Lessons from the historical dynamics of environmental law enforcement in the Brazilian Amazon.

Here, we analyze critical changes in environmental law enforcement in the Brazilian Amazon between 2000 and 2020. Based on a dataset of law enforcement indicators, we discuss how these changes explain recent Amazon deforestation dynamics. Our analysis also covers changes in the legal prosecution process and documents a militarization of enforcement between 2018 and 2022. From 2004 to 2018, 43.6 thousand land-use embargoes and 84.3 thousand fines were issued, targeting 3.3 million ha of land, and totaling USD 9.3 billion in penalties. Nevertheless, enforcement relaxed and became spatially more limited, signaling an increasing lack of commitment by the State to enforcing the law. The number of embargoes and asset confiscations dropped by 59% and 55% in 2019 and 2020, respectively. These changes were accompanied by a marked increase in enforcement expenditure, suggesting a massive efficiency loss. More importantly, the creation of so-called conciliation hearings and the centralization of legal processes in 2019 reduced the number of actual judgments and fines collected by 85% and decreased the ratio between lawsuits resulting in paid fines over filed ones from 17 to 5%. As Brazil gears up to crack-down on illegal deforestation once again, our assessment suggests urgent entry points for policy action.

Spatial distribution of sedentary behavior and unhealthy eating habits in Belo Horizonte, Brazil: the role of the neighborhood environment.

The study aimed to analyze the spatial distribution of sedentary behavior and unhealthy eating habits, and to assess its relationship with the neighborhood environment. Cross-sectional study with data of Surveillance System of Risk and Protective Factors for Chronic Diseases, carried out in Belo Horizonte, Minas Gerais. Watching television for four hours or more per day was identified as sedentary behavior. Unhealthy eating habits were defined based on regular consumption of sodas, excess fat meat, and red meat, and irregular consumption of fruits and vegetables. Georeferenced data of places for physical activity, food establishments, population and residential density, homicide rate, mean total income, and social vulnerability index were entered into the Vigitel database. The coverage area by basic health units was used as the geographical unit of neighborhood. SaTScan was used to analyze the spatial distribution. Spatial analysis identified a significant cluster of high prevalence of sedentary behavior and unhealthy eating habits, after adjusting for sociodemographic characteristics. The comparison of environmental characteristics inside and outside clusters showed significant differences in the physical and social environment. Physical and social environment might be related to clusters of high prevalence of sedentary behavior and unhealthy eating habits.

Spatial distribution of sedentary behavior and unhealthy eating habits in Belo Horizonte, Brazil: the role of the neighborhood environment / Distribuição espacial do comportamento sedentário e do hábito alimentar não saudável em Belo Horizonte, Brasil: o papel do ambiente da vizinhança

Abstract The study aimed to analyze the spatial distribution of sedentary behavior and unhealthy eating habits, and to assess its relationship with the neighborhood environment. Cross-sectional study with data of Surveillance System of Risk and Protective Factors for Chronic Diseases, carried out in Belo Horizonte, Minas Gerais. Watching television for four hours or more per day was identified as sedentary behavior. Unhealthy eating habits were defined based on regular consumption of sodas, excess fat meat, and red meat, and irregular consumption of fruits and vegetables. Georeferenced data of places for physical activity, food establishments, population and residential density, homicide rate, mean total income, and social vulnerability index were entered into the Vigitel database. The coverage area by basic health units was used as the geographical unit of neighborhood. SaTScan was used to analyze the spatial distribution. Spatial analysis identified a significant cluster of high prevalence of sedentary behavior and unhealthy eating habits, after adjusting for sociodemographic characteristics. The comparison of environmental characteristics inside and outside clusters showed significant differences in the physical and social environment. Physical and social environment might be related to clusters of high prevalence of sedentary behavior and unhealthy eating habits.

Resumo O objetivo foi analisar a distribuição espacial do comportamento sedentário e do hábito alimentar não saudável e verificar a relação com o ambiente da vizinhança. Estudo transversal com dados do Sistema de Vigilância de fatores de risco e proteção para doenças crônicas, realizado em Belo Horizonte, Minas Gerais. Considerou-se comportamento sedentário o hábito de assistir televisão quatro ou mais horas por dia. O hábito alimentar não saudável foi avaliado pelo consumo regular de carne com excesso de gordura, refrigerante e carne vermelha e irregular de frutas e hortaliças. Informações georreferenciadas dos locais para a prática de atividade física, estabelecimentos com venda de alimentos, densidade populacional e residencial, taxa de homicídio, renda e índice de vulnerabilidade social foram inseridas na base do Vigitel. A área de abrangência da unidade básica de saúde foi usada como unidade geográfica da vizinhança. A análise espacial identificou cluster significativo de alta prevalência de comportamento sedentário e hábito alimentar não saudável, mesmo após ajuste. Os ambientes físico e social podem estar relacionados a cluster de alta prevalência de comportamento sedentário e hábito alimentar não saudável.

A Data-Driven Framework for Small Hydroelectric Plant Prognosis Using Tsfresh and Machine Learning Survival Models.

Maintenance in small hydroelectric plants (SHPs) is essential for securing the expansion of clean energy sources and supplying the energy estimated to be required for the coming years. Identifying failures in SHPs before they happen is crucial for allowing better management of asset maintenance, lowering operating costs, and enabling the expansion of renewable energy sources. Most fault prognosis models proposed thus far for hydroelectric generating units are based on signal decomposition and regression models. In the specific case of SHPs, there is a high occurrence of data being censored, since the operation is not consistently steady and can be repeatedly interrupted due to transmission problems or scarcity of water resources. To overcome this, we propose a two-step, data-driven framework for SHP prognosis based on time series feature engineering and survival modeling. We compared two different strategies for feature engineering: one using higher-order statistics and the other using the Tsfresh algorithm. We adjusted three machine learning survival models-CoxNet, survival random forests, and gradient boosting survival analysis-for estimating the concordance index of these approaches. The best model presented a significant concordance index of 77.44%. We further investigated and discussed the importance of the monitored sensors and the feature extraction aggregations. The kurtosis and variance were the most relevant aggregations in the higher-order statistics domain, while the fast Fourier transform and continuous wavelet transform were the most frequent transformations when using Tsfresh. The most important sensors were related to the temperature at several points, such as the bearing generator, oil hydraulic unit, and turbine radial bushing.

Spatial analysis of leisure-time physical activity in an urban area.

OBJECTIVE: To analyze the spatial distribution of the prevalence of leisure-time physical activity (LTPA) in a Brazilian urban area and its association with the characteristics of the physical and social environments. METHODS: A cross-sectional study conducted with data from the Surveillance System for Risk and Protective Factors for Chronic Diseases from the years 2008-2010, in Belo Horizonte, state of Minas Gerais, Brazil. The outcome was the practice of LTPA and the independent variables were residential and population density, the density of places for physical activity, homicide rates, average family income, and health vulnerability index. The spatial scanning technique was employed to identify clusters with a high prevalence of PA at leisure time. The Mann-Whitney test was used to compare variables inside and outside the cluster. RESULTS: The sample included 5,779 participants, 33.3% (SE = 0.73) of whom reported sufficient PA during leisure time. We identified a significant cluster of a high prevalence of LTPA. After adjustments, the cluster presented a radius of 3,041.99 meters and 603 individuals, and 293 (48.6%) of them reported sufficient LTPA. The probability of performing sufficient LTPA in the cluster was 27% higher (PR = 1.27; p = 0.002) than in the coverage areas of primary healthcare units outside the cluster. There was a higher density of places for LTPA practice, higher population and residential density, and higher family income in the cluster. CONCLUSION: The results evidenced a cluster of high prevalence of LTPA in a privileged physical and socioeconomic environment in Belo Horizonte, even after adjustments, demonstrating that reducing inequalities can increase LTPA.

Spatial analysis of leisure-time physical activity in an urban area / Análise espacial da prática de atividade física no lazer em área urbana

ABSTRACT: Objective: To analyze the spatial distribution of the prevalence of leisure-time physical activity (LTPA) in a Brazilian urban area and its association with the characteristics of the physical and social environments. Methods: A cross-sectional study conducted with data from the Surveillance System for Risk and Protective Factors for Chronic Diseases from the years 2008-2010, in Belo Horizonte, state of Minas Gerais, Brazil. The outcome was the practice of LTPA and the independent variables were residential and population density, the density of places for physical activity, homicide rates, average family income, and health vulnerability index. The spatial scanning technique was employed to identify clusters with a high prevalence of PA at leisure time. The Mann-Whitney test was used to compare variables inside and outside the cluster. Results: The sample included 5,779 participants, 33.3% (SE = 0.73) of whom reported sufficient PA during leisure time. We identified a significant cluster of a high prevalence of LTPA. After adjustments, the cluster presented a radius of 3,041.99 meters and 603 individuals, and 293 (48.6%) of them reported sufficient LTPA. The probability of performing sufficient LTPA in the cluster was 27% higher (PR = 1.27; p = 0.002) than in the coverage areas of primary healthcare units outside the cluster. There was a higher density of places for LTPA practice, higher population and residential density, and higher family income in the cluster. Conclusion: The results evidenced a cluster of high prevalence of LTPA in a privileged physical and socioeconomic environment in Belo Horizonte, even after adjustments, demonstrating that reducing inequalities can increase LTPA.

RESUMO: Objetivo: Analisar a distribuição espacial da prevalência da prática de atividade física (AF) no lazer suficiente em uma área urbana brasileira, no período de 2008 a 2010, e verificar se ela é influenciada por características dos ambientes físico e social. Métodos: Estudo transversal com dados do sistema de Vigilância de Fatores de Risco para doenças crônicas não transmissíveis, realizado em Belo Horizonte (MG), entre os anos 2008 e 2010. O desfecho foi a realização de AF no lazer e as exposições foram densidade residencial e populacional, densidade de locais de prática de AF no lazer, taxa de homicídio, renda familiar média e índice de vulnerabilidade da saúde. Foi empregada a técnica de varredura espacial para identificar clusters de alta prevalência de AF no lazer. Utilizou-se o teste de Mann-Whitney para comparar variáveis ambientais dentro e fora do cluster. Resultados: A amostra foi constituída de 5.779 participantes, dos quais 33,3% referiram praticar AF no lazer suficientemente. Identificou-se um cluster significativo de alta prevalência de prática de AF no lazer. Após ajustes, ele apresentou raio de 3.041,99 m e 603 indivíduos, dos quais 293 (48,6%) realizavam AF no lazer suficiente. A probabilidade de um indivíduo praticar AF no lazer suficiente no cluster foi 27% maior (razão de prevalência — RP = 1,27; p = 0,002) do que nas áreas de abrangência das unidades básicas de saúde não pertencentes a ele. Esse cluster teve maior densidade de locais para a prática de AF no lazer, maior densidade populacional e residencial e maior renda familiar. Conclusão: Constatou-se cluster de alta prevalência de AF no lazer em um contexto físico e econômico privilegiado de Belo Horizonte, o que demonstra que diminuir desigualdades pode aumentar a prática de AF no lazer.

Novel Insights into Plasmodium vivax Therapeutic Failure: CYP2D6 Activity and Time of Exposure to Malaria Modulate the Risk of Recurrence.

Plasmodium vivax relapse is one of the major causes of sustained global malaria transmission. Primaquine (PQ) is the only commercial drug available to prevent relapses, and its efficacy is dependent on metabolic activation by cytochrome P450 2D6 (CYP2D6). Impaired CYP2D6 function, caused by allelic polymorphisms, leads to the therapeutic failure of PQ as a radical cure for P. vivax malaria. Here, we hypothesized that the host immune response to malaria parasites modulates susceptibility to P. vivax recurrences in association with CYP2D6 activity. We performed a 10-year retrospective study by genotyping CYP2D6 polymorphisms in 261 malaria-exposed individuals from the Brazilian Amazon. The immune responses against a panel of P. vivax blood-stage antigens were evaluated by serological assays. We confirmed our previous findings, which indicated an association between impaired CYP2D6 activity and a higher risk of multiple episodes of P. vivax recurrence (risk ratio, 1.75; 95% confidence interval [CI], 1.2 to 2.6; P = 0.0035). An important finding was a reduction of 3% in the risk of recurrence (risk ratio, 0.97; 95% CI, 0.96 to 0.98; P < 0.0001) per year of malaria exposure, which was observed for individuals with both reduced and normal CYP2D6 activity. Accordingly, subjects with long-term malaria exposure and persistent antibody responses to various antigens showed fewer episodes of malaria recurrence. Our findings have direct implications for malaria control, since it was shown that nonimmune individuals who do not respond adequately to treatment due to reduced CYP2D6 activity may present a significant challenge for sustainable progress toward P. vivax malaria elimination.

Susceptibility to Plasmodium vivax malaria associated with DARC (Duffy antigen) polymorphisms is influenced by the time of exposure to malaria.

Malaria has provided a major selective pressure and has modulated the genetic diversity of the human genome. The variants of the Duffy Antigen/Receptor for Chemokines (DARC) gene have probably been selected by malaria parasites, particularly the FY*O allele, which is fixed in sub-Saharan Africa and confers resistance to Plasmodium vivax infection. Here, we showed the influence of genomic ancestry on the distribution of DARC genotypes in a highly admixed Brazilian population and confirmed the decreased susceptibility of the FY*A/FY*O genotype to clinical P. vivax malaria. FY*B/FY*O individuals were associated with a greater risk of developing clinical malaria. A remarkable difference among DARC variants concerning the susceptibility to clinical malaria was more evident for individuals who were less exposed to malaria, as measured by the time of residence in the endemic area. Additionally, we found that DARC-negative and FY*A/FY*O individuals had a greater chance of acquiring high levels of antibodies against the 19-kDa C-terminal region of the P. vivax merozoite surface protein-1. Altogether, our results provide evidence that DARC polymorphisms modulate the susceptibility to clinical P. vivax malaria and influence the naturally-acquired humoral immune response to malaria blood antigens, which may interfere with the efficacy of a future vaccine against malaria.

A new item response theory model to adjust data allowing examinee choice.

In a typical questionnaire testing situation, examinees are not allowed to choose which items they answer because of a technical issue in obtaining satisfactory statistical estimates of examinee ability and item difficulty. This paper introduces a new item response theory (IRT) model that incorporates information from a novel representation of questionnaire data using network analysis. Three scenarios in which examinees select a subset of items were simulated. In the first scenario, the assumptions required to apply the standard Rasch model are met, thus establishing a reference for parameter accuracy. The second and third scenarios include five increasing levels of violating those assumptions. The results show substantial improvements over the standard model in item parameter recovery. Furthermore, the accuracy was closer to the reference in almost every evaluated scenario. To the best of our knowledge, this is the first proposal to obtain satisfactory IRT statistical estimates in the last two scenarios.

A Ranking Approach for Probe Selection and Classification of Microarray Data with Artificial Neural Networks.

Acute leukemia classification into its myeloid and lymphoblastic subtypes is usually accomplished according to the morphology of the tumor. Nevertheless, the subtypes may have similar histopathological appearance, making screening procedures difficult. In addition, approximately one-third of acute myeloid leukemias are characterized by aberrant cytoplasmic localization of nucleophosmin (NPMc(+)), where the majority has a normal karyotype. This work is based on two DNA microarray datasets, available publicly, to differentiate leukemia subtypes. The datasets were split into training and test sets, and feature selection methods were applied. Artificial neural network classifiers were developed to compare the feature selection methods. For the first dataset, 50 genes selected using the best classifier was able to classify all patients in the test set. For the second dataset, five genes yielded 97.5% accuracy in the test set.

[Spatial distribution of obesity in an urban Brazilian area]. / Distribuição espacial da obesidade em área urbana no Brasil.

The spatial distribution of a disease is important for the diagnosis and epidemiological understanding of the health situation and trends, enabling a better grasp of the factors that determine the health status of populations. The scope of the study was to analyze the spatial distribution of obesity in adults in Belo Horizonte. This cross-sectional study was developed by Telephone Survey from the database for 2008 to 2010 of the Surveillance of Risk and Protective Factors for Chronic Diseases. Obesity was defined as body mass index 30 kg/m2. A georeferenced base with the environmental data of addresses and zip codes of the location was developed and spatial scan statistics were employed. A comparative analysis of environmental variables related to clusters of higher and lower prevalence of obesity was conducted. A cluster of obese individuals without statistical significance was found in the central area of the city. Also, a significant cluster of non-obese individuals was found in the eastern area of the city. These findings suggest that reasons for low prevalence of obesity in urban Brazilian areas could be related to better social organization and high availability of places for food stores and the practice of physical activity.

Distribuição espacial da obesidade em área urbana no Brasil / Spatial distribution of obesity in an urban Brazilian area

ResumoA distribuição espacial de uma doença é importante para o diagnóstico e o conhecimento epidemiológico da situação e das tendências de saúde, permitindo uma melhor compreensão acerca dos fatores que determinam o estado de saúde das populações. O objetivo do estudo foi analisar a distribuição espacial da obesidade em adultos em Belo Horizonte, a partir da base de dados do Sistema de Vigilância de Fatores de Risco e de Proteção para Doenças Crônicas por Inquérito Telefônico de 2008 a 2010. A obesidade foi definida como índice de massa corporal 30 kg/m2. Foi desenvolvida uma base georreferenciada com os dados ambientais a partir do endereço e CEP do local. Empregou-se a estatística de varredura espacial. Uma análise comparativa das variáveis ambientais referentes aos conglomerados de maior e menor prevalência de obesidade foi realizada. Foi encontrado um conglomerado de indivíduos obesos na área central da cidade, sem significância estatística. Verificou-se, também, agrupamento significativo de indivíduos não obesos no leste da cidade. Esses resultados sugerem que as razões para a baixa prevalência de obesidade em áreas urbanas brasileiras podem estar relacionadas à melhor organização social e alta disponibilidade de comércios de alimentos e de locais para a prática de atividade física.

AbstractThe spatial distribution of a disease is important for the diagnosis and epidemiological understanding of the health situation and trends, enabling a better grasp of the factors that determine the health status of populations. The scope of the study was to analyze the spatial distribution of obesity in adults in Belo Horizonte. This cross-sectional study was developed by Telephone Survey from the database for 2008 to 2010 of the Surveillance of Risk and Protective Factors for Chronic Diseases. Obesity was defined as body mass index 30 kg/m2. A georeferenced base with the environmental data of addresses and zip codes of the location was developed and spatial scan statistics were employed. A comparative analysis of environmental variables related to clusters of higher and lower prevalence of obesity was conducted. A cluster of obese individuals without statistical significance was found in the central area of the city. Also, a significant cluster of non-obese individuals was found in the eastern area of the city. These findings suggest that reasons for low prevalence of obesity in urban Brazilian areas could be related to better social organization and high availability of places for food stores and the practice of physical activity.

RAP1 GTPase overexpression is associated with cervical intraepithelial neoplasia.

RAP1 (RAS proximate 1), a small GTP-binding protein of the RAS superfamily, is a putative oncogene that is highly expressed in several malignant cell lines and types of cancers, including some types of squamous cell carcinoma. However, the participation of RAP1 in cervical carcinogenesis is unknown. We conducted a cross-sectional study of paraffin-embedded cervical biopsies to determine the association of RAP1 with cervical intraepithelial neoplasia (CIN). Standard and quantitative immunohistochemistry assessment of RAP1 expression in fixed tissue was performed on 183 paraffin-embedded cervical biopsies that were classified as normal or non-dysplastic mucosa (NDM) (n = 33); CIN grade 1 (n = 84) and CIN grade 2/3 (n = 66). A gradual increase in RAP1 expression in NDM < CIN 1 < CIN 2/3 (p<0.001) specimens was observed and was in agreement with the histopathologic diagnosis. A progressive increase in the RAP1 expression levels increased the risk of CIN 1 [odds ratio (OR) = 3.50; 95% confidence interval (CI) 1.30-10.64] 3.5 fold and the risk of CIN 2/3 (OR = 19.86, 95% CI 6.40-70.79) nearly 20 fold when compared to NDM. In addition, stereotype ordinal regression analysis showed that this progressive increase in RAP1 expression more strongly impacted CIN 2/3 than CIN 1. Our findings suggest that RAP1 may be a useful biomarker for the diagnosis of CIN.

Optimal selection of the spatial scan parameters for cluster detection: a simulation study.

Circular and elliptic spatial scan statistics requires the user to choose a maximum cluster size. A common value for this parameter is 50% of the underlying population. In addition to the detected primary cluster, the user may be interested in the analysis of significant secondary clusters. It can also be argued that if the true cluster is irregular, then choosing a small value for the maximum cluster size and evaluating significant secondary clusters may improve cluster detection and avoid the use of irregular cluster methods. This work explores the performance of the circular, elliptic and double scan statistics for different values of the maximum cluster size and different options for the analysis of secondary clusters. Empirical results show that for hot-spot clusters, the analysis of secondary clusters which are statistically significant do not improve the detection of the true unknown cluster, on average. There is evidence that a variable maximum cluster size improves performance. That is, the double scan statistic applies an early-stopping procedure which improves positive predictive values.

Convergence analysis of sliding mode trajectories in multi-objective neural networks learning.

The Pareto-optimality concept is used in this paper in order to represent a constrained set of solutions that are able to trade-off the two main objective functions involved in neural networks supervised learning: data-set error and network complexity. The neural network is described as a dynamic system having error and complexity as its state variables and learning is presented as a process of controlling a learning trajectory in the resulting state space. In order to control the trajectories, sliding mode dynamics is imposed to the network. It is shown that arbitrary learning trajectories can be achieved by maintaining the sliding mode gains within their convergence intervals. Formal proofs of convergence conditions are therefore presented. The concept of trajectory learning presented in this paper goes further beyond the selection of a final state in the Pareto set, since it can be reached through different trajectories and states in the trajectory can be assessed individually against an additional objective function.