter in this analysis, the underlying causal structure of the conditional. Four experiments showed that causal structure moderated utility-informed conditional reasoning. These inferences were strongly invited when the underlying structure of the conditional was causal, and significantly less so when the underlying structure of the conditional was diagnostic. This asymmetry was only observed for conditionals in which the utility of q was clear, and disappeared when the utility of q was unclear. Thus, an adequate account of utility-informed inferences conditional reasoning requires three components: utility, probability, and causal structure. Copyright © 2012 Cognitive Science Society, Inc.
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…
Inductive reasoning about causally transmitted properties.
Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B
2008-11-01
Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.
Exploring Causal Models of Educational Achievement.
Parkerson, Jo Ann; And Others
1984-01-01
This article evaluates five causal model of educational productivity applied to learning science in a sample of 882 fifth through eighth graders. Each model explores the relationship between achievement and a combination of eight constructs: home environment, peer group, media, ability, social environment, time on task, motivation, and…
Sequential causal learning in humans and rats
Lu, H.; Rojas, R.R.; Beckers, T.; Yuille, A.; Love, B.C.; McRae, K.; Sloutsky, V.M.
2008-01-01
Recent experiments (Beckers, De Houwer, Pineño, & Miller, 2005;Beckers, Miller, De Houwer, & Urushihara, 2006) have shown that pretraining with unrelated cues can dramatically influence the performance of humans in a causal learning paradigm and rats in a standard Pavlovian conditioning paradigm.
The Causal Foundations of Structural Equation Modeling
2012-02-16
and Baumrind (1993).” This, together with the steady influx of statisticians into the field, has left SEM re- searchers in a quandary about the...considerations. Journal of Personality and Social Psychology 51 1173–1182. Baumrind , D. (1993). Specious causal attributions in social sciences: The
Causal Measurement Models: Can Criticism Stimulate Clarification?
Markus, Keith A.
2016-01-01
In their 2016 work, Aguirre-Urreta et al. provided a contribution to the literature on causal measurement models that enhances clarity and stimulates further thinking. Aguirre-Urreta et al. presented a form of statistical identity involving mapping onto the portion of the parameter space involving the nomological net, relationships between the…
A quantum probability model of causal reasoning
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Jennifer S Trueblood
2012-05-01
Full Text Available People can often outperform statistical methods and machine learning algorithms in situations that involve making inferences about the relationship between causes and effects. While people are remarkably good at causal reasoning in many situations, there are several instances where they deviate from expected responses. This paper examines three situations where judgments related to causal inference problems produce unexpected results and describes a quantum inference model based on the axiomatic principles of quantum probability theory that can explain these effects. Two of the three phenomena arise from the comparison of predictive judgments (i.e., the conditional probability of an effect given a cause with diagnostic judgments (i.e., the conditional probability of a cause given an effect. The third phenomenon is a new finding examining order effects in predictive causal judgments. The quantum inference model uses the notion of incompatibility among different causes to account for all three phenomena. Psychologically, the model assumes that individuals adopt different points of view when thinking about different causes. The model provides good fits to the data and offers a coherent account for all three causal reasoning effects thus proving to be a viable new candidate for modeling human judgment.
A Causal Model of Faculty Turnover Intentions.
Smart, John C.
1990-01-01
A causal model assesses the relative influence of individual attributes, institutional characteristics, contextual-work environment variables, and multiple measures of job satisfaction on faculty intentions to leave their current institutions. Factors considered include tenure status, age, institutional status, governance style, organizational…
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
Probable autoimmune causal relationship between periodontitis and ...
African Journals Online (AJOL)
Periodontitis is a multifactorial disease with microbial dental plaque as the initiator of periodontal disease. However, the manifestation and progression of the disease is influenced by a wide variety of determinants and factors. The strongest type of causal relationship is the association of systemic and periodontal disease.
On minimizers of causal variational principles
International Nuclear Information System (INIS)
Schiefeneder, Daniela
2011-01-01
Causal variational principles are a class of nonlinear minimization problems which arise in a formulation of relativistic quantum theory referred to as the fermionic projector approach. This thesis is devoted to a numerical and analytic study of the minimizers of a general class of causal variational principles. We begin with a numerical investigation of variational principles for the fermionic projector in discrete space-time. It is shown that for sufficiently many space-time points, the minimizing fermionic projector induces non-trivial causal relations on the space-time points. We then generalize the setting by introducing a class of causal variational principles for measures on a compact manifold. In our main result we prove under general assumptions that the support of a minimizing measure is either completely timelike, or it is singular in the sense that its interior is empty. In the examples of the circle, the sphere and certain flag manifolds, the general results are supplemented by a more detailed analysis of the minimizers. (orig.)
Causality and analyticity in quantum fields theory
International Nuclear Information System (INIS)
Iagolnitzer, D.
1992-01-01
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.)
Causality and Time in Historical Institutionalism
DEFF Research Database (Denmark)
Mahoney, James; Mohamedali, Khairunnisa; Nguyen, Christoph
2016-01-01
This chapter explores the dual concern with causality and time in historical institutionalism using a graphical approach. The analysis focuses on three concepts that are central to this field: critical junctures, gradual change, and path dependence. The analysis makes explicit and formal the logi...
Inductive Reasoning about Causally Transmitted Properties
Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D.; Tenenbaum, Joshua B.
2008-01-01
Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates'…
Black Hole Complementarity and Violation of Causality
Rozenblit, Moshe
2017-01-01
Analysis of a massive shell collapsing on a solid sphere shows that black hole complementarity (BHC) violates causality in its effort to save information conservation. In particular, this note describes a hypothetical contraption based on BHC that would allow the transfer of information from the future to the present.
Encoding dependence in Bayesian causal networks
Bayesian networks (BNs) represent complex, uncertain spatio-temporal dynamics by propagation of conditional probabilities between identifiable states with a testable causal interaction model. Typically, they assume random variables are discrete in time and space with a static network structure that ...
Causality in the semantics of Esterel : revisited
Mousavi, M.R.; Klin, B.; Sobocinski, P.
2010-01-01
We re-examine the challenges concerning causality in the semantics of Esterel and show that they pertain to the known issues in the semantics of Structured Operational Semantics with negative premises. We show that the solutions offered for the semantics of SOS also provide answers to the semantic
Scalar field Green functions on causal sets
International Nuclear Information System (INIS)
Nomaan Ahmed, S; Surya, Sumati; Dowker, Fay
2017-01-01
We examine the validity and scope of Johnston’s models for scalar field retarded Green functions on causal sets in 2 and 4 dimensions. As in the continuum, the massive Green function can be obtained from the massless one, and hence the key task in causal set theory is to first identify the massless Green function. We propose that the 2d model provides a Green function for the massive scalar field on causal sets approximated by any topologically trivial 2-dimensional spacetime. We explicitly demonstrate that this is indeed the case in a Riemann normal neighbourhood. In 4d the model can again be used to provide a Green function for the massive scalar field in a Riemann normal neighbourhood which we compare to Bunch and Parker’s continuum Green function. We find that the same prescription can also be used for de Sitter spacetime and the conformally flat patch of anti-de Sitter spacetime. Our analysis then allows us to suggest a generalisation of Johnston’s model for the Green function for a causal set approximated by 3-dimensional flat spacetime. (paper)
Are bruxism and the bite causally related?
Lobbezoo, F.; Ahlberg, J.; Manfredini, D.; Winocur, E.
2012-01-01
In the dental profession, the belief that bruxism and dental (mal-)occlusion (‘the bite’) are causally related is widespread. The aim of this review was to critically assess the available literature on this topic. A PubMed search of the English-language literature, using the query ‘Bruxism [Majr
Causality relationship between energy demand and economic ...
African Journals Online (AJOL)
This paper attempts to examine the causal relationship between electricity demand and economic growth in Nigeria using data for 1970 – 2003. The study uses the Johansen cointegration VAR approach. The ADF and Phillips – Perron test statistics were used to test for stationarity of the data. It was found that the data were ...
Does Causality Matter More Now? Increase in the Proportion of Causal Language in English Texts.
Iliev, Rumen; Axelrod, Robert
2016-05-01
The vast majority of the work on culture and cognition has focused on cross-cultural comparisons, largely ignoring the dynamic aspects of culture. In this article, we provide a diachronic analysis of causal cognition over time. We hypothesized that the increased role of education, science, and technology in Western societies should be accompanied by greater attention to causal connections. To test this hypothesis, we compared word frequencies in English texts from different time periods and found an increase in the use of causal language of about 40% over the past two centuries. The observed increase was not attributable to general language effects or to changing semantics of causal words. We also found that there was a consistent difference between the 19th and the 20th centuries, and that the increase happened mainly in the 20th century. © The Author(s) 2016.
Causal knowledge and the development of inductive reasoning.
Bright, Aimée K; Feeney, Aidan
2014-06-01
We explored the development of sensitivity to causal relations in children's inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey→predator) or diagnostic (predator→prey), and the property that participants reasoned about established either a taxonomic or causal context. There was a causal asymmetry effect across all age groups, with more causal choices when the causal link was predictive than when it was diagnostic. Furthermore, context-sensitive causal reasoning showed a curvilinear development, with causal choices being most frequent for 8-year-olds regardless of context. Causal inductions decreased thereafter because 12-year-olds and adults made more taxonomic choices when reasoning in the taxonomic context. These findings suggest that simple causal relations may often be the default knowledge structure in young children's inductive reasoning, that sensitivity to causal direction is present early on, and that children over-generalize their causal knowledge when reasoning. Copyright © 2013 Elsevier Inc. All rights reserved.
The causal link between energy and output growth: Evidence from Markov switching Granger causality
International Nuclear Information System (INIS)
Kandemir Kocaaslan, Ozge
2013-01-01
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
Elements of Causal Inference: Foundations and Learning Algorithms
DEFF Research Database (Denmark)
Peters, Jonas Martin; Janzing, Dominik; Schölkopf, Bernhard
A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning......A concise and self-contained introduction to causal inference, increasingly important in data science and machine learning...
The causal relationship between Foreign Direct Investment (FDI ...
African Journals Online (AJOL)
The causal relationship between Foreign Direct Investment (FDI) and the ... of selected west African countries: Panel ARDL/Granger Causality Analysis. ... among this developing countries and an important revelation for policy implication.
The Hankel transform of causal distributions
Directory of Open Access Journals (Sweden)
Manuel A. Aguirre T.
2012-03-01
Full Text Available In this note we evaluate the unidimensional distributional Hankel transform of \\dfrac{x^{\\alpha-1}_{+}}{\\Gamma^{\\alpha}},\\dfrac{x^{\\alpha-1}_{-}}{\\Gamma^{\\alpha}},dfrac{|x|^{\\alpha-1}}{\\Gamma^{\\frac{\\alpha}{2}}},dfrac{|x|^{\\alpha-1}sgn(x}{\\Gamma^{\\frac{\\alpha +1}{2}}} and (x± i0^{\\alpha-1} and then we extend the formulae to certain kinds of n-dimensional distributions calles "causal" and "anti-causal" distributions. We evaluate the distributional Handel transform of \\dfrac{(m^2+P^{\\alpha -1}_{-}}{\\Gamma^{(\\alpha} }, \\dfrac{|m^2+P|^{\\alpha -1}_{-}}{\\Gamma^{(\\frac{\\alpha}{2}}}, \\dfrac{|m^2+P|^{\\alpha -1}sgn(m^2+P}{\\Gamma (\\frac{\\alpha +1}{2 }} and (m^2+P±i0^{\\alpha-1}
A new spin on causality constraints
Energy Technology Data Exchange (ETDEWEB)
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan [Department of Physics, Cornell University, Ithaca, New York (United States)
2016-10-26
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.
Reciprocity, passivity and causality in Willis materials.
Muhlestein, Michael B; Sieck, Caleb F; Alù, Andrea; Haberman, Michael R
2016-10-01
Materials that require coupling between the stress-strain and momentum-velocity constitutive relations were first proposed by Willis (Willis 1981 Wave Motion 3 , 1-11. (doi:10.1016/0165-2125(81)90008-1)) and are now known as elastic materials of the Willis type, or simply Willis materials. As coupling between these two constitutive equations is a generalization of standard elastodynamic theory, restrictions on the physically admissible material properties for Willis materials should be similarly generalized. This paper derives restrictions imposed on the material properties of Willis materials when they are assumed to be reciprocal, passive and causal. Considerations of causality and low-order dispersion suggest an alternative formulation of the standard Willis equations. The alternative formulation provides improved insight into the subwavelength physical behaviour leading to Willis material properties and is amenable to time-domain analyses. Finally, the results initially obtained for a generally elastic material are specialized to the acoustic limit.
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 16 February (2016), č. článku 022213. ISSN 2470-0045 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: 2.366, year: 2016
Curvature constraints from the causal entropic principle
International Nuclear Information System (INIS)
Bozek, Brandon; Albrecht, Andreas; Phillips, Daniel
2009-01-01
Current cosmological observations indicate a preference for a cosmological constant that is drastically smaller than what can be explained by conventional particle physics. The causal entropic principle (Bousso et al.) provides an alternative approach to anthropic attempts to predict our observed value of the cosmological constant by calculating the entropy created within a causal diamond. We have extended this work to use the causal entropic principle to predict the preferred curvature within the 'multiverse'. We have found that values larger than ρ k =40ρ m are disfavored by more than 99.99% peak value at ρ Λ =7.9x10 -123 and ρ k =4.3ρ m for open universes. For universes that allow only positive curvature or both positive and negative curvature, we find a correlation between curvature and dark energy that leads to an extended region of preferred values. Our universe is found to be disfavored to an extent depending on the priors on curvature. We also provide a comparison to previous anthropic constraints on open universes and discuss future directions for this work.
Structure induction in diagnostic causal reasoning.
Meder, Björn; Mayrhofer, Ralf; Waldmann, Michael R
2014-07-01
Our research examines the normative and descriptive adequacy of alternative computational models of diagnostic reasoning from single effects to single causes. Many theories of diagnostic reasoning are based on the normative assumption that inferences from an effect to its cause should reflect solely the empirically observed conditional probability of cause given effect. We argue against this assumption, as it neglects alternative causal structures that may have generated the sample data. Our structure induction model of diagnostic reasoning takes into account the uncertainty regarding the underlying causal structure. A key prediction of the model is that diagnostic judgments should not only reflect the empirical probability of cause given effect but should also depend on the reasoner's beliefs about the existence and strength of the link between cause and effect. We confirmed this prediction in 2 studies and showed that our theory better accounts for human judgments than alternative theories of diagnostic reasoning. Overall, our findings support the view that in diagnostic reasoning people go "beyond the information given" and use the available data to make inferences on the (unobserved) causal rather than on the (observed) data level. (c) 2014 APA, all rights reserved.
Causal inference of asynchronous audiovisual speech
Directory of Open Access Journals (Sweden)
John F Magnotti
2013-11-01
Full Text Available During speech perception, humans integrate auditory information from the voice with visual information from the face. This multisensory integration increases perceptual precision, but only if the two cues come from the same talker; this requirement has been largely ignored by current models of speech perception. We describe a generative model of multisensory speech perception that includes this critical step of determining the likelihood that the voice and face information have a common cause. A key feature of the model is that it is based on a principled analysis of how an observer should solve this causal inference problem using the asynchrony between two cues and the reliability of the cues. This allows the model to make predictions abut the behavior of subjects performing a synchrony judgment task, predictive power that does not exist in other approaches, such as post hoc fitting of Gaussian curves to behavioral data. We tested the model predictions against the performance of 37 subjects performing a synchrony judgment task viewing audiovisual speech under a variety of manipulations, including varying asynchronies, intelligibility, and visual cue reliability. The causal inference model outperformed the Gaussian model across two experiments, providing a better fit to the behavioral data with fewer parameters. Because the causal inference model is derived from a principled understanding of the task, model parameters are directly interpretable in terms of stimulus and subject properties.
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…
How to Be Causal: Time, Spacetime and Spectra
Kinsler, Paul
2011-01-01
I explain a simple definition of causality in widespread use, and indicate how it links to the Kramers-Kronig relations. The specification of causality in terms of temporal differential equations then shows us the way to write down dynamical models so that their causal nature "in the sense used here" should be obvious to all. To extend existing…
Causal Relations and Feature Similarity in Children's Inductive Reasoning
Hayes, Brett K.; Thompson, Susan P.
2007-01-01
Four experiments examined the development of property induction on the basis of causal relations. In the first 2 studies, 5-year-olds, 8-year-olds, and adults were presented with triads in which a target instance was equally similar to 2 inductive bases but shared a causal antecedent feature with 1 of them. All 3 age groups used causal relations…
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...
A Bayesian Theory of Sequential Causal Learning and Abstract Transfer.
Lu, Hongjing; Rojas, Randall R; Beckers, Tom; Yuille, Alan L
2016-03-01
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 abstract causal constraints? Recent empirical studies have revealed that experience with one set of causal cues can dramatically alter subsequent learning and performance with entirely different cues, suggesting that learning involves abstract transfer, and such transfer effects involve sequential presentation of distinct sets of causal cues. It has been demonstrated that pre-training (or even post-training) can modulate classic causal learning phenomena such as forward and backward blocking. To account for these effects, we propose a Bayesian theory of sequential causal learning. The theory assumes that humans are able to consider and use several alternative causal generative models, each instantiating a different causal integration rule. Model selection is used to decide which integration rule to use in a given learning environment in order to infer causal knowledge from sequential data. Detailed computer simulations demonstrate that humans rely on the abstract characteristics of outcome variables (e.g., binary vs. continuous) to select a causal integration rule, which in turn alters causal learning in a variety of blocking and overshadowing paradigms. When the nature of the outcome variable is ambiguous, humans select the model that yields the best fit with the recent environment, and then apply it to subsequent learning tasks. Based on sequential patterns of cue-outcome co-occurrence, the theory can account for a range of phenomena in sequential causal learning, including various blocking effects, primacy effects in some experimental conditions, and apparently abstract transfer of causal knowledge. Copyright © 2015
Information causality from an entropic and a probabilistic perspective
International Nuclear Information System (INIS)
Al-Safi, Sabri W.; Short, Anthony J.
2011-01-01
The information causality principle is a generalization of the no-signaling principle which implies some of the known restrictions on quantum correlations. But despite its clear physical motivation, information causality is formulated in terms of a rather specialized game and figure of merit. We explore different perspectives on information causality, discussing the probability of success as the figure of merit, a relation between information causality and the nonlocal ''inner-product game,'' and the derivation of a quadratic bound for these games. We then examine an entropic formulation of information causality with which one can obtain the same results, arguably in a simpler fashion.
Interactions of information transfer along separable causal paths
Jiang, Peishi; Kumar, Praveen
2018-04-01
Complex systems arise as a result of interdependences between multiple variables, whose causal interactions can be visualized in a time-series graph. Transfer entropy and information partitioning approaches have been used to characterize such dependences. However, these approaches capture net information transfer occurring through a multitude of pathways involved in the interaction and as a result mask our ability to discern the causal interaction within a subgraph of interest through specific pathways. We build on recent developments of momentary information transfer along causal paths proposed by Runge [Phys. Rev. E 92, 062829 (2015), 10.1103/PhysRevE.92.062829] to develop a framework for quantifying information partitioning along separable causal paths. Momentary information transfer along causal paths captures the amount of information transfer between any two variables lagged at two specific points in time. Our approach expands this concept to characterize the causal interaction in terms of synergistic, unique, and redundant information transfer through separable causal paths. Through a graphical model, we analyze the impact of the separable and nonseparable causal paths and the causality structure embedded in the graph as well as the noise effect on information partitioning by using synthetic data generated from two coupled logistic equation models. Our approach can provide a valuable reference for an autonomous information partitioning along separable causal paths which form a causal subgraph influencing a target.
The selective power of causality on memory errors.
Marsh, Jessecae K; Kulkofsky, Sarah
2015-01-01
We tested the influence of causal links on the production of memory errors in a misinformation paradigm. Participants studied a set of statements about a person, which were presented as either individual statements or pairs of causally linked statements. Participants were then provided with causally plausible and causally implausible misinformation. We hypothesised that studying information connected with causal links would promote representing information in a more abstract manner. As such, we predicted that causal information would not provide an overall protection against memory errors, but rather would preferentially help in the rejection of misinformation that was causally implausible, given the learned causal links. In two experiments, we measured whether the causal linkage of information would be generally protective against all memory errors or only selectively protective against certain types of memory errors. Causal links helped participants reject implausible memory lures, but did not protect against plausible lures. Our results suggest that causal information may promote an abstract storage of information that helps prevent only specific types of memory errors.
Causal asymmetry across cultures: Assigning causal roles in symmetric physical settings
Directory of Open Access Journals (Sweden)
Andrea eBender
2011-09-01
Full Text Available In the cognitive sciences, causal cognition in the physical domain has featured as a core research topic, but the impact of culture has been rarely ever explored. One case in point for a topic on which this neglect is pronounced is the pervasive tendency of people to consider one of two (equally important entities as more important for bringing about an effect. In order to scrutinize how robust such tendencies are across cultures, we asked German and Tongan participants to assign prime causality in nine symmetric settings. For most settings, strong asymmetries in both cultures were found, but not always in the same direction, depending on the task content. This indicates that causal asymmetries, while indeed being a robust phenomenon across cultures, are also subject to culture-specific concepts. Moreover, the asymmetries were found to be modulated by figure-ground relations, but not by marking agency.
How multiple causes combine: independence constraints on causal inference.
Liljeholm, Mimi
2015-01-01
According to the causal power view, two core constraints-that causes occur independently (i.e., no confounding) and influence their effects independently-serve as boundary conditions for causal induction. This study investigated how violations of these constraints modulate uncertainty about the existence and strength of a causal relationship. Participants were presented with pairs of candidate causes that were either confounded or not, and that either interacted or exerted their influences independently. Consistent with the causal power view, uncertainty about the existence and strength of causal relationships was greater when causes were confounded or interacted than when unconfounded and acting independently. An elemental Bayesian causal model captured differences in uncertainty due to confounding but not those due to an interaction. Implications of distinct sources of uncertainty for the selection of contingency information and causal generalization are discussed.
Emergent Geometry from Entropy and Causality
Engelhardt, Netta
In this thesis, we investigate the connections between the geometry of spacetime and aspects of quantum field theory such as entanglement entropy and causality. This work is motivated by the idea that spacetime geometry is an emergent phenomenon in quantum gravity, and that the physics responsible for this emergence is fundamental to quantum field theory. Part I of this thesis is focused on the interplay between spacetime and entropy, with a special emphasis on entropy due to entanglement. In general spacetimes, there exist locally-defined surfaces sensitive to the geometry that may act as local black hole boundaries or cosmological horizons; these surfaces, known as holographic screens, are argued to have a connection with the second law of thermodynamics. Holographic screens obey an area law, suggestive of an association with entropy; they are also distinguished surfaces from the perspective of the covariant entropy bound, a bound on the total entropy of a slice of the spacetime. This construction is shown to be quite general, and is formulated in both classical and perturbatively quantum theories of gravity. The remainder of Part I uses the Anti-de Sitter/ Conformal Field Theory (AdS/CFT) correspondence to both expand and constrain the connection between entanglement entropy and geometry. The AdS/CFT correspondence posits an equivalence between string theory in the "bulk" with AdS boundary conditions and certain quantum field theories. In the limit where the string theory is simply classical General Relativity, the Ryu-Takayanagi and more generally, the Hubeny-Rangamani-Takayanagi (HRT) formulae provide a way of relating the geometry of surfaces to entanglement entropy. A first-order bulk quantum correction to HRT was derived by Faulkner, Lewkowycz and Maldacena. This formula is generalized to include perturbative quantum corrections in the bulk at any (finite) order. Hurdles to spacetime emergence from entanglement entropy as described by HRT and its quantum
A Causal Theory of Mnemonic Confabulation
Directory of Open Access Journals (Sweden)
Sven Bernecker
2017-07-01
Full Text Available This paper attempts to answer the question of what defines mnemonic confabulation vis-à-vis genuine memory. The two extant accounts of mnemonic confabulation as “false memory” and as ill-grounded memory are shown to be problematic, for they cannot account for the possibility of veridical confabulation, ill-grounded memory, and well-grounded confabulation. This paper argues that the defining characteristic of mnemonic confabulation is that it lacks the appropriate causal history. In the confabulation case, there is no proper counterfactual dependence of the state of seeming to remember on the corresponding past representation.
De Broglie's causal interpretations of quantum mechanics
International Nuclear Information System (INIS)
Ben-Dov, Y.
1989-01-01
In this article we trace the history of de Broglie's two causal interpretations of quantum mechanics, namely the double solution and the pilot wave theories, at the two periods in which he developed them: 1924-27 and 1952 onwards. Examining the reasons for which he always preferred the first theory to the second, reasons that are mainly concerned with the question of the physical nature of the quantum wave function, we try to show the continuity and the coherence of his underlying vision
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.
Conditional Granger Causality of Diffusion Processes
Czech Academy of Sciences Publication Activity Database
Wahl, B.; Feudel, U.; Hlinka, Jaroslav; Wächter, M.; Peinke, J.; Freund, J.A.
2017-01-01
Roč. 90, č. 10 (2017), č. článku 197. ISSN 1434-6028 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 OBOR OECD: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8) Impact factor: 1.461, year: 2016
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
¿CONFIEREN PODERES CAUSALES LOS UNIVERSALES TRASCENDENTES?
Directory of Open Access Journals (Sweden)
José Tomás Alvarado Marambio
2013-11-01
Full Text Available This work discusses the so-called ‘Eleatic’ argument against the existence of transcendent universals, i. e. universals which does not require instantiation for its existence. The Eleatic Principle states that everything produces a difference in the causal powers of something. As transcendent universals seem not to produce such a difference, transcendent universals seem not to exist. The argument depends crucially on the justification and the interpretation of the Eleatic Principle. It is argued, first, that it is not very clear that the principle is justified, and, second, that there are several alternatives for its interpretation, in relation with the different theories one can endorse about modality or causality. Anti-realist theories of modality or causality are not very appropriate for the understanding of what should be a ‘causal power’. Neither does a realist theory of causality conjoined with a combinatorial theory of possible worlds. A ‘causal power’ seems to be better understood in connection with a realist –non-reductionist– theory of causality and a causal theory of modality. Taken in this way the Eleatic Principle, nonetheless, it is argued that transcendent universals do ‘produce’ a difference in causal powers, for every causal connection requires such universals for its existence.
Are bruxism and the bite causally related?
Lobbezoo, F; Ahlberg, J; Manfredini, D; Winocur, E
2012-07-01
In the dental profession, the belief that bruxism and dental (mal-)occlusion ('the bite') are causally related is widespread. The aim of this review was to critically assess the available literature on this topic. A PubMed search of the English-language literature, using the query 'Bruxism [Majr] AND (Dental Occlusion [Majr] OR Malocclusion [Majr])', yielded 93 articles, of which 46 papers were finally included in the present review*. Part of the included publications dealt with the possible associations between bruxism and aspects of occlusion, from which it was concluded that neither for occlusal interferences nor for factors related to the anatomy of the oro-facial skeleton, there is any evidence available that they are involved in the aetiology of bruxism. Instead, there is a growing awareness of other factors (viz. psychosocial and behavioural ones) being important in the aetiology of bruxism. Another part of the included papers assessed the possible mediating role of occlusion between bruxism and its purported consequences (e.g. tooth wear, loss of periodontal tissues, and temporomandibular pain and dysfunction). Even though most dentists agree that bruxism may have several adverse effects on the masticatory system, for none of these purported adverse effects, evidence for a mediating role of occlusion and articulation has been found to date. Hence, based on this review, it should be concluded that to date, there is no evidence whatsoever for a causal relationship between bruxism and the bite. © 2012 Blackwell Publishing Ltd.
[Antibibiotic resistance by nosocomial infections' causal agents].
Salazar-Holguín, Héctor Daniel; Cisneros-Robledo, María Elena
2016-01-01
The antibibiotic resistance by nosocomial infections (NI) causal agents constitutes a seriously global problematic that involves the Mexican Institute of Social Security's Regional General Hospital 1 in Chihuahua, Mexico; although with special features that required to be specified and evaluated, in order to concrete an effective therapy. Observational, descriptive and prospective study; by means of active vigilance all along 2014 in order to detect the nosocomial infections, for epidemiologic study, culture and antibiogram to identify its causal agents and antibiotics resistance and sensitivity. Among 13527 hospital discharges, 1079 displayed NI (8 %), standed out: the related on vascular lines, of surgical site, pneumonia and urinal track; they added up two thirds of the total. We carried out culture and antibiogram about 300 of them (27.8 %); identifying 31 bacterian species, mainly seven of those (77.9 %): Escherichia coli, Staphylococcus aureus and epidermidis, Pseudomonas aeruginosa, Acinetobacter baumannii, Klebsiella pneumoniae and Enterobacter cloacae; showing multiresistance to 34 tested antibiotics, except in seven with low or without resistance at all: vancomycin, teicoplanin, linezolid, quinupristin-dalfopristin, piperacilin-tazobactam, amikacin and carbapenems. When we contrasted those results with the recommendations in the clinical practice guides, it aroused several contradictions; so they must be taken with reserves and has to be tested in each hospital, by means of cultures and antibiograms in practically every case of nosocomial infection.
Diagnostic reasoning using qualitative causal models
International Nuclear Information System (INIS)
Sudduth, A.L.
1992-01-01
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
Introducing mechanics by tapping core causal knowledge
International Nuclear Information System (INIS)
Klaassen, Kees; Westra, Axel; Emmett, Katrina; Eijkelhof, Harrie; Lijnse, Piet
2008-01-01
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
Causal Inference in the Perception of Verticality.
de Winkel, Ksander N; Katliar, Mikhail; Diers, Daniel; Bülthoff, Heinrich H
2018-04-03
The perceptual upright is thought to be constructed by the central nervous system (CNS) as a vector sum; by combining estimates on the upright provided by the visual system and the body's inertial sensors with prior knowledge that upright is usually above the head. Recent findings furthermore show that the weighting of the respective sensory signals is proportional to their reliability, consistent with a Bayesian interpretation of a vector sum (Forced Fusion, FF). However, violations of FF have also been reported, suggesting that the CNS may rely on a single sensory system (Cue Capture, CC), or choose to process sensory signals based on inferred signal causality (Causal Inference, CI). We developed a novel alternative-reality system to manipulate visual and physical tilt independently. We tasked participants (n = 36) to indicate the perceived upright for various (in-)congruent combinations of visual-inertial stimuli, and compared models based on their agreement with the data. The results favor the CI model over FF, although this effect became unambiguous only for large discrepancies (±60°). We conclude that the notion of a vector sum does not provide a comprehensive explanation of the perception of the upright, and that CI offers a better alternative.
Quantum causality conceptual issues in the causal theory of quantum mechanics
Riggs, Peter J; French, Steven RD
2009-01-01
This is a treatise devoted to the foundations of quantum physics and the role that causality plays in the microscopic world governed by the laws of quantum mechanics. The book is controversial and will engender some lively debate on the various issues raised.
Links between causal effects and causal association for surrogacy evaluation in a gaussian setting.
Conlon, Anna; Taylor, Jeremy; Li, Yun; Diaz-Ordaz, Karla; Elliott, Michael
2017-11-30
Two paradigms for the evaluation of surrogate markers in randomized clinical trials have been proposed: the causal effects paradigm and the causal association paradigm. Each of these paradigms rely on assumptions that must be made to proceed with estimation and to validate a candidate surrogate marker (S) for the true outcome of interest (T). We consider the setting in which S and T are Gaussian and are generated from structural models that include an unobserved confounder. Under the assumed structural models, we relate the quantities used to evaluate surrogacy within both the causal effects and causal association frameworks. We review some of the common assumptions made to aid in estimating these quantities and show that assumptions made within one framework can imply strong assumptions within the alternative framework. We demonstrate that there is a similarity, but not exact correspondence between the quantities used to evaluate surrogacy within each framework, and show that the conditions for identifiability of the surrogacy parameters are different from the conditions, which lead to a correspondence of these quantities. Copyright © 2017 John Wiley & Sons, Ltd.
Causal inference in nonlinear systems: Granger causality versus time-delayed mutual information
Li, Songting; Xiao, Yanyang; Zhou, Douglas; Cai, David
2018-05-01
The Granger causality (GC) analysis has been extensively applied to infer causal interactions in dynamical systems arising from economy and finance, physics, bioinformatics, neuroscience, social science, and many other fields. In the presence of potential nonlinearity in these systems, the validity of the GC analysis in general is questionable. To illustrate this, here we first construct minimal nonlinear systems and show that the GC analysis fails to infer causal relations in these systems—it gives rise to all types of incorrect causal directions. In contrast, we show that the time-delayed mutual information (TDMI) analysis is able to successfully identify the direction of interactions underlying these nonlinear systems. We then apply both methods to neuroscience data collected from experiments and demonstrate that the TDMI analysis but not the GC analysis can identify the direction of interactions among neuronal signals. Our work exemplifies inference hazards in the GC analysis in nonlinear systems and suggests that the TDMI analysis can be an appropriate tool in such a case.
International Nuclear Information System (INIS)
Solarin, Sakiru Adebola; Shahbaz, Muhammad
2013-01-01
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
Causality as a Rigorous Notion and Quantitative Causality Analysis with Time Series
Liang, X. S.
2017-12-01
Given two time series, can one faithfully tell, in a rigorous and quantitative way, the cause and effect between them? Here we show that this important and challenging question (one of the major challenges in the science of big data), which is of interest in a wide variety of disciplines, has a positive answer. Particularly, for linear systems, the maximal likelihood estimator of the causality from a series X2 to another series X1, written T2→1, turns out to be concise in form: T2→1 = [C11 C12 C2,d1 — C112 C1,d1] / [C112 C22 — C11C122] where Cij (i,j=1,2) is the sample covariance between Xi and Xj, and Ci,dj the covariance between Xi and ΔXj/Δt, the difference approximation of dXj/dt using the Euler forward scheme. An immediate corollary is that causation implies correlation, but not vice versa, resolving the long-standing debate over causation versus correlation. The above formula has been validated with touchstone series purportedly generated with one-way causality that evades the classical approaches such as Granger causality test and transfer entropy analysis. It has also been applied successfully to the investigation of many real problems. Through a simple analysis with the stock series of IBM and GE, an unusually strong one-way causality is identified from the former to the latter 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 computer market. Another example presented here regards the cause-effect relation between the two climate modes, El Niño and Indian Ocean Dipole (IOD). In general, these modes are mutually causal, but the causality is asymmetric. To El Niño, the information flowing from IOD manifests itself as a propagation of uncertainty from the Indian Ocean. In the third example, an unambiguous one-way causality is found between CO2 and the global mean temperature anomaly. While it is confirmed that CO2 indeed drives the recent global warming
Entanglement, non-Markovianity, and causal non-separability
Milz, Simon; Pollock, Felix A.; Le, Thao P.; Chiribella, Giulio; Modi, Kavan
2018-03-01
Quantum mechanics, in principle, allows for processes with indefinite causal order. However, most of these causal anomalies have not yet been detected experimentally. We show that every such process can be simulated experimentally by means of non-Markovian dynamics with a measurement on additional degrees of freedom. In detail, we provide an explicit construction to implement arbitrary a causal processes. Furthermore, we give necessary and sufficient conditions for open system dynamics with measurement to yield processes that respect causality locally, and find that tripartite entanglement and nonlocal unitary transformations are crucial requirements for the simulation of causally indefinite processes. These results show a direct connection between three counter-intuitive concepts: entanglement, non-Markovianity, and causal non-separability.
Causal theory in (2+1)-dimensional Qed
International Nuclear Information System (INIS)
Scharf, G.; Wreszinski, W.F.
1994-01-01
The program of constructing the S-matrix by means of causality in quantum field theory goes back to Stueckelberg and Bogoliubov. Epstein and Glaser proposed an axiomatic construct where ultraviolet divergences do not appear, leading directly to the renormalized perturbation series. They have shown that in the causal theory the UV problem is a consequence of incorrect distribution splitting. This paper studies the causal theory in (2+1)D Qed
Causal knowledge and the development of inductive reasoning
Bright, Aimée K.; Feeney, Aidan
2014-01-01
We explored the development of sensitivity to causal relations in children’s inductive reasoning. Children (5-, 8-, and 12-year-olds) and adults were given trials in which they decided whether a property known to be possessed by members of one category was also possessed by members of (a) a taxonomically related category or (b) a causally related category. The direction of the causal link was either predictive (prey → predator) or diagnostic (predator → prey), and the property that participan...
Analogy in causal inference: rethinking Austin Bradford Hill's neglected consideration.
Weed, Douglas L
2018-05-01
The purpose of this article was to rethink and resurrect Austin Bradford Hill's "criterion" of analogy as an important consideration in causal inference. In epidemiology today, analogy is either completely ignored (e.g., in many textbooks), or equated with biologic plausibility or coherence, or aligned with the scientist's imagination. None of these examples, however, captures Hill's description of analogy. His words suggest that there may be something gained by contrasting two bodies of evidence, one from an established causal relationship, the other not. Coupled with developments in the methods of systematic assessments of evidence-including but not limited to meta-analysis-analogy can be restructured as a key component in causal inference. This new approach will require that a collection-a library-of known cases of causal inference (i.e., bodies of evidence involving established causal relationships) be developed. This library would likely include causal assessments by organizations such as the International Agency for Research on Cancer, the National Toxicology Program, and the United States Environmental Protection Agency. In addition, a process for describing key features of a causal relationship would need to be developed along with what will be considered paradigm cases of causation. Finally, it will be important to develop ways to objectively compare a "new" body of evidence with the relevant paradigm case of causation. Analogy, along with all other existing methods and causal considerations, may improve our ability to identify causal relationships. Copyright © 2018 Elsevier Inc. All rights reserved.
Granger Causality and Transfer Entropy Are Equivalent for Gaussian Variables
Barnett, Lionel; Barrett, Adam B.; Seth, Anil K.
2009-12-01
Granger causality is a statistical notion of causal influence based on prediction via vector autoregression. Developed originally in the field of econometrics, it has since found application in a broader arena, particularly in neuroscience. More recently transfer entropy, an information-theoretic measure of time-directed information transfer between jointly dependent processes, has gained traction in a similarly wide field. While it has been recognized that the two concepts must be related, the exact relationship has until now not been formally described. Here we show that for Gaussian variables, Granger causality and transfer entropy are entirely equivalent, thus bridging autoregressive and information-theoretic approaches to data-driven causal inference.
Explaining quantum correlations through evolution of causal models
Harper, Robin; Chapman, Robert J.; Ferrie, Christopher; Granade, Christopher; Kueng, Richard; Naoumenko, Daniel; Flammia, Steven T.; Peruzzo, Alberto
2017-04-01
We propose a framework for the systematic and quantitative generalization of Bell's theorem using causal networks. We first consider the multiobjective optimization problem of matching observed data while minimizing the causal effect of nonlocal variables and prove an inequality for the optimal region that both strengthens and generalizes Bell's theorem. To solve the optimization problem (rather than simply bound it), we develop a genetic algorithm treating as individuals causal networks. By applying our algorithm to a photonic Bell experiment, we demonstrate the trade-off between the quantitative relaxation of one or more local causality assumptions and the ability of data to match quantum correlations.
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.
Delinquency among pathological gamblers: A causal approach.
Meyer, G; Fabian, T
1992-03-01
In a comprehensive research project on gamblers in self-help groups in West Germany one object of investigation was the question of whether or not pathological gambling has a criminogenic effect. 54.5% of the 437 members of Gamblers Anonymous interviewed stated that they had committed illegal actions in order to obtain money for gambling. Comparisons of this sub-group with those interviewees who did not admit having committed criminal offences show distinct differences: Those who admitted illegal action were more excessive in their gambling behavior and experienced a higher degree of subjective satisfaction through gambling. They also showed a more pronounced problem behavior and more psychosocial problems because of gambling. A multiple regression within the framework of path analysis was computed in order to explore causal links between pathological gambling and delinquency. The results support the hypothesis that pathological gambling can lead to delinquent behavior. Forensic implications are discussed.
Exploring Torus Universes in Causal Dynamical Triangulations
DEFF Research Database (Denmark)
Budd, Timothy George; Loll, R.
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....... Apart from setting the stage for the analysis of shape dynamics on the torus, the new set-up highlights the role of nontrivial boundaries and topology....
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
Directory of Open Access Journals (Sweden)
Alexios Arvanitis
2016-08-01
Full Text Available 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.
The emerging causal understanding of institutional objects.
Noyes, Alexander; Keil, Frank C; Dunham, Yarrow
2018-01-01
Institutional objects, such as money, drivers' licenses, and borders, have functions because of their social roles rather than their immediate physical properties. These objects are causally different than standard artifacts (e.g. hammers, chairs, and cars), sharing more commonality with other social roles. Thus, they inform psychological theories of human-made objects as well as children's emerging understanding of social reality. We examined whether children (N=180, ages 4-9) differentiate institutional objects from standard artifacts. Specifically, we examine whether children understand that mutual intentions (i.e., the intentions of a social collective) underlie the functional affordances of institutional objects in ways that they do not for standard artifacts. We find that young children assimilate institutional objects into their intuitive theories of standard artifacts; children begin to differentiate between the domains in the elementary school years. Published by Elsevier B.V.
A study in cosmology and causal thermodynamics
International Nuclear Information System (INIS)
Oliveira, H.P. de.
1986-01-01
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.) [pt
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.
Causality and hyperbolicity of Lovelock theories
International Nuclear Information System (INIS)
Reall, Harvey S; Tanahashi, Norihiro; Way, Benson
2014-01-01
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)
Causality constraints in conformal field theory
Energy Technology Data Exchange (ETDEWEB)
Hartman, Thomas; Jain, Sachin; Kundu, Sandipan [Department of Physics, Cornell University,Ithaca, New York (United States)
2016-05-17
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){sup 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.
Diagnostic causal reasoning with verbal information.
Meder, Björn; Mayrhofer, Ralf
2017-08-01
In diagnostic causal reasoning, the goal is to infer the probability of causes from one or multiple observed effects. Typically, studies investigating such tasks provide subjects with precise quantitative information regarding the strength of the relations between causes and effects or sample data from which the relevant quantities can be learned. By contrast, we sought to examine people's inferences when causal information is communicated through qualitative, rather vague verbal expressions (e.g., "X occasionally causes A"). We conducted three experiments using a sequential diagnostic inference task, where multiple pieces of evidence were obtained one after the other. Quantitative predictions of different probabilistic models were derived using the numerical equivalents of the verbal terms, taken from an unrelated study with different subjects. We present a novel Bayesian model that allows for incorporating the temporal weighting of information in sequential diagnostic reasoning, which can be used to model both primacy and recency effects. On the basis of 19,848 judgments from 292 subjects, we found a remarkably close correspondence between the diagnostic inferences made by subjects who received only verbal information and those of a matched control group to whom information was presented numerically. Whether information was conveyed through verbal terms or numerical estimates, diagnostic judgments closely resembled the posterior probabilities entailed by the causes' prior probabilities and the effects' likelihoods. We observed interindividual differences regarding the temporal weighting of evidence in sequential diagnostic reasoning. Our work provides pathways for investigating judgment and decision making with verbal information within a computational modeling framework. Copyright © 2017 Elsevier Inc. All rights reserved.
The balanced survivor average causal effect.
Greene, Tom; Joffe, Marshall; Hu, Bo; Li, Liang; Boucher, Ken
2013-05-07
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.
World oil and agricultural commodity prices: Evidence from nonlinear causality
International Nuclear Information System (INIS)
Nazlioglu, Saban
2011-01-01
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.
Tachyon kinematics and causality: a systematic thorough analysis of the tachyon causal paradoxes
International Nuclear Information System (INIS)
Recami, E.
1987-01-01
The chronological order of the events along a spacelike path is not invariant under Lorentz transformations, as is well known. This led to an early conviction that tachyons would give rise to causal anomalies. A relativistic version of the Stueckelberg-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 detector. 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 the tachyon relativistic mechanics has been properly developed. They start by showing how to apply the SWP, both in the case of ordinary special relativity and in the case with tachyons. Then they carefully exploit the kinetics of the tachyon exchange between two (ordinary) bodies. Being finally able to tackle the tachyon causality problem, they successively solve the paradoxes of: (i) Tolman-Regge, (ii) Pirani, (iii) Edmonds, and (iv) Bell. Finally, they discuss a further, new paradox associated with the transmission of signals by modulated tachyon beams
Is there a causal relationship between alcohol and HIV? Implications ...
African Journals Online (AJOL)
There is now conclusive evidence of a causal linkage between heavy drinking patterns and/or alcohol use disorders and the worsening of the disease course for HIV. However, while alcohol usage is consistently associated with the prevalence and incidence of HIV, further research is needed to substantiate causality in ...
An Information Processing Approach to Children's Causal Reasoning.
Siegler, Robert S.
This paper questions evidence for the thesis that causal reasoning of older children is more logical than that of younger ones, and describes two experiments which attempted to determine (1) whether there are true developmental differences in causal reasoning, and (2) what explanations for developmental differences can be supported. In the first…
The relative performance of bivariate causality tests in small samples
Bult, J..R.; Leeflang, P.S.H.; Wittink, D.R.
1997-01-01
Causality tests have been applied to establish directional effects and to reduce the set of potential predictors, For the latter type of application only bivariate tests can be used, In this study we compare bivariate causality tests. Although the problem addressed is general and could benefit
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 Effect Inference with Deep Latent-Variable Models
Louizos, C; Shalit, U.; Mooij, J.; Sontag, D.; Zemel, R.; Welling, M.
2017-01-01
Learning individual-level causal effects from observational data, such as inferring the most effective medication for a specific patient, is a problem of growing importance for policy makers. The most important aspect of inferring causal effects from observational data is the handling of
Optimal relaxed causal sampler using sampled-date system theory
Shekhawat, Hanumant; Meinsma, Gjerrit
This paper studies the design of an optimal relaxed causal sampler using sampled data system theory. A lifted frequency domain approach is used to obtain the existence conditions and the optimal sampler. A state space formulation of the results is also provided. The resulting optimal relaxed causal
Temporal and Statistical Information in Causal Structure Learning
McCormack, Teresa; Frosch, Caren; Patrick, Fiona; Lagnado, David
2015-01-01
Three experiments examined children's and adults' abilities to use statistical and temporal information to distinguish between common cause and causal chain structures. In Experiment 1, participants were provided with conditional probability information and/or temporal information and asked to infer the causal structure of a 3-variable mechanical…
Non-Bayesian Inference: Causal Structure Trumps Correlation
Bes, Benedicte; Sloman, Steven; Lucas, Christopher G.; Raufaste, Eric
2012-01-01
The study tests the hypothesis that conditional probability judgments can be influenced by causal links between the target event and the evidence even when the statistical relations among variables are held constant. Three experiments varied the causal structure relating three variables and found that (a) the target event was perceived as more…
Weighting-Based Sensitivity Analysis in Causal Mediation Studies
Hong, Guanglei; Qin, Xu; Yang, Fan
2018-01-01
Through a sensitivity analysis, the analyst attempts to determine whether a conclusion of causal inference could be easily reversed by a plausible violation of an identification assumption. Analytic conclusions that are harder to alter by such a violation are expected to add a higher value to scientific knowledge about causality. This article…
Causal inference in biology networks with integrated belief propagation.
Chang, Rui; Karr, Jonathan R; Schadt, Eric E
2015-01-01
Inferring causal relationships among molecular and higher order phenotypes is a critical step in elucidating the complexity of living systems. Here we propose a novel method for inferring causality that is no longer constrained by the conditional dependency arguments that limit the ability of statistical causal inference methods to resolve causal relationships within sets of graphical models that are Markov equivalent. Our method utilizes Bayesian belief propagation to infer the responses of perturbation events on molecular traits given a hypothesized graph structure. A distance measure between the inferred response distribution and the observed data is defined to assess the 'fitness' of the hypothesized causal relationships. To test our algorithm, we infer causal relationships within equivalence classes of gene networks in which the form of the functional interactions that are possible are assumed to be nonlinear, given synthetic microarray and RNA sequencing data. We also apply our method to infer causality in real metabolic network with v-structure and feedback loop. We show that our method can recapitulate the causal structure and recover the feedback loop only from steady-state data which conventional method cannot.
On the conceptual distinction of general causality orientations
DEFF Research Database (Denmark)
Olesen, Martin Hammershøj
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......, that is general causality orientations can be understood as characteristic adaptations of dispositional traits....
Theories of conduct disorder: a causal modelling analysis
Krol, N.P.C.M.; Morton, J.; Bruyn, E.E.J. De
2004-01-01
Background: If a clinician has to make decisions on diagnosis and treatment, he or she is confronted with a variety of causal theories. In order to compare these theories a neutral terminology and notational system is needed. The Causal Modelling framework involving three levels of description –
Financial networks based on Granger causality: A case study
Papana, A.; Kyrtsou, C.; Kugiumtzis, D.; Diks, C.
Connectivity analysis is performed on a long financial record of 21 international stock indices employing a linear and a nonlinear causality measure, the conditional Granger causality index (CGCI) and the partial mutual information on mixed embedding (PMIME), respectively. Both measures aim to
Causal pathways between substance use disorders and personality pathology
Verheul, R.; van den Brink, W.
2005-01-01
A high co-occurrence between personality and substance use disorders suggests causal relationships between these conditions. Most empirical evidence strongly supports causal pathways in which (pathological) personality traits contribute to the development of a substance use disorder (i.e., primary
Nonparametric Identification of Causal Effects under Temporal Dependence
Dafoe, Allan
2018-01-01
Social scientists routinely address temporal dependence by adopting a simple technical fix. However, the correct identification strategy for a causal effect depends on causal assumptions. These need to be explicated and justified; almost no studies do so. This article addresses this shortcoming by offering a precise general statement of the…
Causal inference in survival analysis using pseudo-observations
DEFF Research Database (Denmark)
Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T
2017-01-01
Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs ...
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…
Ends, Principles, and Causal Explanation in Educational Justice
Dum, Jenn
2017-01-01
Many principles characterize educational justice in terms of the relationship between educational inputs, outputs and distributive standards. Such principles depend upon the "causal pathway view" of education. It is implicit in this view that the causally effective aspects of education can be understood as separate from the normative…
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…
A note on mental content in the Causal Theory
African Journals Online (AJOL)
A note on mental content in the Causal Theory. JP Smit. Department of Philosophy, Stellenbosch University, Private Bag X1, 7600 Matieland, South Africa. E-mail: jps@sun.ac.za. Kripke's causal theory requires that downstream users of a name must have the intention to use the name in the same way that upstream users ...
Sartre's Contingency of Being and Asouzu's Principle of Causality ...
African Journals Online (AJOL)
The position of this work is that all contingent beings have a causal agent. This position is taken as a result of trying to delve into the issue of contingency and causality of being which has been discussed by many philosophers of diverse epochs of philosophy. This work tries to participate in the debate of whether contingent ...
Causal Relationship Between Relative Price Variability and Inflation in Turkey:
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Nebiye Yamak
2016-09-01
Full Text Available This study investigates the causal relationship between inflation and relative price variability in Turkey for the period of January 2003-January 2014, by using panel data. In the study, a Granger (1969 non-causality test in heterogeneous panel data models developed by Dumitrescu and Hurlin (2012 is utilized to determine the causal relations between inflation rate relative price variability. The panel data consists of 4123 observations: 133 time observations and 31 cross-section observations. The results of panel causality test indicate that there is a bidirectional causality between inflation rate and relative price variability by not supporting the imperfection information model of Lucas and the menu cost model of Ball and Mankiw.
Statistical causal inferences and their applications in public health research
Wu, Pan; Chen, Ding-Geng
2016-01-01
This book compiles and presents new developments in statistical causal inference. The accompanying data and computer programs are publicly available so readers may replicate the model development and data analysis presented in each chapter. In this way, methodology is taught so that readers may implement it directly. The book brings together experts engaged in causal inference research to present and discuss recent issues in causal inference methodological development. This is also a timely look at causal inference applied to scenarios that range from clinical trials to mediation and public health research more broadly. In an academic setting, this book will serve as a reference and guide to a course in causal inference at the graduate level (Master's or Doctorate). It is particularly relevant for students pursuing degrees in Statistics, Biostatistics and Computational Biology. Researchers and data analysts in public health and biomedical research will also find this book to be an important reference.
Causal Relationship between Construction Production and GDP in Turkey
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Hakkı Kutay Bolkol
2015-12-01
Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.
Causal Relationship between Construction Production and GDP in Turkey
Directory of Open Access Journals (Sweden)
Hakkı Kutay Bolkol
2015-09-01
Full Text Available This study empirically investigates the causal relationship between construction production and GDP for Turkey during 2005Q1-2013Q4 period. Because it is found that, there is no cointegration which means there is no long run relationship between variables, VAR Granger Causality Method is used to test the causality in short run. The findings reveal that, the causality runs from GDP to Building Production and Building Production to Non-Building Production (i.e. bidirectional relationship. Findings of this paper suggest that, because there is no long run relationship between Construction Production (Building and Non-Building and GDP and also in short run the causality runs from GDP to Construction Production, the growth strategy based on mainly Construction Sector growth is not a good idea for Turkey.
Beyond Markov: Accounting for independence violations in causal reasoning.
Rehder, Bob
2018-06-01
Although many theories of causal cognition are based on causal graphical models, a key property of such models-the independence relations stipulated by the Markov condition-is routinely violated by human reasoners. This article presents three new accounts of those independence violations, accounts that share the assumption that people's understanding of the correlational structure of data generated from a causal graph differs from that stipulated by causal graphical model framework. To distinguish these models, experiments assessed how people reason with causal graphs that are larger than those tested in previous studies. A traditional common cause network (Y 1 ←X→Y 2 ) was extended so that the effects themselves had effects (Z 1 ←Y 1 ←X→Y 2 →Z 2 ). A traditional common effect network (Y 1 →X←Y 2 ) was extended so that the causes themselves had causes (Z 1 →Y 1 →X←Y 2 ←Z 2 ). Subjects' inferences were most consistent with the beta-Q model in which consistent states of the world-those in which variables are either mostly all present or mostly all absent-are viewed as more probable than stipulated by the causal graphical model framework. Substantial variability in subjects' inferences was also observed, with the result that substantial minorities of subjects were best fit by one of the other models (the dual prototype or a leaky gate models). The discrepancy between normative and human causal cognition stipulated by these models is foundational in the sense that they locate the error not in people's causal reasoning but rather in their causal representations. As a result, they are applicable to any cognitive theory grounded in causal graphical models, including theories of analogy, learning, explanation, categorization, decision-making, and counterfactual reasoning. Preliminary evidence that independence violations indeed generalize to other judgment types is presented. Copyright © 2018 Elsevier Inc. All rights reserved.
Grotzer, Tina A.; Tutwiler, M. Shane
2014-01-01
This article considers a set of well-researched default assumptions that people make in reasoning about complex causality and argues that, in part, they result from the forms of causal induction that we engage in and the type of information available in complex environments. It considers how information often falls outside our attentional frame…
Triantafillou, Sofia; Lagani, Vincenzo; Heinze-Deml, Christina; Schmidt, Angelika; Tegner, Jesper; Tsamardinos, Ioannis
2017-01-01
Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.
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.
Triantafillou, Sofia
2017-09-29
Learning the causal relationships that define a molecular system allows us to predict how the system will respond to different interventions. Distinguishing causality from mere association typically requires randomized experiments. Methods for automated causal discovery from limited experiments exist, but have so far rarely been tested in systems biology applications. In this work, we apply state-of-the art causal discovery methods on a large collection of public mass cytometry data sets, measuring intra-cellular signaling proteins of the human immune system and their response to several perturbations. We show how different experimental conditions can be used to facilitate causal discovery, and apply two fundamental methods that produce context-specific causal predictions. Causal predictions were reproducible across independent data sets from two different studies, but often disagree with the KEGG pathway databases. Within this context, we discuss the caveats we need to overcome for automated causal discovery to become a part of the routine data analysis in systems biology.
Sanders, T.J.M.|info:eu-repo/dai/nl/075243911; Spooren, W.P.M.S.
Many languages of the world have connectives to express causal relations at the discourse level. Often, language users systematically prefer one lexical item (because) over another (even highly similar) one (since) to express a causal relationship. Such choices provide a window on speakers'
Averaged null energy condition from causality
Hartman, Thomas; Kundu, Sandipan; Tajdini, Amirhossein
2017-07-01
Unitary, Lorentz-invariant quantum field theories in flat spacetime obey mi-crocausality: commutators vanish at spacelike separation. For interacting theories in more than two dimensions, we show that this implies that the averaged null energy, ∫ duT uu , must be non-negative. This non-local operator appears in the operator product expansion of local operators in the lightcone limit, and therefore contributes to n-point functions. We derive a sum rule that isolates this contribution and is manifestly positive. The argument also applies to certain higher spin operators other than the stress tensor, generating an infinite family of new constraints of the form ∫ duX uuu··· u ≥ 0. These lead to new inequalities for the coupling constants of spinning operators in conformal field theory, which include as special cases (but are generally stronger than) the existing constraints from the lightcone bootstrap, deep inelastic scattering, conformal collider methods, and relative entropy. We also comment on the relation to the recent derivation of the averaged null energy condition from relative entropy, and suggest a more general connection between causality and information-theoretic inequalities in QFT.
Reconstructing Causal Biological Networks through Active Learning.
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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.
Causality and local determinism versus quantum nonlocality
International Nuclear Information System (INIS)
Kupczynski, M
2014-01-01
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 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 local determinism. If quantum theory is emergent then there exist perhaps some fine structures in time-series of experimental data which were not predicted by quantum theory. In this paper we explain how a systematic search for such fine structures can be done. If such reproducible fine structures were found it would show that quantum theory is not predictably complete, which would be a major discovery.
From causal dynamical triangulations to astronomical observations
Mielczarek, Jakub
2017-09-01
This letter discusses phenomenological aspects of dimensional reduction predicted by the Causal Dynamical Triangulations (CDT) approach to quantum gravity. The deformed form of the dispersion relation for the fields defined on the CDT space-time is reconstructed. Using the Fermi satellite observations of the GRB 090510 source we find that the energy scale of the dimensional reduction is E* > 0.7 \\sqrt{4-d\\text{UV}} \\cdot 1010 \\text{GeV} at (95% CL), where d\\text{UV} is the value of the spectral dimension in the UV limit. By applying the deformed dispersion relation to the cosmological perturbations it is shown that, for a scenario when the primordial perturbations are formed in the UV region, the scalar power spectrum PS \\propto kn_S-1 , where n_S-1≈ \\frac{3 r (d\\text{UV}-2)}{(d\\text{UV}-1)r-48} . Here, r is the tensor-to-scalar ratio. We find that within the considered model, the predicted from CDT deviation from the scale invariance (n_S=1) is in contradiction with the up to date Planck and BICEP2.
Hypothyroidism and Hyponatremia: Rather Coincidence Than Causality.
Wolf, Peter; Beiglböck, Hannes; Smaijs, Sabina; Wrba, Thomas; Rasoul-Rockenschaub, Susanne; Marculescu, Rodrig; Gessl, Alois; Luger, Anton; Winhofer, Yvonne; Krebs, Michael
2017-05-01
Hypothyroidism is referred to be a rare but possible cause of hyponatremia. However, there is only poor evidence supporting this association. Since hyponatremia and hypothyroidism are both common conditions themselves, co-occurrence does not have to be causal. To address a potential relationship, a retrospective analysis of data from the Division of Endocrinology of the Medical University of Vienna from April 2004 to February 2016 was performed. A total of 8053 hypothyroid patients (48 ± 18 years of age; 71% female) with thyrotropin >4.0 μIU/mL and available blood tests for free thyroxine and sodium (Na + ) within maximal ± seven days were included and screened for hyponatremia. Patients' records were searched for concomitant disease and medication when Na + concentration was causes of hyponatremia in 442/448 (98.88%) patients (i.e., side effects of medication, concomitant underlying disease, or other endocrine disorders). This distribution did not differ between patients suffering from clinical or subclinical hypothyroidism. No case of clinically relevant hyponatremia (Na + hypothyroidism. There was a very weak but statistically significant trend toward a positive association between thyroid function and serum Na + levels (Na + /thyrotropin: R = 0.022, p = 0.046; Na + /free thyroxine: R = -0.047, p hypothyroid patients with moderate to severe hyponatremia often have other potential explanations for their low serum Na + concentrations in routine care.
Dynamic Causal Models and Autopoietic Systems
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OLIVIER DAVID
2007-01-01
Full Text Available 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
Physics Without Causality — Theory and Evidence
Shoup, Richard
2006-10-01
The principle of cause and effect is deeply rooted in human experience, so much so that it is routinely and tacitly assumed throughout science, even by scientists working in areas where time symmetry is theoretically ingrained, as it is in both classical and quantum physics. Experiments are said to cause their results, not the other way around. In this informal paper, we argue that this assumption should be replaced with a more general notion of mutual influence — bi-directional relations or constraints on joint values of two or more variables. From an analysis based on quantum entropy, it is proposed that quantum measurement is a unitary three-interaction, with no collapse, no fundamental randomness, and no barrier to backward influence. Experimental results suggesting retrocausality are seen frequently in well-controlled laboratory experiments in parapsychology and elsewhere, especially where a random element is included. Certain common characteristics of these experiments give the appearance of contradicting well-established physical laws, thus providing an opportunity for deeper understanding and important clues that must be addressed by any explanatory theory. We discuss how retrocausal effects and other anomalous phenomena can be explained without major injury to existing physical theory. A modified quantum formalism can give new insights into the nature of quantum measurement, randomness, entanglement, causality, and time.
Dilepton production in schematic causal viscous hydrodynamics
International Nuclear Information System (INIS)
Song, Taesoo; Han, Kyong Chol; Ko, Che Ming
2011-01-01
Assuming that in the hot dense matter produced in relativistic heavy-ion collisions, the energy density, entropy density, and pressure as well as the azimuthal and space-time rapidity components of the shear tensor are uniform in the direction transversal to the reaction plane, we derive a set of schematic equations from the Isreal-Stewart causal viscous hydrodynamics. These equations are then used to describe the evolution dynamics of relativistic heavy-ion collisions by taking the shear viscosity to entropy density ratio of 1/4π for the initial quark-gluon plasma (QGP) phase and of 10 times this value for the later hadron-gas (HG) phase. Using the production rate evaluated with particle distributions that take into account the viscous effect, we study dilepton production in central heavy-ion collisions. Compared with results from the ideal hydrodynamics, we find that although the dilepton invariant mass spectra from the two approaches are similar, the transverse momentum spectra are significantly enhanced at high transverse momenta by the viscous effect. We also study the transverse momentum dependence of dileptons produced from QGP for a fixed transverse mass, which is essentially absent in the ideal hydrodynamics, and find that this so-called transverse mass scaling is violated in the viscous hydrodynamics, particularly at high transverse momenta.
The Causal Factors Associated with the Loving
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Seyed Taghi Heydari
2015-10-01
Full Text Available Background: Families with disabled children need more psycho-social considerations. Motherhood care of the children with multiple disabilities is difficult. Due to its importance, the aim of this study was to investigate the causal factors affecting loving care of mothers of children with multiple disabilities. Methods: The study used a cross-sectional method in which 75 mothers of exceptional children with multiple disabilities (physical and mental in elementary schools in Shiraz, Iran. The data were collected through questionnaires which, besides demographical factors, evaluated the relationship between mothers’ loving care of children with multiple disabilities and four other variables including purpose in life, life satisfaction, religious attitude, and sense of coherence. Mann-Whitney U was used for comparison between mothers’ loving care and other variables. Results: Results revealed that demographic variables did not have a significant relationship with loving care. In the case of social variables, there was a significant relationship between mothers’ loving care and purpose in life (P<0.001, religious attitude (P<0.001, and life satisfaction (P=0.01. Conclusion: Motherhood care of disabled children is a unique phenomenon which is due to attachment of mother-child situation. Nevertheless, these mothers are vulnerable and marginalized people who need more attention and social supports provided by related governmental institutions and also NGOs actors.
Quantum erasure with causally disconnected choice.
Ma, Xiao-Song; Kofler, Johannes; Qarry, Angie; Tetik, Nuray; Scheidl, Thomas; Ursin, Rupert; Ramelow, Sven; Herbst, Thomas; Ratschbacher, Lothar; Fedrizzi, Alessandro; Jennewein, Thomas; Zeilinger, Anton
2013-01-22
The counterintuitive features of quantum physics challenge many common-sense assumptions. In an interferometric quantum eraser experiment, one can actively choose whether or not to erase which-path information (a particle feature) of one quantum system and thus observe its wave feature via interference or not by performing a suitable measurement on a distant quantum system entangled with it. In all experiments performed to date, this choice took place either in the past or, in some delayed-choice arrangements, in the future of the interference. Thus, in principle, physical communications between choice and interference were not excluded. Here, we report a quantum eraser experiment in which, by enforcing Einstein locality, no such communication is possible. This is achieved by independent active choices, which are space-like separated from the interference. Our setup employs hybrid path-polarization entangled photon pairs, which are distributed over an optical fiber link of 55 m in one experiment, or over a free-space link of 144 km in another. No naive realistic picture is compatible with our results because whether a quantum could be seen as showing particle- or wave-like behavior would depend on a causally disconnected choice. It is therefore suggestive to abandon such pictures altogether.
Quantum Steering Beyond Instrumental Causal Networks
Nery, R. V.; Taddei, M. M.; Chaves, R.; Aolita, L.
2018-04-01
We theoretically predict, and experimentally verify with entangled photons, that outcome communication is not enough for hidden-state models to reproduce quantum steering. Hidden-state models with outcome communication correspond, in turn, to the well-known instrumental processes of causal inference but in the one-sided device-independent scenario of one black-box measurement device and one well-characterized quantum apparatus. We introduce one-sided device-independent instrumental inequalities to test against these models, with the appealing feature of detecting entanglement even when communication of the black box's measurement outcome is allowed. We find that, remarkably, these inequalities can also be violated solely with steering, i.e., without outcome communication. In fact, an efficiently computable formal quantifier—the robustness of noninstrumentality—naturally arises, and we prove that steering alone is enough to maximize it. Our findings imply that quantum theory admits a stronger form of steering than known until now, with fundamental as well as practical potential implications.
Directory of Open Access Journals (Sweden)
Lucimar Pereira Bonett
2010-12-01
Full Text Available O fungo Colletotrichum gloeosporioides infecta uma grande variedade de plantas em regiões tropicais, subtropicais e temperadas ocasionando consideráveis perdas econômicas em doenças pré e pós-colheita. O objetivo deste trabalho foi caracterizar a morfologia e a infecção cruzada de isolados de Colletotrichum gloeosporioides obtidos de frutos e hortaliças em pós-colheita. Os isolados foram obtidos de lesões de frutos com sintomas de antracnose e cultivados em meio de cultivo BDA, sendo a avaliação do crescimento micelial realizada por meio de duas leituras diárias do diâmetro das colônias pelo período de quatorze dias e a caracterização morfológica das colônias realizada no final deste período. Para a realização do experimento, utilizou-se o delineamento experimental inteiramente casualisado com três repetições por tratamento. Para o experimento da infecção cruzada foram realizados dois ferimentos em frutos sadios nos quais foram depositados blocos de meio de cultura com 6 mm2 contendo os isolados. O delineamento experimental foi em esquema fatorial de 8 x 8, com quatro repetições. As médias de ambos os experimentos foram analisadas por meio do teste de Scott-Knott com 5% de probabilidade. A maioria dos isolados de C. gloeosporioides possuem grande potencial de infecção cruzada, já que foram capazes de causar lesões em frutos de mamão, manga, abacate, chuchu, jiló, pimentão verde e pimenta. Os isolados de frutos de mamão e abacate apresentaram o maior índice de crescimento micelial e os isolados provenientes do chuchu apresentaram o menor. Quanto ao desenvolvimento de lesões, o mamão apresentou-se mais suscetível, com lesões maiores, enquanto que a pimenta cambuci demonstrou-se a mais resistente, apresentando as menores lesões.
Tabaquismo. La naturaleza causal pide respeto
Chávez-Domínguez,Rafael César
2010-01-01
El tabaquismo es responsable de la pandemia cardiovascular mediada por aterosclerosis. Altera y acelera cambios en estructuras y funciones. Estimula factores tumorales y forma el ateroma. Induce trombosis y ocluye las arterias. La siniestra intromisión arremete contra el sistema cardiovascular. Lo daña desde sus cimientos genéticos e intimidad bimolecular. El remedio es abstención, lo resuelve todo y es sólo conducta. La adicción alimenta disentimiento que se sustenta en falacias y controvers...
New Insights into Signed Path Coefficient Granger Causality Analysis.
Zhang, Jian; Li, Chong; Jiang, Tianzi
2016-01-01
Granger causality analysis, as a time series analysis technique derived from econometrics, has been applied in an ever-increasing number of publications in the field of neuroscience, including fMRI, EEG/MEG, and fNIRS. The present study mainly focuses on the validity of "signed path coefficient Granger causality," a Granger-causality-derived analysis method that has been adopted by many fMRI researches in the last few years. This method generally estimates the causality effect among the time series by an order-1 autoregression, and defines a positive or negative coefficient as an "excitatory" or "inhibitory" influence. In the current work we conducted a series of computations from resting-state fMRI data and simulation experiments to illustrate the signed path coefficient method was flawed and untenable, due to the fact that the autoregressive coefficients were not always consistent with the real causal relationships and this would inevitablely lead to erroneous conclusions. Overall our findings suggested that the applicability of this kind of causality analysis was rather limited, hence researchers should be more cautious in applying the signed path coefficient Granger causality to fMRI data to avoid misinterpretation.
Causal Learning in Gambling Disorder: Beyond the Illusion of Control.
Perales, José C; Navas, Juan F; Ruiz de Lara, Cristian M; Maldonado, Antonio; Catena, Andrés
2017-06-01
Causal learning is the ability to progressively incorporate raw information about dependencies between events, or between one's behavior and its outcomes, into beliefs of the causal structure of the world. In spite of the fact that some cognitive biases in gambling disorder can be described as alterations of causal learning involving gambling-relevant cues, behaviors, and outcomes, general causal learning mechanisms in gamblers have not been systematically investigated. In the present study, we compared gambling disorder patients against controls in an instrumental causal learning task. Evidence of illusion of control, namely, overestimation of the relationship between one's behavior and an uncorrelated outcome, showed up only in gamblers with strong current symptoms. Interestingly, this effect was part of a more complex pattern, in which gambling disorder patients manifested a poorer ability to discriminate between null and positive contingencies. Additionally, anomalies were related to gambling severity and current gambling disorder symptoms. Gambling-related biases, as measured by a standard psychometric tool, correlated with performance in the causal learning task, but not in the expected direction. Indeed, performance of gamblers with stronger biases tended to resemble the one of controls, which could imply that anomalies of causal learning processes play a role in gambling disorder, but do not seem to underlie gambling-specific biases, at least in a simple, direct way.
Cortical hierarchies perform Bayesian causal inference in multisensory perception.
Directory of Open Access Journals (Sweden)
Tim Rohe
2015-02-01
Full Text Available To form a veridical percept of the environment, the brain needs to integrate sensory signals from a common source but segregate those from independent sources. Thus, perception inherently relies on solving the "causal inference problem." Behaviorally, humans solve this problem optimally as predicted by Bayesian Causal Inference; yet, the underlying neural mechanisms are unexplored. Combining psychophysics, Bayesian modeling, functional magnetic resonance imaging (fMRI, and multivariate decoding in an audiovisual spatial localization task, we demonstrate that Bayesian Causal Inference is performed by a hierarchy of multisensory processes in the human brain. At the bottom of the hierarchy, in auditory and visual areas, location is represented on the basis that the two signals are generated by independent sources (= segregation. At the next stage, in posterior intraparietal sulcus, location is estimated under the assumption that the two signals are from a common source (= forced fusion. Only at the top of the hierarchy, in anterior intraparietal sulcus, the uncertainty about the causal structure of the world is taken into account and sensory signals are combined as predicted by Bayesian Causal Inference. Characterizing the computational operations of signal interactions reveals the hierarchical nature of multisensory perception in human neocortex. It unravels how the brain accomplishes Bayesian Causal Inference, a statistical computation fundamental for perception and cognition. Our results demonstrate how the brain combines information in the face of uncertainty about the underlying causal structure of the world.
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.
Non-Gaussian Methods for Causal Structure Learning.
Shimizu, Shohei
2018-05-22
Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.
Causal uncertainty, claimed and behavioural self-handicapping.
Thompson, Ted; Hepburn, Jonathan
2003-06-01
Causal uncertainty beliefs involve doubts about the causes of events, and arise as a consequence of non-contingent evaluative feedback: feedback that leaves the individual uncertain about the causes of his or her achievement outcomes. Individuals high in causal uncertainty are frequently unable to confidently attribute their achievement outcomes, experience anxiety in achievement situations and as a consequence are likely to engage in self-handicapping behaviour. Accordingly, we sought to establish links between trait causal uncertainty, claimed and behavioural self-handicapping. Participants were N=72 undergraduate students divided equally between high and low causally uncertain groups. We used a 2 (causal uncertainty status: high, low) x 3 (performance feedback condition: success, non-contingent success, non-contingent failure) between-subjects factorial design to examine the effects of causal uncertainty on achievement behaviour. Following performance feedback, participants completed 20 single-solution anagrams and 12 remote associate tasks serving as performance measures, and 16 unicursal tasks to assess practice effort. Participants also completed measures of claimed handicaps, state anxiety and attributions. Relative to low causally uncertain participants, high causally uncertain participants claimed more handicaps prior to performance on the anagrams and remote associates, reported higher anxiety, attributed their failure to internal, stable factors, and reduced practice effort on the unicursal tasks, evident in fewer unicursal tasks solved. These findings confirm links between trait causal uncertainty and claimed and behavioural self-handicapping, highlighting the need for educators to facilitate means by which students can achieve surety in the manner in which they attribute the causes of their achievement outcomes.
The causal approach in quantum field theory
International Nuclear Information System (INIS)
Grigore, D. R.
2003-01-01
The mathematical formulation of perturbative renormalization theory starts from Bogoliubov axioms imposed on the S-matrix (or equivalently on the chronological products). The S-matrix is a formal series of operator valued distributions: these distributions are denoted by T(x 1 , ... , x n ) and one supposes that they act in the Fock space of some collection of free fields. These operator-valued distributions are called chronological products. The expression T(x) is called the interaction Lagrangian. It is convenient to construct more general objects namely, the operator-valued distributions T(W 1 (x 1 ), ... ,W n (x n )), where W j are arbitrary Wick monomials. These objects verify some properties (following from Bogolyubov axioms) and express the following properties: the initial condition, skew-symmetry in all arguments, Poincare invariance, causality and unitarity. The existence of solutions follows from the analysis of Epstein and Glaser as a recursive procedure using in an essential way the causality axiom. Sometimes it is possible to supplement these axioms by other invariance properties with respect to space-time symmetries (inversions and/or scale invariance), charge conjugation, global symmetry with respect to some internal symmetry group, supersymmetric invariance, etc. if they are valid for the interaction Lagrangian. In the literature, the invariance properties of the chronological products with respect to scale invariance was analyzed in detail. The scale invariance operators U λ are transforming field operators corresponding to particles of masses m j in fields corresponding to scaled masses λ -1 m j . One can prove that if all masses are positive the chronological products can be normalized such that they are scale invariant. On the contrary, if all masses of the model are zero then the scale invariance of the chronological products can be implemented only up to some logarithmic terms in λ. For models describing higher spin particles unphysical
Causal mediation analysis with multiple mediators.
Daniel, R M; De Stavola, B L; Cousens, S N; Vansteelandt, S
2015-03-01
In diverse fields of empirical research-including many in the biological sciences-attempts are made to decompose the effect of an exposure on an outcome into its effects via a number of different pathways. For example, we may wish to separate the effect of heavy alcohol consumption on systolic blood pressure (SBP) into effects via body mass index (BMI), via gamma-glutamyl transpeptidase (GGT), and via other pathways. Much progress has been made, mainly due to contributions from the field of causal inference, in understanding the precise nature of statistical estimands that capture such intuitive effects, the assumptions under which they can be identified, and statistical methods for doing so. These contributions have focused almost entirely on settings with a single mediator, or a set of mediators considered en bloc; in many applications, however, researchers attempt a much more ambitious decomposition into numerous path-specific effects through many mediators. In this article, we give counterfactual definitions of such path-specific estimands in settings with multiple mediators, when earlier mediators may affect later ones, showing that there are many ways in which decomposition can be done. We discuss the strong assumptions under which the effects are identified, suggesting a sensitivity analysis approach when a particular subset of the assumptions cannot be justified. These ideas are illustrated using data on alcohol consumption, SBP, BMI, and GGT from the Izhevsk Family Study. We aim to bridge the gap from "single mediator theory" to "multiple mediator practice," highlighting the ambitious nature of this endeavor and giving practical suggestions on how to proceed. © 2014 The Authors Biometrics published by Wiley Periodicals, Inc. on behalf of International Biometric Society.
Spatial Causality. An application to the Deforestation Process in Bolivia
Directory of Open Access Journals (Sweden)
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.
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.
The causal structure of spacetime is a parameterized Randers geometry
Energy Technology Data Exchange (ETDEWEB)
Skakala, Jozef; Visser, Matt, E-mail: jozef.skakala@msor.vuw.ac.nz, E-mail: matt.visser@msor.vuw.ac.nz [School of Mathematics, Statistics and Operations Research, Victoria University of Wellington, PO Box 600, Wellington (New Zealand)
2011-03-21
There is a well-established isomorphism between stationary four-dimensional spacetimes and three-dimensional purely spatial Randers geometries-these Randers geometries being a particular case of the more general class of three-dimensional Finsler geometries. We point out that in stably causal spacetimes, by using the (time-dependent) ADM decomposition, this result can be extended to general non-stationary spacetimes-the causal structure (conformal structure) of the full spacetime is completely encoded in a parameterized (t-dependent) class of Randers spaces, which can then be used to define a Fermat principle, and also to reconstruct the null cones and causal structure.
The causal structure of spacetime is a parameterized Randers geometry
International Nuclear Information System (INIS)
Skakala, Jozef; Visser, Matt
2011-01-01
There is a well-established isomorphism between stationary four-dimensional spacetimes and three-dimensional purely spatial Randers geometries-these Randers geometries being a particular case of the more general class of three-dimensional Finsler geometries. We point out that in stably causal spacetimes, by using the (time-dependent) ADM decomposition, this result can be extended to general non-stationary spacetimes-the causal structure (conformal structure) of the full spacetime is completely encoded in a parameterized (t-dependent) class of Randers spaces, which can then be used to define a Fermat principle, and also to reconstruct the null cones and causal structure.
Ma, Sisi; Kemmeren, Patrick; Aliferis, Constantin F.; Statnikov, Alexander
2016-01-01
Reverse-engineering of causal pathways that implicate diseases and vital cellular functions is a fundamental problem in biomedicine. Discovery of the local causal pathway of a target variable (that consists of its direct causes and direct effects) is essential for effective intervention and can facilitate accurate diagnosis and prognosis. Recent research has provided several active learning methods that can leverage passively observed high-throughput data to draft causal pathways and then refine the inferred relations with a limited number of experiments. The current study provides a comprehensive evaluation of the performance of active learning methods for local causal pathway discovery in real biological data. Specifically, 54 active learning methods/variants from 3 families of algorithms were applied for local causal pathways reconstruction of gene regulation for 5 transcription factors in S. cerevisiae. Four aspects of the methods’ performance were assessed, including adjacency discovery quality, edge orientation accuracy, complete pathway discovery quality, and experimental cost. The results of this study show that some methods provide significant performance benefits over others and therefore should be routinely used for local causal pathway discovery tasks. This study also demonstrates the feasibility of local causal pathway reconstruction in real biological systems with significant quality and low experimental cost. PMID:26939894
Charakopoulos, A. K.; Katsouli, G. A.; Karakasidis, T. E.
2018-04-01
Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly established. The purpose of this study was to examine the performance of two main additional methodologies for the identification of spatiotemporal underlying dynamic characteristics and patterns among atmospheric and oceanic variables from Seawatch buoys from Aegean and Ionian Sea, provided by the Hellenic Center for Marine Research (HCMR). The first approach involves the estimation of cross correlation analysis in an attempt to investigate time-lagged relationships, and further in order to identify the direction of interactions between the variables we performed the Granger causality method. According to the second approach the time series are converted into complex networks and then the main topological network properties such as degree distribution, average path length, diameter, modularity and clustering coefficient are evaluated. Our results show that the proposed analysis of complex network analysis of time series can lead to the extraction of hidden spatiotemporal characteristics. Also our findings indicate high level of positive and negative correlations and causalities among variables, both from the same buoy and also between buoys from different stations, which cannot be determined from the use of simple statistical measures.
Mixed Causal-Noncausal Autoregressions with Strictly Exogenous Regressors
Hecq, Alain; Issler, J.V.; Telg, Sean
2017-01-01
The mixed autoregressive causal-noncausal model (MAR) has been proposed to estimate economic relationships involving explosive roots in their autoregressive part, as they have stationary forward solutions. In previous work, possible exogenous variables in economic relationships are substituted into
Defining the Locus of Developmental Differences in Children's Causal Reasoning
Siegler, Robert S.
1975-01-01
Five experiments were performed in the area of children's causal reasoning to validate a previously reported developmental difference, to examine the role of a possible mediating mechanism, and to test a number of competing theoretical interpretations. (GO)
Moment problems and the causal set approach to quantum gravity
International Nuclear Information System (INIS)
Ash, Avner; McDonald, Patrick
2003-01-01
We study a collection of discrete Markov chains related to the causal set approach to modeling discrete theories of quantum gravity. The transition probabilities of these chains satisfy a general covariance principle, a causality principle, and a renormalizability condition. The corresponding dynamics are completely determined by a sequence of non-negative real coupling constants. Using techniques related to the classical moment problem, we give a complete description of any such sequence of coupling constants. We prove a representation theorem: every discrete theory of quantum gravity arising from causal set dynamics satisfying covariance, causality, and renormalizability corresponds to a unique probability distribution function on the non-negative real numbers, with the coupling constants defining the theory given by the moments of the distribution
causal variables and academic performance of students in cross
African Journals Online (AJOL)
This study investigated the causal variables (Child, Family, School, Society and Government) and academic ... parents in the immediate daily aspect of education ... This study employed the descriptive .... on cognitive development. Journal of.
Energy consumption and economic growth: A causality analysis for Greece
International Nuclear Information System (INIS)
Tsani, Stela Z.
2010-01-01
This paper investigates the causal relationship between aggregated and disaggregated levels of energy consumption and economic growth for Greece for the period 1960-2006 through the application of a later development in the methodology of time series proposed by Toda and Yamamoto (1995). At aggregated levels of energy consumption empirical findings suggest the presence of a uni-directional causal relationship running from total energy consumption to real GDP. At disaggregated levels empirical evidence suggests that there is a bi-directional causal relationship between industrial and residential energy consumption to real GDP but this is not the case for the transport energy consumption with causal relationship being identified in neither direction. The importance of these findings lies on their policy implications and their adoption on structural policies affecting energy consumption in Greece suggesting that in order to address energy import dependence and environmental concerns without hindering economic growth emphasis should be put on the demand side and energy efficiency improvements.
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
On Storks and Babies: Correlation, Causality and Field Experiments
Directory of Open Access Journals (Sweden)
Lambrecht Anja
2016-11-01
Full Text Available The explosion of available data has created much excitement among marketing practitioners about their ability to better understand the impact of marketing investments. Big data allows for detecting patterns and often it seems plausible to interpret them as causal. While it is quite obvious that storks do not bring babies, marketing relationships are usually less clear. Apparent “causalities” often fail to hold up under examination. If marketers want to be sure not to walk into a causality trap, they need to conduct field experiments to detect true causal relationships. In the present digital environment, experiments are easier than ever to execute. However, they need to be prepared and interpreted with great care in order to deliver meaningful and genuinely causal results that help improve marketing decisions.
Causality and symmetry in cosmology and the conformal group
International Nuclear Information System (INIS)
Segal, I.E.
1977-01-01
A new theoretic postulate in fundamental physics is considered which is called the chronometric principle because it deals primarily with the nature of time, or its dual or conjugate, energy. Conformality is equivalent to causality. Thus, the group of all local causality-preserving transformations in the vicinity of a point of Minkowski space is, as a local Lie group, identical with the conformal group. The same statement made globally on Minkowski space is: The set of all vector fields on Minkowski space which generate smooth local causality-preserving transformations is identical with the set of all conformal vector fields. The main validation for the chronometric principle is in cosmology or ultramacroscopic physics. Therefore this principle is illustrated along the lines of the red shift. This principle in combination with quantum field theory leads to a convergent and causal description of particle production in which nonlinearities are supplanted by more sophisticated and comprehensive actions for the fundamental symmetry groups. 11 references
Is Host-Based Anomaly Detection + Temporal Correlation = Worm Causality
National Research Council Canada - National Science Library
Sekar, Vyas; Xie, Yinglian; Reiter, Michael K; Zhang, Hui
2007-01-01
Epidemic-spreading attacks (e.g., worm and botnet propagation) have a natural notion of attack causality - a single network flow causes a victim host to get infected and subsequently spread the attack...
Implications of causality for quantum biology - I: topology change
Scofield, D. F.; Collins, T. C.
2018-06-01
A framework for describing the causal, topology changing, evolution of interacting biomolecules is developed. The quantum dynamical manifold equations (QDMEs) derived from this framework can be related to the causality restrictions implied by a finite speed of light and to Planck's constant to set a transition frequency scale. The QDMEs imply conserved stress-energy, angular-momentum and Noether currents. The functional whose extremisation leads to this result provides a causal, time-dependent, non-equilibrium generalisation of the Hohenberg-Kohn theorem. The system of dynamical equations derived from this functional and the currents J derived from the QDMEs are shown to be causal and consistent with the first and second laws of thermodynamics. This has the potential of allowing living systems to be quantum mechanically distinguished from non-living ones.
Contrasting cue-density effects in causal and prediction judgments.
Vadillo, Miguel A; Musca, Serban C; Blanco, Fernando; Matute, Helena
2011-02-01
Many theories of contingency learning assume (either explicitly or implicitly) that predicting whether an outcome will occur should be easier than making a causal judgment. Previous research suggests that outcome predictions would depart from normative standards less often than causal judgments, which is consistent with the idea that the latter are based on more numerous and complex processes. However, only indirect evidence exists for this view. The experiment presented here specifically addresses this issue by allowing for a fair comparison of causal judgments and outcome predictions, both collected at the same stage with identical rating scales. Cue density, a parameter known to affect judgments, is manipulated in a contingency learning paradigm. The results show that, if anything, the cue-density bias is stronger in outcome predictions than in causal judgments. These results contradict key assumptions of many influential theories of contingency learning.
QED representation for the net of causal loops
Ciolli, Fabio; Ruzzi, Giuseppe; Vasselli, Ezio
2015-06-01
The present work tackles the existence of local gauge symmetries in the setting of Algebraic Quantum Field Theory (AQFT). The net of causal loops, previously introduced by the authors, is a model independent construction of a covariant net of local C*-algebras on any 4-dimensional globally hyperbolic space-time, aimed to capture structural properties of any reasonable quantum gauge theory. Representations of this net can be described by causal and covariant connection systems, and local gauge transformations arise as maps between equivalent connection systems. The present paper completes these abstract results, realizing QED as a representation of the net of causal loops in Minkowski space-time. More precisely, we map the quantum electromagnetic field Fμν, not free in general, into a representation of the net of causal loops and show that the corresponding connection system and the local gauge transformations find a counterpart in terms of Fμν.
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
Causality relationship between electricity consumption and GDP in Bangladesh
International Nuclear Information System (INIS)
Mozumder, Pallab; Marathe, Achla
2007-01-01
In this paper, we examine the causal relationship between the per capita electricity consumption and the per capita GDP for Bangladesh using cointegration and vector error correction model. Our results show that there is unidirectional causality from per capita GDP to per capita electricity consumption. However, the per capita electricity consumption does not cause per capita GDP in case of Bangladesh. The finding has significant implications from the point of view of energy conservation, emission reduction and economic development
Ultra-Wideband Electromagnetic Pulse Propagation through Causal Media
2016-03-04
AFRL-AFOSR-VA-TR-2016-0112 Ultra-Wideband Electromagnetic Pulse Propagation through Causal Media Natalie Cartwright RESEARCH FOUNDATION OF STATE... Electromagnetic Pulse Propagation through Causal Media 5a. CONTRACT NUMBER 5b. GRANT NUMBER FA9550-13-1-0013 5c. PROGRAM ELEMENT NUMBER 61102F 6...SUPPLEMENTARY NOTES 14. ABSTRACT When an electromagnetic pulse travels through a dispersive material each frequency of the transmitted pulse changes in both
Causal Bayes Model of Mathematical Competence in Kindergarten
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Božidar Tepeš
2016-06-01
Full Text Available In this paper authors define mathematical competences in the kindergarten. The basic objective was to measure the mathematical competences or mathematical knowledge, skills and abilities in mathematical education. Mathematical competences were grouped in the following areas: Arithmetic and Geometry. Statistical set consisted of 59 children, 65 to 85 months of age, from the Kindergarten Milan Sachs from Zagreb. The authors describe 13 variables for measuring mathematical competences. Five measuring variables were described for the geometry, and eight measuring variables for the arithmetic. Measuring variables are tasks which children solved with the evaluated results. By measuring mathematical competences the authors make causal Bayes model using free software Tetrad 5.2.1-3. Software makes many causal Bayes models and authors as experts chose the model of the mathematical competences in the kindergarten. Causal Bayes model describes five levels for mathematical competences. At the end of the modeling authors use Bayes estimator. In the results, authors describe by causal Bayes model of mathematical competences, causal effect mathematical competences or how intervention on some competences cause other competences. Authors measure mathematical competences with their expectation as random variables. When expectation of competences was greater, competences improved. Mathematical competences can be improved with intervention on causal competences. Levels of mathematical competences and the result of intervention on mathematical competences can help mathematical teachers.
Causal inference in survival analysis using pseudo-observations.
Andersen, Per K; Syriopoulou, Elisavet; Parner, Erik T
2017-07-30
Causal inference for non-censored response variables, such as binary or quantitative outcomes, is often based on either (1) direct standardization ('G-formula') or (2) inverse probability of treatment assignment weights ('propensity score'). To do causal inference in survival analysis, one needs to address right-censoring, and often, special techniques are required for that purpose. We will show how censoring can be dealt with 'once and for all' by means of so-called pseudo-observations when doing causal inference in survival analysis. The pseudo-observations can be used as a replacement of the outcomes without censoring when applying 'standard' causal inference methods, such as (1) or (2) earlier. We study this idea for estimating the average causal effect of a binary treatment on the survival probability, the restricted mean lifetime, and the cumulative incidence in a competing risks situation. The methods will be illustrated in a small simulation study and via a study of patients with acute myeloid leukemia who received either myeloablative or non-myeloablative conditioning before allogeneic hematopoetic cell transplantation. We will estimate the average causal effect of the conditioning regime on outcomes such as the 3-year overall survival probability and the 3-year risk of chronic graft-versus-host disease. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.
Causal quantum theory and the collapse locality loophole
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Kent, Adrian
2005-01-01
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
Whose statistical reasoning is facilitated by a causal structure intervention?
McNair, Simon; Feeney, Aidan
2015-02-01
People often struggle when making Bayesian probabilistic estimates on the basis of competing sources of statistical evidence. Recently, Krynski and Tenenbaum (Journal of Experimental Psychology: General, 136, 430-450, 2007) proposed that a causal Bayesian framework accounts for peoples' errors in Bayesian reasoning and showed that, by clarifying the causal relations among the pieces of evidence, judgments on a classic statistical reasoning problem could be significantly improved. We aimed to understand whose statistical reasoning is facilitated by the causal structure intervention. In Experiment 1, although we observed causal facilitation effects overall, the effect was confined to participants high in numeracy. We did not find an overall facilitation effect in Experiment 2 but did replicate the earlier interaction between numerical ability and the presence or absence of causal content. This effect held when we controlled for general cognitive ability and thinking disposition. Our results suggest that clarifying causal structure facilitates Bayesian judgments, but only for participants with sufficient understanding of basic concepts in probability and statistics.
Partial Granger causality--eliminating exogenous inputs and latent variables.
Guo, Shuixia; Seth, Anil K; Kendrick, Keith M; Zhou, Cong; Feng, Jianfeng
2008-07-15
Attempts to identify causal interactions in multivariable biological time series (e.g., gene data, protein data, physiological data) can be undermined by the confounding influence of environmental (exogenous) inputs. Compounding this problem, we are commonly only able to record a subset of all related variables in a system. These recorded variables are likely to be influenced by unrecorded (latent) variables. To address this problem, we introduce a novel variant of a widely used statistical measure of causality--Granger causality--that is inspired by the definition of partial correlation. Our 'partial Granger causality' measure is extensively tested with toy models, both linear and nonlinear, and is applied to experimental data: in vivo multielectrode array (MEA) local field potentials (LFPs) recorded from the inferotemporal cortex of sheep. Our results demonstrate that partial Granger causality can reveal the underlying interactions among elements in a network in the presence of exogenous inputs and latent variables in many cases where the existing conditional Granger causality fails.
Human Papilloma Viruses and Breast Cancer – Assessment of Causality
Lawson, James Sutherland; Glenn, Wendy K.; Whitaker, Noel James
2016-01-01
High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case–control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is “specificity.” HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers. PMID:27747193
Human Papilloma Viruses and Breast Cancer - Assessment of Causality.
Lawson, James Sutherland; Glenn, Wendy K; Whitaker, Noel James
2016-01-01
High risk human papilloma viruses (HPVs) may have a causal role in some breast cancers. Case-control studies, conducted in many different countries, consistently indicate that HPVs are more frequently present in breast cancers as compared to benign breast and normal breast controls (odds ratio 4.02). The assessment of causality of HPVs in breast cancer is difficult because (i) the HPV viral load is extremely low, (ii) HPV infections are common but HPV associated breast cancers are uncommon, and (iii) HPV infections may precede the development of breast and other cancers by years or even decades. Further, HPV oncogenesis can be indirect. Despite these difficulties, the emergence of new evidence has made the assessment of HPV causality, in breast cancer, a practical proposition. With one exception, the evidence meets all the conventional criteria for a causal role of HPVs in breast cancer. The exception is "specificity." HPVs are ubiquitous, which is the exact opposite of specificity. An additional reservation is that the prevalence of breast cancer is not increased in immunocompromised patients as is the case with respect to HPV-associated cervical cancer. This indicates that HPVs may have an indirect causal influence in breast cancer. Based on the overall evidence, high-risk HPVs may have a causal role in some breast cancers.
Increasing fMRI sampling rate improves Granger causality estimates.
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Fa-Hsuan Lin
Full Text Available Estimation of causal interactions between brain areas is necessary for elucidating large-scale functional brain networks underlying behavior and cognition. Granger causality analysis of time series data can quantitatively estimate directional information flow between brain regions. Here, we show that such estimates are significantly improved when the temporal sampling rate of functional magnetic resonance imaging (fMRI is increased 20-fold. Specifically, healthy volunteers performed a simple visuomotor task during blood oxygenation level dependent (BOLD contrast based whole-head inverse imaging (InI. Granger causality analysis based on raw InI BOLD data sampled at 100-ms resolution detected the expected causal relations, whereas when the data were downsampled to the temporal resolution of 2 s typically used in echo-planar fMRI, the causality could not be detected. An additional control analysis, in which we SINC interpolated additional data points to the downsampled time series at 0.1-s intervals, confirmed that the improvements achieved with the real InI data were not explainable by the increased time-series length alone. We therefore conclude that the high-temporal resolution of InI improves the Granger causality connectivity analysis of the human brain.
CAUSAL PEER EFFECTS IN FINANCIAL DECISION MAKING
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Ana Njegovanović
2016-03-01
Full Text Available The research paper connects three key elements from the study (conducted using neural database of experimental asset market that have tested the fundamental mechanisms that generate peer effect, the neural database was measured using functional magnetic resonance imaging (fMRI; Cary Frydman, 2015- University of Southern California-Marshall School of Business relating to: experimental control in the laboratory of random peer assignment,; neural activity in testing new prediction explaining peer effect and neural activity in the conduct of trade. The methodology used in the research of peer effect relies on the theory of predicting error, the signal which measures changes in anticipation of the net present value which generates new information. Cognitive neuroscience shows that the prediction error is measured in a certain part of the brain known as the ventral striatum. Measuring the potential value gives insights to economists on which factors affecting the subjective utility. Testing is constructed with 48 patients who were given $ 100 of experimental money and they were given the opportunity to invest in two separate assets in over two hundred experiments. The experiment showed that subjects converted their final portfolio from experimental currency to real dollars using the exchange rate of 5: 1. In addition to profits from the experiment, subjects were paid a fixed "show-up" fee of $ 20. There are two difficulties in identifying causal peer effect in economic behavior (Minsk, 1993. Correlated behavior between two representatives may potentially be the engine by common shocks of the peer group or endogenous election in the peer group. In addition to the prediction that deals with causal peer effect, there have been further developed predictions that generate different mechanisms of peer effects using neural database. Focus on neural prediction is the neural activity that generates the moment when peers allocation investment is published
Ordem temporal e inferência causal
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Warren E. Miller
2001-11-01
Full Text Available Medidas de mudança em pares de variáveis atitudinais podem proporcionar insights Importantes sobre a estrutura dos sistemas de crenças políticas dos públicos de massa. Dados de painéis revelam evidências da grande centralidade de alguns elementos de idéias em vez de outros no contexto de constrangimento dinâmico de curto prazo. A especificação dos atributos teoricamente relevantes dos eleitores torna possível testar diferenças estruturais esperadas que conectam predisposições relacionadas a políticas e preferências por políticas; a especificação também torna possível testar proposições que envolvem os efeitos recíprocos de atitudes e preferências emergentes de voto. Algumas das especificações mais úteis revelam até que ponto a heterogeneidade da população produz uma imagem embaçada de relações quando a análise se baseia no eleitorado total, em vez de se limitar a eleitores ou subconjuntos de eleitores especificados por critérios teóricos.Measures of change in pairs of attitudinal variables can provide important insights into the structure of the political belief systems of mass publics. Panel data reveal evidence of the greater centrality of some idea elements rather than others in the context of short-term dynamic constraint. Specification of the theoretically relevant voter attributes makes it possible to test for expected structural differences connecting policy related pre-dispositions and policy preferences; specification also makes it possible to test propositions involving the reciprocal effects of attitudes and emerging vote preferences. Some of the more helpful specifications disclose the extent to which population heterogeneity produces a blurred image of relationships when analysis is based on the total electorate rather than limited to voters or subsets of voters specified by theoretical criteria.
Manu, Patrick A; Ankrah, Nii A; Proverbs, David G; Suresh, Subashini
2012-09-01
Construction project features (CPFs) are organisational, physical and operational attributes that characterise construction projects. Although previous studies have examined the accident causal influence of CPFs, the multi-causal attribute of this causal phenomenon still remain elusive and thus requires further investigation. Aiming to shed light on this facet of the accident causal phenomenon of CPFs, this study examines relevant literature and crystallises the attained insight of the multi-causal attribute by a graphical model which is subsequently operationalised by a derived mathematical risk expression that offers a systematic approach for evaluating the potential of CPFs to cause harm and consequently their health and safety (H&S) risk implications. The graphical model and the risk expression put forth by the study thus advance current understanding of the accident causal phenomenon of CPFs and they present an opportunity for project participants to manage the H&S risk associated with CPFs from the early stages of project procurement. Copyright © 2011 Elsevier Ltd. All rights reserved.
UMA TEORÍA CAUSAL PARA LOS CASOS FREGE
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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.
Opening the Black Box and Searching for Smoking Guns: Process Causality in Qualitative Research
Bennett, Elisabeth E.; McWhorter, Rochell R.
2016-01-01
Purpose: The purpose of this paper is to explore the role of qualitative research in causality, with particular emphasis on process causality. In one paper, it is not possible to discuss all the issues of causality, but the aim is to provide useful ways of thinking about causality and qualitative research. Specifically, a brief overview of the…
Sensitivity Analysis and Bounding of Causal Effects with Alternative Identifying Assumptions
Jo, Booil; Vinokur, Amiram D.
2011-01-01
When identification of causal effects relies on untestable assumptions regarding nonidentified parameters, sensitivity of causal effect estimates is often questioned. For proper interpretation of causal effect estimates in this situation, deriving bounds on causal parameters or exploring the sensitivity of estimates to scientifically plausible…
They Work Together to Roar: Kindergartners' Understanding of an Interactive Causal Task
Solis, S. Lynneth; Grotzer, Tina A.
2016-01-01
The aim of this study was to investigate kindergartners' exploration of interactive causality during their play with a pair of toy sound blocks. Interactive causality refers to a type of causal pattern in which two entities interact to produce a causal force, as in particle attraction and symbiotic relationships. Despite being prevalent in nature,…
The Causal Relationship between Health and Education Expenditures in Malaysia
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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.
The Bradford Hill considerations on causality: a counterfactual perspective
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Höfler Michael
2005-11-01
Full Text Available Abstract Bradford Hill's considerations published in 1965 had an enormous influence on attempts to separate causal from non-causal explanations of observed associations. These considerations were often applied as a checklist of criteria, although they were by no means intended to be used in this way by Hill himself. Hill, however, avoided defining explicitly what he meant by "causal effect". This paper provides a fresh point of view on Hill's considerations from the perspective of counterfactual causality. I argue that counterfactual arguments strongly contribute to the question of when to apply the Hill considerations. Some of the considerations, however, involve many counterfactuals in a broader causal system, and their heuristic value decreases as the complexity of a system increases; the danger of misapplying them can be high. The impacts of these insights for study design and data analysis are discussed. The key analysis tool to assess the applicability of Hill's considerations is multiple bias modelling (Bayesian methods and Monte Carlo sensitivity analysis; these methods should be used much more frequently.
Causal Scale of Rotors in a Cardiac System
Ashikaga, Hiroshi; Prieto-Castrillo, Francisco; Kawakatsu, Mari; Dehghani, Nima
2018-04-01
Rotors of spiral waves are thought to be one of the potential mechanisms that maintain atrial fibrillation (AF). However, disappointing clinical outcomes of rotor mapping and ablation to eliminate AF raise a serious doubt on rotors as a macro-scale mechanism that causes the micro-scale behavior of individual cardiomyocytes to maintain spiral waves. In this study, we aimed to elucidate the causal relationship between rotors and spiral waves in a numerical model of cardiac excitation. To accomplish the aim, we described the system in a series of spatiotemporal scales by generating a renormalization group, and evaluated the causal architecture of the system by quantifying causal emergence. Causal emergence is an information-theoretic metric that quantifies emergence or reduction between micro- and macro-scale behaviors of a system by evaluating effective information at each scale. We found that the cardiac system with rotors has a spatiotemporal scale at which effective information peaks. A positive correlation between the number of rotors and causal emergence was observed only up to the scale of peak causation. We conclude that rotors are not the universal mechanism to maintain spiral waves at all spatiotemporal scales. This finding may account for the conflicting benefit of rotor ablation in clinical studies.
Concepts in causality: chemically induced human urinary bladder cancer
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Lower, G.M. Jr.
1982-01-01
A significant portion of the incidence of human urinary bladder cancer can be attributed to occupational and cultural (tobacco smoking) situations associated with exposures to various arylamines, many of which represent established human carcinogens. A brief historical overview of research in bladder cancer causality indicates that the identification of causal agents and causal mechanism has been approached and rests upon information gathered at the organismal (geographical/historical), cellular, and molecular levels of biologic organization. This viewpoint speaks of a natural evolution within the biomedical sciences; a natural evolution from descriptive approaches to mechanistic approaches; and a natural evolution from more or less independent discipline-oriented approaches to hierarchically organized multidisciplinary approaches. Available information relevant to bladder cancer causality can be readily integrated into general conceptual frameworks to yield a hierarchial view of the natural history of urinary bladder cancer, a view consistent with contemporary natural systems and information theory and perhaps relevant also to other chemically induced epithelial cancers. Such frameworks are useful in appreciating the spatial and temporal boundaries and interrelationships in causality and the conceptual interrelationships within the biomedical sciences. Recent approaches in molecular epidemiology and the assessment of relative individual susceptibility to bladder cancer indicate that such frameworks are useful in forming hypotheses
The causality between energy consumption and economic growth in Turkey
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Erdal, Guelistan; Erdal, Hilmi; Esenguen, Kemal
2008-01-01
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
Causality analysis of diesel consumption and economic growth in Cameroon
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Tamba, Jean Gaston; Njomo, Donatien; Limanond, Thirayoot; Ntsafack, Borel
2012-01-01
This study examines the causal relationship between diesel consumption and economic growth in Cameroon by using a three-step modern time-series technique. Tests for unit roots, cointegration, and Granger-causality based on error correction model are employed on annual data covering the period 1975–2008. Empirical results of the study confirm the presence of a long-run equilibrium relationship between diesel consumption and economic growth. The error correction model shows that an estimated 1% increase in economic growth causes a rise in diesel consumption of 1.30% in the long-run. The overall results show that there exists bidirectional causality in the long-run relationship and no causality in the short-run relationship between diesel consumption and economic growth at the 5% level of significance. Thus, the energy policies in Cameroon should place priority on the discovery of new oil field and building capacity additions of the refinery to increase production of petroleum products, as this would propel the economic growth of the country. - Highlights: ► We examine the causal relationship between diesel consumption and GDP in Cameroon. ► we analyze the petroleum products sector in Cameroon. ► 1% increase in economic growth causes a rise in diesel consumption of 1.30%. ► The policy aimed at improving diesel supply have a positive impact on economics.
On the entanglement entropy of quantum fields in causal sets
Belenchia, Alessio; Benincasa, Dionigi M. T.; Letizia, Marco; Liberati, Stefano
2018-04-01
In order to understand the detailed mechanism by which a fundamental discreteness can provide a finite entanglement entropy, we consider the entanglement entropy of two classes of free massless scalar fields on causal sets that are well approximated by causal diamonds in Minkowski spacetime of dimensions 2, 3 and 4. The first class is defined from discretised versions of the continuum retarded Green functions, while the second uses the causal set’s retarded nonlocal d’Alembertians parametrised by a length scale l k . In both cases we provide numerical evidence that the area law is recovered when the double-cutoff prescription proposed in Sorkin and Yazdi (2016 Entanglement entropy in causal set theory (arXiv:1611.10281)) is imposed. We discuss in detail the need for this double cutoff by studying the effect of two cutoffs on the quantum field and, in particular, on the entanglement entropy, in isolation. In so doing, we get a novel interpretation for why these two cutoff are necessary, and the different roles they play in making the entanglement entropy on causal sets finite.
Corporate Governance and Financial Performance Nexus: Any Bidirectional Causality?
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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.
Causal attributions in Brazilian children's reasoning about health and illness
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Boruchovitch Evely
2000-01-01
Full Text Available INTRODUCTION: At a time when a great number of diseases can be prevented by changing one's habits and life style, investigations have focused on understanding what adults and children believe to be desirable health practices and uncovering the factors associated with successful adherence to such practices. For these, causal attributions for health and illness were investigated among 96 Brazilian elementary school students. METHODS: Ninety six subjects, aged 6 to 14, were interviewed individually and their causal attributions were assessed through 14 true-false items (e.g. people stay well [healthy] because they are lucky. The relationship between the children's causal attributions and demographic characteristics were also examined. RESULTS: Overall, the results were consistent with previous researches. "Taking care of oneself" was considered the most important cause of good health. "Viruses and germs" and "lack of self-care" were the most selected causes of illness. Analyses revealed significant relationship between subjects' causal attribution and their age, school grade level, socioeconomic status and gender. CONCLUSIONS: The study findings suggest that there may be more cross-cultural similarities than differences in children's causal attributions for health and illness. Finding ways to help individuals engage in appropriate preventive-maintenance health practices without developing an exaggerated notion that the individuals can control their own health and illness is a challenge which remains to be addressed by further research.
On the Temporal Causal Relationship Between Macroeconomic Variables
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Srinivasan Palamalai
2014-02-01
Full Text Available The present study examines the dynamic interactions among macroeconomic variables such as real output, prices, money supply, interest rate (IR, and exchange rate (EXR in India during the pre-economic crisis and economic crisis periods, using the autoregressive distributed lag (ARDL bounds test for cointegration, Johansen and Juselius multivariate cointegration test, Granger causality/Block exogeneity Wald test based on Vector Error Correction Model, variance decomposition analysis and impulse response functions. The empirical results reveal a stronger long-run bilateral relationship between real output, price level, IR, and EXR during the pre-crisis sample period. Moreover, the empirical results confirm a unidirectional short-run causality running from price level to EXR, IR to price level, and real output to money supply during the pre-crisis period. Also, it is evident from the test results that there exist short-run bidirectional relationships running between real output and EXR, price level and IR, and IR and EXR in the pre-crisis era, respectively. Most importantly, long-run bidirectional causality is found between real output, EXR, and IR during the economic crisis period. And the study results indicate short-run bidirectional causality between money supply and EXR, IR and price level, and IR and output in India during the crisis era. Also, a short-run unidirectional causality runs from prices to real output in the crisis period.
Causality between public policies and exports of renewable energy technologies
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Sung, Bongsuk; Song, Woo-Yong
2013-01-01
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
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Wesseh, Presley K.; Zoumara, Babette
2012-01-01
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.
Tensor products of process matrices with indefinite causal structure
Jia, Ding; Sakharwade, Nitica
2018-03-01
Theories with indefinite causal structure have been studied from both the fundamental perspective of quantum gravity and the practical perspective of information processing. In this paper we point out a restriction in forming tensor products of objects with indefinite causal structure in certain models: there exist both classical and quantum objects the tensor products of which violate the normalization condition of probabilities, if all local operations are allowed. We obtain a necessary and sufficient condition for when such unrestricted tensor products of multipartite objects are (in)valid. This poses a challenge to extending communication theory to indefinite causal structures, as the tensor product is the fundamental ingredient in the asymptotic setting of communication theory. We discuss a few options to evade this issue. In particular, we show that the sequential asymptotic setting does not suffer the violation of normalization.
Predicting the Cosmological Constant from the Causal Entropic Principle
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Bousso, Raphael; Bousso, Raphael; Harnik, Roni; Kribs, Graham D.; Perez, Gilad
2007-05-01
We compute the expected value of the cosmological constant in our universe from the Causal Entropic Principle. Since observers must obey the laws of thermodynamics and causality, the principle asserts that physical parameters are most likely to be found in the range of values for which the total entropy production within a causally connected region is maximized. Despite the absence of more explicit anthropic criteria, the resulting probability distribution turns out to be in excellent agreement with observation. In particular, we find that dust heated by stars dominates the entropy production, demonstrating the remarkable power of this thermodynamic selection criterion. The alternative approach-weighting by the number of"observers per baryon" -- is less well-defined, requires problematic assumptions about the nature of observers, and yet prefers values larger than present experimental bounds.
Predicting the Cosmological Constant from the CausalEntropic Principle
Energy Technology Data Exchange (ETDEWEB)
Bousso, Raphael; Harnik, Roni; Kribs, Graham D.; Perez, Gilad
2007-02-20
We compute the expected value of the cosmological constant in our universe from the Causal Entropic Principle. Since observers must obey the laws of thermodynamics and causality, it asserts that physical parameters are most likely to be found in the range of values for which the total entropy production within a causally connected region is maximized. Despite the absence of more explicit anthropic criteria, the resulting probability distribution turns out to be in excellent agreement with observation. In particular, we find that dust heated by stars dominates the entropy production, demonstrating the remarkable power of this thermodynamic selection criterion. The alternative approach--weighting by the number of ''observers per baryon''--is less well-defined, requires problematic assumptions about the nature of observers, and yet prefers values larger than present experimental bounds.
Relating the thermodynamic arrow of time to the causal arrow
International Nuclear Information System (INIS)
Allahverdyan, Armen E; Janzing, Dominik
2008-01-01
Consider a Hamiltonian system that consists of a slow subsystem S and a fast subsystem F. The autonomous dynamics of S is driven by an effective Hamiltonian, but its thermodynamics is unexpected. We show that a well-defined thermodynamic arrow of time (second law) emerges for S whenever there is a well-defined causal arrow from S to F and the back-action is negligible. This is because the back-action of F on S is described by a non-globally Hamiltonian Born–Oppenheimer term that violates the Liouville theorem, and makes the second law inapplicable to S. If S and F are mixing, under the causal arrow condition they are described by microcanonical distributions P(S) and P(S|F). Their structure supports a causal inference principle proposed recently in machine learning
No simple dual to the causal holographic information?
Energy Technology Data Exchange (ETDEWEB)
Engelhardt, Netta [Department of Physics, Princeton University,Princeton, NJ, 08544 (United States); Wall, Aron C. [Institute for Advanced Study,Einstein Drive, Princeton, NJ, 08540 (United States)
2017-04-21
In AdS/CFT, the fine grained entropy of a boundary region is dual to the area of an extremal surface X in the bulk. It has been proposed that the area of a certain ‘causal surface’ C — i.e. the ‘causal holographic information’ (CHI) — corresponds to some coarse-grained entropy in the boundary theory. We construct two kinds of counterexamples that rule out various possible duals, using (1) vacuum rigidity and (2) thermal quenches. This includes the ‘one-point entropy’ proposed by Kelly and Wall, and a large class of related procedures. Also, any coarse-graining that fixes the geometry of the bulk ‘causal wedge’ bounded by C, fails to reproduce CHI. This is in sharp contrast to the holographic entanglement entropy, where the area of the extremal surface X measures the same information that is found in the ‘entanglement wedge’ bounded by X.
Informational and Causal Architecture of Discrete-Time Renewal Processes
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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.
The latent causal chain of industrial water pollution in China.
Miao, Xin; Tang, Yanhong; Wong, Christina W Y; Zang, Hongyu
2015-01-01
The purpose of this paper is to discover the latent causal chain of industrial water pollution in China and find ways to cure the want on discharge of toxic waste from industries. It draws evidences from the past pollution incidents in China. Through further digging the back interests and relations by analyzing representative cases, extended theory about loophole derivations and causal chain effect is drawn. This theoretical breakthrough reflects deeper causality. Institutional defect instead of human error is confirmed as the deeper reason of frequent outbreaks of water pollution incidents in China. Ways for collaborative environmental governance are proposed. This paper contributes to a better understanding about the deep inducements of industrial water pollution in China, and, is meaningful for ensuring future prevention and mitigation of environmental pollution. It illuminates multiple dimensions for collaborative environmental governance to cure the stubborn problem.
Causal Analysis for Performance Modeling of Computer Programs
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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.
Economic growth and energy consumption in Algeria: a causality analysis
International Nuclear Information System (INIS)
Cherfi, S.
2011-01-01
The purpose of this study is to review the causal link in the Granger sense, between energy consumption and economic growth in Algeria, to determine its implications for economic policy. The analysis was done based on Granger static and causality tests using statistical data on per capita primary energy consumption and gross domestic product per inhabitant in Algeria, over the 1965-2008 period. The results of the survey show that there is, in Algeria, a strong link between energy consumption per inhabitant and GDP per inhabitant. The results also suggest the lack of a long term impetus (no co-integration) between energy consumption and economic growth. In addition, there is a one-way causal link between GDP and energy consumption, i.e. the prior GDP data provides a better forecast of energy consumption level, but not the contrary. In other words, GDP explains consumption, not the contrary. (author)
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...
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...
4. VACUI RATIONE. OBSERVABILITY AND CAUSAL POWERS OF A NONENTITY
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Enrico Pasini
2013-08-01
Full Text Available The notion of the vacuum is transmitted to early modern natural philosophy mainly in two versions: macroscopic void space, as a component of standard atomist theories; and microscopic void spaces interspersed within matter, that according to the pneumatic literature can be forcefully collected into artificial vacua of the first sort. Both kinds of natural vacua are directly or indirectly connected to causal effects, that may be attributed to different causal powers, directly or indirectly pertaining to the vacuum itself. The question also arises whether the purported physical vacuum ought to be observable, either directly or through the presence versus the testable absence of the same causal powers. In contrast to natural philosophy, within the medical discourse—more open to different interpretations of phenomena connected with the vacuum—even the question of observability might present unexpected facets.
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......It is a relatively new insight of classical statistics that empirical data can contain information about causation rather than mere correlation. First algorithms have been proposed that are capable of testing whether a presumed causal relationship is compatible with an observed distribution...
Markovits, Henry
2014-12-01
Understanding the development of conditional (if-then) reasoning is critical for theoretical and educational reasons. Here we examined the hypothesis that there is a developmental transition between reasoning with true and contrary-to-fact (CF) causal conditionals. A total of 535 students between 11 and 14 years of age received priming conditions designed to encourage use of either a true or CF alternatives generation strategy and reasoning problems with true causal and CF causal premises (with counterbalanced order). Results show that priming had no effect on reasoning with true causal premises. By contrast, priming with CF alternatives significantly improved logical reasoning with CF premises. Analysis of the effect of order showed that reasoning with CF premises reduced logical responding among younger students but had no effect among older students. Results support the idea that there is a transition in the reasoning processes in this age range associated with the nature of the alternatives generation process required for logical reasoning with true and CF causal conditionals. Copyright © 2014 Elsevier Inc. All rights reserved.
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.
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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.
A Hierarchical Causal Taxonomy of Psychopathology across the Life Span
Lahey, Benjamin B.; Krueger, Robert F.; Rathouz, Paul J.; Waldman, Irwin D.; Zald, David H.
2016-01-01
We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the three levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. PMID:28004947
Occupational safety management: the role of causal attribution.
Gyekye, Seth Ayim
2010-12-01
The paper addresses the causal attribution theory, an old and well-established theme in social psychology which denotes the everyday, commonsense explanations that people use to explain events and the world around them. The attribution paradigm is considered one of the most appropriate analytical tools for exploratory and descriptive studies in social psychology and organizational literature. It affords the possibility of describing accident processes as objectively as possible and with as much detail as possible. Causal explanations are vital to the formal analysis of workplace hazards and accidents, as they determine how organizations act to prevent accident recurrence. Accordingly, they are regarded as fundamental and prerequisite elements for safety management policies. The paper focuses primarily on the role of causal attributions in occupational and industrial accident analyses and implementation of safety interventions. It thus serves as a review of the contribution of attribution theory to occupational and industrial accidents. It comprises six sections. The first section presents an introduction to the classic attribution theories, and the second an account of the various ways in which the attribution paradigm has been applied in organizational settings. The third and fourth sections review the literature on causal attributions and demographic and organizational variables respectively. The sources of attributional biases in social psychology and how they manifest and are identified in the causal explanations for industrial and occupational accidents are treated in the fifth section. Finally, conclusion and recommendations are presented. The recommendations are particularly important for the reduction of workplace accidents and associated costs. The paper touches on the need for unbiased causal analyses, belief in the preventability of accidents, and the imperative role of management in occupational safety management.
Bayesian detection of causal rare variants under posterior consistency.
Liang, Faming; Xiong, Momiao
2013-01-01
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.
An Algorithmic Information Calculus for Causal Discovery and Reprogramming Systems
Zenil, Hector
2017-09-08
We introduce a conceptual framework and an interventional calculus to steer and manipulate systems based on their intrinsic algorithmic probability using the universal principles of the theory of computability and algorithmic information. By applying sequences of controlled interventions to systems and networks, we estimate how changes in their algorithmic information content are reflected in positive/negative shifts towards and away from randomness. The strong connection between approximations to algorithmic complexity (the size of the shortest generating mechanism) and causality induces a sequence of perturbations ranking the network elements by the steering capabilities that each of them is capable of. This new dimension unmasks a separation between causal and non-causal components providing a suite of powerful parameter-free algorithms of wide applicability ranging from optimal dimension reduction, maximal randomness analysis and system control. We introduce methods for reprogramming systems that do not require the full knowledge or access to the system\\'s actual kinetic equations or any probability distributions. A causal interventional analysis of synthetic and regulatory biological networks reveals how the algorithmic reprogramming qualitatively reshapes the system\\'s dynamic landscape. For example, during cellular differentiation we find a decrease in the number of elements corresponding to a transition away from randomness and a combination of the system\\'s intrinsic properties and its intrinsic capabilities to be algorithmically reprogrammed can reconstruct an epigenetic landscape. The interventional calculus is broadly applicable to predictive causal inference of systems such as networks and of relevance to a variety of machine and causal learning techniques driving model-based approaches to better understanding and manipulate complex systems.
Determination of Causality between Remittance and Import: Evidence from Bangladesh
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Dewan Muktadir-Al-Mukit
2013-07-01
Full Text Available This study investigates the relationship between remittance and import for the economy of Bangladesh. The study used different econometric techniques of measuring the long and short term relationship between variables. The Johansen Cointegration test is used to determine the existence of a long term relationships between study variables. The normalized Cointegrating coefficients are found statistically significant and show a stable and positive relationship between study variables. Our Granger causality analysis suggests the existence of a unidirectional causality running from import to remittance. This confirms that remittances have no significant impact on the demand for imported goods rather import exerts a positive shock on the remittance of Bangladesh.
Causality and Information Dynamics in Networked Systems with Many Agents
2017-05-11
algorithms. 6 Future Perspectives Causal graph reconstruction from noisy data is a problem of central importance. In our research we have shown how the idea ...thrust of the research was to develop methods for GCG sparsification using ideas from Tikhonov regularization and ADMM based proximal algorithms...not vary with time. The notion of Granger-causality is captured in the following definition . Definition 2.1 If ξ̂[xi(t) |Ht] < ξ̂[xi(t) |H−jt ] , (2.2
David Bohm : causality and chance, letters to three women
2017-01-01
The letters transcribed in this book were written by physicist David Bohm to three close female acquaintances in the period 1950 to 1956. They provide a background to his causal interpretation of quantum mechanics and the Marxist philosophy that inspired his scientific work in quantum theory, probability and statistical mechanics. In his letters, Bohm reveals the ideas that led to his ground breaking book Causality and Chance in Modern Physics. The political arguments as well as the acute personal problems contained in these letters help to give a rounded, human picture of this leading scientist and twentieth century thinker.
Causal binary mask estimation for speech enhancement using sparsity constraints
DEFF Research Database (Denmark)
Kressner, Abigail Anne; Anderson, David V.; Rozell, Christopher J.
2013-01-01
and interferer signals to preserve only the time-frequency regions that are target-dominated. Single-channel noise suppression algorithms trying to approximate the IBM using locally estimated signal-to-noise ratios without oracle knowledge have had limited success. Thought of in another way, the IBM exploits...... algorithm from the signal processing literature. However, the algorithm employs a non-causal estimator. The present work introduces an improved de-noising algorithm that uses more realistic frame-based (causal) computations to estimate a binary mask....
Causal Analysis of Databases Concerning Electromagnetism and Health
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Kristian Alonso-Stenberg
2016-12-01
Full Text Available In this article, we conducted a causal analysis of a system extracted from a database of current data in the telecommunications domain, namely the Eurobarometer 73.3 database arose from a survey of 26,602 citizens EU on the potential health effects that electromagnetic fields can produce. To determine the cause-effect relationships between variables, we represented these data by a directed graph that can be applied to a qualitative version of the theory of discrete chaos to highlight causal circuits and attractors, as these are basic elements of system behavior.
Causality and unitarity via the tree-loop duality relation
Energy Technology Data Exchange (ETDEWEB)
Tomboulis, E.T. [Mani L. Bhaumik Institute for Theoretical Physics,Department of Physics and Astronomy, UCLA,Los Angeles, CA 90095-1547 (United States)
2017-05-29
The tree-loop duality relation is used as a starting point to derive the constraints of causality and unitarity. Specifically, the Bogoliubov causality condition is ab initio derived at the individual graph level. It leads to a representation of a graph in terms of lower order cut graphs. Extracting the absorptive part gives then the general unitarity relation (Cutkosky rule). The derivation, being carried out directly in momentum space, holds for any local (polynomial) hermitian interaction vertices. This is in contrast to the technical difficulties arising from contact terms in the spacetime approach based on the largest time equation.
The discourse of causal explanations in school science
Slater, Tammy Jayne Anne
Researchers and educators working from a systemic functional linguistic perspective have provided a body of work on science discourse which offers an excellent starting point for examining the linguistic aspects of the development of causal discourse in school science, discourse which Derewianka (1995) claimed is critical to success in secondary school. No work has yet described the development of causal language by identifying the linguistic features present in oral discourse or by comparing the causal discourse of native and non-native (ESL) speakers of English. The current research responds to this gap by examining the oral discourse collected from ESL and non-ESL students at the primary and high school grades. Specifically, it asks the following questions: (1) How do the teachers and students in these four contexts develop causal explanations and their relevant taxonomies through classroom interactions? (2) What are the causal discourse features being used by the students in these four contexts to construct oral causal explanations? The findings of the social practice analysis showed that the teachers in the four contexts differed in their approaches to teaching, with the primary school mainstream teacher focusing largely on the hands-on practice , the primary school ESL teacher moving from practice to theory, the high school mainstream teacher moving from theory to practice, and the high school ESL teacher relying primarily on theory. The findings from the quantitative, small corpus approach suggest that the developmental path of cause which has been identified in the writing of experts shows up not only in written texts but also in the oral texts which learners construct. Moreover, this move appears when the discourse of high school ESL and non-ESL students is compared, suggesting a developmental progression in the acquisition of these features by these students. The findings also reveal that the knowledge constructed, as shown by the concept maps created
Temporal sequence in observational studies to establish causality
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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.
A Bayesian nonparametric approach to causal inference on quantiles.
Xu, Dandan; Daniels, Michael J; Winterstein, Almut G
2018-02-25
We propose a Bayesian nonparametric approach (BNP) for causal inference on quantiles in the presence of many confounders. In particular, we define relevant causal quantities and specify BNP models to avoid bias from restrictive parametric assumptions. We first use Bayesian additive regression trees (BART) to model the propensity score and then construct the distribution of potential outcomes given the propensity score using a Dirichlet process mixture (DPM) of normals model. We thoroughly evaluate the operating characteristics of our approach and compare it to Bayesian and frequentist competitors. We use our approach to answer an important clinical question involving acute kidney injury using electronic health records. © 2018, The International Biometric Society.
The causal boundary of wave-type spacetimes
International Nuclear Information System (INIS)
Flores, J.L.; Sanchez, M.
2008-01-01
A complete and systematic approach to compute the causal boundary of wave-type spacetimes is carried out. The case of a 1-dimensional boundary is specially analyzed and its critical appearance in pp-wave type spacetimes is emphasized. In particular, the corresponding results obtained in the framework of the AdS/CFT correspondence for holography on the boundary, are reinterpreted and very widely generalized. Technically, a recent new definition of causal boundary is used and stressed. Moreover, a set of mathematical tools is introduced (analytical functional approach, Sturm-Liouville theory, Fermat-type arrival time, Busemann-type functions)
Metodologia psicopatológica e ética em psicanálise: o princípio da alteridade hermética
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Nelson da Silva Junior
Full Text Available A compreensão da metapsicologia como sistema causal de representação da subjetividade exclui implicitamente a legitimidade do registro da ética como tal. Contra tal compreensão, apresentamos a noção de alteridade hermética enquanto um princípio da metodologia psicopatológica da psicanálise que não somente convive com a ética, mas ainda que solicita a independência e a transformação dos valores da normalidade.
Directory of Open Access Journals (Sweden)
Lenz Alberto Alves Cabral
2018-02-01
Full Text Available Resumo Introdução: a determinação do nexo causal do acidente de trabalho/doença ocupacional é de suma importância, pois sua análise envolve fatores ideológicos, éticos, humanísticos e legais, sendo realizada nos âmbitos trabalhista, previdenciário e cível. Objetivo: identificar e sistematizar atos normativos legais para subsidiar a compreensão interpretativa do nexo causal entre o sinistro laboral e o trabalho, nos âmbitos trabalhista, previdenciário e cível. Métodos: ensaio crítico-reflexivo, com base em levantamento e sistematização da legislação trabalhista brasileira que dá suporte ao estabelecimento do nexo causal no acidente do trabalho pelos atores sociais legalmente responsáveis por sua determinação. Resultados: são identificadas três modalidades de nexo causal: trabalhista, pelos Serviços Especializados de Engenharia de Segurança e Medicina do Trabalho (SESMT; previdenciário, pelo Instituto Nacional do Seguro Social (INSS; e cível, pela Justiça do Trabalho. A Lei nº 8.213/1991 é referência comum para as três instituições; outros atos legais normativos são específicos no âmbito de cada instituição: as Normas Regulamentadoras do Trabalho (SESMT; a Instrução Normativa 31 (INSS e o Código Civil (Justiça do Trabalho. Conclusão: o uso correto da legislação facilita o estabelecimento do elo entre o acidente e o trabalho, auxiliando na sua compreensão, padronização, diminuição de conflitos e aumento da notificação.
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John F Magnotti
2017-02-01
Full Text Available Audiovisual speech integration combines information from auditory speech (talker's voice and visual speech (talker's mouth movements to improve perceptual accuracy. However, if the auditory and visual speech emanate from different talkers, integration decreases accuracy. Therefore, a key step in audiovisual speech perception is deciding whether auditory and visual speech have the same source, a process known as causal inference. A well-known illusion, the McGurk Effect, consists of incongruent audiovisual syllables, such as auditory "ba" + visual "ga" (AbaVga, that are integrated to produce a fused percept ("da". This illusion raises two fundamental questions: first, given the incongruence between the auditory and visual syllables in the McGurk stimulus, why are they integrated; and second, why does the McGurk effect not occur for other, very similar syllables (e.g., AgaVba. We describe a simplified model of causal inference in multisensory speech perception (CIMS that predicts the perception of arbitrary combinations of auditory and visual speech. We applied this model to behavioral data collected from 60 subjects perceiving both McGurk and non-McGurk incongruent speech stimuli. The CIMS model successfully predicted both the audiovisual integration observed for McGurk stimuli and the lack of integration observed for non-McGurk stimuli. An identical model without causal inference failed to accurately predict perception for either form of incongruent speech. The CIMS model uses causal inference to provide a computational framework for studying how the brain performs one of its most important tasks, integrating auditory and visual speech cues to allow us to communicate with others.
International Nuclear Information System (INIS)
Narayan, Paresh Kumar; Prasad, Arti
2008-01-01
The goal of this paper is to examine any causal effects between electricity consumption and real GDP for 30 OECD countries. We use a bootstrapped causality testing approach and unravel evidence in favour of electricity consumption causing real GDP in Australia, Iceland, Italy, the Slovak Republic, the Czech Republic, Korea, Portugal, and the UK. The implication is that electricity conservation policies will negatively impact real GDP in these countries. However, for the rest of the 22 countries our findings suggest that electricity conversation policies will not affect real GDP
Finance and growth : Time series evidence on causality
Peia, Oana; Roszbach, Kasper
2015-01-01
This paper re-examines the empirical relationship between financial and economic development while (i) taking into account their dynamics and (ii) differentiating between stock market and banking sector development. We study the cointegration and causality between the real and the financial sector
Causality and cointegration analysis between macroeconomic variables and the Bovespa.
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Fabiano Mello da Silva
Full Text Available The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI, industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa. The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988 causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988 long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.
Towards a definition of locality in a manifoldlike causal set
DEFF Research Database (Denmark)
Glaser, Lisa; Surya, Sumati
2013-01-01
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 of m...
An integrated theory of causal scenarios and evidential arguments
Bex, F.J.
2015-01-01
In the process of proof alternative stories that explain 'what happened' in a case are tested using arguments based on evidence. Building on the author's earlier hybrid theory, this paper presents a formal theory that combines causal stories and evidential arguments, further integrating the
Causal Variables and Academic Performance of Students in Cross ...
African Journals Online (AJOL)
This study investigated the causal variables (Child, Family, School, Society and Government) and academic performance of secondary school students in Cross River State: A basis for counselling and programme planning. The study adopted the descriptive survey method. It made use of two research questions and ...
Perceived causality, force, and resistance in the absence of launching.
Hubbard, Timothy L; Ruppel, Susan E
2017-04-01
In the launching effect, a moving object (the launcher) contacts a stationary object (the target), and upon contact, the launcher stops and the target begins moving in the same direction and at the same or slower velocity as previous launcher motion (Michotte, 1946/1963). In the study reported here, participants viewed a modified launching effect display in which the launcher stopped before or at the moment of contact and the target remained stationary. Participants rated perceived causality, perceived force, and perceived resistance of the launcher on the target or the target on the launcher. For launchers and for targets, increases in the size of the spatial gap between the final location of the launcher and the location of the target decreased ratings of perceived causality and ratings of perceived force and increased ratings of perceived resistance. Perceived causality, perceived force, and perceived resistance exhibited gradients or fields extending from the launcher and from the target and were not dependent upon contact of the launcher and target. Causal asymmetries and force asymmetries reported in previous studies did not occur, and this suggests that such asymmetries might be limited to typical launching effect stimuli. Deviations from Newton's laws of motion are noted, and the existence of separate radii of action extending from the launcher and from the target is suggested.
A Bayesian Nonparametric Causal Model for Regression Discontinuity Designs
Karabatsos, George; Walker, Stephen G.
2013-01-01
The regression discontinuity (RD) design (Thistlewaite & Campbell, 1960; Cook, 2008) provides a framework to identify and estimate causal effects from a non-randomized design. Each subject of a RD design is assigned to the treatment (versus assignment to a non-treatment) whenever her/his observed value of the assignment variable equals or…
Academic Procrastination and Causal Perception of Tabor Senior ...
African Journals Online (AJOL)
Nekky Umera
examine the extent of relationship of academic procrastination and causal attribution and Sex ... concerned bodies such as parents, teachers, counsellors, and directors to help students inside and outside the classroom. ... coping and general activity. ... is to lead one to effective management of him-or-herself and his/her.
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,…
Causality and skies: is non-refocussing necessary?
International Nuclear Information System (INIS)
Bautista, A; Ibort, A; Lafuente, J
2015-01-01
The causal structure of a strongly causal, null pseudo-convex, space-time M is completely characterized in terms of a partial order on its space of skies defined by means of a class of non-negative Legendrian isotopies called sky isotopies. It is also shown that such partial order is determined by the class of future causal celestial curves, that is, curves in the space of light rays which are tangent to skies and such that they determine non-negative sky isotopies. It will also be proved that the space of skies Σ equipped with Low’s (or reconstructive) topology is homeomorphic and diffeomorphic to M under the only additional assumption that M separates skies, that is, that different events determine different skies. The sky-separating property of M is sharp and the previous result provides an answer to the question about the class of space-times whose causal structure, topological and differentiable structure can be reconstructed from their spaces of light rays and skies. These results can be understood as a Malament–Hawking-like theorem stated in terms of the partial order defined on the space of skies. (paper)
Explanation in causal inference methods for mediation and interaction
VanderWeele, Tyler
2015-01-01
A comprehensive examination of methods for mediation and interaction, VanderWeele's book is the first to approach this topic from the perspective of causal inference. Numerous software tools are provided, and the text is both accessible and easy to read, with examples drawn from diverse fields. The result is an essential reference for anyone conducting empirical research in the biomedical or social sciences.
Mathematical Intelligence and Mathematical Creativity: A Causal Relationship
Tyagi, Tarun Kumar
2017-01-01
This study investigated the causal relationship between mathematical creativity and mathematical intelligence. Four hundred thirty-nine 8th-grade students, age ranged from 11 to 14 years, were included in the sample of this study by random cluster technique on which mathematical creativity and Hindi adaptation of mathematical intelligence test…
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…
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…
A Causal Contiguity Effect That Persists across Time Scales
Kilic, Asli; Criss, Amy H.; Howard, Marc W.
2013-01-01
The contiguity effect refers to the tendency to recall an item from nearby study positions of the just recalled item. Causal models of contiguity suggest that recalled items are used as probes, causing a change in the memory state for subsequent recall attempts. Noncausal models of the contiguity effect assume the memory state is unaffected by…
Meaningful mediation analysis : Plausible causal inference and informative communication
Pieters, Rik
2017-01-01
Statistical mediation analysis has become the technique of choice in consumer research to make causal inferences about the influence of a treatment on an outcome via one or more mediators. This tutorial aims to strengthen two weak links that impede statistical mediation analysis from reaching its
Commentary: Using Potential Outcomes to Understand Causal Mediation Analysis
Imai, Kosuke; Jo, Booil; Stuart, Elizabeth A.
2011-01-01
In this commentary, we demonstrate how the potential outcomes framework can help understand the key identification assumptions underlying causal mediation analysis. We show that this framework can lead to the development of alternative research design and statistical analysis strategies applicable to the longitudinal data settings considered by…
Comments: Improving Weighting Methods for Causal Mediation Analysis
Imai, Kosuke
2012-01-01
The author begins this discussion by thanking Larry Hedges, the editor of the journal, for giving him an opportunity to provide a commentary on this stimulating article. He also would like to congratulate the authors of the article for their insightful discussion on causal mediation analysis, which is one of the most important and challenging…
The causal texture of trade union environments | Iyayi | Global ...
African Journals Online (AJOL)
This paper is an attempt to fill an important gap in the existing literature on trade unions by providing a more adequate theoretical formulation of trade union environments. The discussion suggests that unlike the environment of business and related organisations whose causal texture is understood in terms of uncertainty, ...
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…
Learning What Works in Sensory Disabilities: Establishing Causal Inference
Cooney, John B.; Young, John, III; Luckner, John L.; Ferrell, Kay Alicyn
2015-01-01
This article is intended to assist teachers and researchers in designing studies that examine the efficacy of a particular intervention or strategy with students with sensory disabilities. Ten research designs that can establish causal inference (the ability to attribute any effects to the intervention) with and without randomization are discussed.
Causal approach to (2+1)-dimensional Quantum Electrodynamics
International Nuclear Information System (INIS)
Scharf, G.; Wreszinski, W.F.; Pimentel, B.M.; Tomazelli, J.L.
1993-05-01
It is shown that the causal approach to (2+1)-dimensional quantum electrodynamics yields a well-defined perturbative theory. In particular, and in contrast to renormalized perturbative quantum field theory, it is free of any ambiguities and ascribes a nonzero value to the dynamically generated, nonperturbative photon mass. (author). 12 refs
Causal Indicator Models Have Nothing to Do with Measurement
Howell, Roy D.; Breivik, Einar
2016-01-01
In this article, Roy Howell, and Einar Breivik, congratulate Aguirre-Urreta, M. I., Rönkkö, M., & Marakas, G. M., for their work (2016) "Omission of Causal Indicators: Consequences and Implications for Measurement," Measurement: Interdisciplinary Research and Perspectives, 14(3), 75-97. doi:10.1080/15366367.2016.1205935. They call it…
Do New Caledonian crows solve physical problems through causal reasoning?
Taylor, A.H.; Hunt, G.R.; Medina, F.S.; Gray, R.D.
2008-01-01
The extent to which animals other than humans can reason about physical problems is contentious. The benchmark test for this ability has been the trap-tube task. We presented New Caledonian crows with a series of two-trap versions of this problem. Three out of six crows solved the initial trap-tube. These crows continued to avoid the trap when the arbitrary features that had previously been associated with successful performances were removed. However, they did not avoid the trap when a hole and a functional trap were in the tube. In contrast to a recent primate study, the three crows then solved a causally equivalent but visually distinct problem—the trap-table task. The performance of the three crows across the four transfers made explanations based on chance, associative learning, visual and tactile generalization, and previous dispositions unlikely. Our findings suggest that New Caledonian crows can solve complex physical problems by reasoning both causally and analogically about causal relations. Causal and analogical reasoning may form the basis of the New Caledonian crow's exceptional tool skills. PMID:18796393
Causality in Psychiatry: A Hybrid Symptom Network Construct Model
Directory of Open Access Journals (Sweden)
Gerald eYoung
2015-11-01
Full Text Available 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; American Psychiatric Association, 2013. However, network approaches to symptom interaction (i.e., symptoms are formative of the construct; e.g., McNally, Robinaugh, Wu, Wang, Deserno, & Borsboom, 2014, for PTSD (posttraumatic stress disorder 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 nonlinear dynamical systems theory (NLDST. The article applies the concept of emergent circular causality (Young, 2011 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.
Mechanism-Based Causal Reasoning in Young Children
Buchanan, David W.; Sobel, David M.
2011-01-01
The hypothesis that children develop an understanding of causal mechanisms was tested across 3 experiments. In Experiment 1 (N = 48), preschoolers had to choose as efficacious either a cause that had worked in the past, but was now disconnected from its effect, or a cause that had failed to work previously, but was now connected. Four-year-olds…
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
Causality and cointegration analysis between macroeconomic variables and the Bovespa.
da Silva, Fabiano Mello; Coronel, Daniel Arruda; Vieira, Kelmara Mendes
2014-01-01
The aim of this study is to analyze the causality relationship among a set of macroeconomic variables, represented by the exchange rate, interest rate, inflation (CPI), industrial production index as a proxy for gross domestic product in relation to the index of the São Paulo Stock Exchange (Bovespa). The period of analysis corresponded to the months from January 1995 to December 2010, making a total of 192 observations for each variable. Johansen tests, through the statistics of the trace and of the maximum eigenvalue, indicated the existence of at least one cointegration vector. In the analysis of Granger (1988) causality tests via error correction, it was found that a short-term causality existed between the CPI and the Bovespa. Regarding the Granger (1988) long-term causality, the results indicated a long-term behaviour among the macroeconomic variables with the BOVESPA. The results of the long-term normalized vector for the Bovespa variable showed that most signals of the cointegration equation parameters are in accordance with what is suggested by the economic theory. In other words, there was a positive behaviour of the GDP and a negative behaviour of the inflation and of the exchange rate (expected to be a positive relationship) in relation to the Bovespa, with the exception of the Selic rate, which was not significant with that index. The variance of the Bovespa was explained by itself in over 90% at the twelfth month, followed by the country risk, with less than 5%.
Causal Reasoning in Medicine: Analysis of a Protocol.
Kuipers, Benjamin; Kassirer, Jerome P.
1984-01-01
Describes the construction of a knowledge representation from the identification of the problem (nephrotic syndrome) to a running computer simulation of causal reasoning to provide a vertical slice of the construction of a cognitive model. Interactions between textbook knowledge, observations of human experts, and computational requirements are…
Causality: School Libraries and Student Success (CLASS). White Paper
American Association of School Librarians, 2014
2014-01-01
On April 11 and 12, 2014, the American Association of School Librarians (AASL) held "Causality: School Libraries and Student Success" (CLASS), an IMLS-funded national forum. Dr. Thomas Cook, one of the most influential methodologists in education research, and a five member panel of expert scholars and practitioners led 50 established…
The causal effect of institutional quality on outsourcing
Roelfsema, H.J.; Yi, Zhang
This paper empirically investigates the relationship between institutional quality and outsourcing to developing economies. In contrast to cross-sectional studies on institutions, this paper uses panel data for 76 countries over 25 years (1980-2004). Employing panel data helps to show the causal
Causal Indicator Models: Unresolved Issues of Construction and Evaluation
West, Stephen G.; Grimm, Kevin J.
2014-01-01
These authors agree with Bainter and Bollen that causal effects represents a useful measurement structure in some applications. The structure of the science of the measurement problem should determine the model; the measurement model should not determine the science. They also applaud Bainter and Bollen's important reminder that the full…
Revisiting Aristotle's causality: model for development in Nigeria ...
African Journals Online (AJOL)
Thus, the development equation must be balanced. Aristotle‟s theory of causality balances the equation. Since Aristotle has no theory of development therefore every individual, nation or industry in pursuit of development should seek to drive economic growth and human capital development together rather than focus on ...
Confounding factors in determining causal soil moisture-precipitation feedback
Tuttle, Samuel E.; Salvucci, Guido D.
2017-07-01
Identification of causal links in the land-atmosphere system is important for construction and testing of land surface and general circulation models. However, the land and atmosphere are highly coupled and linked by a vast number of complex, interdependent processes. Statistical methods, such as Granger causality, can help to identify feedbacks from observational data, independent of the different parameterizations of physical processes and spatiotemporal resolution effects that influence feedbacks in models. However, statistical causal identification methods can easily be misapplied, leading to erroneous conclusions about feedback strength and sign. Here, we discuss three factors that must be accounted for in determination of causal soil moisture-precipitation feedback in observations and model output: seasonal and interannual variability, precipitation persistence, and endogeneity. The effect of neglecting these factors is demonstrated in simulated and observational data. The results show that long-timescale variability and precipitation persistence can have a substantial effect on detected soil moisture-precipitation feedback strength, while endogeneity has a smaller effect that is often masked by measurement error and thus is more likely to be an issue when analyzing model data or highly accurate observational data.
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.
Applying causal mediation analysis to personality disorder research.
Walters, Glenn D
2018-01-01
This article is designed to address fundamental issues in the application of causal mediation analysis to research on personality disorders. Causal mediation analysis is used to identify mechanisms of effect by testing variables as putative links between the independent and dependent variables. As such, it would appear to have relevance to personality disorder research. It is argued that proper implementation of causal mediation analysis requires that investigators take several factors into account. These factors are discussed under 5 headings: variable selection, model specification, significance evaluation, effect size estimation, and sensitivity testing. First, care must be taken when selecting the independent, dependent, mediator, and control variables for a mediation analysis. Some variables make better mediators than others and all variables should be based on reasonably reliable indicators. Second, the mediation model needs to be properly specified. This requires that the data for the analysis be prospectively or historically ordered and possess proper causal direction. Third, it is imperative that the significance of the identified pathways be established, preferably with a nonparametric bootstrap resampling approach. Fourth, effect size estimates should be computed or competing pathways compared. Finally, investigators employing the mediation method are advised to perform a sensitivity analysis. Additional topics covered in this article include parallel and serial multiple mediation designs, moderation, and the relationship between mediation and moderation. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Causal attributions of cleft lip and palate across cultures.
Mednick, Lauren; Snyder, Julie; Schook, Carolyn; Blood, Emily A; Brown, Shan-Estelle; Weatherley-White, R C A
2013-11-01
Objective : To describe and compare the causal beliefs associated with cleft lips and/or palates across several different countries. Design : Cross-sectional survey. Setting : Operation Smile surgery screenings in six developing countries. Participants : Two hundred seventy-nine adult patients and parents of children with cleft lips and/or palates in Kenya, Russia, Cambodia, India, Egypt, and Peru. Interventions : In person interviews were conducted with interpreters. Main Outcome Measure : As part of a larger study, a semistructured questionnaire was created to explore cleft perceptions, belief systems that affect these perceptions, and social reactions to individuals with clefts. Results : Causal attributions were grouped by category (environment, self-blame, supernatural, chance, unknown, or other) and type of locus of control (external, internal, or unknown). Results indicate significant difference by country for both causal attribution category (P < .001) and type (P < .001). This difference was maintained in multivariate analyses, which controlled for differences by demographic variables between countries. Conclusions : This study provides evidence that causal attributions for clefts are influenced by culture. As harmful beliefs about cause may continue to impact affected individuals and their families even after a repair, it is insufficient to provide surgical care alone. Care of the entire person must include attempts to change misinformed cultural beliefs through educating the broader community.
Causal vs. analytic constraints on anomalous quartic gauge couplings
International Nuclear Information System (INIS)
Vecchi, L.
2007-01-01
We derive one loop constraints on the anomalous quartic gauge couplings using a general non-forward dispersion relation for the elastic scattering amplitude of two longitudinally polarized vector bosons. We show that for exactly chiral theories more stringent bounds can be obtained by the assumption that the underlying theory satisfies the causality principle of Special Relativity
Causal vs. Analytic constraints on anomalous quartic gauge couplings
Vecchi, Luca
2007-01-01
We derive one loop constraints on the anomalous quartic gauge couplings using a general non-forward dispersion relation for the elastic scattering amplitude of two longitudinally polarized vector bosons. We compare this result with another one derived by the assumption that the underlying theory satisfies the causality principle of Special Relativity and show that this latter is more constraining.
Testing for Granger causality in large mixed-frequency VARs
Götz, T.B.; Hecq, A.W.
2014-01-01
In this paper we analyze Granger causality testing in a mixed-frequency VAR, originally proposed by Ghysels (2012), where the difference in sampling frequencies of the variables is large. In particular, we investigate whether past information on a low-frequency variable help in forecasting a
Causal Inference for Statistics, Social, and Biomedical Sciences: An Introduction
Imbens, Guido W.; Rubin, Donald B.
2015-01-01
Most questions in social and biomedical sciences are causal in nature: what would happen to individuals, or to groups, if part of their environment were changed? In this groundbreaking text, two world-renowned experts present statistical methods for studying such questions. This book starts with the notion of potential outcomes, each corresponding…
Causal gene identification using combinatorial V-structure search.
Cai, Ruichu; Zhang, Zhenjie; Hao, Zhifeng
2013-07-01
With the advances of biomedical techniques in the last decade, the costs of human genomic sequencing and genomic activity monitoring are coming down rapidly. To support the huge genome-based business in the near future, researchers are eager to find killer applications based on human genome information. Causal gene identification is one of the most promising applications, which may help the potential patients to estimate the risk of certain genetic diseases and locate the target gene for further genetic therapy. Unfortunately, existing pattern recognition techniques, such as Bayesian networks, cannot be directly applied to find the accurate causal relationship between genes and diseases. This is mainly due to the insufficient number of samples and the extremely high dimensionality of the gene space. In this paper, we present the first practical solution to causal gene identification, utilizing a new combinatorial formulation over V-Structures commonly used in conventional Bayesian networks, by exploring the combinations of significant V-Structures. We prove the NP-hardness of the combinatorial search problem under a general settings on the significance measure on the V-Structures, and present a greedy algorithm to find sub-optimal results. Extensive experiments show that our proposal is both scalable and effective, particularly with interesting findings on the causal genes over real human genome data. Copyright © 2013 Elsevier Ltd. All rights reserved.
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 ...
The Causal Pattern of Mobile Phone Ownership and Implications for ...
African Journals Online (AJOL)
This paper examined a number of predictors of mobile phone ownership amongst fish and vegetable sellers in Yola Metropolis, Nigeria. Using regression path analysis, it identified the causal pattern of mobile phone ownership for Male and Female in the study area. Although there were few significant differences between ...
The Causal Effects of Grade Retention on Behavioral Outcomes
Martorell, Paco; Mariano, Louis T.
2018-01-01
This study examines the impact of grade retention on behavioral outcomes under a comprehensive assessment-based student promotion policy in New York City. To isolate the causal effect of grade retention, we implement a fuzzy regression discontinuity (RD) design that exploits the fact that grade retention is largely determined by whether a student…
k-Essence, superluminal propagation, causality and emergent geometry
International Nuclear Information System (INIS)
Babichev, Eugeny; Mukhanov, Viatcheslav; Vikman, Alexander
2008-01-01
The k-essence theories admit in general the superluminal propagation of the perturbations on classical backgrounds. We show that in spite of the superluminal propagation the causal paradoxes do not arise in these theories and in this respect they are not less safe than General Relativity
Computation of Probabilities in Causal Models of History of Science
Directory of Open Access Journals (Sweden)
Osvaldo Pessoa Jr.
2006-12-01
Full Text Available : The aim of this paper is to investigate the ascription of probabilities in a causal model of an episode in the history of science. The aim of such a quantitative approach is to allow the implementation of the causal model in a computer, to run simulations. As an example, we look at the beginning of the science of magnetism, “explaining” — in a probabilistic way, in terms of a single causal model — why the field advanced in China but not in Europe (the difference is due to different prior probabilities of certain cultural manifestations. Given the number of years between the occurrences of two causally connected advances X and Y, one proposes a criterion for stipulating the value pY=X of the conditional probability of an advance Y occurring, given X. Next, one must assume a specific form for the cumulative probability function pY=X(t, which we take to be the time integral of an exponential distribution function, as is done in physics of radioactive decay. Rules for calculating the cumulative functions for more than two events are mentioned, involving composition, disjunction and conjunction of causes. We also consider the problems involved in supposing that the appearance of events in time follows an exponential distribution, which are a consequence of the fact that a composition of causes does not follow an exponential distribution, but a “hypoexponential” one. We suggest that a gamma distribution function might more adequately represent the appearance of advances.
Quantum gravity from simplices: analytical investigations of causal dynamical triangulations
Benedetti, D.
2007-01-01
A potentially powerful approach to quantum gravity has been developed over the last few years under the name of Causal Dynamical Triangulations. Although these models can be solved exactly in a variety of ways in the case of pure gravity in (1+1) dimensions,it is difficult to extend any of the
Neural theory for the perception of causal actions.
Fleischer, Falk; Christensen, Andrea; Caggiano, Vittorio; Thier, Peter; Giese, Martin A
2012-07-01
The efficient prediction of the behavior of others requires the recognition of their actions and an understanding of their action goals. In humans, this process is fast and extremely robust, as demonstrated by classical experiments showing that human observers reliably judge causal relationships and attribute interactive social behavior to strongly simplified stimuli consisting of simple moving geometrical shapes. While psychophysical experiments have identified critical visual features that determine the perception of causality and agency from such stimuli, the underlying detailed neural mechanisms remain largely unclear, and it is an open question why humans developed this advanced visual capability at all. We created pairs of naturalistic and abstract stimuli of hand actions that were exactly matched in terms of their motion parameters. We show that varying critical stimulus parameters for both stimulus types leads to very similar modulations of the perception of causality. However, the additional form information about the hand shape and its relationship with the object supports more fine-grained distinctions for the naturalistic stimuli. Moreover, we show that a physiologically plausible model for the recognition of goal-directed hand actions reproduces the observed dependencies of causality perception on critical stimulus parameters. These results support the hypothesis that selectivity for abstract action stimuli might emerge from the same neural mechanisms that underlie the visual processing of natural goal-directed action stimuli. Furthermore, the model proposes specific detailed neural circuits underlying this visual function, which can be evaluated in future experiments.
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
Detecting switching and intermittent causalities in time series
Zanin, Massimiliano; Papo, David
2017-04-01
During the last decade, complex network representations have emerged as a powerful instrument for describing the cross-talk between different brain regions both at rest and as subjects are carrying out cognitive tasks, in healthy brains and neurological pathologies. The transient nature of such cross-talk has nevertheless by and large been neglected, mainly due to the inherent limitations of some metrics, e.g., causality ones, which require a long time series in order to yield statistically significant results. Here, we present a methodology to account for intermittent causal coupling in neural activity, based on the identification of non-overlapping windows within the original time series in which the causality is strongest. The result is a less coarse-grained assessment of the time-varying properties of brain interactions, which can be used to create a high temporal resolution time-varying network. We apply the proposed methodology to the analysis of the brain activity of control subjects and alcoholic patients performing an image recognition task. Our results show that short-lived, intermittent, local-scale causality is better at discriminating both groups than global network metrics. These results highlight the importance of the transient nature of brain activity, at least under some pathological conditions.
Acute appendicitis following blunt abdominal trauma. Coincidence or causality?
Directory of Open Access Journals (Sweden)
Sergio Iván Latorre
2017-01-01
Full Text Available Acute appendicitis is a common disease in clinical practice; some well-defined causes include luminal obstruction by fecoliths, lymphoid hyperplasia, foreign bodies and intestinal parasites. Closed abdominal trauma has been associated as an etiological factor, although, their causal relationship is still unclear. This paper presents the case of a patient with appendicitis after a closed abdominal trauma.
Causal models in epidemiology: past inheritance and genetic future
Directory of Open Access Journals (Sweden)
Kriebel David
2006-07-01
Full Text Available Abstract The eruption of genetic research presents a tremendous opportunity to epidemiologists to improve our ability to identify causes of ill health. Epidemiologists have enthusiastically embraced the new tools of genomics and proteomics to investigate gene-environment interactions. We argue that neither the full import nor limitations of such studies can be appreciated without clarifying underlying theoretical models of interaction, etiologic fraction, and the fundamental concept of causality. We therefore explore different models of causality in the epidemiology of disease arising out of genes, environments, and the interplay between environments and genes. We begin from Rothman's "pie" model of necessary and sufficient causes, and then discuss newer approaches, which provide additional insights into multifactorial causal processes. These include directed acyclic graphs and structural equation models. Caution is urged in the application of two essential and closely related concepts found in many studies: interaction (effect modification and the etiologic or attributable fraction. We review these concepts and present four important limitations. 1. Interaction is a fundamental characteristic of any causal process involving a series of probabilistic steps, and not a second-order phenomenon identified after first accounting for "main effects". 2. Standard methods of assessing interaction do not adequately consider the life course, and the temporal dynamics through which an individual's sufficient cause is completed. Different individuals may be at different stages of development along the path to disease, but this is not usually measurable. Thus, for example, acquired susceptibility in children can be an important source of variation. 3. A distinction must be made between individual-based and population-level models. Most epidemiologic discussions of causality fail to make this distinction. 4. At the population level, there is additional
Causality from the Cosmological Perspective in Vedanta and Western Physics.
Hawley, Danny Lee
The relation between Western physics and Indian Vedanta philosophy is investigated through the topic of causality, taken in the sense of explanatory theories of the origin of the universe and the relations among its physical, mental, and spiritual aspects. Both physics and Vedanta have a common goal of explanation by means of a unitary principle. While physics has long been separated from metaphysics, its discoveries indicate that consciousness must be included in a complete explanation. Consciousness is taken as the fundamental basis and source of all phenomena in Vedanta. This work traces the developments of causal explanation in Western physics and Indian philosophy, and considers how these views may relate to each other and how they may together suggest a comprehensive view of reality. Approaches typically applied by historians of religion to the study of creation myths, especially the psychological approach which considers myths from the perspective or cyclical stages of conscious development, are applied to the causal theories of the two cultures. The question of how causal explanations attempt to bridge the gap between cause and effect, unity and multiplicity, absolute and relative, conscious and unconscious, etc., is addressed. Though the investigation begins from the earliest causal explanations, viz., creation myths, emphasis is placed upon Samkara's commentaries of Advaita Vedanta, examined in the original Sanskrit, and upon the convergence of modern field theory, astrophysics, and cosmology, seen from the perspective of a previous doctorate in physics. Consideration is given to the comparison between physics and Vedanta as to goals, methods, and domains, to the question of the incompleteness of physics and the extent to which it nevertheless points beyond itself, to the possibility of a synthetic view and how it might be effected, and to analogies and metaphors through which physics and Vedanta may illuminate each other. An intuitive picture is
Confounding effects of phase delays on causality estimation.
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Vasily A Vakorin
Full Text Available Linear and non-linear techniques for inferring causal relations between the brain signals representing the underlying neuronal systems have become a powerful tool to extract the connectivity patterns in the brain. Typically these tools employ the idea of Granger causality, which is ultimately based on the temporal precedence between the signals. At the same time, phase synchronization between coupled neural ensembles is considered a mechanism implemented in the brain to integrate relevant neuronal ensembles to perform a cognitive or perceptual task. Phase synchronization can be studied by analyzing the effects of phase-locking between the brain signals. However, we should expect that there is no one-to-one mapping between the observed phase lag and the time precedence as specified by physically interacting systems. Specifically, phase lag observed between two signals may interfere with inferring causal relations. This could be of critical importance for the coupled non-linear oscillating systems, with possible time delays in coupling, when classical linear cross-spectrum strategies for solving phase ambiguity are not efficient. To demonstrate this, we used a prototypical model of coupled non-linear systems, and compared three typical pipelines of inferring Granger causality, as established in the literature. Specifically, we compared the performance of the spectral and information-theoretic Granger pipelines as well as standard Granger causality in their relations to the observed phase differences for frequencies at which the signals become synchronized to each other. We found that an information-theoretic approach, which takes into account different time lags between the past of one signal and the future of another signal, was the most robust to phase effects.
CAUSAL INFERENCE WITH A GRAPHICAL HIERARCHY OF INTERVENTIONS.
Shpitser, Ilya; Tchetgen, Eric Tchetgen
2016-12-01
Identifying causal parameters from observational data is fraught with subtleties due to the issues of selection bias and confounding. In addition, more complex questions of interest, such as effects of treatment on the treated and mediated effects may not always be identified even in data where treatment assignment is known and under investigator control, or may be identified under one causal model but not another. Increasingly complex effects of interest, coupled with a diversity of causal models in use resulted in a fragmented view of identification. This fragmentation makes it unnecessarily difficult to determine if a given parameter is identified (and in what model), and what assumptions must hold for this to be the case. This, in turn, complicates the development of estimation theory and sensitivity analysis procedures. In this paper, we give a unifying view of a large class of causal effects of interest, including novel effects not previously considered, in terms of a hierarchy of interventions, and show that identification theory for this large class reduces to an identification theory of random variables under interventions from this hierarchy. Moreover, we show that one type of intervention in the hierarchy is naturally associated with queries identified under the Finest Fully Randomized Causally Interpretable Structure Tree Graph (FFRCISTG) model of Robins (via the extended g-formula), and another is naturally associated with queries identified under the Non-Parametric Structural Equation Model with Independent Errors (NPSEM-IE) of Pearl, via a more general functional we call the edge g-formula. Our results motivate the study of estimation theory for the edge g-formula, since we show it arises both in mediation analysis, and in settings where treatment assignment has unobserved causes, such as models associated with Pearl's front-door criterion.
Causal learning and inference as a rational process: the new synthesis.
Holyoak, Keith J; Cheng, Patricia W
2011-01-01
Over the past decade, an active line of research within the field of human causal learning and inference has converged on a general representational framework: causal models integrated with bayesian probabilistic inference. We describe this new synthesis, which views causal learning and inference as a fundamentally rational process, and review a sample of the empirical findings that support the causal framework over associative alternatives. Causal events, like all events in the distal world as opposed to our proximal perceptual input, are inherently unobservable. A central assumption of the causal approach is that humans (and potentially nonhuman animals) have been designed in such a way as to infer the most invariant causal relations for achieving their goals based on observed events. In contrast, the associative approach assumes that learners only acquire associations among important observed events, omitting the representation of the distal relations. By incorporating bayesian inference over distributions of causal strength and causal structures, along with noisy-logical (i.e., causal) functions for integrating the influences of multiple causes on a single effect, human judgments about causal strength and structure can be predicted accurately for relatively simple causal structures. Dynamic models of learning based on the causal framework can explain patterns of acquisition observed with serial presentation of contingency data and are consistent with available neuroimaging data. The approach has been extended to a diverse range of inductive tasks, including category-based and analogical inferences.
Violation of causality in f(T) gravity
Energy Technology Data Exchange (ETDEWEB)
Otalora, G. [Pontificia Universidad Catolica de Valparaiso, Instituto de Fisica, Valparaiso (Chile); Reboucas, M.J. [Centro Brasileiro de Pesquisas Fisicas, Rio de Janeiro, RJ (Brazil)
2017-11-15
In the standard formulation, the f(T) field equations are not invariant under local Lorentz transformations, and thus the theory does not inherit the causal structure of special relativity. Actually, even locally violation of causality can occur in this formulation of f(T) gravity. A locally Lorentz covariant f(T) gravity theory has been devised recently, and this local causality problem seems to have been overcome. The non-locality question, however, is left open. If gravitation is to be described by this covariant f(T) gravity theory there are a number of issues that ought to be examined in its context, including the question as to whether its field equations allow homogeneous Goedel-type solutions, which necessarily leads to violation of causality on non-local scale. Here, to look into the potentialities and difficulties of the covariant f(T) theories, we examine whether they admit Goedel-type solutions. We take a combination of a perfect fluid with electromagnetic plus a scalar field as source, and determine a general Goedel-type solution, which contains special solutions in which the essential parameter of Goedel-type geometries, m{sup 2}, defines any class of homogeneous Goedel-type geometries. We show that solutions of the trigonometric and linear classes (m{sup 2} < 0 and m = 0) are permitted only for the combined matter sources with an electromagnetic field matter component. We extended to the context of covariant f(T) gravity a theorem which ensures that any perfect-fluid homogeneous Goedel-type solution defines the same set of Goedel tetrads h{sub A}{sup μ} up to a Lorentz transformation. We also showed that the single massless scalar field generates Goedel-type solution with no closed time-like curves. Even though the covariant f(T) gravity restores Lorentz covariance of the field equations and the local validity of the causality principle, the bare existence of the Goedel-type solutions makes apparent that the covariant formulation of f(T) gravity
International Nuclear Information System (INIS)
Pimentel, B.M.; Suzuki, A.T.; Tomazelli, J.L.
1992-01-01
The principle of analytic continuation can be used to derive causal distributions for covariant propagators. We apply this principle as a basis for deriving analytically continued causal distributions for algebraic non-covariant propagators. (author)
Testing causal relationships between wholesale electricity prices and primary energy prices
International Nuclear Information System (INIS)
Nakajima, Tadahiro; Hamori, Shigeyuki
2013-01-01
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
Impact of Systematic Sampling on Causality in the presence of Unit Roots
Rajaguru GULASEKARAN
2002-01-01
Quite contrary to the stationary case where systematic sampling preserves the direction of Granger causality, this paper shows that systematic sampling of integrated series may induce spurious causality, even if they are used in differenced form.
Frewen, Paul A.; Schmittmann, Verena D.; Bringmann, Laura F.; Borsboom, Denny
2013-01-01
Background: Previous research demonstrates that posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame are frequently co-occurring problems that may be causally related. Objectives: The present study utilized Perceived Causal Relations (PCR) scaling in order to assess
Frewen, P.A.; Schmittmann, V.D.; Bringmann, L.F.; Borsboom, D.
2013-01-01
Background Previous research demonstrates that posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame are frequently co-occurring problems that may be causally related. Objectives The present study utilized Perceived Causal Relations (PCR) scaling in order to assess participants’
Frewen, P.A.; Schmittmann, V.D.; Bringmann, L.F.; Borsboom, D.
2013-01-01
Background: Previous research demonstrates that posttraumatic memory reexperiencing, depression, anxiety, and guilt-shame are frequently co-occurring problems that may be causally related. Objectives: The present study utilized Perceived Causal Relations (PCR) scaling in order to assess
Szilagyi, Andrew D.
1977-01-01
Attempts to empirically verify the causal source and direction of causal influence between role ambiguity, role conflict and job satisfaction and performance for three organizational levels in a hospital environment. (Author/RK)
Investigating Causality Between Agricultural and Economic Growth in Iran
Directory of Open Access Journals (Sweden)
A. Falsafian
2010-10-01
Full Text Available Although rate of economic growth is not the only way to measure economic development, it is relatively more important than the other indices. Agriculture sector plays the main role on economic growth and sustainable development. In addition, it has significant impact on most social, political and economic issues by producing strategic food products for ever-increasing population. Therefore, the present study investigated causal relationship between agricultural and economic growth in Iran. To this end, the Granjer’s causality test was used after employing the Augmented Dicky-Fuller test to see if the variables under consideration are stationary. The result showed that there is a long learn feedback relationship between these variables and agricultural developments.
Enfermedades emergentes y reemergentes: factores causales y vigilancia
Directory of Open Access Journals (Sweden)
Carmen Luisa Suárez Larreinaga
2000-12-01
Full Text Available Este artículo tiene como objetivo exponer los conceptos y algunos de los factores causales más importantes en la aparición y diseminación de las enfermedades emergentes y reemergentes, así como presentar brevemente algunas de las actividades de vigilancia epidemiológica y su importancia en la detección y control de estas enfermedadesThe objective of this paper is to expound the concepts and some of the most important causal factors in the appearance and spreading of emergent and reemergent diseases, as well as to make a brief presentation of some of the epidemiological surveillance activities and their importance in the detection and control of these diseases
Zika Virus Infection and Microcephaly: Evidence for a Causal Link
Directory of Open Access Journals (Sweden)
Jin-Na Wang
2016-10-01
Full Text Available Zika virus (ZIKV is a flavivirus related to the Dengue, yellow fever and West Nile viruses. Since the explosive outbreaks of ZIKV in Latin America in 2015, a sudden increase in the number of microcephaly cases has been observed in infants of women who were pregnant when they contracted the virus. The severity of this condition raises grave concerns, and extensive studies on the possible link between ZIKV infection and microcephaly have been conducted. There is substantial evidence suggesting that there is a causal link between ZIKV and microcephaly, however, future studies are warranted to solidify this association. To summarize the most recent evidence on this issue and provide perspectives for future studies, we reviewed the literature to identify existing evidence of the causal link between ZIKV infection and microcephaly within research related to the epidemics, laboratory diagnosis, and possible mechanisms.
Causality and relativistic effects in intranuclear cascade calculations
International Nuclear Information System (INIS)
Kodama, T.; Duarte, S.B.; Chung, K.C.; Donangelo, R.J.; Nazareth, R.A.M.S.
1983-01-01
Relativistic effects in high energy nuclear collisions, when non-invariance of simultaneity is taken into account, are studied. It is shown that the time ordering of nucleon-nucleon collisions is quite different for different observers, giving in some cases non-invariant final results for intranuclear cascade (INC) calculations. In particular, an example of such a case is shown, in which the INC simulation, depending on the reference frame, presents a kind of density instability caused by a specific time ordering of collision events. A new INC calculation, using a causality preserving scheme, which minimizes this kind of relativistic effect is proposed. It is verified that the causality preserving INC prescription essentially recovers the relativistic invariance. (Author) [pt
Scenario development, qualitative causal analysis and system dynamics
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Michael H. Ruge
2009-02-01
Full Text Available The aim of this article is to demonstrate that technology assessments can be supported by methods such as scenario modeling and qualitative causal analysis. At Siemens, these techniques are used to develop preliminary purely qualitative models. These or parts of these comprehensive models may be extended to system dynamics models. While it is currently not possible to automatically generate a system dynamics models (or vice versa, obtain a qualitative simulation model from a system dynamics model, the two thechniques scenario development and qualitative causal analysis provide valuable indications on how to proceed towards a system dynamics model. For the qualitative analysis phase, the Siemens – proprietary prototype Computer – Aided Technology Assessment Software (CATS supportes complete cycle and submodel analysis. Keywords: Health care, telecommucations, qualitative model, sensitivity analysis, system dynamics.
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...
Women's caregiving and paid work: causal relationships in late midlife.
Pavalko, E K; Artis, J E
1997-07-01
Care of an ill or disabled family member or friend is disproportionately done by women and typically is done in late midlife. Because this is-also a time in the life course when women's labor force participation peaks, many women faced with caregiving demands have to decide how to balance them with their employment. In this study we use the National Longitudinal Survey (NLS) of Mature Women to examine the causal relationship between employment and caring for an ill or disabled friend or relative over a three-year period. We find that employment does not affect whether or not women start caregiving, but that women who do start are more likely to reduce employment hours or stop work. Thus, the causal relationship between employment and caregiving in late midlife is largely unidirectional, with women reducing hours to meet caregiving demands.
Renormalization group approach to causal bulk viscous cosmological models
International Nuclear Information System (INIS)
Belinchon, J A; Harko, T; Mak, M K
2002-01-01
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
Research designs and making causal inferences from health care studies.
Flannelly, Kevin J; Jankowski, Katherine R B
2014-01-01
This article summarizes the major types of research designs used in healthcare research, including experimental, quasi-experimental, and observational studies. Observational studies are divided into survey studies (descriptive and correlational studies), case-studies and analytic studies, the last of which are commonly used in epidemiology: case-control, retrospective cohort, and prospective cohort studies. Similarities and differences among the research designs are described and the relative strength of evidence they provide is discussed. Emphasis is placed on five criteria for drawing causal inferences that are derived from the writings of the philosopher John Stuart Mill, especially his methods or canons. The application of the criteria to experimentation is explained. Particular attention is given to the degree to which different designs meet the five criteria for making causal inferences. Examples of specific studies that have used various designs in chaplaincy research are provided.
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.
2016-01-01
Summary 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
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....... Such 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...
Causal attribution of mental illness in South-Eastern Nigeria.
Ikwuka, Ugo; Galbraith, Niall; Nyatanga, Lovemore
2014-05-01
Understanding of mental illness in sub-Saharan Africa has remained under-researched in spite of the high and increasing neuropsychiatric burden of disease in the region. This study investigated the causal beliefs that the Igbo people of south-eastern Nigeria hold about schizophrenia, with a view to establishing the extent to which the population makes psychosocial, biological and supernatural attributions. Multi-stage sampling was used to select participants (N = 200) to which questionnaires were administered. Mean comparison of the three causal models revealed a significant endorsement of supernatural causation. Logistic regressions revealed significant contributions of old age and female gender to supernatural attribution; old age, high education and Catholic religious denomination to psychosocial attributions; and high education to biological attributions. It is hoped that the findings would enlighten, augment literature and enhance mental health care service delivery.
Zika Virus Infection and Microcephaly: Evidence for a Causal Link.
Wang, Jin-Na; Ling, Feng
2016-10-20
Zika virus (ZIKV) is a flavivirus related to the Dengue, yellow fever and West Nile viruses. Since the explosive outbreaks of ZIKV in Latin America in 2015, a sudden increase in the number of microcephaly cases has been observed in infants of women who were pregnant when they contracted the virus. The severity of this condition raises grave concerns, and extensive studies on the possible link between ZIKV infection and microcephaly have been conducted. There is substantial evidence suggesting that there is a causal link between ZIKV and microcephaly, however, future studies are warranted to solidify this association. To summarize the most recent evidence on this issue and provide perspectives for future studies, we reviewed the literature to identify existing evidence of the causal link between ZIKV infection and microcephaly within research related to the epidemics, laboratory diagnosis, and possible mechanisms.
Negative vacuum energy densities and the causal diamond measure
International Nuclear Information System (INIS)
Salem, Michael P.
2009-01-01
Arguably a major success of the landscape picture is the prediction of a small, nonzero vacuum energy density. The details of this prediction depend in part on how the diverging spacetime volume of the multiverse is regulated, a question that remains unresolved. One proposal, the causal diamond measure, has demonstrated many phenomenological successes, including predicting a distribution of positive vacuum energy densities in good agreement with observation. In the string landscape, however, the vacuum energy density is expected to take positive and negative values. We find the causal diamond measure gives a poor fit to observation in such a landscape - in particular, 99.6% of observers in galaxies seemingly just like ours measure a vacuum energy density smaller than we do, most of them measuring it to be negative.
Altered cortical causality after remifentanil administration in healthy volunteers
DEFF Research Database (Denmark)
Khodayari-Rostamabad, Ahmad; Graversen, Carina; Olesen, Soren S
2014-01-01
and after infusion of remifentanil and placebo. Additionally, to assess cognitive function and analgesic effect, continuous reaction time (CRT) and bone pressure and heat pain were assessed, respectively. The causality information was extracted from the EEG by phase slope index (PSI). Among the 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 perturbation expansion revisited: Rescaling the interacting Dirac sea
International Nuclear Information System (INIS)
Finster, Felix; Grotz, Andreas
2010-01-01
The causal perturbation expansion defines the Dirac sea in the presence of a time-dependent external field. It yields an operator whose image generalizes the vacuum solutions of negative energy and thus gives a canonical splitting of the solution space into two subspaces. After giving a self-contained introduction to the ideas and techniques, we show that this operator is, in general, not idempotent. We modify the standard construction by a rescaling procedure giving a projector on the generalized negative-energy subspace. The resulting rescaled causal perturbation expansion uniquely defines the fermionic projector in terms of a series of distributional solutions of the Dirac equation. The technical core of the paper is to work out the combinatorics of the expansion in detail. It is also shown that the fermionic projector with interaction can be obtained from the free projector by a unitary transformation. We finally analyze the consequences of the rescaling procedure on the light-cone expansion.
The causal perturbation expansion revisited: Rescaling the interacting Dirac sea
Finster, Felix; Grotz, Andreas
2010-07-01
The causal perturbation expansion defines the Dirac sea in the presence of a time-dependent external field. It yields an operator whose image generalizes the vacuum solutions of negative energy and thus gives a canonical splitting of the solution space into two subspaces. After giving a self-contained introduction to the ideas and techniques, we show that this operator is, in general, not idempotent. We modify the standard construction by a rescaling procedure giving a projector on the generalized negative-energy subspace. The resulting rescaled causal perturbation expansion uniquely defines the fermionic projector in terms of a series of distributional solutions of the Dirac equation. The technical core of the paper is to work out the combinatorics of the expansion in detail. It is also shown that the fermionic projector with interaction can be obtained from the free projector by a unitary transformation. We finally analyze the consequences of the rescaling procedure on the light-cone expansion.
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.
A causal link between prediction errors, dopamine neurons and learning.
Steinberg, Elizabeth E; Keiflin, Ronald; Boivin, Josiah R; Witten, Ilana B; Deisseroth, Karl; Janak, Patricia H
2013-07-01
Situations in which rewards are unexpectedly obtained or withheld represent opportunities for new learning. Often, this learning includes identifying cues that predict reward availability. Unexpected rewards strongly activate midbrain dopamine neurons. This phasic signal is proposed to support learning about antecedent cues by signaling discrepancies between actual and expected outcomes, termed a reward prediction error. However, it is unknown whether dopamine neuron prediction error signaling and cue-reward learning are causally linked. To test this hypothesis, we manipulated dopamine neuron activity in rats in two behavioral procedures, associative blocking and extinction, that illustrate the essential function of prediction errors in learning. We observed that optogenetic activation of dopamine neurons concurrent with reward delivery, mimicking a prediction error, was sufficient to cause long-lasting increases in cue-elicited reward-seeking behavior. Our findings establish a causal role for temporally precise dopamine neuron signaling in cue-reward learning, bridging a critical gap between experimental evidence and influential theoretical frameworks.
CAUSALITY OF WEATHER CONDITIONS IN AUSTRALIAN STOCK EQUITY RETURNS
Svetlana Vlady; Ekrem Tufan; Bahattin Hamarat
2011-01-01
This study investigates causality of weather and its impact on the The S&P/ASX All Australian 200 Index has been selected as a proxy for the Australian capital market. The index consists exclusively of Australian domiciled companies. Following previous research in behaviour finance in the area of environmental psychology, the data set covers temperature, quality temperature, wet bulb temperature, quality wet bulb temperature, humidity, pressure and vapour pressure variables. The data set is a...
Scientific realism in particle physics a causal approach
Egg, Matthias
2014-01-01
Does particle physics really describe the basic constituents of the material world or is it just a useful tool for deriving empirical predictions? This book proposes a novel answer to that question, emphasizing the importance of causal reasoning for the justification of scientific claims. It thereby responds to general worries about scientific realism as well as to more specific challenges stemming from the interpretation of quantum physics.
Speeding Up Maximal Causality Reduction with Static Dependency Analysis
Huang, Shiyou; Huang, Jeff
2017-01-01
Stateless Model Checking (SMC) offers a powerful approach to verifying multithreaded programs but suffers from the state-space explosion problem caused by the huge thread interleaving space. The pioneering reduction technique Partial Order Reduction (POR) mitigates this problem by pruning equivalent interleavings from the state space. However, limited by the happens-before relation, POR still explores redundant executions. The recent advance, Maximal Causality Reduction (MCR), shows a promisi...
In defense of causal-formative indicators: A minority report.
Bollen, Kenneth A; Diamantopoulos, Adamantios
2017-09-01
Causal-formative indicators directly affect their corresponding latent variable. They run counter to the predominant view that indicators depend on latent variables and are thus often controversial. If present, such indicators have serious implications for factor analysis, reliability theory, item response theory, structural equation models, and most measurement approaches that are based on reflective or effect indicators. Psychological Methods has published a number of influential articles on causal and formative indicators as well as launching the first major backlash against them. This article examines 7 common criticisms of these indicators distilled from the literature: (a) A construct measured with "formative" indicators does not exist independently of its indicators; (b) Such indicators are causes rather than measures; (c) They imply multiple dimensions to a construct and this is a liability; (d) They are assumed to be error-free, which is unrealistic; (e) They are inherently subject to interpretational confounding; (f) They fail proportionality constraints; and (g) Their coefficients should be set in advance and not estimated. We summarize each of these criticisms and point out the flaws in the logic and evidence marshaled in their support. The most common problems are not distinguishing between what we call causal-formative and composite-formative indicators, tautological fallacies, and highlighting issues that are common to all indicators, but presenting them as special problems of causal-formative indicators. We conclude that measurement theory needs (a) to incorporate these types of indicators, and (b) to better understand their similarities to and differences from traditional indicators. (PsycINFO Database Record (c) 2017 APA, all rights reserved).