Volume 6 | Issue 1 |

 Abstract

Depression is common among cardiovascular groups and is linked to a variety of negative outcomes. Even in the absence of a clinical diagnosis of depression, depressed symptoms predict cardiac mortality, hospitalisation, lower patient health status, and higher healthcare expenses in patients with acute myocardial infarction (AMI). The theoretical system for this theory is adjusted from before specialists who directed an audit of the writing on the connection among depression and AMI. This structure traces a causal pathway for factors that are associated with the connection among depression and AMI. . Depressive symptoms following a MI, on the other hand, could be a sign of ongoing depression. It's unclear if individuals who have transient depression at the time of their MI hospitalisation or those who have persistent depression have a higher risk of negative outcomes than nondepressed patients. Depressive symptoms after a myocardial infarction (MI) are a common psychological condition that has a detrimental impact on heart disease prognosis. A growing body of research suggests that depression can be an independent risk factor for MI, as well as the mortality and complications that come with it. It can also lower the quality of life in people who have had a heart attack. Although depression is commonly encountered as comorbidity in people with somatic disorders, it is often overlooked. Given the high prevalence of post-MI depression symptoms and their detrimental implications on heart disease prognosis, this psychological issue in MI patients requires special attention. Acute myocardial infarction patients frequently experience depression (AMI).

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

depressive, symptom, acute myocardial infarction, health, coronary heart disease, etc

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Comorbidity exists when any two medical or mental conditions co-occur. The predominance of depression is generously higher in populations with medical illnesses than in populations without medical illnesses. Since it was first revealed that depression was linked to higher mortality in individuals recuperating from an acute myocardial infarction (AMI), there has been a growing focus on mood disruption in patients recovering from an AMI. The ENRICHD (Enhancing Recovery in Coronary Heart Disease Patients) clinical trial, which was just completed, was meant to see if treating depression and social isolation after an acute myocardial infarction increases survival (AMI). There was no significant difference in survival between the intervention and control groups in the experiment. Depression may no longer be a risk factor for death following an AMI, which could explain the lack of an intervention impact. Depression is linked to increased patient morbidity and death following an acute myocardial infarction (AMI). Anxiety, on the other hand, has received little attention in this setting, despite the fact that it has been shown to predict in-hospital mortality. Given the potential clinical importance of depression and anxiety after MI, the mixed results for the former and the paucity of evidence on the latter suggest that more research is needed.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

depression, mortality, risk factor, acute myocardial infarction, etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

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Information Seeking Behavior, Engineering students, Annamalai University, ICT and Information sources

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Creative Commons Attribution 4.0 and The Open Definition

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The Data Mining trends have been created and explored regarding technologies and methodologies. Frequent pattern mining is one of the particular data mining errands, especially from retail data. The errand is to find every successive pattern with a user specified minimum support, where the support of a pattern is the quantity of data arrangements that contain the pattern. This papercentres around concepts identified with frequent data mining for learning based framework. These issues have broken down and the arrangements have been made for the issues identified with before process and new strategies have been created for mining frequent patterns.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Data mining, pattern, algorithm. stream, input, output

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bridges, highway, vehicle, weight, reinforced, etc.

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Creative Commons Attribution 4.0 and The Open Definition

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The quantity of dynamic clients on microblogging locales is enormous and so is the messages posted by them. This data can be utilized to mine knowledge like the current subject of conversation between the clients. Finding answers to such queries is challenging because of the enormous measure of data produced. In this paper we propose a framework which incrementally packs the components in a sliding window. By incremental we mean that pressure is done while a component enters or leaves the sliding window not at all like where itemsets are packed toward the finish of a bunch. The pressure of components is based on the utility of the components in the current sliding window. The methodology introduced in this section is appropriate for processing data stream using a sliding window model as it permits more components to be put away in a sliding window for a fixed memory spending plan.

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Data mining, itemsets, stream, database, pattern.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Licence: creative commons attribution 4.0

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Bridge, construction, vehicles, project, load, etc.

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

This article is intended to provide a general overview of the issues surrounding genotoxic impurities and their potential resources. Here we shall focus on general and regulatory aspects review the toxicological issues.

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Creative Commons Attribution 4.0 and The Open Definition

 Keywords

Geotoxic impurity pharmaceutical Drug GTI

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

COMPARATIVE ANALYSIS OF HEALTH RELETED FITNESS AND RISK FACTOR OF DISEASE AMONG RURAL AND URBAN CHILDERNS OF MADHYA PRADESH

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Creative Commons Attribution 4.0 and The Open Definition

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COMPARATIVE ANALYSIS OF HEALTH RELETED FITNESS AND RISK FACTOR OF DISEASE AMONG RURAL AND URBAN CHILDERNS OF MADHYA PRADESH

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Creative Commons Attribution 4.0 and The Open Definition

 Abstract

Abstract: The notion of interval valued intuitionistic fuzzy Hv-submodules of an Hv-module with respect to a t-norm T and an s-norm S is given by J.M. Zhan. In this paper, we give some results on interval valued intuitionistic (S, T)-fuzzy Hv-submodules of an Hv-modules.

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Creative Commons Attribution 4.0 and The Open Definition

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Keywords: Hv-module, interval valued intuitionistic (S, T)-fuzzy Hv-submodule, interval valued intuitinistic (S, T)-fuzzy relation.

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Creative Commons Attribution 4.0 and The Open Definition