Esta es la tercera vez que un coronavirus zoonótico ha podido infectar diversas poblaciones humanas. Este nuevo virus, clasificado como SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), ...es el agente causal de la epidemia denominada COVID-19 (coronavirus disease 2019). La investigación internacional realizada en torno a este nuevo brote fue tan eficaz que en poco tiempo ya se conocía el genoma del virus, su biología y sus principales aspectos epidemiológicos. En Ecuador se han reportado hasta la fecha 1962 casos positivos de SARS-CoV-2, situación que generó una gran preocupación por parte de la sociedad y la Academia ecuatoriana. Por lo tanto, en este artículo de opinión se detallarán las principales investigaciones realizadas sobre el SARS-CoV-2 a nivel internacional, se discutirá sobre la importancia de la Academia en la toma de decisiones sanitarias y se pondrá en perspectiva el papel de la investigación fundamental para la contención de un posible brote en Ecuador.
•We characterise the design space for multi-level modelling solutions in the form of a feature model.•We provide a classification and comparison of existing multi-level modelling tools.•We propose a ...new conceptual approach to multi-level modelling, embedded within two meta-levels.•We realise the ideas in practice on a practical tool called TOTEM.•We report on empirical and analytical evaluations of the tool.
Model driven Engineering (MDE) advocates the active use of models throughout the different software development phases. In MDE, models are described using meta-models, one meta-level above. This approach effectively leaves developers with one single meta-level to create their models. However, there are scenarios where the use of multiple meta-levels results in simpler models with less accidental complexity. Hence, to simplify modelling in these cases, several multi-level modelling approaches and tools have recently emerged to increase the flexibility in modelling. While they provide advanced primitives to simplify modelling, there are possibilities to improve interoperability with mainstream two-level modelling approaches based on the Meta-Object Facility (MOF) standard of the Object Management Group (OMG), and achieve wider adoption.
For this purpose, we first characterise the design space of multi-level modelling approaches using a feature model. On such a basis, we provide a detailed comparison of existing multi-level modelling tools, identifying gaps and research opportunities. As a result of this gap analysis, we propose a new approach to multi-level modelling that embeds multiple meta-levels within one meta-model (i.e., encoding objects as classes, and instantiation as inheritance), and a tool – called TOTEM – which implements these concepts. The tool capabilities and its benefits in terms of interoperability with mainstream, standard modelling frameworks are illustrated through an example, as well as with empirical and analytical evaluations.
Multiple psychological treatments for emotional disorders have been developed and implemented, improving the quality of life of individuals. Nevertheless, relapse and poor response to psychotherapy ...are common. This article argues that a greater understanding of both the psychological and neurobiological mechanisms of change in psychotherapy is essential to improve treatment for emotional disorders. It aims to demonstrate how an understanding of these mechanisms provides a basis for (i) reconceptualizing some mental disorders, (ii) refining and establishing the evidence for existing therapeutic techniques and (iii) designing new techniques that precisely target the processes that maintain these disorders. Possible future directions for researchers and practitioners working at the intersection of neuropsychology and clinical psychology are discussed.
•Define and explore MSU as a correlation measure for multiple nominal variables.•Introduce representativeness as desirable property of a sample from a nominal variable.•Prove that a ...non-representative sample under-estimates the actual value of MSU.•Calculate the sample size that assures representativeness at 1-α level of probability.•Show how MSU with its interaction detection can be applied to feature selection.
In this work we propose an extension of the Symmetrical Uncertainty (SU) measure in order to address the multivariate case, simultaneously acquiring the capability to detect possible correlations and interactions among features. This generalization, denoted Multivariate Symmetrical Uncertainty (MSU), is based on the concepts of Total Correlation (TC) and Mutual Information (MI) extended to the multivariate case. The generalized measure accounts for the total amount of dependency within a set of variables as a single monolithic quantity. Multivariate measures are usually biased due to several factors. To overcome this problem, a mathematical expression is proposed, based on the cardinality of all features, which can be used to calculate the number of samples needed to estimate the MSU without bias at a pre-specified significance level. Theoretical and experimental results on synthetic data show that the proposed sample size expression properly controls the bias. In addition, when the MSU is applied to feature selection on synthetic and real-world data, it has the advantage of adequately capturing linear and nonlinear correlations and interactions, and it can therefore be used as a new feature subset evaluation method.
Background
Cultivating self‐compassion is increasingly recognized as a powerful method to regulate hyperactive threat processes such as shame and self‐criticism, but fear of self‐compassion (FSC) can ...inhibit this. These difficulties are underexplored in personality disorder (PD) despite their prevalence. Furthermore, little evidence exists regarding how these factors relate to adverse childhood experiences (ACEs) and attachment.
Method
Fifty‐three participants with a diagnosis of PD completed measures including childhood abuse/neglect, invalidation, early warmth, self‐compassion, shame, self‐criticism, FSC, and anxious/avoidant attachment.
Results
Self‐compassion was predicted uniquely by low early warmth; self‐inadequacy by invalidation and abuse; and FSC by multiple ACEs. FSC and self‐compassion were significantly correlated with self‐criticism and shame, but not with one another.
Conclusions
Low self‐compassion and high FSC appear to be distinct problems, substantiating physiological models proposing distinct threat and soothing systems. Results are consistent with theories positing that low self‐compassion has distinct origins to shame, self‐criticism, and FSC.
Introduction Chronic use of various compounds can have long-lasting effects on animal behavior, and some of these effects can be influenced by the environment. Many environmental enrichment protocols ...have the potential to induce behavioral changes. Aim The aim of the present study was to investigate how environmental enrichment can mitigate the effects of chronic methylphenidate consumption on the behavior of Wistar rats. Methods The animals were housed for 20 days under either an environmental enrichment protocol (which included tubes of different shapes) or standard housing conditions. After seven days, half of the rats received 13 days of oral administration of methylphenidate (2 mg/kg). After seven days, the rats underwent behavioral tests, including the elevated plus maze (anxiety), open field (locomotion), object-in-place recognition test (spatial memory), and a test for social interaction (social behavior). Results The results showed that the enriched environmental condition reversed the enhanced time in the open arms of the elevated plus maze induced by methylphenidate (F 1,43 = 4.275, p = 0.045). Methylphenidate also enhanced exploratory rearing in the open field (F 1,43 = 4.663, p = 0.036) and the time spent in the open area of the open field (H3 = 8.786, p = 0.032). The enriched environment mitigated the inhibition of social interaction with peers induced by methylphenidate (H3 = 16.755, p < 0.001) as well as the preference for single exploratory behavior (H3 = 9.041, p = 0.029). Discussion These findings suggest that environmental enrichment can counteract some of the effects of methylphenidate. These results are relevant for the clinical treatment of the long-lasting secondary effects associated with methylphenidate pharmacological treatment.
While the transcriptional network of human embryonic stem cells (hESCs) has been extensively studied, relatively little is known about how post-transcriptional modulations determine hESC function. ...RNA-binding proteins play central roles in RNA regulation, including translation and turnover. Here we show that the RNA-binding protein CSDE1 (cold shock domain containing E1) is highly expressed in hESCs to maintain their undifferentiated state and prevent default neural fate. Notably, loss of CSDE1 accelerates neural differentiation and potentiates neurogenesis. Conversely, ectopic expression of CSDE1 impairs neural differentiation. We find that CSDE1 post-transcriptionally modulates core components of multiple regulatory nodes of hESC identity, neuroectoderm commitment and neurogenesis. Among these key pro-neural/neuronal factors, CSDE1 binds fatty acid binding protein 7 (FABP7) and vimentin (VIM) mRNAs, as well as transcripts involved in neuron projection development regulating their stability and translation. Thus, our results uncover CSDE1 as a central post-transcriptional regulator of hESC identity and neurogenesis.
Display omitted
•Quinoline, indole, and naphthalene enhanced the rate of hydrodesulfurization of dibenzothiophene.•Reaction rates for the direct route of hydrodesulfurization were enhanced.•Lower ...temperatures favored positive effects of the co-reactants on hydrodesulfurization.•In the presence of quinoline, indole, and naphthalene the rate of hydrodesulfurization increased with the concentration of dibenzothiophene.
In this work, we report a statistically significant increase in the rates of direct C–S bond scission of dibenzothiophene when co-reactants such as naphthalene, quinoline, and indole are present during its hydrodesulfurization over a Ni–MoS2/γ-Al2O3 catalyst. The competitive adsorption of these compounds on the same active sites has usually been associated with inhibitory effects of sulfur elimination. However, we carried out statistically designed experiments at temperatures between 260 and 300 °C, concentrations of dibenzothiophene between 1.0 and 3.7 wt%, and concentrations of the co-reactants between 0.13 and 0.52 wt%, and observed that the kinetic constant of the direct desulfurization pathway can increase up to 200% when either naphthalene, indole, or quinoline is co-fed to the reaction system at 260 °C and 3.7 wt% of dibenzothiophene. Therefore, the classical paradigm that aromatics and nitrogen heterocycles always inhibit hydrodesulfurization needs reexamination.
Interaction between variables is often found in statistical models, and it is usually expressed in the model as an additional term when the variables are numeric. However, when the variables are ...categorical (also known as nominal or qualitative) or mixed numerical-categorical, defining, detecting, and measuring interactions is not a simple task. In this work, based on an entropy-based correlation measure for
nominal variables (named as Multivariate Symmetrical Uncertainty (MSU)), we propose a formal and broader definition for the interaction of the variables. Two series of experiments are presented. In the first series, we observe that datasets where some record types or combinations of categories are absent, forming
of records, which often display interactions among their attributes. In the second series, the interaction/non-interaction behavior of a regression model (entirely built on continuous variables) gets successfully replicated under a discretized version of the dataset. It is shown that there is an interaction-wise correspondence between the continuous and the discretized versions of the dataset. Hence, we demonstrate that the proposed definition of interaction enabled by the MSU is a valuable tool for detecting and measuring interactions within linear and non-linear models.
PDF
