318 research outputs found
Dimensionamento Otimizado de Vigas Alveolares de Aço
Vigas alveolares são elementos estruturais, obtidos por meio de corte em ziguezague de perfis laminados. As partes são deslocadas e soldadas novamente de forma a obter perfis com maior altura sem aumento de peso. As aberturas, acompanhadas do acréscimo da altura útil do perfil, tornam esse tipo de viga suscetível a novos modos de colapso, bem como potencializa modos de colapso já existentes. O presente trabalho propõe uma formulação para o dimensionamento otimizado de vigas alveolares de aço, utilizando as equações desenvolvidas por Cimadevilla (2000), Abreu (2011), Silveira (2011) e Veríssimo et al. (2012), levando em consideração as restrições de geometria estabelecidas por Oliveira (2012). A validação do programa de computador desenvolvido foi realizada a partir da comparação com os resultados obtidos através de exemplos resolvidos manualmente utilizando como base a formulação descrita por Veríssimo et al. (2012), uma vez que a norma brasileira não define os parâmetros de dimensionamento para vigas alveolares. O programa foi desenvolvido na plataforma do Matlab, e para a solução dos problemas de otimização foram utilizados os algoritmos internos do Matlab, tais como pontos interiores, programação quadrática e algoritmos genéticos. Exemplos iniciais apontam que o dimensionamento pode ser melhorado e no caso de fabricação de perfil uma nova linha de corte pode ser definida.
Palavras Chave: Dimensionamento. Vigas alveolares. Otimização. Estruturas de aço
A Novel Document Generation Process for Topic Detection based on Hierarchical Latent Tree Models
We propose a novel document generation process based on hierarchical latent
tree models (HLTMs) learned from data. An HLTM has a layer of observed word
variables at the bottom and multiple layers of latent variables on top. For
each document, we first sample values for the latent variables layer by layer
via logic sampling, then draw relative frequencies for the words conditioned on
the values of the latent variables, and finally generate words for the document
using the relative word frequencies. The motivation for the work is to take
word counts into consideration with HLTMs. In comparison with LDA-based
hierarchical document generation processes, the new process achieves
drastically better model fit with much fewer parameters. It also yields more
meaningful topics and topic hierarchies. It is the new state-of-the-art for the
hierarchical topic detection
Multiple Deprivation, Severity and Latent Sub-Groups:Advantages of Factor Mixture Modelling for Analysing Material Deprivation
Material deprivation is represented in different forms and manifestations. Two individuals with the same deprivation score (i.e. number of deprivations), for instance, are likely to be unable to afford or access entirely or partially different sets of goods and services, while one individual may fail to purchase clothes and consumer durables and another one may lack access to healthcare and be deprived of adequate housing . As such, the number of possible patterns or combinations of multiple deprivation become increasingly complex for a higher number of indicators. Given this difficulty, there is interest in poverty research in understanding multiple deprivation, as this analysis might lead to the identification of meaningful population sub-groups that could be the subjects of specific policies. This article applies a factor mixture model (FMM) to a real dataset and discusses its conceptual and empirical advantages and disadvantages with respect to other methods that have been used in poverty research . The exercise suggests that FMM is based on more sensible assumptions (i.e. deprivation covary within each class), provides valuable information with which to understand multiple deprivation and is useful to understand severity of deprivation and the additive properties of deprivation indicators
Landsat Program
Landsat initiated the revolution in moderate resolution Earth remote sensing in the 1970s. With seven successful missions over 40+ years, Landsat has documented - and continues to document - the global Earth land surface and its evolution. The Landsat missions and sensors have evolved along with the technology from a demonstration project in the analog world of visual interpretation to an operational mission in the digital world, with incremental improvements along the way in terms of spectral, spatial, radiometric and geometric performance as well as acquisition strategy, data availability, and products
Evaluation of POSSUM scoring system in patients with gastric cancer undergoing D2-gastrectomy
BACKGROUND: Risk adjustment and stratification play an important role in quality assurance and in clinical research. The Physiological and Operative Severity Score for the enUmeration of Mortality and morbidity (POSSUM) is a patient risk prediction model based on 12 patient characteristics and 6 characteristics of the surgery performed. However, because the POSSUM was developed for quality assessment in general surgical units, its performance within specific subgroups still requires evaluation. The aim of the present study was to assess the accuracy of POSSUM in predicting mortality and morbidity in patients with gastric cancer undergoing D2-gastrectomy. METHODS: 137 patients with gastric cancer undergoing gastrectomy were included in this study. Detailed, standardized risk assessments and thorough documentation of the post-operative courses were performed prospectively, and the POSSUM scores were then calculated. RESULTS: The 30- and 90- day mortality rates were 3.6% (n = 5) and 5.8% (n = 8), respectively. 65.7% (n = 90) of patients had normal postoperative courses without major complications, 14.6% (n = 20) had moderate and 13.9% (n = 19) had severe complications. The number of mortalities predicted by the POSSUM-Mortality Risk Score (R1) was double the actual number of mortalities occurring in the median and high-risk groups, and was more than eight times the actual number of mortalities occurring in the low-risk group (R1 < 20%). However, the calculated R1 predicted rather well in terms of severe morbidity or post-operative death in each risk group: in predicted low risk patients the actual occurrence rate (AR) of severe morbidity or post-operative death was 14%, for predicted medium risk patients the AR was 23%, and for predicted high risk patients the AR was 50% (p < 0.05). The POSSUM-Morbidity Risk Score (R2) overestimated the risk of morbidity. CONCLUSION: The POSSUM Score may be beneficial and can be used for assessment of the peri- and post-operative courses of patients with gastric carcinoma undergoing D2-gastrectomy. However, none of the scores examined here are useful for preoperative prediction of postoperative course
Genetics of callous-unemotional behavior in children
Callous-unemotional behavior (CU) is currently under consideration as a subtyping index for conduct disorder diagnosis. Twin studies routinely estimate the heritability of CU as greater than 50%. It is now possible to estimate genetic influence using DNA alone from samples of unrelated individuals, not relying on the assumptions of the twin method. Here we use this new DNA method (implemented in a software package called Genome-wide Complex Trait Analysis, GCTA) for the first time to estimate genetic influence on CU. We also report the first genome-wide association (GWA) study of CU as a quantitative trait. We compare these DNA results to those from twin analyses using the same measure and the same community sample of 2,930 children rated by their teachers at ages 7, 9 and 12. GCTA estimates of heritability were near zero, even though twin analysis of CU in this sample confirmed the high heritability of CU reported in the literature, and even though GCTA estimates of heritability were substantial for cognitive and anthropological traits in this sample. No significant associations were found in GWA analysis, which, like GCTA, only detects additive effects of common DNA variants. The phrase ‘missing heritability’ was coined to refer to the gap between variance associated with DNA variants identified in GWA studies versus twin study heritability. However, GCTA heritability, not twin study heritability, is the ceiling for GWA studies because both GCTA and GWA are limited to the overall additive effects of common DNA variants, whereas twin studies are not. This GCTA ceiling is very low for CU in our study, despite its high twin study heritability estimate. The gap between GCTA and twin study heritabilities will make it challenging to identify genes responsible for the heritability of CU
Assessing the presence of shared genetic architecture between Alzheimer's disease and major depressive disorder using genome-wide association data
We are grateful to the families and individuals who took part in the GS:SFHS and UKB studies, and to all those involved in participant recruitment, data collection, sample processing and QC, including academic researchers, clinical staff, laboratory technicians, clerical workers, IT staff, statisticians and research managers. This work is supported by the Wellcome Trust through a Strategic Award, reference 104036/Z/ 14/Z. We acknowledge with gratitude the financial support received from the Dr Mortimer and Theresa Sackler Foundation. This research has been conducted using the GS:SFHS and UK Biobank (project #4844) resources. GS:SFHS received core funding from the Chief Scientist Office of the Scottish Government Health Directorates [CZD/16/6] and the Scottish Funding Council [HR03006]. UKB was established using funding from the Wellcome Trust, Medical Research Council, the Scottish Government Department of Health, and the Northwest Regional Development Agency. DJP, IJD, TCR and AMM are members of the University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1). TCR is supported by Alzheimer's Scotland, through the Marjorie MacBeath bequest. Funding from the Biotechnology and Biological Sciences Research Council and Medical Research Council is gratefully acknowledged. We are grateful for the use of summary data from the International Genomics of Alzheimer's Project and the Major Depressive Disorder working group of the Psychiatric Genomics Consortium.Peer reviewedPublisher PD
Simultaneous Determination of Various Isothiocyanates by RP-LC Following Precolumn Derivatization with Mercaptoethanol
Numerous isothiocyanates (ITCs) are poorly soluble in water which causes their precipitation in aqueous mobile phases used in reversed phase liquid chromatography (RP-LC), thus impacting the accuracy of the quantification. By comparing the amounts of ITCs injected and released from the column, losses could be estimated at 5–32% depending on polarities and concentrations. Results could be dramatically improved in terms of separation and quantification using RP-LC with a mercaptoethanol precolumn derivatization aimed at avoiding ITCs precipitation. The cancer chemoprotective allyl-ITC and sulforaphane were found in cabbage extracts at 1.2 and 2.7 μg g−1 fresh weight, respectively
Recent advances in understanding Cushing disease: resistance to glucocorticoid negative feedback and somatic USP8 mutations
Cushing’s disease is a rare disease with a characteristic phenotype due to significant hypercortisolism driven by over-secretion of adrenocorticotropic hormone and to high morbidity and mortality if untreated. It is caused by a corticotroph adenoma of the pituitary, but the exact mechanisms leading to tumorigenesis are not clear. Recent advances in molecular biology such as the discovery of somatic mutations of the ubiquitin-specific peptidase 8 (USP8) gene allow new insights into the pathogenesis, which could be translated into exciting and much-needed therapeutic applications
Epidemiology and heritability of Major Depressive Disorder, stratified by age of onset, sex, and illness course in Generation Scotland:Scottish Family Health Study (GS:SFHS)
The heritability of Major Depressive Disorder (MDD) has been estimated at 37% based largely on twin studies that rely on contested assumptions. More recently, the heritability of MDD has been estimated on large populations from registries such as the Swedish, Finnish, and Chinese cohorts. Family-based designs utilise a number of different relationships and provide an alternative means of estimating heritability. Generation Scotland: Scottish Family Health Study (GS:SFHS) is a large (n = 20,198), family-based population study designed to identify the genetic determinants of common diseases, including Major Depressive Disorder. Two thousand seven hundred and six individuals were SCID diagnosed with MDD, 13.5% of the cohort, from which we inferred a population prevalence of 12.2% (95% credible interval: 11.4% to 13.1%). Increased risk of MDD was associated with being female, unemployed due to a disability, current smokers, former drinkers, and living in areas of greater social deprivation. The heritability of MDD in GS:SFHS was between 28% and 44%, estimated from a pedigree model. The genetic correlation of MDD between sexes, age of onset, and illness course were examined and showed strong genetic correlations. The genetic correlation between males and females with MDD was 0.75 (0.43 to 0.99); between earlier (≤ age 40) and later (> age 40) onset was 0.85 (0.66 to 0.98); and between single and recurrent episodic illness course was 0.87 (0.72 to 0.98). We found that the heritability of recurrent MDD illness course was significantly greater than the heritability of single MDD illness course. The study confirms a moderate genetic contribution to depression, with a small contribution of the common family environment (variance proportion = 0.07, CI: 0.01 to 0.15), and supports the relationship of MDD with previously identified risk factors. This study did not find robust support for genetic differences in MDD due to sex, age of onset, or illness course. However, we found an intriguing difference in heritability between recurrent and single MDD illness course. These findings establish GS:SFHS as a valuable cohort for the genetic investigation of MDD
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