scholarly journals The role of brain lipids in the causal model of autism. Re-interpretation of the existing data.

Hypothesis ◽  
2016 ◽  
Vol 14 (1) ◽  
Author(s):  
Barbara Hall
Keyword(s):  
Causal Model ◽  
Brain Lipids ◽  
Existing Data

Looking into a New Challenge, DKA and Covid-19 A Review on Pediatric DKA Cases during New Coronavirus Pandemic Who is to Blame, the Virus or Health System?

2021 ◽  
Vol 5 (7) ◽  
pp. 01-04
Author(s):  
Vida Tajiknia ◽  
Maryam Ghandali ◽  
Ardavan Ahmadvand ◽  
Ali Afrasiabi ◽  
Reza Pirdehghan ◽  
...  
Keyword(s):  
Immune System ◽  
Virus Infection ◽  
Pediatric Patients ◽  
Strong Association ◽  
Diabetes Type ◽  
Diabetes Type 1 ◽  
The World ◽  
Existing Data

Since the first month of this new pandemic situation, all around the world healthcare system has been facing different challenges and difficulties; patients with chronic diseases such as cancer or diabetes with impaired immune system were at greater risk of infections and complications. It goes without saying that this issue was extremely important among pediatric clinicians dealing with diabetic pediatrics. Diabetes is the number one chronic illness among pediatric patients and the most dangerous and frightened complication of it is Diabetic Ketoacidosis (DKA). Studies have shown a strong association between pandemic and increase in new diabetes type 1 cases and its lethal complication called DKA. Here we are going to take a look at existing data and report about cases with this condition trying to find the missing piece of a big puzzle; what is the role of Covid-19 in causing Diabetes in previously healthy kids and what is the real association between SARS-COV2 virus infection and DKA? We are going to review different studies, possible mechanism, new t1dm cases and old cases, with or without covid infection, DKA cases and its severity.

Prior Beliefs and Ambiguity Attitudes in Decision from Experience

2021 ◽  
Author(s):  
Ilke Aydogan
Keyword(s):  
Decision Analysis ◽  
Crucial Role ◽  
Decision Model ◽  
Data Sets ◽  
Subjective Probabilities ◽  
Prior Beliefs ◽  
Decisions From Experience ◽  
Ambiguity Attitudes ◽  
Existing Data

Prior beliefs and their updating play a crucial role in decisions under uncertainty, and theories about them have been well established in classical Bayesianism. Yet, they are almost absent for ambiguous decisions from experience. This paper proposes a new decision model that incorporates the role of prior beliefs, beyond the role of ambiguity attitudes, into the analysis of such decisions. Hence, it connects ambiguity theories, popular in economics, with decision from experience, popular (mostly) in psychology, to the benefit of both. A reanalysis of some existing data sets from the literature on decisions from experience shows that the model that incorporates prior beliefs into the estimation of subjective probabilities outperforms the commonly used model that approximates subjective probabilities with observed relative frequencies. Controlling for subjective priors, we obtain more accurate measurements of ambiguity attitudes, and thus a new explanation of the gap between decision from description and decision from experience. This paper was accepted by Manel Baucells, decision analysis.

Cryptic Diversity and Sexual Selection

2020 ◽  
pp. 447-471
Author(s):  
Matthias Galipaud ◽  
Loïc Bollache ◽  
Clément Lagrue
Keyword(s):  
Sexual Selection ◽  
Morphological Traits ◽  
Character Displacement ◽  
Secondary Contact ◽  
Cryptic Diversity ◽  
Reproductive Character Displacement ◽  
Behavioral Traits ◽  
Genetic Techniques ◽  
Existing Data

Recent advances in molecular and genetic techniques have revealed tremendous hidden genetic diversity in plants and animals. Crustaceans are no exception and, in fact, present one of the highest levels of cryptic diversity among the metazoans. Beyond the importance of such discovery and its multiple implications for taxonomy and ecology, it is now timely to investigate the potential causes of cryptic diversity. This chapter reviews the theoretical and experimental literature, seeking evidences for a relationship between sexual selection and cryptic diversity in crustaceans. It proposes three scenarios for the role of sexual selection on the origin and maintenance of pre-mating isolation and genetic divergence among crustacean populations, and suggests ways to discriminate among them experimentally or using existing data. Assuming that taxonomic identification is largely based on differences in sexually selected morphological traits, it also reviews evidence for a cryptic action of sexual selection on crustacean phenotypes. Specifically, if sexual selection acts primarily on chemical, visual, or behavioral traits, it is likely that allopatric crustacean populations remain morphologically similar even when they are reproductively isolated. This review shows that the strength of sexual selection likely differs among allopatric populations but does not seem to consistently induce pre-mating isolation (e.g. as in copepods and amphipods). Research is now needed to try to identify general patterns and determine the role of sexual selection on pre-mating isolation after secondary contact between populations, through reinforcement and reproductive character displacement.

The Role of Knowledge Sharing on Organisational Innovation

2016 ◽  
pp. 406-429 ◽  
Author(s):  
Kijpokin Kasemsap
Keyword(s):  
Knowledge Management ◽  
Knowledge Sharing ◽  
Causal Model ◽  
Organisational Learning ◽  
Organisational Innovation ◽  
Business Goals ◽  
Management Knowledge ◽  
Innovation Knowledge ◽  
Positive Effect

This chapter introduces the framework and causal model of organisational learning, knowledge management, knowledge-sharing behaviour, and organisational innovation. It argues that dimensions of organisational learning, knowledge management, and knowledge-sharing behaviour have mediated positive effect on organisational innovation. Knowledge-sharing behaviour positively mediates the relationships between organisational learning and organisational innovation and between knowledge management and organisational innovation. Organisational learning is positively related to knowledge management. Understanding the theoretical learning is positively beneficial for organisations aiming to increase organisational innovation and achieve business goals.

scholarly journals The Effects of Doxorubicin-based Chemotherapy and Omega-3 Supplementation on Mouse Brain Lipids

Metabolites ◽  
2019 ◽  
Vol 9 (10) ◽  
pp. 208
Author(s):  
Djawed Bennouna ◽  
Melissa Solano ◽  
Tonya S. Orchard ◽  
A. Courtney DeVries ◽  
Maryam Lustberg ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Breast Cancer Survivors ◽  
Omega 3 ◽  
Resolvin D1 ◽  
Brain Lipids ◽  
Fatty Acid Supplementation ◽  
Ovariectomized Mice ◽  
The Brain ◽  
Injection Study

Chemotherapy-induced cognitive impairment affects ~30% of breast cancer survivors, but the effects on how chemotherapy impacts brain lipids, and how omega-3 polyunsaturated fatty acid supplementation may confer protection, is unknown. Ovariectomized mice were randomized to two rounds of injections of doxorubicin + cyclophosphamide or vehicle after consuming a diet supplemented with 2% or 0% EPA+DHA, and sacrificed 4, 7, and 14 days after the last injection (study 1, n = 120) or sacrificed 10 days after the last injection (study 2, n = 40). Study 1 whole brain samples were extracted and analyzed by UHPLC-MS/MS to quantify specialized pro-resolving mediators (SPMs). Lipidomics analyses were performed on hippocampal extracts from study 2 to determine changes in the brain lipidome. Study 1 results: only resolvin D1 was present in all samples, but no differences in concentration were observed (P > 0.05). Study 2 results: chemotherapy was positively correlated with omega-9 fatty acids, and EPA+DHA supplementation helped to maintain levels of plasmalogens. No statistically significant chemotherapy*diet effect was observed. Results demonstrate a limited role of SPMs in the brain post-chemotherapy, but a significant alteration of hippocampal lipids previously associated with other models of cognitive impairment (i.e., Alzheimer’s and Parkinson’s disease).

scholarly journals Itemformaat, differensiële itemskeefheid en die faktorstruktuur van 'n selfvoltooïngsvraelys

1999 ◽  
Vol 25 (2) ◽  
Author(s):  
C. Swart ◽  
G. Roodt ◽  
J. M. Schepers
Keyword(s):  
Factor Analysis ◽  
Random Sample ◽  
Financial Institution ◽  
Test Construction ◽  
Second Order ◽  
Order Factor ◽  
The Empirical Analysis ◽  
Existing Data ◽  
Second Order Factor Analysis

The purpose of this study was twofold: Firstly an existing Workvalues questionnaire was evaluated against criteria for test construction; and secondly the role of differential item skewness in the grouping of second order factors, within this Workvalues questionnaire, was empirically investigated. The existing data of the Workvalues questionnaire, consisting of 110 items on a random sample of 8000 respondents, within a financial institution, was used for the empirical analysis. A first- and second order factor analysis was done on the items of the 2099 completed quiestionnaires. Three clearly differentiated second order factors with seemingly acceptable internal consistencies were identified. The results indicated that the items of the first second order factor, grouped together on the base of differential skewness. The items of the second and third scale were less skew and could be interpreted. Opsomming Die doel van hierdie studie was tweeledig: Eerstens is 'n bestaande Werkwaardesvraelys teenoor kriteria vir toetskonstruksie geevalueer; en tweedens is die rol van differensiele itemskeefheid in die groepering van tweedeordefaktore van hierdie Werkwaardesvraelys empiries ondersoek. Die bestaande datastel van die Werkwaardesvraelys se 110 items, op 'n ewekansige steekproef van 8000 respondente in 'n finansiele instelling, is vir die empiriese ontleding gebruik. 'n Eerste- en tweedeordefaktorontleding is ten opsigte van die items van 2099 voltooide vraelyste uitgevoer en drie duidelik gedifferensieerde tweedeordefaktore met öenskynlike, aanneemlike interne konstanthede het na vore gekom. Resultate dui daarop dat items van die eerste tweedeordefaktor gegroepeer het op grond van differensiële skeefheid. Die items van die tweede en derde skaal was minder skeef en kon vertolk word.

scholarly journals Invariant Causal Prediction for Nonlinear Models

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Christina Heinze-Deml ◽  
Jonas Peters ◽  
Nicolai Meinshausen
Keyword(s):  
Linear Models ◽  
Causal Model ◽  
Nonlinear Models ◽  
Causal Structure ◽  
Nonparametric Tests ◽  
Population Projections ◽  
World Population ◽  
Residual Distribution ◽  
Using Data

AbstractAn important problem in many domains is to predict how a system will respond to interventions. This task is inherently linked to estimating the system’s underlying causal structure. To this end, Invariant Causal Prediction (ICP) [1] has been proposed which learns a causal model exploiting the invariance of causal relations using data from different environments. When considering linear models, the implementation of ICP is relatively straightforward. However, the nonlinear case is more challenging due to the difficulty of performing nonparametric tests for conditional independence.In this work, we present and evaluate an array of methods for nonlinear and nonparametric versions of ICP for learning the causal parents of given target variables. We find that an approach which first fits a nonlinear model with data pooled over all environments and then tests for differences between the residual distributions across environments is quite robust across a large variety of simulation settings. We call this procedure “invariant residual distribution test”. In general, we observe that the performance of all approaches is critically dependent on the true (unknown) causal structure and it becomes challenging to achieve high power if the parental set includes more than two variables.As a real-world example, we consider fertility rate modeling which is central to world population projections. We explore predicting the effect of hypothetical interventions using the accepted models from nonlinear ICP. The results reaffirm the previously observed central causal role of child mortality rates.

scholarly journals Legal Pathways to Coal Phase-Out in Italy in 2025

Energies ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 5605 ◽  
Author(s):  
Matteo Fermeglia ◽  
Paolo Bevilacqua ◽  
Claudia Cafaro ◽  
Paolo Ceci ◽  
Antonio Fardelli
Keyword(s):  
Power Plants ◽  
State Of The Art ◽  
Renewable Energy Sources ◽  
Energy Generation ◽  
Electricity Production ◽  
Coal Power Plants ◽  
Coal Power ◽  
Phase Out ◽  
Existing Data

This contribution aims to provide an in-depth outlook of the phase-out of coal-fired energy generation in Italy. In particular, this article analyzes the state-of-the-art with regard to both the current role of coal generation and the performance of the main legal and regulatory tools as implemented in Italy thus far to ensure the closure of all coal power plants by 2025 as announced in the Italian National Climate and Energy Plan. Based on existing data and scenarios on both electricity production and demand trends, this article unfolds the marginal role played by coal-fired generation in the Italian energy mix. In addition, this paper aims to highlight the outstanding technical uncertainties and regulatory hurdles in the way towards de-carbonization of energy generation in Italy. This paper argues that several remarkable improvements are needed in order to avoid over-generation (especially through natural gas), to upscale the penetration of renewable energy sources, and develop the necessary infrastructures to adequately deliver on the full phasing-out of coal within the expected timeframes.

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