A new alpha logarithmic-generated class to model precipitation data with theory and inference.

Precipitation, or rainfall, is a central feature of the weather cycle and plays a vital role in sustaining life on Earth. However, existing models such as the Poisson, exponential, normal, log-normal, generalized Pareto, gamma, generalized extreme value, lognormal, beta, Gumbel, Weibull, and Pearson type III distributions used for predicting precipitation are often inadequate for precisely representing the complex pattern of rainfall. This study proposes a novel and innovative approach to address these limitations through the new alpha logarithmic-generated (NAL-G) class of distributions. The study authors thoroughly examine the NAL-G class and a unique model, the NAL-Exponential (NAL-Exp) distribution, with a focus on analyzing mathematical properties such as moments, quantile function, entropy, order statistics, and more. Six recognized classical estimation methods are employed, and extensive simulations are conducted to determine the best one. The NAL-Exp distribution demonstrates its high adaptability and value through its superior performance in modeling four distinct rainfall data sets. The results show that the NAL-Exp distribution outperforms other commonly used distribution models, highlighting its potential as a valuable tool in hydrological modeling and analysis. The increased versatility and flexibility of this new approach hold great potential for enhancing the accuracy and reliability of future rainfall predictions.

Spatial Dynamic Subspaces Encode Sex-Specific Schizophrenia Disruptions in Transient Network Overlap and its Links to Genetic Risk.

Background: Recent advances in resting-state fMRI allow us to study spatial dynamics, the phenomenon of brain networks spatially evolving over time. However, most dynamic studies still use subject-specific, spatially-static nodes. As recent studies have demonstrated, incorporating time-resolved spatial properties is crucial for precise functional connectivity estimation and gaining unique insights into brain function. Nevertheless, estimating time-resolved networks poses challenges due to the low signal-to-noise ratio, limited information in short time segments, and uncertain identification of corresponding networks within and between subjects. Methods: We adapt a reference-informed network estimation technique to capture time-resolved spatial networks and their dynamic spatial integration and segregation. We focus on time-resolved spatial functional network connectivity (spFNC), an estimate of network spatial coupling, to study sex-specific alterations in schizophrenia and their links to multi-factorial genomic data. Results: Our findings are consistent with the dysconnectivity and neurodevelopment hypotheses and align with the cerebello-thalamo-cortical, triple-network, and frontoparietal dysconnectivity models, helping to unify them. The potential unification offers a new understanding of the underlying mechanisms. Notably, the posterior default mode/salience spFNC exhibits sex-specific schizophrenia alteration during the state with the highest global network integration and correlates with genetic risk for schizophrenia. This dysfunction is also reflected in high-dimensional (voxel-level) space in regions with weak functional connectivity to corresponding networks. Conclusions: Our method can effectively capture spatially dynamic networks, detect nuanced SZ effects, and reveal the intricate relationship of dynamic information to genomic data. The results also underscore the potential of dynamic spatial dependence and weak connectivity in the clinical landscape.

An approach to the pollution haven and pollution halo hypotheses in Asian countries.

Present climate change consists of global warming that is caused by the emission of greenhouse gases, generally carbon dioxide. The study examines the pollution haven, pollution halo, and environmental Kuznets curve for a number of Asian countries during the period of 1985 to 2020. Outcomes suggest that urbanization, gross domestic product per capita, energy consumption, and foreign direct investment inflow have positive effects, while gross domestic product square, foreign direct investment square, and tourism have negative effects on emissions of carbon dioxide. Furthermore, findings support the validity of the environmental Kuznets curve, pollution haven, and pollution halo hypothesis for the selected Asian countries. We also find robust results of rationality of the environmental Kuznets curve hypothesis for Pakistan, Bangladesh, India, China, Indonesia, Korea, Japan, Malaysia, Vietnam, and Singapore; of pollution haven hypothesis for Bangladesh, China, Indonesia, Japan, Pakistan, and Singapore; and of pollution halo hypothesis for Bangladesh, China, Indonesia, Japan, Pakistan, and Singapore.

Estimation of Yoga Postures Using Machine Learning Techniques.

Yoga is a traditional Indian way of keeping the mind and body fit, through physical postures (asanas), voluntarily regulated breathing (pranayama), meditation, and relaxation techniques. The recent pandemic has seen a huge surge in numbers of yoga practitioners, many practicing without proper guidance. This study was proposed to ease the work of such practitioners by implementing deep learning-based methods, which can estimate the correct pose performed by a practitioner. The study implemented this approach using four different deep learning architectures: EpipolarPose, OpenPose, PoseNet, and MediaPipe. These architectures were separately trained using the images obtained from S-VYASA Deemed to be University. This database had images for five commonly practiced yoga postures: tree pose, triangle pose, half-moon pose, mountain pose, and warrior pose. The use of this authentic database for training paved the way for the deployment of this model in real-time applications. The study also compared the estimation accuracy of all architectures and concluded that the MediaPipe architecture provides the best estimation accuracy.

New Insights into the Estimation of Reproduction Numbers during an Epidemic.

In this paper, we deal with the problem of estimating the reproduction number Rt during an epidemic, as it represents one of the most used indicators to study and control this phenomenon. In particular, we focus on two issues. First, to estimate Rt, we consider the use of positive test case data as an alternative to the first symptoms data, which are typically used. We both theoretically and empirically study the relationship between the two approaches. Second, we modify a method for estimating Rt during an epidemic that is widely used by public institutions in several countries worldwide. Our procedure is not affected by the problems deriving from the hypothesis of Rt local constancy, which is assumed in the standard approach. We illustrate the results obtained by applying the proposed methodologies to real and simulated SARS-CoV-2 datasets. In both cases, we also apply some specific methods to reduce systematic and random errors affecting the data. Our results show that the Rt during an epidemic can be estimated by using the positive test data, and that our estimator outperforms the standard estimator that makes use of the first symptoms data. It is hoped that the techniques proposed here could help in the study and control of epidemics, particularly the current SARS-CoV-2 pandemic.

A Simulation Study to Assess the Factors of Influence on Mean and Median Frequency of sEMG Signals during Muscle Fatigue.

Mean and Median frequency are typically used for detecting and monitoring muscle fatigue. These parameters are extracted from power spectral density whose estimate can be obtained by several techniques, each one characterized by advantages and disadvantages. Previous works studied how the implementation settings can influence the performance of these techniques; nevertheless, the estimation results have never been fully evaluated when the power density spectrum is in a low-frequency zone, as happens to the surface electromyography (sEMG) spectrum during muscle fatigue. The latter is therefore the objective of this study that has compared the Welch and the autoregressive parametric approaches on synthetic sEMG signals simulating severe muscle fatigue. Moreover, the sensitivity of both the approaches to the observation duration and to the level of noise has been analyzed. Results showed that the mean frequency greatly depends on the noise level, and that for Signal to Noise Ratio (SNR) less than 10dB the errors make the estimate unacceptable. On the other hand, the error in calculating the median frequency is always in the range 2-10 Hz, so this parameter should be preferred in the tracking of muscle fatigue. Results show that the autoregressive model always outperforms the Welch technique, and that the 3rd order continuously produced accurate and precise estimates; consequently, the latter should be used when analyzing severe fatiguing contraction.

Fatores associados ao conhecimento da dengue no município de Parauapebas, Pará / Factors associated with knowledge of dengue in the municipality of Parauapebas, Pará

A dengue é uma das arboviroses de maior incidência no Brasil e no mundo. Compreender como ela se associa a diversos fatores é de suma importância para tentar diminuir sua incidência. Dessa forma, este estudo foi realizado no ano de 2018 em bairros, tanto da zona urbana quanto da zona rural, do município de Parauapebas, no estado do Pará, com o objetivo de gerar um modelo probabilístico para descrever a probabilidade de uma pessoa do município de Parauapebas conhecer como os patógenos da doença podem ser transmitidos e sobre os sintomas da doença. Foram utilizadas técnicas estatísticas de análise exploratória de dados para descrever as variáveis utilizadas no modelo e a regressão logística múltipla, onde, de acordo com os dados obtidos, na cidade de Parauapebas, que as mulheres têm mais de duas vezes mais chance de saber os principais sintomas da doença do que uma pessoa do sexo masculino. Constatou-se ainda que uma grande parcela da população de Parauapebas não sabe como é a forma de transmissão da dengue.

Dengue is one of the arboviruses with the highest incidence in Brazil and worldwide. Understanding how it is associated with several factors is of paramount importance in trying to reduce its incidence. Thus, this study was carried out in 2018 in neighborhoods, both in the urban and rural areas of the municipality of Parauapebas in the state of Pará, with the aim of generating a probabilistic model to identify an identification of a person in the municipality from Parauapebas knows how the pathogens of the disease can be transmitted the form of dengue transmission and about the symptoms of the disease. Statistical statistics of exploratory data analysis were used to describe the variables used in the model and multiple logistic regression, where according to the data obtained, in the city of Parauapebas, women are more than twice as likely to know the major symptoms of the disease than a male person. It was also found that a person who a large portion of the population of Parauapebas does not know how the form of transmission of dengue is.

A novel extended model with versatile shaped failure rate: Statistical inference with Covid -19 applications.

Statistical models perform an essential role in data analysis, and statisticians are constantly looking for novel or pretty recent statistical models to fit data sets across a broad variety of fields. In this study, we used modified Kies generalized transformation and the new power function to suggest an unique statistical model. We present and discuss a linear illustration of the density function. Theoretically, quantile function, characteristic function, stochastic ordering, mean, and moments are just a few of the structure properties we discuss. By defining an ideal statistical distribution for assessing the COVID-19 mortality rate, an attempt is performed to determine the model of COVID-19 spread in different nations like the United Kingdom and Italy. In some countries, the novel distribution have been shown to be more appropriate than existing competing models when fitted to COVID-19.

Methods of Hidden Periodicity Discovering for Gearbox Fault Detection.

It is shown that the models of gear pair vibration, proposed in literature, are particular cases of the bi-periodically correlated random processes (BPCRPs), which describe its stochastic recurrence with two periods. The possibility of vibration and analysis within the framework of BPCRP approximation, in the form of periodically correlated random processes (PCRPs), is grounded and the implementation of vibration processing procedures using PCRP techniques, which are worked out by the authors, is given. Searching for hidden periodicities of the first and the second orders was considered as the main issue of this approach. The estimation of the non-stationary period (basic frequency) allowed us to carry out a detailed analysis of the deterministic part, the covariance structure of the stochastic part, and to form, using their parameters, the sensitive indicators for fault detection. The results of the processing of the wind turbine gearbox vibration signals are presented. The amplitude spectra of the deterministic oscillations and the time changes of the stochastic part power for different fault stages are analyzed. The most efficient indicators, which are formed using the amplitude spectra for practical applications, are proposed. The presented approach was compared with known in literature cyclostationary analysis and envelope techniques, and its advantages are shown.

A new modified Kies Fréchet distribution: Applications of mortality rate of Covid-19.

The purpose of this paper is to identify an effective statistical distribution for examining COVID-19 mortality rates in Canada and Netherlands in order to model the distribution of COVID-19. The modified Kies Frechet (MKIF) model is an advanced three parameter lifetime distribution that was developed by incorporating the Frechet and modified Kies families. In particular with respect to current distributions, the latest one has very versatile probability functions: increasing, decreasing, and inverted U shapes are observed for the hazard rate functions, indicating that the capability of adaptability of the model. A straight forward linear representation of PDF, moment generating functions, Probability weighted moments and hazard rate functions are among the enticing features of this novel distribution. We used three different estimation methodologies to estimate the pertinent parameters of MKIF model like least squares estimators (LSEs), maximum likelihood estimators (MLEs) and weighted least squares estimators (WLSEs). The efficiency of these estimators is assessed using a thorough Monte Carlo simulation analysis. We evaluated the newest model for a variety of data sets to examine how effectively it handled data modeling. The real implementation demonstrates that the proposed model outperforms competing models and can be selected as a superior model for developing a statistical model for COVID-19 data and other similar data sets.

Exploring determinants of financial system and environmental quality in high-income developed countries of the world: the demonstration of robust penal data estimation techniques.

The financial system development has got considerable attention due to its association with the environment of the country. To address the apprehension of the researchers about the effect of the determinants of the financial system on the environmental quality of high-income developed countries, we analyze the data of twenty developed countries with sound and strong financial systems for the period 2001 to 2018. We consider both banking development and stock market development as the main key determinants of the financial system. We employ numerous modern-day penal data estimation techniques, namely Dynamic Penal GMM in both linear and non-linear form, Common Correlated Effect Mean Group (CCEMG), and Dynamic Fixed Effect for capturing the issues of heterogeneity, endogeneity, and cross-sectional dependence. Our results show that banking development substantiates the environmental quality in high-income developed countries. The positive gesture of the banking development on environmental quality could be the reason for the established environmentally friendly policies in the developed part of the world. Hence, we conclude that banking development in high-income developed countries significantly reduces the emissions of dangerous gases, which resultantly enhances the environmental quality. The study reveals an insignificant and tenuous impact of the market development on the environmental quality that might be due to the adoption of cleaner technologies by firms in the developed world that are environmentally friendly. The results of our long-term estimations also predict the significant effect of banking development and an insignificant effect of the market development on environmental quality. In addition, our results also demonstrate an inverted U-shaped relationship of the determinants of the financial system and environmental quality. More institutional and legal initiatives must be made for a more robust banking and stock market development framework by the policy makers with a view to substantiating the quality of the environment to a more sustainable level in the developed world.

A non-parametric method for determining epidemiological reproduction numbers.

In the spreading of infectious diseases, an important number to determine is how many other people will be infected on average by anyone who has become infected themselves. This is known as the reproduction number. This paper describes a non-parametric inverse method for extracting the full transfer function of infection, of which the reproduction number is the integral. The method is demonstrated by applying it to the timeline of hospitalisation admissions for covid-19 in the Netherlands up to May 20 2020, which is publicly available from the site of the Dutch National Institute of Public Health and the Environment (rivm.nl).

Symptom-specific effectiveness of an internet-based intervention in the treatment of mild to moderate depressive symptomatology: The potential of network estimation techniques.

The internet-based intervention Deprexis® has proven to be effective in improving overall depression severity. The current pragmatic randomized controlled trial included 1013 participants with mild to moderate symptomatology and aimed to identify the symptom-specific effects of the internet-based intervention Deprexis (intervention group) in comparison to care as usual (control group). All participants -in both conditions- were permitted to use any type of treatment. Of the nine considered symptoms (assessed with the Patient Health Questionnaire), seven showed larger improvements in the intervention condition relative to care as usual (effect sizes ranging from 0.15 to 0.31). No significant differences were found for the two other symptoms. In a next step, a network was estimated including treatment condition as well as changes in all nine symptoms. The resulting network suggests that four of the seven identified symptom-specific effects were direct, whereas the three other symptom-specific effects were indirect and could be explained by effects on other symptoms. Lastly, exploratory analyses showed that the intervention was more effective in improving overall depression severity for participants with higher scores on those four symptoms that were directly affected by the intervention; consequently, the network estimation techniques showed potential in precision psychiatry.

Hidden deaths: corrected estimates of homicides in Bahia, Brazil, 1996- 2015. / Muertes ocultas: estimaciones corregidas de homicidios en Bahía, Brasil, 1996-2015.

The objective of this study was to correct and estimate five-year homicide rates in Bahia, Brazil, for the 1996-2015 period. An ecological study of the homicides was carried out using official data from the Mortality Information System of the Ministry of Health. Deaths due to assault are classified in the codes X85-Y09 of the International Classification of Disease 10th Revision (ICD-10). A proportional redistribution of deaths classified as events of undetermined intent (Y10-Y34) was carried out and mortality correction factors were applied. In the analyzed period, 67,599 homicides were registered in the Mortality Information System; after the second correction, 88,429 homicide deaths were estimated. Comparing the official and adjusted figures, there was an underreporting of 30.8%. The highest corrected homicide rates were observed in the eastern region, in Pojuca (129.8 homicides per 100,000 inhabitants), Lauro de Freitas (117.7) and Simões Filho (114.3); in the southern region, in Santa Luzia (121.4), Valença (87.6) and Itabuna (86.5); and in the far south, Santa Cruz Cabrália (128.2), Itabela (113.3) and Porto Seguro (106.8). After correction, there was an increase in homicides in all of the five-year periods in the municipalities analyzed, which resulted in an even higher mortality rate.

El objetivo del estudio fue corregir y estimar las tasas quinquenales de homicidios en Bahía, Brasil, en el período 1996-2015. Se realizó un estudio ecológico de los homicidios a partir de datos oficiales del Sistema de Información sobre Mortalidad del Ministerio de Salud. Estas defunciones por agresiones corresponden a los códigos X85-Y09 de la Clasificación internacional de enfermedades 10ª revisión (CIE 10). Se realizó una redistribución proporcional de las defunciones clasificadas como eventos de intención indeterminada (Y10-Y34) y se aplicaron factores de corrección de la mortalidad. En el período analizado, se registraron 67.599 homicidios en el Sistema de Información sobre Mortalidad y, luego de la segunda corrección, se estimaron 88.429 homicidios. Al comparar los números oficiales a los ajustados, se observó una subnotificación del 30,8%. Las mayores tasas de homicidio corregidas se observaron en la región este, en Pojuca (129,8 homicidios por 100.000 habitantes), Lauro de Freitas (117,7) y Simões Filho (114,3); en la región sur, en Santa Luzia (121,4), Valença (87,6) e Itabuna (86,5); y en el extremo sur, en Santa Cruz Cabrália (128,2), Itabela (113,3) y Porto Seguro (106,8). Luego de las correcciones, se observó un incremento de los homicidios en todos los quinquenios en los municipios analizados, lo que resultó en una tasa de mortalidad aún más elevada.

Effects of the export product quality on carbon dioxide emissions: evidence from developing economies.

Using the new measure of the export quality of the International Monetary Fund (IMF), this paper investigates the effects of the product quality of exports on the growth rate of the per capita carbon dioxide emissions. The paper focuses on the panel dataset of 82 developing economies for the period from 1970 to 2014. Along with the index of export quality, we also consider the measures of the per capita income, per capita energy consumption, natural resource rents, and trade openness. The results indicate that there is the positive impact of the quality of exports on carbon dioxide emissions. There is also the positive relationship between the per capita income and carbon dioxide emissions. In addition, we find that the trade openness measures are positively related to carbon dioxide emissions. These results are robust to consider different income measures and to divide the developing economies, according to their income levels.

Muertes ocultas: estimaciones corregidas de homicidios en Bahía, Brasil, 1996-2015 / Hidden deaths: corrected estimates of homicides in Bahia, Brazil, 1996- 2015

RESUMEN El objetivo del estudio fue corregir y estimar las tasas quinquenales de homicidios en Bahía, Brasil, en el período 1996-2015. Se realizó un estudio ecológico de los homicidios a partir de datos oficiales del Sistema de Información sobre Mortalidad del Ministerio de Salud. Estas defunciones por agresiones corresponden a los códigos X85-Y09 de la Clasificación internacional de enfermedades 10ª revisión (CIE 10). Se realizó una redistribución proporcional de las defunciones clasificadas como eventos de intención indeterminada (Y10-Y34) y se aplicaron factores de corrección de la mortalidad. En el período analizado, se registraron 67.599 homicidios en el Sistema de Información sobre Mortalidad y, luego de la segunda corrección, se estimaron 88.429 homicidios. Al comparar los números oficiales a los ajustados, se observó una subnotificación del 30,8%. Las mayores tasas de homicidio corregidas se observaron en la región este, en Pojuca (129,8 homicidios por 100.000 habitantes), Lauro de Freitas (117,7) y Simões Filho (114,3); en la región sur, en Santa Luzia (121,4), Valença (87,6) e Itabuna (86,5); y en el extremo sur, en Santa Cruz Cabrália (128,2), Itabela (113,3) y Porto Seguro (106,8). Luego de las correcciones, se observó un incremento de los homicidios en todos los quinquenios en los municipios analizados, lo que resultó en una tasa de mortalidad aún más elevada.

ABSTRACT The objective of this study was to correct and estimate five-year homicide rates in Bahia, Brazil, for the 1996-2015 period. An ecological study of the homicides was carried out using official data from the Mortality Information System of the Ministry of Health. Deaths due to assault are classified in the codes X85-Y09 of the International Classification of Disease 10th Revision (ICD-10). A proportional redistribution of deaths classified as events of undetermined intent (Y10-Y34) was carried out and mortality correction factors were applied. In the analyzed period, 67,599 homicides were registered in the Mortality Information System; after the second correction, 88,429 homicide deaths were estimated. Comparing the official and adjusted figures, there was an underreporting of 30.8%. The highest corrected homicide rates were observed in the eastern region, in Pojuca (129.8 homicides per 100,000 inhabitants), Lauro de Freitas (117.7) and Simões Filho (114.3); in the southern region, in Santa Luzia (121.4), Valença (87.6) and Itabuna (86.5); and in the far south, Santa Cruz Cabrália (128.2), Itabela (113.3) and Porto Seguro (106.8). After correction, there was an increase in homicides in all of the five-year periods in the municipalities analyzed, which resulted in an even higher mortality rate.

Estimativa de peso corporal e estatura em idosos: concordância entre métodos / Estimated body weight and height in older adults: agreement between methods

OBJETIVO: Comparar os métodos de estimativa de peso corporal e altura em idosos e identificar o(s) melhor(es). MÉTODOS: Trata-se de um estudo do tipo descritivo e transversal realizado em uma clínica de saúde do município de Lagarto (SE). A população do estudo foram idosos de ambos os sexos com capacidade de deambulação. Aferiram-se peso corporal, altura, altura do joelho, circunferência da panturrilha, circunferência do braço, circunferência da cintura, meia envergadura do braço e prega cutânea subescapular, e foram avaliadas as equações de estimativa de altura e peso corporal. Em seguida, as equações foram comparadas aos valores de peso e altura aferidos, verificando-se se havia discordância entre essas variáveis. Utilizou-se o teste de correlação de Pearson, o teste t pareado e o teste de Bland-Altman. Para todos os testes, adotou-se como nível de significância estatística o valor de p ≤ 0,05. RESULTADOS: Participaram do estudo 63 pacientes, sendo a maioria do sexo feminino (74,6%), com média de idade de 68,1 ± 5,8 anos. Notou-se que a equação de Rabito et al., que utiliza a circunferência do braço, apresentou menor diferença de média. Em relação ao peso, a equação de Chumlea et al. apontou a menor diferença de média para o peso aferido. CONCLUSÃO: Recomendam-se as equações supracitadas para a obtenção da altura e do peso corporal em idosos, especialmente nessa população.

OBJECTIVE: To compare different equations to estimate body weight and height in older adults and determine which ones provide the most reliable estimates. METHODS: This descriptive, cross-sectional study was conducted at a health clinic in Lagarto, Sergipe, Brazil. The sample consisted of older men and women who were able to walk. We measured body weight, body height, knee height, calf circumference, arm circumference, waist circumference, half arm span, and subscapular skinfold thickness. Then, we used different equations to estimate weight and height in that sample. The results of the equations were compared with actual measures of weight and height to determine their level of agreement. Paired t-test and Bland-Altman test were used in the statistical analysis. The level of statistical significance was set at p ≤ 0.05. RESULTS: Sixty-three patients participated in the study. Most of them were women (74.6%), and mean age was 68.1 ± 5.8 years. Rabito et al.'s equation, which uses arm circumference to estimate height, showed a smaller mean difference from the actual measure. Regarding weight, Chumlea et al.'s equation showed a smaller mean difference. CONCLUSION: Those two equations are recommended to assess height and weight, especially in the older population

Precisão das equações preditivas de peso corporal e altura: proposta de um percentual de ajuste / Precision of the body weight and stature predictive equations: proposition of an adjustment percentage

Introdução: As equações preditivas de peso corporal e altura foram criadas tendo como referência indivíduos norte-americanos, portanto, diante da distinção de populações, torna-se necessário que sejam analisadas.Dessa forma, o objetivo do estudo foi analisar as equações preditivas de peso e altura, propondo um percentual de ajuste para adequação das mesmas. Método: Estudo transversal realizado em um hospital universitário do Nordeste brasileiro. Foram selecionados pacientes com idade entre 19 e 80 anos, internados nas clínicas médica e cirúrgica do referido hospital. Os dados antropométricos aferidos foram peso atual, altura, circunferência do braço e altura do joelho. Para comparação entre medidas estimadas e aferidas, foi utilizado o teste t pareado de Student e, para as variáveis categóricas, o teste do Qui-quadrado de Pearson. Adotou-se como nível de significância estatística o valor de p<0,05. Resultados: Ao comparar os resultados das medidas aferidas com os das equações preditivas, foi observada uma subestimação nas medidas estimadas de peso (-3,3%), altura, (-4,5%), levando à subestimação na taxa metabólica basal (-6%) e necessidades energéticas (-6%) e uma superestimação nos valores de Índice de Massa Corporal (+5%) em relação às medidas aferidas, resultando numa subestimação no total de pacientes com baixo peso e eutróficos e superestimação daqueles com sobrepeso e obesidade. Conclusão: A análise da precisão das equações preditivas nos pacientes do estudo demonstrou que houve subestimação no total de indivíduos com baixo peso e eutróficos e superestimação daqueles com sobrepeso e obesidade. Baseado nos percentuais de subestimação encontrados ao comparar as medidas estimadas com as aferidas nos pacientes da amostra, sugere-se um ajuste de 3,3% no peso e 4,5% na altura para correção das equações preditivas.(AU)

Introduction: The predictive equations of body weight and stature were created with reference to American individuals, therefore, before the distinction of populations, it becomes necessary to be analyzed. Thus, the objective of the study was to analyze the predictive equations of weight and stature, proposing a percentage of adjustment to fit them. Methods: Cross-sectional study carried out in a university hospital in Brazilian northeastern. Patients aged between 19 and 80 years old admitted to the medical and surgical clinics of the referred hospital were selected. The anthropometric data measured were current weight, stature, arm circumference, calf circumference and knee height. The paired t-test of Student was used to compare the estimated and measured measurements. For the categorical variables, the Pearson Chi-square test was used. The level of statistical significance was set at p<0,05. Results: When comparing the results of the measures measured with those of the predictive equations, there was an underestimation in the estimated measures of weight (-3.3%), stature (-4.5%), leading to a underestimation of basal metabolic rate (-6%) and estimated energy requirements (-6%) and an overestimation in the values of Body Mass Index (+5%) in relation to the measures measured, resulting in an underestimation in the total of patients with low weight and eutrophic, and overestimation of those with overweight/ obesity. Conclusion: The analysis of the precision of the predictive equations in the study patients showed that there was an underestimation in the total of individuals with low weight and eutrophic and overestimation of those with overweight and obesity. Based on the underestimation percentages found when comparing the estimated measures with those measured in the patients in the sample, an adjustment of 3.3% in weight and 4.5% in stature for correcting the predictive equations is suggested.(AU)

Does trade matter for carbon emissions in OECD countries? Evidence from a new trade openness measure.

This paper analyzes the impacts of the per capita income, the per capita energy consumption, and the trade openness on the level of per capita carbon emissions in the panel dataset of 35 Organization for Economic Cooperation and Development (OECD) countries over the period 1960-2013. Along with the nominal trade openness, the paper uses a different trade openness measure, so called as the "trade potential index" (TPI). To the best of our knowledge, this is the first paper that uses the TPI in the empirical environmental Kuznets curve (EKC) hypothesis literature. The paper finds that the EKC hypothesis is valid and there is an "inverted-U" relationship between the income and the carbon emissions. In addition, the paper observes that there is a positive effect of the energy consumption on the carbon emissions. Furthermore, the results indicate that both trade openness measures are negatively associated with the carbon emissions in the OECD countries in the long run.

Adequação das informações de mortalidade e correção dos óbitos informados a partir da Pesquisa de Busca Ativa / Adequacy of mortality data and correction of reported deaths from the Proactive Search of Deaths

Resumo O objetivo deste artigo é propor indicadores de adequação e estimar fatores de correção para os óbitos informados ao SIM. Em 2014, foi realizada uma Pesquisa de Busca Ativa para captar óbitos ocorridos no ano de 2012 em uma amostra de municípios das regiões Norte e Nordeste, e dos estados de Minas Gerais, Mato Grosso e Goiás. Para caracterizar a cobertura das informações de óbitos, foram propostos indicadores de adequação por município. Os fatores de correção foram estimados para indivíduos com um ano ou mais de idade e para crianças menores de 1 ano. Entre os óbitos de 1 ano ou mais, as coberturas são superiores a 90% em 12 estados. Já para óbitos infantis, a cobertura foi inferior a 80% em 7 estados. Os resultados dos modelos de regressão mostraram associação entre os fatores de correção estimados e os indicadores de adequação propostos. Verificou-se grande precariedade das informações em 227 municípios, para os quais o número informado de óbitos infantis, mesmo corrigido, não conseguiu atingir o mínimo esperado. Embora os avanços conseguidos na informação dos dados vitais no Brasil sejam reconhecidos, os resultados mostram que o nosso maior desafio está em alcançar municípios rurais e remotos, que ainda não dispõem de informações vitais adequadas.

Abstract The aim of this paper is to propose indicators of adequacy and to estimate correction factors for deaths reported to SIM. In 2014, we carried out a Proactive Search to capture deaths that occurred in 2012 in a sample of municipalities in the regions North and Northeast, and the states of Minas Gerais, Mato Grosso and Goiás. To characterize the coverage of deaths information, we proposed indicators of adequacy by municipality. Correction factors were estimated for individuals one year of age or older and younger than 1 year old. Among the deaths of people aged one year or more, the coverage was above 90% in 12 states. As for infant deaths, the coverage was less than 80% in 7 states. The results of the regression models showed association between the correction factors estimated and the proposed indicators of adequacy. We found very poor death information in 227 municipalities, for which the reported number of infant deaths even after correction, could not reach the minimum expected. Although the progress made in information of vital data in Brazil is recognized, the results show that our greatest challenge is to reach rural and remote municipalities, which do not yet have adequate vital information.