Dificultad específica de lectura en los procesos léxicos en estudiantes en etapa escolar

El trabajo académico tuvo como objetivo general explicar la dificultad específica de lectura en procesos léxicos en estudiantes etapa escolar. La información fue recolectada en diferentes fuentes de consulta, la misma que se organizó en secuencia lógica. En conclusión, las dificultades lectoras específicamente en los procesos léxicos varían según la edad del estudiante y el nivel en el que se encuentra, por ello el desarrollo debe ser gradual según cada año de la etapa escolarTrabajo académic

Entorno familiar y conducta agresiva en estudiantes de 5 años de la institución educativa N°320 – Chimbote

La presente investigación tuvo como objetivo determinar si el entorno familiar se relaciona con las conductas agresivas que presentan los niños de 5 años de la institución educativa 320 del A.H. Bolívar Alto; es de tipo cuantitativa descriptiva y ha utilizado el diseño correlacional. Para recabar la información, en una muestra de 25 niños, ha utilizado dos instrumentos, un cuestionario, aplicado a los padres de familia de los niños que integraron la muestra, para conocer el nivel en que se encuentra el entorno familiar y una ficha de observación para recabar información sobre el nivel de la variable conducta agresiva. Los instrumentos previos a su aplicación han sido sometidos a validación a través de juicio de expertos y a una prueba piloto para garantizar su confiabilidad. La información recabada nos arroja como resultados que un mayoritario 56% de las familias presentan un entorno malo para la formación de los niños; respecto a la variable conductas agresivas, un 72% de los niños presentan un nivel de agresividad alto. En cuanto a la correlación entre variables se concluye que la relación es alta y negativa, hallándose una elación significativa p=0,00 < 0,01 por lo que se comprueba la hipótesis que afirma la relación entre las dos variables estudiadas, reflejándose esto en el 79% de la muestra

Impacto directo e indirecto de cambios en la cotización internacional del petróleo sobre la inflación: un estudio para Perú 2007 – 2019

La presente investigación tiene como objetivo cuantificar en términos de duración e impacto del efecto de choques en la cotización internacional del precio del petróleo sobre la inflación del Perú para el periodo 2007 al 2019. Por ello, se realiza una diferenciación entre el efecto directo e indirecto, ya que el efecto sobre la economía no solo se visualiza en los precios de los combustibles, sino también en variables macroeconómicas consideradas como variables control (crecimiento de la economía de Estados Unidos, términos de intercambio, tasa de crecimiento de Perú, tasa de referencia y la tasa de desempleo), las cuales multiplican aún más el efecto sobre la inflación. El análisis del efecto directo se desarrolló mediante una regresión simple OLS, la cual evaluará cambios en la cotización internacional del petróleo sobre el precio de los combustibles y derivados y su efecto sobre la inflación. Mientras que para los efectos indirectos se ejecutó utilizando un SVAR bajo la metodología de identificación de SIMS (1980) y la imposición de restricciones estructurales según la teoría económica. El resultado esperado, es demostrar que cambios en el precio de la cotización internacional del petróleo afectará en mayor medida (magnitud, duración e impacto) a la inflación por el canal indirecto, que por el canal directo.The objective of this research is to quantify in terms of duration and impact the effect of shocks in the international price of oil on inflation in Peru for the period 2007-2019. Therefore, a differentiation is made between the direct and indirect effect since the effect on the economy is not only seen in fuel prices, but also in macroeconomic variables considered as control variables (growth of the United States economy, terms of trade, Peru's growth rate, reference rate, and unemployment rate), which further multiply the effect on inflation. The direct effect analysis was developed through a simple OLS regression, which will evaluate changes in the international price of oil on the price of fuels and derivatives and their effect on inflation. While for indirect effects, it is executed using an SVAR under the identification methodology of SIMS (1980) and the imposition of structural restrictions according to economic theory. The expected result is to show that changes in the international price of oil will affect inflation to a greater extent (magnitude, duration, and impact) through the indirect channel than through the direct channel.Tesi

Curso de Especialización en Psicología, ciclo I y II 2022

Con el presente trabajo realizado de acuerdo al curso de especialización en psicología, se ha podido comprobar que dentro de este campo, tanto la entrevista psicológica como las pruebas psicométricas son las herramientas fundamentales; ya que permiten al profesional, obtener información valiosa sobre la personalidad, el funcionamiento cognitivo y emocional de una persona, o cualquier afección que pueda estar experimentando. Existen diferentes tipos de entrevistas psicológicas, cada una con un enfoque y objetivos específicos, y son realizadas por psicólogos y psicólogas cualificadas que utilizan técnicas y estrategias específicas para obtener la información necesaria, que permita ayudar a las personas a comprenderse a sí mismas y a encontrar soluciones a sus problemas. Por lo que, para lograr una adecuada entrevista es necesario establecer una relación psicoterapéutica auténtica que favorezca una relación de confianza y apertura con el individuo, lo que propicie una comunicación más fluida, que minimice el riesgo de engaño en la entrevista y la obtención de información relevante, que tenga como resultado Informes de calidad en los cuales que se respete la objetividad, los derechos y las leyes que rigen el campo de la psicología, pues son una herramienta importante para la investigación y el avance del conocimiento en esta disciplina, y que trae como resultado mayores beneficios para el bienestar psicológico del individuo y para el éxito del tratamiento

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder

Brain multiplexes reveal morphological connectional biomarkers fingerprinting late brain dementia states

Accurate diagnosis of mild cognitive impairment (MCI) before conversion to Alzheimer’s disease (AD) is invaluable for patient treatment. Many works showed that MCI and AD affect functional and structural connections between brain regions as well as the shape of cortical regions. However, ‘shape connections’ between brain regions are rarely investigated -e.g., how morphological attributes such as cortical thickness and sulcal depth of a specific brain region change in relation to morphological attributes in other regions. To fill this gap, we unprecedentedly design morphological brain multiplexes for late MCI/AD classification. Specifically, we use structural T1-w MRI to define morphological brain networks, each quantifying similarity in morphology between different cortical regions for a specific cortical attribute. Then, we define a brain multiplex where each intra-layer represents the morphological connectivity network of a specific cortical attribute, and each inter-layer encodes the similarity between two consecutive intra-layers. A significant performance gain is achieved when using the multiplex architecture in comparison to other conventional network analysis architectures. We also leverage this architecture to discover morphological connectional biomarkers fingerprinting the difference between late MCI and AD stages, which included the right entorhinal cortex and right caudal middle frontal gyrus

Multimodal and Multiscale Deep Neural Networks for the Early Diagnosis of Alzheimer’s Disease using structural MR and FDG-PET images

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease where biomarkers for disease based on pathophysiology may be able to provide objective measures for disease diagnosis and staging. Neuroimaging scans acquired from MRI and metabolism images obtained by FDG-PET provide in-vivo measurements of structure and function (glucose metabolism) in a living brain. It is hypothesized that combining multiple different image modalities providing complementary information could help improve early diagnosis of AD. In this paper, we propose a novel deep-learning-based framework to discriminate individuals with AD utilizing a multimodal and multiscale deep neural network. Our method delivers 82.4% accuracy in identifying the individuals with mild cognitive impairment (MCI) who will convert to AD at 3 years prior to conversion (86.4% combined accuracy for conversion within 1–3 years), a 94.23% sensitivity in classifying individuals with clinical diagnosis of probable AD, and a 86.3% specificity in classifying non-demented controls improving upon results in published literature

The impact of PICALM genetic variations on reserve capacity of posterior cingulate in AD continuum

Phosphatidylinositolbinding clathrin assembly protein (PICALM) gene is one novel genetic player associated with late-onset Alzheimer’s disease (LOAD), based on recent genome wide association studies (GWAS). However, how it affects AD occurrence is still unknown. Brain reserve hypothesis highlights the tolerant capacities of brain as a passive means to fight against neurodegenerations. Here, we took the baseline volume and/or thickness of LOAD-associated brain regions as proxies of brain reserve capacities and investigated whether PICALM genetic variations can influence the baseline reserve capacities and the longitudinal atrophy rate of these specific regions using data from Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset. In mixed population, we found that brain region significantly affected by PICALM genetic variations was majorly restricted to posterior cingulate. In sub-population analysis, we found that one PICALM variation (C allele of rs642949) was associated with larger baseline thickness of posterior cingulate in health. We found seven variations in health and two variations (rs543293 and rs592297) in individuals with mild cognitive impairment were associated with slower atrophy rate of posterior cingulate. Our study provided preliminary evidences supporting that PICALM variations render protections by facilitating reserve capacities of posterior cingulate in non-demented elderly

Conversion Discriminative Analysis on Mild Cognitive Impairment Using Multiple Cortical Features from MR Images

Neuroimaging measurements derived from magnetic resonance imaging provide important information required for detecting changes related to the progression of mild cognitive impairment (MCI). Cortical features and changes play a crucial role in revealing unique anatomical patterns of brain regions, and further differentiate MCI patients from normal states. Four cortical features, namely, gray matter volume, cortical thickness, surface area, and mean curvature, were explored for discriminative analysis among three groups including the stable MCI (sMCI), the converted MCI (cMCI), and the normal control (NC) groups. In this study, 158 subjects (72 NC, 46 sMCI, and 40 cMCI) were selected from the Alzheimer's Disease Neuroimaging Initiative. A sparse-constrained regression model based on the l2-1-norm was introduced to reduce the feature dimensionality and retrieve essential features for the discrimination of the three groups by using a support vector machine (SVM). An optimized strategy of feature addition based on the weight of each feature was adopted for the SVM classifier in order to achieve the best classification performance. The baseline cortical features combined with the longitudinal measurements for 2 years of follow-up data yielded prominent classification results. In particular, the cortical thickness produced a classification with 98.84% accuracy, 97.5% sensitivity, and 100% specificity for the sMCI–cMCI comparison; 92.37% accuracy, 84.78% sensitivity, and 97.22% specificity for the cMCI–NC comparison; and 93.75% accuracy, 92.5% sensitivity, and 94.44% specificity for the sMCI–NC comparison. The best performances obtained by the SVM classifier using the essential features were 5–40% more than those using all of the retained features. The feasibility of the cortical features for the recognition of anatomical patterns was certified; thus, the proposed method has the potential to improve the clinical diagnosis of sub-types of MCI and predict the risk of its conversion to Alzheimer's disease

Early role of vascular dysregulation on late-onset Alzheimer's disease based on multifactorial data-driven analysis

Multifactorial mechanisms underlying late-onset Alzheimer's disease (LOAD) are poorly characterized from an integrative perspective. Here spatiotemporal alterations in brain amyloid-β deposition, metabolism, vascular, functional activity at rest, structural properties, cognitive integrity and peripheral proteins levels are characterized in relation to LOAD progression. We analyse over 7,700 brain images and tens of plasma and cerebrospinal fluid biomarkers from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Through a multifactorial data-driven analysis, we obtain dynamic LOAD–abnormality indices for all biomarkers, and a tentative temporal ordering of disease progression. Imaging results suggest that intra-brain vascular dysregulation is an early pathological event during disease development. Cognitive decline is noticeable from initial LOAD stages, suggesting early memory deficit associated with the primary disease factors. High abnormality levels are also observed for specific proteins associated with the vascular system's integrity. Although still subjected to the sensitivity of the algorithms and biomarkers employed, our results might contribute to the development of preventive therapeutic interventions