Intention in the Causal Network

1972 ◽  
Vol 17 (5) ◽  
pp. 280-282
Author(s):  
THOMAS NATSOULAS
Keyword(s):  
Causal Network

Incremental causal network construction over event streams

2014 ◽  
Vol 261 ◽  
pp. 32-51 ◽  
Author(s):  
Saurav Acharya ◽  
Byung Suk Lee
Keyword(s):  
Causal Network ◽  
Network Construction

scholarly journals Concurrent TMS-fMRI for causal network perturbation and proof of target engagement

NeuroImage ◽  
2021 ◽  
pp. 118093
Author(s):  
Til Ole Bergmann ◽  
Rathiga Varatheeswaran ◽  
Colleen A. Hanlon ◽  
Kristoffer H. Madsen ◽  
Axel Thielscher ◽  
...  
Keyword(s):  
Causal Network ◽  
Target Engagement

scholarly journals Decision Making Under Acute Stress Modeled by an Adaptive Temporal–Causal Network Model

2020 ◽  
Vol 07 (04) ◽  
pp. 433-452 ◽  
Author(s):  
S. Sahand Mohammadi Ziabari ◽  
Jan Treur
Keyword(s):  
Decision Making ◽  
Network Model ◽  
Real World ◽  
Acute Stress ◽  
Second Phase ◽  
Causal Network ◽  
Severe Stress ◽  
Modeling Methodology ◽  
Network Connections ◽  
New Learning

The influence of acute severe stress or extreme emotion based on a Network-Oriented modeling methodology has been addressed here. Adaptive temporal causal network model is an approach to address the phenomena with complexity which cannot be or hard to be explained in a real-world experiment. In the first phase, the suppression of the existing network connections as a consequence of the acute stress modeled and in the second phase relaxing the suppression by giving some time and starting a new learning of the decision making in accordance to presence of stress starts again.

INDEPENDENCE IN COMPLETE AND INCOMPLETE CAUSAL NETWORKS UNDER MAXIMUM ENTROPY

2008 ◽  
Vol 16 (05) ◽  
pp. 699-713 ◽  
Author(s):  
MICHAEL J. MARKHAM
Keyword(s):  
Expert System ◽  
Probability Distribution ◽  
Maximum Entropy ◽  
Linear Constraints ◽  
Causal Network ◽  
Missing Information ◽  
Causal Networks ◽  
Small Set

In an expert system having a consistent set of linear constraints it is known that the Method of Tribus may be used to determine a probability distribution which exhibits maximised entropy. The method is extended here to include independence constraints (Accommodation). The paper proceeds to discusses this extension, and its limitations, then goes on to advance a technique for determining a small set of independencies which can be added to the linear constraints required in a particular representation of an expert system called a causal network, so that the Maximum Entropy and Causal Networks methodologies give matching distributions (Emulation). This technique may also be applied in cases where no initial independencies are given and the linear constraints are incomplete, in order to provide an optimal ME fill-in for the missing information.

scholarly journals Causal Network Modeling of the Determinants of Drinking Behavior in Comorbid Alcohol Use and Anxiety Disorder

2018 ◽  
Vol 43 (1) ◽  
pp. 91-97 ◽  
Author(s):  
Justin J. Anker ◽  
Erich Kummerfeld ◽  
Alexander Rix ◽  
Scott J. Burwell ◽  
Matt G. Kushner
Keyword(s):  
Anxiety Disorder ◽  
Alcohol Use ◽  
Network Modeling ◽  
Drinking Behavior ◽  
Causal Network

scholarly journals Directed Causal Network Construction Using Linkage Analysis with Metabolic Syndrome-Related Expression Quantitative Traits

2011 ◽  
Vol 9 (4) ◽  
pp. 143-151 ◽  
Author(s):  
Kyee-Zu Kim ◽  
Jin-Young Min ◽  
Geun-Yong Kwon ◽  
Joo-Hon Sung ◽  
Sung-Il Cho
Keyword(s):  
Metabolic Syndrome ◽  
Linkage Analysis ◽  
Quantitative Traits ◽  
Causal Network ◽  
Network Construction

scholarly journals System-based DNA microarray analyses of different gene expression profile in spontaneously hypertensive rats treated with Songling Xuemaikang Capsule reveals underlying causal mechanisms.

2019 ◽  
Author(s):  
Li-tao Liu ◽  
Cui-qi Yan ◽  
Qiao-xin Tang ◽  
Man-xi Zhao ◽  
Chuan-zhen Teng ◽  
...  
Keyword(s):  
Gene Expression ◽  
Vascular Remodeling ◽  
Spontaneously Hypertensive Rats ◽  
Control Group ◽  
Causal Network ◽  
Ang Ii ◽  
Dosage Group ◽  
Hypertensive Rats ◽  
Spontaneously Hypertensive ◽  
Songling Xuemaikang Capsule

Abstract Background: Hypertension is considered the major risk factor for human health in the world. Songling Xuemaikang Capsule (SXC) is clinically used as a medicine for the prevention and treatment of cardiovascular and cerebrovascular diseases such as hypertension and hyperlipidemia. However, the underlying mechanisms have yet to be fully identified. Methods: Valsartan, as a positive control drug, high- and low-dose of SXC were orally administration with for 28 days to investigate the anti-hypertensive effect of SXC in spontaneously hypertensive rats (SHRs). The serum levels of aldosterone and Angiotensin II (Ang II) were detected. The gene expression profiling was performed in the thoracic aorta of SHRs using the Whole Rat Genome Oligo nucleotide Microarray. The integrated causal network analysis was performed to understand the mechanism of antihypertensive effect of SXC. Results: The results shown that the systolic and diastolic blood pressure were significant decreased in SXC low-dosage group and high-dosage group compared with the control group respectively. SXC low and high-dosage treatment decreased serum aldosterone levels significantly but increased serum Ang II compared with the control group respectively. Causal network analysis shown that treatment with SXC reversing the vascular remodeling process, inhibiting vascular inflammation and atherosclerosis, reversing endothelial cells dysfunction and likely reducing peripheral vascular resistance by down-regulated processes related to vascular remodeling, dyslipidemia, the complement system, leukocyte rolling, and endothelial dysfunction. In addition, SXC treatment may also activate fibrinolysis and regulate lipid and glucose metabolism. Conclusions: Those obtained data could help our understanding and potential utilization of SXC in the treatment or prevention of hypertension。

Influence of fishers’ behaviour on the catchability of surface tuna schools in the Venezuelan purse-seiner fishery in the Caribbean Sea

1999 ◽  
Vol 56 (3) ◽  
pp. 394-406
Author(s):  
Daniel Gaertner ◽  
Mauricio Pagavino ◽  
Jesus Marcano
Keyword(s):  
Environmental Factors ◽  
Daily Activity ◽  
Caribbean Sea ◽  
Catch Rate ◽  
Causal Network ◽  
Fine Scale ◽  
Network Approach ◽  
Logistic Regressions ◽  
The Caribbean ◽  
The Impact

The influence of Venezuelan skippers' behaviour on the catchability of surface tuna schools was modelled using logistic regressions. Data obtained from observers onboard purse seiners indicated that fishers' fine-scale decisions, such as chasing and setting a school, were influenced by (i) the skipper's skill, (ii) the fishing equipment used (e.g., whether a bird radar was used or not), (iii) the features of the tuna school, and (iv) some environmental factors. The connections among the decisions related to the fishing process and these variables were synthesized in a causal network approach. Results clearly showed that schools (i) composed by fishes under 2 kg and (ii) where biomass was lower than 5 metric tons were disregarded by fishers. Because fishers used these thresholds to decide when to set the net, modifications in their behaviour over the years may introduce serious biases in the analysis of any catch rate and abundance relationship. An average daily activity record of a purse seiner shows the proportion of time spent in searching and in setting activities and highlights the impact that the use of new fishing equipment may have on fishing power.

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