Did Brisbane grow smartly? Drivers of city growth 1991-2001 and lessons for current policies

Urban areas are growing unsustainably around the world; however, the growth patterns and their associated drivers vary between contexts. As a result, research has highlighted the need to adopt case study based approaches to stimulate the development of new theoretic understandings. Using land-cover data sets derived from Landsat images (30 m × 30 m), this research identifies both patterns and drivers of urban growth in a period (1991-2001) when a number of policy acts were enacted aimed at fostering smart growth in Brisbane, Australia. A linear multiple regression model was estimated using the proportion of lands that were converted from non-built-up (1991) to built-up usage (2001) within a suburb as a dependent variable to identify significant drivers of land-cover changes. In addition, the hot spot analysis was conducted to identify spatial biases of land-cover changes, if any. Results show that the built-up areas increased by 1.34% every year. About 19.56% of the non-built-up lands in 1991 were converted into built-up lands in 2001. This conversion pattern was significantly biased in the northernmost and southernmost suburbs in the city. This is due to the fact that, as evident from the regression analysis, these suburbs experienced a higher rate of population growth, and had the availability of habitable green field sites in relatively flat lands. The above findings suggest that the policy interventions undertaken between the periods were not as effective in promoting sustainable changes in the environment as they were aimed for.

Níveis circulantes de Grelina, índices de adiposidade e fatores de risco cardiovascular e metabólico relacionados, em população multiétnica do Estado do Rio de Janeiro

O objetivo deste estudo foi analisar o comportamento dos níveis plasmáticos de grelina, em relação aos fatores de risco cardiometabólico, em uma população multiétnica de eutróficos e de obesos..A grelina é um peptídeo produzido predominantemente pelas células oxínticas gástricas, que desempenha importante papel na homeostase energética, promovendo estímulo do apetite e aumento do peso corporal, além de participar do controle do metabolismo lipídico e glicídico, interagindo diretamente com os fatores de risco cardiometabólico. Este é um estudo transversal. Duzentos indivíduos entre 18 e 60 anos com diferentes graus de índice de massa corporal (IMC) compuseram a amostra, assim dividida: cem eutróficos (IMC < 25 kg/m2) e 100 obesos (IMC ≥ 30 kg/m2). Todos foram avaliados para parâmetros antropométricos, determinação da pressão arterial (aferida por método oscilométrico através de monitor automático) e variáveis metabólicas (métodos usuais certificados). A grelina acilada foi mensurada pela técnica de sanduíche ELISA; a leptina, pelo método Milliplex MAP. O marcador inflamatório proteína C reativa ultrassensível(PCRUS)foi estimado por nefelometria ultrassensível. A insulina foi determinada por quimioluminescência e o HOMA-IR calculado pelo produto insulinemia (U/ml) X níveis de glicemia de jejum (mmol/L) / 22.5. Foram excluídos do estudo aqueles com história de comorbidades crônicas, doenças inflamatórias agudas, dependência de drogas e em uso de medicação nos dez dias anteriores à entrada no estudo. As concentrações de grelina acilada mostraram tendência de redução ao longo dos graus de adiposidade (P<0,001); a leptina se comportou de maneira oposta (P<0,001). Os níveis de grelina se correlacionaram negativamente com IMC (r = -.36; P<0,001), circunferência da cintura (CC) (r=-.34; P<0,001), relação cintura/quadril (RCQ) (r=-.22; P=0,001), diâmetro abdominal sagital (DAS) (r=-.28; P<0,001), pressão arterial sistólica (PAS) (r=-.21; P=0,001), insulina (r=-.27; P<0,001), HOMA-IR (r=-.24; P=0,001) e PCRUS (r=-.29; P<0,001); e positivamente com o HDL-colesterol (r=.30; P<0,001).A PCRUS acompanhou o grau de resistência insulínica e os níveis de grelina também mostraram tendência de redução ao longo dos tercis de resistência insulínica (P=0,001). Em modelo de regressão linear múltipla as principais associações independentes da grelina acilada foram sexo feminino (P=0,005) e HDL-colesterol (P=0,008), ambos com associação positiva e IMC (P<0,001) (associação negativa). Esses achados apontam para uma associação da grelina acilada com melhor perfil metabólico, já que seus níveis se correlacionaram positivamente com HDL-colesterol e negativamente com indicadores de resistência insulínica e atividade inflamatória.

An efficient feature selection method for mobile devices with application to activity recognition

This paper presents a feature selection method for data classification, which combines a model-based variable selection technique and a fast two-stage subset selection algorithm. The relationship between a specified (and complete) set of candidate features and the class label is modelled using a non-linear full regression model which is linear-in-the-parameters. The performance of a sub-model measured by the sum of the squared-errors (SSE) is used to score the informativeness of the subset of features involved in the sub-model. The two-stage subset selection algorithm approaches a solution sub-model with the SSE being locally minimized. The features involved in the solution sub-model are selected as inputs to support vector machines (SVMs) for classification. The memory requirement of this algorithm is independent of the number of training patterns. This property makes this method suitable for applications executed in mobile devices where physical RAM memory is very limited. An application was developed for activity recognition, which implements the proposed feature selection algorithm and an SVM training procedure. Experiments are carried out with the application running on a PDA for human activity recognition using accelerometer data. A comparison with an information gain based feature selection method demonstrates the effectiveness and efficiency of the proposed algorithm.

Interaction between FTO gene variants and lifestyle factors on metabolic traits in an Asian Indian population

Background Lifestyle factors such as diet and physical activity have been shown to modify the association between fat mass and obesity–associated (FTO) gene variants and metabolic traits in several populations; however, there are no gene-lifestyle interaction studies, to date, among Asian Indians living in India. In this study, we examined whether dietary factors and physical activity modified the association between two FTO single nucleotide polymorphisms (rs8050136 and rs11076023) (SNPs) and obesity traits and type 2 diabetes (T2D). Methods The study included 734 unrelated T2D and 884 normal glucose-tolerant (NGT) participants randomly selected from the urban component of the Chennai Urban Rural Epidemiology Study (CURES). Dietary intakes were assessed using a validated interviewer administered semi-quantitative food frequency questionnaire (FFQ). Physical activity was based upon the self-report. Interaction analyses were performed by including the interaction terms in the linear/logistic regression model. Results There was a significant interaction between SNP rs8050136 and carbohydrate intake (% energy) (Pinteraction = 0.04), where the ‘A’ allele carriers had 2.46 times increased risk of obesity than those with ‘CC’ genotype (P = 3.0 × 10−5) among individuals in the highest tertile of carbohydrate intake (% energy, 71 %). A significant interaction was also observed between SNP rs11076023 and dietary fibre intake (Pinteraction = 0.0008), where individuals with AA genotype who are in the 3rd tertile of dietary fibre intake had 1.62 cm lower waist circumference than those with ‘T’ allele carriers (P = 0.02). Furthermore, among those who were physically inactive, the ‘A’ allele carriers of the SNP rs8050136 had 1.89 times increased risk of obesity than those with ‘CC’ genotype (P = 4.0 × 10−5). Conclusions This is the first study to provide evidence for a gene-diet and gene-physical activity interaction on obesity and T2D in an Asian Indian population. Our findings suggest that the association between FTO SNPs and obesity might be influenced by carbohydrate and dietary fibre intake and physical inactivity. Further understanding of how FTO gene influences obesity and T2D through dietary and exercise interventions is warranted to advance the development of behavioral intervention and personalised lifestyle strategies, which could reduce the risk of metabolic diseases in this Asian Indian population.

Relevância do estado de hidratação na interpretação de parâmetros nutricionais em diálise peritoneal

OBJETIVO: Identificar determinantes do estado de hidratação de pacientes em diálise peritoneal crônica, bem como investigar os efeitos da sobrecarga líquida sobre o estado nutricional. MÉTODOS: Foi feito estudo transversal, realizado em 2006, avaliando 27 pacientes em diálise peritoneal crônica, acompanhados no Hospital das Clínicas da Faculdade de Medicina de Botucatu (SP), quanto a parâmetros clínicos, dialíticos, laboratoriais, antropométricos e de bioimpedância elétrica. Para avaliar a influência de parâmetros sobre o estado de hidratação empregou-se modelo de regressão linear múltipla. A amostra foi estratificada quanto ao estado de hidratação pela relação entre água extracelular e água corporal total (0,47 para homens e 0,52 para mulheres), parâmetros obtidos por meio de bioimpedância elétrica. Comparações foram realizadas por análise de covariância, Mann-Whitney, Qui-quadrado ou teste exato de Fisher. Considerou-se significância estatística quando p≤0,05. RESULTADOS: Pacientes com maior volume urinário e em modalidade dialítica automatizada apresentaram melhor estado de hidratação. Pacientes com maior sobrecarga líquida, comparados àqueles com menor sobrecarga, apresentaram menor ângulo de fase (M=4,2, DP=0,9 vs M=5,7, DP=0,7º; p=0,006), menor albumina (M=3,06, DP=0,46 vs M=3,55, DP=0,52g/dL; p=0,05) e maior % prega cutânea tricipital (M=75,3, DP=36,9 vs M=92,1, DP=56,9%; p=0,058), sem outras evidências antropométricas. CONCLUSÃO: Pode-se sugerir que os níveis reduzidos de albumina e ângulo de fase nos pacientes com maior sobrecarga líquida não estiveram relacionados a pior estado nutricional. Para o diagnóstico nutricional em vigência de sobrecarga líquida, deve-se considerar o conjunto de variáveis obtidas por diversos métodos, buscando relacioná-las e interpretá-las de maneira abrangente, possibilitando um diagnóstico nutricional fidedigno.

Prevalência de sintomas ansiosos e depressivos em pacientes acompanhados em Ambulatório de Cuidados Paliatiovos do Hospital das Clínicas da Faculdade de Medicina de Botucatu

Pós-graduação em Saúde Coletiva - FMB

Efeitos da exposição aos poluentes do ar com base nas internações por doenças cardiovasculares e respiratórias no município de Taubaté, SP

Pós-graduação em Engenharia Civil e Ambiental - FEB

Development and validation of energy expenditure prediction models based on GT3X accelerometer data in 5- to 9-year-old children

Background: Accelerometry has been established as an objective method that can be used to assess physical activity behavior in large groups. The purpose of the current study was to provide a validated equation to translate accelerometer counts of the triaxial GT3X into energy expenditure in young children. Methods: Thirty-two children aged 5–9 years performed locomotor and play activities that are typical for their age group. Children wore a GT3X accelerometer and their energy expenditure was measured with indirect calorimetry. Twenty-one children were randomly selected to serve as development group. A cubic 2-regression model involving separate equations for locomotor and play activities was developed on the basis of model fit. It was then validated using data of the remaining children and compared with a linear 2-regression model and a linear 1-regression model. Results: All 3 regression models produced strong correlations between predicted and measured MET values. Agreement was acceptable for the cubic model and good for both linear regression approaches. Conclusions: The current linear 1-regression model provides valid estimates of energy expenditure for ActiGraph GT3X data for 5- to 9-year-old children and shows equal or better predictive validity than a cubic or a linear 2-regression model.

The impact of a child's unexpected hospitalization upon Taiwanese parents' situational anxiety

Background. The parents of a sick child likely experience situational anxiety due to their young child being unexpectedly hospitalized. The emotional upheaval may be great enough that their anxiety inhibits them in providing positive support to their hospitalized child. Because anxiety affects psychological distress as well as behavioral distress, identifying parental distress helps parents improving their coping mechanisms. ^ Purpose. The study compared situational anxiety levels between Taiwanese fathers and mothers and focused on differences between parental anxiety levels at the beginning of the child's unplanned hospitalization and at time of discharge. The study also identified factors related to the parents' distress and use of coping mechanisms. ^ Methods. A descriptive, comparative research design was used to determine the difference between the anxiety levels of 62 Taiwanese father-mother dyads during the situational crisis of their child's unexpected hospitalization. The Mandarin version (M) of Visual Analog Scale (VAS-M), State-Trait Anxiety Inventory (STAI-M), and the Index of Parent Participation/Hospitalized Child (IPP/HC-M) were used to differentiate maternal and paternal anxiety levels and identify factors related to the parents' distress. Questionnaires were completed by parents within 24-36 hours of the child's hospital admission and within 24 hours prior to discharge. A paired t-test, two sample t-test, and linear mixed regression model were used to test and support the study hypothesis. ^ Results. The findings reveal that the mothers' anxiety levels did not significantly differ from the fathers' anxiety level when their child had a sudden admission to the hospital. In particular, parental state anxiety levels did not decrease during the child's hospital stay and subsequent discharge. Moreover, anxiety levels did not differ between parents regardless of whether the child's disease was acute or chronic. The most effective factor related to parental situational anxiety was parental perception of the severity of the child's illness. ^ Conclusions. Parental anxiety was found to be significantly related to changes in their perception of the severity of their child's illness. However, the study was not able to illustrate how parental involvement in the child's hospital care was related to parental perception of the severity of their child's illness. Future studies, using a qualitative approach to gamer more information as to what variables influence parental anxiety during a situational crisis, may provide a richer database from which to modify key variables as well as the instruments used to improve the quality of the data obtained. ^

The net benefit of saving the Asian elephant: a policy and contingent valuation study

Reports results from a contingent valuation (CV) survey of willingness to pay (WTP) for the conservation of the Asian elephant of a sample of urban residents living in three selected housing schemes in Colombo, the capital of Sri Lanka. Face-to-face surveys were conducted using an interview schedule (IS). A non-linear logit regression model is used to analyse the respondents' responses for the payment principle questions and to identify the factors that influence their responses. We investigate whether urban residents' WTP for the conservation of elephants is sufficient to compensate farmers for the damage caused by elephants. We find that the beneficiaries (the urban residents) could compensate losers (the fanners in the areas affected by human-elephant conflict, HEC) and be better off than in the absence of elephants in Sri Lanka. Therefore, there is a strong economic case for the conservation of the wild elephant population in Sri Lanka. However, we have insufficient data to determine the optimal level of this elephant population in the Kaldor-Hicks sense. Nevertheless, the current population of elephant in Sri Lanka is Kaldor-Hicks preferable to having none. (C) 2003 Elsevier B.V. All rights reserved.

Linear regression under fixed-rank constraints: A Riemannian approach

In this paper, we tackle the problem of learning a linear regression model whose parameter is a fixed-rank matrix. We study the Riemannian manifold geometry of the set of fixed-rank matrices and develop efficient line-search algorithms. The proposed algorithms have many applications, scale to high-dimensional problems, enjoy local convergence properties and confer a geometric basis to recent contributions on learning fixed-rank matrices. Numerical experiments on benchmarks suggest that the proposed algorithms compete with the state-of-the-art, and that manifold optimization offers a versatile framework for the design of rank-constrained machine learning algorithms. Copyright 2011 by the author(s)/owner(s).

Regression on fixed-rank positive semidefinite matrices: A Riemannian approach

The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space and on scalability to high-dimensional problems. The mathematical developments rely on the theory of gradient descent algorithms adapted to the Riemannian geometry that underlies the set of fixedrank positive semidefinite matrices. In contrast with previous contributions in the literature, no restrictions are imposed on the range space of the learned matrix. The resulting algorithms maintain a linear complexity in the problem size and enjoy important invariance properties. We apply the proposed algorithms to the problem of learning a distance function parameterized by a positive semidefinite matrix. Good performance is observed on classical benchmarks. © 2011 Gilles Meyer, Silvere Bonnabel and Rodolphe Sepulchre.

Random regression models using Legendre polynomials or linear splines for test-day milk yield of dairy Gyr (Bos indicus) cattle

Studies investigating the use of random regression models for genetic evaluation of milk production in Zebu cattle are scarce. In this study, 59,744 test-day milk yield records from 7,810 first lactations of purebred dairy Gyr (Bos indicus) and crossbred (dairy Gyr × Holstein) cows were used to compare random regression models in which additive genetic and permanent environmental effects were modeled using orthogonal Legendre polynomials or linear spline functions. Residual variances were modeled considering 1, 5, or 10 classes of days in milk. Five classes fitted the changes in residual variances over the lactation adequately and were used for model comparison. The model that fitted linear spline functions with 6 knots provided the lowest sum of residual variances across lactation. On the other hand, according to the deviance information criterion (DIC) and Bayesian information criterion (BIC), a model using third-order and fourth-order Legendre polynomials for additive genetic and permanent environmental effects, respectively, provided the best fit. However, the high rank correlation (0.998) between this model and that applying third-order Legendre polynomials for additive genetic and permanent environmental effects, indicates that, in practice, the same bulls would be selected by both models. The last model, which is less parameterized, is a parsimonious option for fitting dairy Gyr breed test-day milk yield records. © 2013 American Dairy Science Association.

Efficient estimation for rank-based regression with clustered data

Rank-based inference is widely used because of its robustness. This article provides optimal rank-based estimating functions in analysis of clustered data with random cluster effects. The extensive simulation studies carried out to evaluate the performance of the proposed method demonstrate that it is robust to outliers and is highly efficient given the existence of strong cluster correlations. The performance of the proposed method is satisfactory even when the correlation structure is misspecified, or when heteroscedasticity in variance is present. Finally, a real dataset is analyzed for illustration.

Quantile regression for longitudinal data with a working correlation model

This paper proposes a linear quantile regression analysis method for longitudinal data that combines the between- and within-subject estimating functions, which incorporates the correlations between repeated measurements. Therefore, the proposed method results in more efficient parameter estimation relative to the estimating functions based on an independence working model. To reduce computational burdens, the induced smoothing method is introduced to obtain parameter estimates and their variances. Under some regularity conditions, the estimators derived by the induced smoothing method are consistent and have asymptotically normal distributions. A number of simulation studies are carried out to evaluate the performance of the proposed method. The results indicate that the efficiency gain for the proposed method is substantial especially when strong within correlations exist. Finally, a dataset from the audiology growth research is used to illustrate the proposed methodology.