Patrones de actividad de mamíferos alrededor de la línea transportadora de gas natural de Camisea en la Reserva Comunal Machiguenga, Cusco, Perú

En el presente trabajo se estudia la actividad horaria de los mamíferos que habitan el área circundante a la línea transportadora de gas de Camisea que atraviesa la Reserva Comunal Machiguenga. Desde febrero del 2020 hasta enero del 2021, se realizó un registro fotográfico mediante cámaras trampa dispuestas a lo largo de la tubería de gas. Los patrones de actividad se estimaron mediante la función de densidad de Kernel. Durante el periodo de estudio, se registraron 25 especies de mamíferos. Se encontró que Dasyprocta kalinowskii y Eira barbara presentan un patrón de actividad diurno; mientras que Cuniculus paca, Tapirus terrestris, Dasypus spp. y Mazama spp. presentan un patrón predominantemente nocturno. Se sugiere que los patrones de actividad observados estarían influenciados por varios factores como la exclusión competitiva entre D. kalinowskii y C. paca, disponibilidad estacional del alimento para T. terrestris, variación de temperatura y precipitación para Dasypus spp., restricciones filogenéticas en Mazama spp., y segregación temporal con otros carnívoros para E. barbara. Se destaca la importancia de la colaboración entre las empresas del rubro energético, las comunidades nativas y las organizaciones gubernamentales.

The present study investigates the hourly activity patterns of mammals inhabiting the area surrounding the Camisea gas pipeline that crosses the Machiguenga Communal Reserve. From February 2020 to January 2021, a photographic record was conducted using camera traps placed along the gas pipeline. Activity patterns were estimated using Kernel density functions. During the study period, 25 mammal species were recorded. It was found that Dasyprocta kalinowskii and Eira barbara exhibit a diurnal activity pattern, whereas Cuniculus paca, Tapirus terrestris, Dasypus spp., and Mazama spp. display predominantly nocturnal behavior. It is suggested that observed activity patterns could be influenced by various factors such as competitive exclusion between D. kalinowskii and C. paca, seasonal food availability for T. terrestris, temperature and precipitation variations for Dasypus spp., phylogenetic constraints in Mazama spp., and temporal segregation with other carnivores for E. barbara. The significance of collaboration between energy industry companies, native communities, and governmental organizations is emphasized.

Spatial distribution of Oncomelania hupensis spread in Hubei Province from 2020 to 2022 / 中国血吸虫病防治杂志

Objective To identify the spatial distribution pattern of Oncomelania hupensis spread in Hubei Province, so as to provide insights into precision O. hupensis snail control in the province. Methods Data pertaining to emerging and reemerging snails were collected from Hubei Province from 2020 to 2022 to build a spatial database of O. hupensis snail spread. The spatial clustering of O. hupensis snail spread was identified using global and local spatial autocorrelation analyses, and the hot spots of snail spread were identified using kernel density estimation. In addition, the correlation between environments with snail spread and the distance from the Yangtze River was evaluated using nearest-neighbor analysis and Spearman correlation analysis. Results O. hupensis snail spread mainly occurred along the Yangtze River and Jianghan Plain in Hubei Province from 2020 to 2022, with a total spread area of 4 320.63 hm2, including 1 230.77 hm2 emerging snail habitats and 3 089.87 hm2 reemerging snail habitats. Global spatial autocorrelation analysis showed spatial autocorrelation in the O. hupensis snail spread in Hubei Province in 2020 and 2021, appearing a spatial clustering pattern (Moran’s I = 0.003 593 and 0.060 973, both P values < 0.05), and the mean density of spread snails showed spatial aggregation in Hubei Province in 2020 (Moran’s I = 0.512 856, P < 0.05). Local spatial autocorrelation analysis showed that the high-high clustering areas of spread snails were mainly distributed in 50 settings of 10 counties (districts) in Hubei Province from 2020 to 2022, and the high-high clustering areas of the mean density of spread snails were predominantly found in 219 snail habitats in four counties of Jiangling, Honghu, Yangxin and Gong’an. Kernel density estimation showed that there were high-, secondary high- and medium-density hot spots in snail spread areas in Hubei Province from 2020 to 2022, which were distributed in Jingzhou District, Wuxue District, Honghu County and Huangzhou District, respectively. There were high- and medium-density hot spots in the mean density of spread snails, which were located in Jiangling County, Honghu County and Yangxin County, respectively. In addition, the snail spread areas negatively correlated with the distance from the Yangtze River (r = −0.108 9, P < 0.05). Conclusions There was spatial clustering of O. hupensis snail spread in Hubei Province from 2020 to 2022. The monitoring and control of O. hupensis snails require to be reinforced in the clustering areas, notably in inner embankments to prevent reemerging schistosomiasis.

Spatial analysis of the COVID-19 distribution pattern in São Paulo State, Brazil / Análise espacial do padrão de distribuição do COVID-19 no Estado de São Paulo, Brasil

Abstract At the end of 2019, the outbreak of COVID-19 was reported in Wuhan, China. The outbreak spread quickly to several countries, becoming a public health emergency of international interest. Without a vaccine or antiviral drugs, control measures are necessary to understand the evolution of cases. Here, we report through spatial analysis the spatial pattern of the COVID-19 outbreak. The study site was the State of São Paulo, Brazil, where the first case of the disease was confirmed. We applied the Kernel Density to generate surfaces that indicate where there is higher density of cases and, consequently, greater risk of confirming new cases. The spatial pattern of COVID-19 pandemic could be observed in São Paulo State, in which its metropolitan region standed out with the greatest cases, being classified as a hotspot. In addition, the main highways and airports that connect the capital to the cities with the highest population density were classified as medium density areas by the Kernel Density method.It indicates a gradual expansion from the capital to the interior. Therefore, spatial analyses are fundamental to understand the spread of the virus and its association with other spatial data can be essential to guide control measures.

Resumo No final de 2019, o surto de COVID-19 foi relatado em Wuhan, China. O surto se espalhou rapidamente para vários países, tornando-se uma emergência de saúde pública de interesse internacional. Sem uma vacina ou medicamentos antivirais, medidas de controle são necessárias para entender a evolução dos casos. Neste estudo, relatamos por análise espacial o padrão espacial do surto do COVID-19. Nosso local de estudo foi no estado de São Paulo, Brasil, onde o primeiro caso da doença foi confirmado. Aplicamos o método "Kernel Density" para gerar superfícies que indicam onde há maior densidade de casos e, consequentemente, maior risco de confirmação de novos casos. O padrão espacial da pandemia de COVID-19 foi observado no estado de São Paulo, em que a região metropolitana do estado foi a que apresentou a maior quantidade de casos, sendo classificada como um "hot spot". Além disso, as principais rodovias e aeroportos que conectam a capital às cidades com maior densidade populacional foram classificadas como áreas de média densidade pelo método "Kernel Density". Isso indica uma expansão gradual da capital para o interior. Portanto, as análises espaciais são fundamentais para entender a disseminação do vírus e sua associação com outros dados espaciais pode ser essencial para orientar as medidas de controle.

Spatio-temporal patterns of Oncomelania hupensis snail habitats in Suzhou, Wuxi and Changzhou cities along the Taihu Lake region / 中国血吸虫病防治杂志

Objective To investigate the spatio-temporal distribution characteristics of Oncomelania hupensis snail habitats in three cities of Suzhou, Wuxi and Changzhou along the Taihu Lake region, so as to provide technical supports for establishing a sensitive and highly effective surveillance and forecast system for schistosomiasis. Methods Snail distribution data were collected from Suzhou, Wuxi and Changzhou cities from 1950 to 2018, and the changing trend for snail habitats were described over years. In addition, the clusters of snail habitats were detected using Kernel density analysis and SaTScan space-time scan analysis. Results The number of snail habitats appeared a single-peak distribution in Suzhou, Wuxi and Changzhou cities from 1950 to 2018, which peaked in 1970 and then declined rapidly. There were 62.68% of snail habitats eliminated within 10 years after identification, of which 38.24% were eliminated at the year of identification. Kernel density analysis and SaTScan space-time scan analysis revealed that high-density clusters of snail habitats were mainly distributed in Kunshan City, Wuzhong District and Xiangcheng District from 1970 to 1980, and in Yixing City in 1990; since then, the clusters gradually shrank, and overall appeared a move from northeast to west of Taihu Lake. A total of 4 new clusters were detected after 1970, as revealed by space-time scanning of snail habitats. In current snail habitats, emerging snail habitats are mainly identified in Huqiu District (Dongzhu Town), Wuzhong District (Guangfu Town), Taicang City (Shaxi Town) and Jintan District, and re-emerging snail habitats are scattered in 7 districts. Conclusions The distribution of snail habitats are spatio-temporal aggregation in Suzhou, Wuxi and Changzhou cities. The monitoring and prediction of emerging and re-emerging snail habitats are the key points in the future.

Spatial point pattern analysis of hemorrhagic fever with renal syndrome in Jingzhou, Hubei Province, 2017 / 中华疾病控制杂志

Objective To analyze the spatial point pattern distribution characteristics of hemorrhagic fever with renal syndrome (HFRS) in Jingzhou city, Hubei province during the two seasons spring- summer and autumn-winter of 2017, to discuss its high incidence area and reason, and to provide basis for the resource allocation of public health. Methods The analytical data was collected from Infectious Disease Reporting Information System in China, and the spring-summer season was from March to August of 2017, while the autumn-winter was from the September of 2017 to the February of 2018. The Ripley's K-function and kernel density estimation were applied to analyze the spatial point pattern distribution and compare the distribution characteristics of spatial point pattern between the two seasons. Results In 2017, 133 cases of HFRS were reported in Jingzhou city, including the spring- summer and autumn-winter two pick incidences. The strongest aggregation distance was 17.77km in spring-summer season, and 14.40 km in autumn-winter season. The spatial gathering center was located in the north of Jianli County in spring-summer, and it moved to the south of Jiangling County and Shashi District in autumn-winter. Conclusions The key areas for the prevention and control of HFRS in Jingzhou City are Jiangling County, the southern part of Shashi District and the northern part of jianli county. The key groups are the residents of the urban-rural junction in the southern part of Shashi City, residents along the route of large-scale projects, and farmers engaged in agricultural planting or crayfish breeding in the gathering areas.

Spatial patterns and interactions of dominant tree species in an Amazon tropical rainforest / Patrones e interacciones espaciales de especies arbóreas dominantes en un bosque tropical en la Amazonia

Abstract Knowledge of spatial patterns and interactions of tree species allows for understanding the ecological processes of spatiotemporal structures of tropical forests, becoming essential for the establishment of strategies for the conservation and management of their resources in the long term. The aim of this study was to investigate the spatial patterns and interactions of Astronium lecointei, Dinizia excelsa and Peltogyne paniculata, three dominant timber tree species in the Jamari National Forest, Rondônia, Brazilian Amazon. The Kernel estimator was used aiming to verify the possible influence of first-order factors on species distributions. Inhomogeneous K-functions were applied to analyze species spatial patterns and interactions by means of second-order factors. Univariate analyses revealed different scale-dependent spatial patterns for the species. Aggregation related to ecological characteristics, such as habitat preference and dispersal limitation, was verified for A. lecointei and P. paniculata. D. excelsa presented a random spatial pattern, explained by specific features of its establishment, such as the need for clearings due to light requirements. Interspecific associations were evidenced by bivariate analyses, in which spatial attraction of species resulted from the same preference for microhabitats and the repulsion was a result of niche segregation. Rev. Biol. Trop. 66(3): 1009-1017. Epub 2018 September 01.

Resumen El conocimiento de los patrones e interacciones espaciales de las especies arbóreas permite la comprensión de los procesos ecológicos de estructuración espacio-temporal de los bosques tropicales, tornándose imprescindible para el establecimiento de estrategias de conservación y manejo de sus recursos a largo plazo. El objetivo de este estudio fue investigar los patrones y las interacciones espaciales de Astronium lecointei, Dinizia excelsa y Peltogyne paniculata, tres especies arbóreas madereras dominantes en la Selva Nacional del Jamari, Rondônia, Amazonia Brasileña. Para ello, se utilizó el estimador Kernel, con el objetivo de verificar la posible influencia de factores de primer orden en la distribución de las especies. Para el análisis de los patrones e interacciones espaciales de las especies por medio de los factores de segundo orden, se empleó la función K no homogénea. Los análisis univariados revelaron diferentes patrones espaciales dependientes de la escala para las especies. Agregación relacionada a características ecológicas, como preferencia de hábitat y limitación de la dispersión, fue constatada para A. lecointei y P. paniculata. Dinizia excelsa presentó un patrón espacial aleatorio, explicado por características particulares de su establecimiento, como la necesidad de claros debido a sus requisitos lumínicos. Las asociaciones interespecíficas fueron evidenciadas por los análisis bivariados, en que la atracción espacial de las especies resultó de la misma preferencia por micro hábitats y la repulsión fue resultado de la segregación de nichos.

Concentração intraurbana de população e empregos: os centros antigos das cidades brasileiras perderam primazia? / Intraurban concentration of people and jobs: have Brazilian inner cities lost their primacy? / ¿Concentración intraurbana de población y puestos de trabajo: los centros antiguos de las ciudades brasileñas perdieron primacía?

Os centros antigos das cidades são regiões internas às metrópoles que se destacam por seu valor simbólico e por estarem sujeitos à decadência e esvaziamento. Em geral, a configuração espacial da população e dos empregos determina a relevância locacional dos sítios urbanos, os fluxos de mobilidade e a própria vitalidade de cada porção urbana, inclusive o centro. Entretanto, informações de localização populacional intraurbana só são disponibilizadas a cada dez anos. Dados de localização de empregos, quando disponíveis, se encontram agregados e não estão georreferenciados. Nesse contexto, o presente trabalho analisa e identifica estruturas intraurbanas de população (1991, 2000 e 2010) e emprego (2002 e 2013), em 12 regiões metropolitanas brasileiras, utilizando áreas mínimas comparáveis para agregar dados populacionais censitários e geolocalização identificada de empregos. Os resultados indicam que há perda populacional nos centros metropolitanos no período 1991-2000, parcialmente recuperada no decênio seguinte. Constata-se ainda desconcentração de empregos com migração para novas áreas centrais, em relação aos centros urbanos tradicionais. Todavia, o comportamento não é linear para cada uma das 12 RMs analisadas e o resultado espacial final é específico para cada uma. O artigo contribui com a construção inédita da espacialização dos empregos para as 12 RMs. Ademais, a metodologia desenvolvida permite análise urbana quantitativa padronizada como apoio a pesquisadores com conhecimento local.

Historical city centers are those regions internal to a metropolis that deserve special attention since, despite their symbolic value, they are prone to fall into decadence and become abandoned. The spatial pattern of metropolitan population and employment determines the locational importance of urban sites, displacement flows and even the vitality of each urban portion of the territory, including the city center. In spite of that, intraurban population location data are available only every ten years. Data on job location, when available, are aggregated and not geocoded. In that context, this article analyses and identifies intraurban population (1991, 2000 and 2010) and employment (2002 and 2013) structures, for 12 Brazilian metropolitan areas, using (a) Minimum comparable Areas to aggregate population Census data and (b) jobs location with identification. Results indicate that there is population loss in metropolitan centers for the 1991-2000 period, partly recovered in the following decade. It is also verified that jobs have spread from traditional city centers, with migration to new central areas. Moreover, the behavior is not linear for each of the 12 areas analyzed and the final spatial result is specific to each of them. This article contributes with the original finding of the spatial location of jobs for the 12 metro areas. Finally, the methodology developed enables a standardized quantitative urban analysis which may support researchers with local knowledge.

Los centros antiguos de las ciudades son regiones internas de las metrópolis que se destacan por su valor simbólico y por estar sometidas a procesos de deterioro y abandono. En general, la configuración espacial de la población y de los empleos determina la relevancia de la ubicación de los sitios urbanos, los flujos de movilidad y la vitalidad propia de cada porción urbana, incluso para el análisis del centro. Asimismo, datos de ubicación poblacional intraurbana solamente están disponibles a cada diez años. Datos de ubicación de puestos de trabajo, de estar disponibles, se encuentran agregados y no están georreferenciados. En este contexto, este trabajo analiza e identifica estructuras intraurbanas de población (1991, 2000 y 2010) y empleo (2002 y 2013) en 12 regiones metropolitanas brasileñas, utilizando a) áreas mínimas comparables para agregar datos poblacionales censitarios y b) georreferenciación identificada de empleos. Los resultados indican que hay pérdida poblacional en los centros metropolitanos en el período 1991-2000, que se recupera parcialmente en el decenio siguiente. Además se constata la desconcentración de empleos con migración hacia nuevas áreas centrales en relación con los centros urbanos tradicionales. A su vez, el comportamiento de cada una de las 12 metrópolis analizadas no es lineal y el resultado espacial final es específico para cada una de ellas. El artículo contribuye con una construcción inédita de la espacialización de los puestos de trabajo para las 12 regiones metropolitanas. Por último, la metodología desarrollada permite el análisis urbano cuantitativo homogeneizado como apoyo a investigadores con conocimiento local.

A study of automatic treatment planning based on kernel density estimation / 中华放射肿瘤学杂志

Objective To develop an automatic algorithm to predict the dose-volume histogram (DVH) and implement it in clinical practice.Methods Based on the prior information in the existing plan,such as dosimetric results of organs at risk (OARs) and OAR-target spatial relationship,a two-dimensional kernel density estimation was implemented to predict the DVH of OARs.The predicted DVH curves were converted into objective functions that would be implemented in the Pinnacle treatment planning system.Comparisons between predicted and actual values and between Auto-plan and manual planning were made by paired t test.Results We applied this algorithm to 10 rectal cancer patients,10 breast cancer patients,and 10 nasopharyngeal carcinoma patients.The predicted DVH of OARs showed that the deviation between the actual and predicted values at important clinical dose points were within 5%(P>0.05).The re-planning for the 10 breast cancer patients using Auto-plan showed that the heart dose was significantly reduced and the target coverage was increased,which was consistent with the predicted results.Conclusions The method proposed in this study allows for accurat DVH prediction,and,combined with Auto-plan,can be used to generate clinically accepted treatment plans.

Does Plan B work? Home range estimations from stored on board and transmitted data sets produced by GPS-telemetry in the Colombian Amazon / ¿Funciona el plan B? Estimación de rango de hogar a partir de datos almacenados en instrumentos a bordo de animales y los obtenidos a partir de telemetría satelital de GPS en el Amazonas colombiano

Abstract:Telemetry based on Global Positioning Systems (GPS) makes possible to gather large quantities of information in a very fine scale and work with species that were impossible to study in the past. When working with GPS telemetry, the option of storing data on board could be more desirable than the sole satellite transmitted data, due to the increase in the amount of locations available for analysis. Nonetheless, the uncertainty in the retrieving of the collar unit makes satellite-transmitted technologies something to take into account. Therefore, differences between store-on-board (SoB) and satellite-transmitted (IT) data sets need to be considered. Differences between SoB and IT data collected from two lowland tapirs (Tapirus terrestris), were explored by means of the calculation of home range areas by three different methods: the Minimum Convex Polygon (MCP), the Fixed Kernel Density Estimator (KDE) and the Brownian Bridges (BB). Results showed that SoB and IT data sets for the same individual were similar, with fix ranging from 63 % to 85 % respectively, and 16 m to 17 m horizontal errors. Depending on the total number of locations available for each individual, the home ranges estimated showed differences between 2.7 % and 79.3 %, for the 50 % probability contour and between 9.9 % and 61.8 % for the 95 % probability contour. These differences imply variations in the spatial coincidence of the estimated home ranges. We concluded that the use of IT data is not a good option for the estimation of home range areas if the collar settings have not been designed specifically for this use. Nonetheless, geographical representations of the IT based estimators could be of great help to identify areas of use, besides its assistance to locate the collar for its retrieval at the end of the field season and as a proximate backup when collars disappear. Rev. Biol. Trop. 64 (4): 1441-1450. Epub 2016 December 01.

Resumen:La telemetría basada en los sistemas de geopocisionamiento global (GPS) hace posible recopilar gran cantidad de información a escalas muy finas, y trabajar con especies imposibles de estudiar en el pasado. Al trabajar con telemetría de GPS, la opción de guardar información en la memoria interna del instrumento puede ser más deseable que sólo tener acceso a la información enviada vía satélite, debido a la mayor cantidad de localizaciones disponibles para analizar. No obstante, la incertidumbre de recuperar el collar hace que las tecnología de trasmisión vía satélite deba ser tenida en cuenta. Diferencias entre las bases de datos almacenadas en el collar (SoB) y las trasmitidas vía satélite (IT), recolectadas de dos individuos de Tapir de tierras bajas (Tapirus terrestris), son consideradas, en términos de las áreas de los rangos de hogar calculados con cada uno y mediante el uso de tres metodologías diferentes: Mínimo Polígono Convexo (MCP), Estimador de Densidad de Kernel Fijo (KDE) y los Puentes Brownianos (BB). Las bases de datos SoB e IT son similares, con tasas de acierto de localizaciones que oscilan entre 63 % to 85 % y errores horizontales de 16 m y 17 m respectivamente. Dependiendo del número total de localizaciones disponibles para cada individuo, los rangos de hogar estimados muestran diferencias entre 2.7 % y 79.3 %, para el contorno del 50 % de probabilidades, y entre 9.9 % y 61.8 % para el contorno del 95 % de probabilidades. Estas diferencias implican variaciones en la coincidencia espacial de los rangos de hogar estimados. Concluimos que el uso de la información trasmitida vía satélite no es una buena opción para la estimación de rangos de hogar, si la programción de los collares no ha sido diseñada específicamente para tal fin. Sin embargo, las representaciones geográficas de los estimados a partir de las bases de datos IT pueden ser de gran ayuda para la identificación de áreas de uso, además de su utilidad para la localización y recuperación de collares tras su liberación de los individuos monitoreados y como una base de datos de soporte en caso de pérdida del collar.

Rapid automated analysis method of flow cytometry data / 军事医学

Objective A major component of flow cytometry data analysis involves gating , which is the process of identifying homogeneous groups of cells .As manual gating is error-prone, non-reproducible, nonstandardized, and time-consuming , we propose a time-efficient and accurate approach to automated analysis of flow cytometry data .Methods Unlike manual analysis that successively gates the data projected onto a two-dimensional filed, this approach, using the K-means clustering results , directly analyzed multidimensional flow cytometry data via a similar subpopulations-merged algorithm.In order to apply the K-means to analysis of flow cytometric data , kernel density estimation for selecting the initial number of clustering and k-d tree for optimizing efficiency were proposed .After K-means clustering , results closest to the true populations could be achieved via a two-segment line regression algorithm .Results The misclassification rate (MR) was 0.0736 and time was 2 s in Experiment One, but was 0.0805 and 1 s respectively in Experiment Two. Conclusion The approach we proposed is capable of a rapid and direct analysis of the multidimensional flow cytometry data with a lower misclassification rate compared to both nonprobabilistic and probabilistic clustering methods .

Quantifying Uncertainties in the Modelled Estimates of Extreme Precipitation Events at Upper Thames River Basin.

Assessment of climate change impact on hydrology at watershed scale incorporates downscaling of global scale climatic variables into local scale hydrologic variables and evaluation of future hydrologic extremes. The climatological inputs obtained from several global climate models suffer the limitations due to incomplete knowledge arising from the inherent physical, chemical processes and the parameterization of the model structure. Downscaled output from a single AOGCM with a single emission scenario represents only one of all possible future climate realizations; averaging outputs from multiple AOGCMs might underestimate the extent of future changes in the intensity and frequency of climatological variables. These available methods, thus cannot be representative of the full extent of climate change. Present research, therefore addresses two major questions: (i) should climate research adopt equal weights from AOGCM outputs to generate future climate?; and (ii) what is the probability of the future extreme events to be more severe? This paper explores the methods available for quantifying uncertainties from the AOGCM outputs and provides an extensive investigation of the nonparametric kernel estimator based on choice of bandwidths for investigating the severity of extreme precipitation events over the next century. The Sheather-Jones plug-in kernel estimate appears to be a major improvement over the parametric methods with known distribution. Results indicate increased probabilities for higher intensities and frequencies of events. The applied methodology is flexible and can be adapted to any uncertainty estimation studies with unknown densities. The presented research is expected to broaden our existing knowledge on the nature of the extreme precipitation events and the propagation and quantification of uncertainties arising from the global climate models and emission scenarios.

Spatial Point Pattern Analysis of Birth Defects / 环境与健康杂志

Objective To detect the spatial point pattern distribution rules of neural tube defects.Methods The kernel density estimation and Ripley's K-function were used to analyze the spatial point pattern of the neural tube birth defects in Heshun county in 1998-2001.Results The kernel density estimation result showed that there was two clusters' distribution in central area and southeastern area respectively.In addition,the result by the Ripley's K-function presented that the location of neural tube birth defects had a significant cluster tendency in the spatial distance from 3.17 to 10.41 kilometers in the investigated area.Conclusion These results can provide an important clue for identifying the relations between environment risk factors and birth defects in this area in the future.