923 resultados para Memory in old age


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Background: Soil-transmitted helminth (STH) infections are endemic in Honduras but their impact on children’s health is not well studied. Objectives: To evaluate the prevalence and intensity of STH infections and their association with nutrition and growth in a sample of Honduran children. Methodology: A cross-sectional study was done among Honduran rural school-age children in 2011. Blood and stool samples and anthropometric measurements were obtained to determine nutritional status, STH infection and growth status, respectively. Results: The STH prevalence among 320 studied children was 72.5%. Prevalence by species was 30%, 67% and 16% for Ascaris, Trichuris and 16% hookworms, respectively. High intensity infections were associated with decreased growth scores but regardless of intensity, co-infections negatively affected growth indicators. Conclusions: The health burden of STH infections is related to high parasitic load but also to the presence of low-intensity concurrent infections. The synergistic effects of polyparasitism in underprivileged children warrants more attention.

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Background: Soil-transmitted helminth (STH) infections are endemic in Honduras and efforts are underway to decrease their transmission. However, current evidence is lacking in regards to their prevalence, intensity and their impact on children’s health. Objectives: To evaluate the prevalence and intensity of STH infections and their association with nutritional status in a sample of Honduran children. Methodology: A cross-sectional study was done among school-age children residing in rural communities in Honduras, in 2011. Demographic data was obtained, hemoglobin and protein concentrations were determined in blood samples and STH infections investigated in single-stool samples by Kato-Katz. Anthropometric measurements were taken to calculate heightfor- age (HAZ), BMI-for-age (BAZ) and weight-for-age (WAZ) to determine stunting, thinness and underweight, respectively. Results: Among 320 children studied (48% girls, aged 7–14 years, mean 9.7661.4) an overall STH prevalence of 72.5% was found. Children .10 years of age were generally more infected than 7–10 year-olds (p = 0.015). Prevalence was 30%, 67% and 16% for Ascaris, Trichuris and hookworms, respectively. Moderate-to-heavy infections as well as polyparasitism were common among the infected children (36% and 44%, respectively). Polyparasitism was four times more likely to occur in children attending schools with absent or annual deworming schedules than in pupils attending schools deworming twice a year (p,0.001). Stunting was observed in 5.6% of children and it was associated with increasing age. Also, 2.2% of studied children were thin, 1.3% underweight and 2.2% had anemia. Moderate-to-heavy infections and polyparasitism were significantly associated with decreased values in WAZ and marginally associated with decreased values in HAZ. Conclusions: STH infections remain a public health concern in Honduras and despite current efforts were highly prevalent in the studied community. The role of multiparasite STH infections in undermining children’s nutritional status warrants more research.

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This research project explored the connection between working memory and children’s learning. The project created a resource titled Working Memory Strategies for the Junior/ Intermediate Educator: A Handbook based on a literature review, the deconstruction of theoretical and empirical studies, teacher resources, and findings from a needs assessment completed by teachers that together show there is insufficient support for teachers working with students who have deficits in working memory along with other common classroom learning disabilities. As learning disabilities become more common in the classroom that increasingly affect working memory in a majority of cases, teachers must be prepared not only to address specific symptoms of the conditions, but also to help students learn how to navigate and become aware of their working memory ability. The handbook thus was developed as a useful resource for teachers looking to expand their knowledge about how learning occurs. A needs assessment completed by junior and intermediate division teachers in Ontario helped determine what educators found most important for inclusion in the handbook, and the same teachers were offered the opportunity to review the completed handbook. Teacher participants provided constructive feedback and indicated that the handbook would be a valuable resource for them and their colleagues when working with students who have working memory issues. It was suggested that the handbook would be useful when creating students’ Individual Education Plans and that the assessment checklist included in the handbook would be an excellent resource for teachers collecting data regarding students’ working memory and ability to learn.

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Ma thèse de doctorat, In the Circle: Jazz Griots and the Mapping of African American Cultural History in Poetry, étudie la façon dont les poètes afro-américains des années 1960 et 1970, Langston Hughes, David Henderson, Sonia Sanchez, et Amiri Baraka, emploient le jazz afin d’ancrer leur poésie dans la tradition de performance. Ce faisant, chacun de ces poètes démontre comment la culture noire, en conceptualisant à travers la performance des modes de résistance, fût utilisée par les peuples de descendance africaine pour contrer le racisme institutionnalisé et les discours discriminatoires. Donc, pour les fins de cette thèse, je me concentre sur quatre poètes engagés dans des dialogues poétiques avec la musicologie, l’esthétique, et la politique afro-américaines des années 1960 et 1970. Ces poètes affirment la centralité de la performativité littéraire noire afin d’assurer la survie et la continuité de la mémoire culturelle collective des afro-américains. De plus, mon argument est que la théorisation de l’art afro-américain comme engagement politique devient un élément central à l’élaboration d’une esthétique noire basée sur la performance. Ma thèse de doctorat propose donc une analyse originale des ces quatre poètes qui infusent leur poèmes avec des références au jazz et à la politique dans le but de rééduquer les générations des années 2000 en ce qui concerne leur mémoire collective.

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En analysant les processus dialectiques par lesquels l’art repense le passé, Between Truth and Trauma : The Work of Art and Memory work in Adorno traite du concept adornien de la mémoire. Je postule que l’œuvre d’art chez Adorno incarne un Zeitkern (noyau temporel). Je démontrerai que l’immanence réciproque de l’histoire dans l’œuvre d’art et l’immanence de l’œuvre d’art dans l’histoire permettent de repenser le passé. Le premier chapitre examine la manière par laquelle le passé est préservé et nié par l’œuvre d’art. Le deuxième chapitre montre comment, à l’aide du processus interprétatif, le passé est transcendé à travers l’œuvre d’art. Le dernier chapitre évoque la lecture adornienne d’écrits de Brecht et de Beckett dans le but d’illustrer la capacité de l’œuvre d’art à naviguer entre la vérité et le trauma.

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Semantic deficits have been documented in the prodromal phase of Alzheimer’s disease, but it is unclear whether these deficits are associated with non-cognitive manifestations. For instance, recent evidence indicates that cognitive deficits in elders with amnestic mild cognitive impairment (aMCI) are modulated by concomitant depressive symptoms. The purposes of this study were to (i) investigate if semantic memory impairment in aMCI is modulated according to the presence (aMCI-D group) or absence (aMCI group) of depressive symptoms, and (ii) compare semantic memory performance of aMCI and aMCI-D groups to that of patients with late-life depression (LLD). Seventeen aMCI, 16 aMCI-D, 15 LLD, and 26 healthy control participants were administered a semantic questionnaire assessing famous person knowledge. Results showed that performance of aMCI-D patients was impaired compared to the control and LLD groups. However, in the aMCI group performance was comparable to that of all other groups. Overall, these findings suggest that semantic deficits in aMCI are somewhat associated with the presence of concomitant depressive symptoms. However, depression alone cannot account solely for the semantic deficits since LLD patients showed no semantic memory impairment in this study. Future studies should aim at clarifying the association between depression and semantic deficits in older adults meeting aMCI criteria.

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Learning Disability (LD) is a general term that describes specific kinds of learning problems. It is a neurological condition that affects a child's brain and impairs his ability to carry out one or many specific tasks. The learning disabled children are neither slow nor mentally retarded. This disorder can make it problematic for a child to learn as quickly or in the same way as some child who isn't affected by a learning disability. An affected child can have normal or above average intelligence. They may have difficulty paying attention, with reading or letter recognition, or with mathematics. It does not mean that children who have learning disabilities are less intelligent. In fact, many children who have learning disabilities are more intelligent than an average child. Learning disabilities vary from child to child. One child with LD may not have the same kind of learning problems as another child with LD. There is no cure for learning disabilities and they are life-long. However, children with LD can be high achievers and can be taught ways to get around the learning disability. In this research work, data mining using machine learning techniques are used to analyze the symptoms of LD, establish interrelationships between them and evaluate the relative importance of these symptoms. To increase the diagnostic accuracy of learning disability prediction, a knowledge based tool based on statistical machine learning or data mining techniques, with high accuracy,according to the knowledge obtained from the clinical information, is proposed. The basic idea of the developed knowledge based tool is to increase the accuracy of the learning disability assessment and reduce the time used for the same. Different statistical machine learning techniques in data mining are used in the study. Identifying the important parameters of LD prediction using the data mining techniques, identifying the hidden relationship between the symptoms of LD and estimating the relative significance of each symptoms of LD are also the parts of the objectives of this research work. The developed tool has many advantages compared to the traditional methods of using check lists in determination of learning disabilities. For improving the performance of various classifiers, we developed some preprocessing methods for the LD prediction system. A new system based on fuzzy and rough set models are also developed for LD prediction. Here also the importance of pre-processing is studied. A Graphical User Interface (GUI) is designed for developing an integrated knowledge based tool for prediction of LD as well as its degree. The designed tool stores the details of the children in the student database and retrieves their LD report as and when required. The present study undoubtedly proves the effectiveness of the tool developed based on various machine learning techniques. It also identifies the important parameters of LD and accurately predicts the learning disability in school age children. This thesis makes several major contributions in technical, general and social areas. The results are found very beneficial to the parents, teachers and the institutions. They are able to diagnose the child’s problem at an early stage and can go for the proper treatments/counseling at the correct time so as to avoid the academic and social losses.

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This paper highlights the prediction of learning disabilities (LD) in school-age children using rough set theory (RST) with an emphasis on application of data mining. In rough sets, data analysis start from a data table called an information system, which contains data about objects of interest, characterized in terms of attributes. These attributes consist of the properties of learning disabilities. By finding the relationship between these attributes, the redundant attributes can be eliminated and core attributes determined. Also, rule mining is performed in rough sets using the algorithm LEM1. The prediction of LD is accurately done by using Rosetta, the rough set tool kit for analysis of data. The result obtained from this study is compared with the output of a similar study conducted by us using Support Vector Machine (SVM) with Sequential Minimal Optimisation (SMO) algorithm. It is found that, using the concepts of reduct and global covering, we can easily predict the learning disabilities in children

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This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

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Learning Disability (LD) is a classification including several disorders in which a child has difficulty in learning in a typical manner, usually caused by an unknown factor or factors. LD affects about 15% of children enrolled in schools. The prediction of learning disability is a complicated task since the identification of LD from diverse features or signs is a complicated problem. There is no cure for learning disabilities and they are life-long. The problems of children with specific learning disabilities have been a cause of concern to parents and teachers for some time. The aim of this paper is to develop a new algorithm for imputing missing values and to determine the significance of the missing value imputation method and dimensionality reduction method in the performance of fuzzy and neuro fuzzy classifiers with specific emphasis on prediction of learning disabilities in school age children. In the basic assessment method for prediction of LD, checklists are generally used and the data cases thus collected fully depends on the mood of children and may have also contain redundant as well as missing values. Therefore, in this study, we are proposing a new algorithm, viz. the correlation based new algorithm for imputing the missing values and Principal Component Analysis (PCA) for reducing the irrelevant attributes. After the study, it is found that, the preprocessing methods applied by us improves the quality of data and thereby increases the accuracy of the classifiers. The system is implemented in Math works Software Mat Lab 7.10. The results obtained from this study have illustrated that the developed missing value imputation method is very good contribution in prediction system and is capable of improving the performance of a classifier.

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El objetivo principal de este estudio es conocer la concordancia entre informantes, padres y maestros, en cada una de las dimensiones o categorías diagnósticas del Early Childhood Inventory-4 (ECI-4). Además, se pretende analizar la influencia de la presencia de problemas de salud en los padres en la descripción y valoración de la conducta de una muestra de 204 alumnos de preescolar (3 a 6 años) de perfiles socioeconómicos diferentes. Los resultados indican que los padres tienden a valorar con mayor severidad los síntomas, observándose una mayor concordancia entre informantes en los relativos a los trastornos del desarrollo

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This study assessed visual working memory through Memonum computerized test in schoolchildren. The effects of three exposure times (1, 4 and 8 seconds) have been evaluated, and the presentation of a distractor on the mnemonic performance in the test Memonum in 72 children from a college in the metropolitan area of Bucaramanga, Colombia, aged between 8 and 11 in grades third, fourth and fifth grade. It has been found significant difference regarding the exposure time in the variables number of hits and successes accumulated, showing a better mnemonic performance in participants who took the test during 8 seconds compared to children who took the test during 1 second; in addition, the presence of a distractor showed a significant difference regarding the strengths and successes accumulated. Such distractor is considered a stimulus generator interference that disrupts the storage capacity of working memory in children. Additionally, a significant difference was found with respect to the use of mental rehearsal strategy, indicating that participants who took the test in 4 and 8 seconds, respectively, assigned higher scores than children who took the test in 1 second. A long exposure time to stimuli during Memonum test increases the holding capacity. Also, the use of a distractor affects the storage capacity and this, at the same time, increases the school progression due to the use of mnemonic strategies that children use to ensure the memory of the numerical series

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