Factors associated with drug use among adolescents

The study aimed to identify factors associated to drug use in adolescents. For this purpose, it has been observed 133 adolescents registred in ninth grade in two municipal schools in Viçosa, who answered an individual questionnaire validated by PAHO / WHO, applied by members of the Uncensored Extension Project of the Federal University of Viçosa (UFV). Substance use and family structure were evaluated. Statistical tools were: Epi-Info 7.0 StatCalc, Pearson's chi-square test, Poisson regression and SPSS version 23.0 and Stata 9.0 programs. The sample had an average of 15 years old, that 26.3% reported drug use, thus, 65,4% related family history of drug use and low education. Other aspects of family structure included: good family perception, absence of violence and family mental disorder by 78.2%, 82.7% and 75.9% of adolescents, respectively. Only males persisted as a factor associated with drug use, with 2.4 times higher use (PR 2.39; 95% IC 1.19-4.78; p = 0.014). Therefore, only the male gender showed a higher risk for drug use, and further studies are needed to evaluate factors associated with drug use, aiming to promote public health

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear un derstanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5–7 vast areas of the tropics remain understudied.8–11 In the American tropics, Amazonia stands out as the world’s most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepre sented in biodiversity databases.13–15 To worsen this situation, human-induced modifications16,17 may elim inate pieces of the Amazon’s biodiversity puzzle before we can use them to understand how ecological com munities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple or ganism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region’s vulnerability to environmental change. 15%–18% of the most ne glected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lostinfo:eu-repo/semantics/publishedVersio

Pervasive gaps in Amazonian ecological research

Biodiversity loss is one of the main challenges of our time,1,2 and attempts to address it require a clear understanding of how ecological communities respond to environmental change across time and space.3,4 While the increasing availability of global databases on ecological communities has advanced our knowledge of biodiversity sensitivity to environmental changes,5,6,7 vast areas of the tropics remain understudied.8,9,10,11 In the American tropics, Amazonia stands out as the world's most diverse rainforest and the primary source of Neotropical biodiversity,12 but it remains among the least known forests in America and is often underrepresented in biodiversity databases.13,14,15 To worsen this situation, human-induced modifications16,17 may eliminate pieces of the Amazon's biodiversity puzzle before we can use them to understand how ecological communities are responding. To increase generalization and applicability of biodiversity knowledge,18,19 it is thus crucial to reduce biases in ecological research, particularly in regions projected to face the most pronounced environmental changes. We integrate ecological community metadata of 7,694 sampling sites for multiple organism groups in a machine learning model framework to map the research probability across the Brazilian Amazonia, while identifying the region's vulnerability to environmental change. 15%–18% of the most neglected areas in ecological research are expected to experience severe climate or land use changes by 2050. This means that unless we take immediate action, we will not be able to establish their current status, much less monitor how it is changing and what is being lost

Applying optimization algorithms for spatial estimation of travel demand variables

Using spatial statistics techniques is a way to improve the forecast of travel demand variables considering their spatial dependence. The semivariogram is a proper geostatistic tool for represent the spatial structure of a Regionalized Variable. Therefore, the semivariogram modeling is a fundamental step and is often done visually, based on data knowledge and researchers’ experience, as well as taking into account automatic criteria, such as weighted least squares function. Moreover, these automatic procedures generally assume that data distribution is Gaussian. This research aims to evaluate the combined use of Genetic Algorithms (GAs) and geostatistical methods to forecast travel demand variables, in order to optimize the calculation and fitting of semivariograms. Car Trip rates and Income by household were estimated using the GA application in variographic models, and therefore enabled us to obtain numerous semivariogram parameters. Consequently, intervals of the most frequent parameters were obtained and those with better performance (based on the fitness value) were chosen to carry out the modeling procedure using geostatistical software. The geostatistical modeling optimization procedure, proposed in this study, was validated considering not only a non spatial model (traditional Linear Regression) but also a different spatial approach, the Geographically Weighted Regression (GWR). The validation was carried out using a bivariate example. Thus, the procedure enabled us to compute and fit semivariograms more accurately, contributing to knowledge about spatial structure and variographic parameters related to almost optimal solutions. It is important to consider that the code developed from this article is available for applications in other knowledge areas with spatial dependence data

NEOTROPICAL XENARTHRANS: a data set of occurrence of xenarthran species in the Neotropics

Xenarthrans—anteaters, sloths, and armadillos—have essential functions for ecosystem maintenance, such as insect control and nutrient cycling, playing key roles as ecosystem engineers. Because of habitat loss and fragmentation, hunting pressure, and conflicts with domestic dogs, these species have been threatened locally, regionally, or even across their full distribution ranges. The Neotropics harbor 21 species of armadillos, 10 anteaters, and 6 sloths. Our data set includes the families Chlamyphoridae (13), Dasypodidae (7), Myrmecophagidae (3), Bradypodidae (4), and Megalonychidae (2). We have no occurrence data on Dasypus pilosus (Dasypodidae). Regarding Cyclopedidae, until recently, only one species was recognized, but new genetic studies have revealed that the group is represented by seven species. In this data paper, we compiled a total of 42,528 records of 31 species, represented by occurrence and quantitative data, totaling 24,847 unique georeferenced records. The geographic range is from the southern United States, Mexico, and Caribbean countries at the northern portion of the Neotropics, to the austral distribution in Argentina, Paraguay, Chile, and Uruguay. Regarding anteaters, Myrmecophaga tridactyla has the most records (n = 5,941), and Cyclopes sp. have the fewest (n = 240). The armadillo species with the most data is Dasypus novemcinctus (n = 11,588), and the fewest data are recorded for Calyptophractus retusus (n = 33). With regard to sloth species, Bradypus variegatus has the most records (n = 962), and Bradypus pygmaeus has the fewest (n = 12). Our main objective with Neotropical Xenarthrans is to make occurrence and quantitative data available to facilitate more ecological research, particularly if we integrate the xenarthran data with other data sets of Neotropical Series that will become available very soon (i.e., Neotropical Carnivores, Neotropical Invasive Mammals, and Neotropical Hunters and Dogs). Therefore, studies on trophic cascades, hunting pressure, habitat loss, fragmentation effects, species invasion, and climate change effects will be possible with the Neotropical Xenarthrans data set. Please cite this data paper when using its data in publications. We also request that researchers and teachers inform us of how they are using these data

NEOTROPICAL CARNIVORES: a data set on carnivore distribution in the Neotropics

Mammalian carnivores are considered a key group in maintaining ecological health and can indicate potential ecological integrity in landscapes where they occur. Carnivores also hold high conservation value and their habitat requirements can guide management and conservation plans. The order Carnivora has 84 species from 8 families in the Neotropical region: Canidae; Felidae; Mephitidae; Mustelidae; Otariidae; Phocidae; Procyonidae; and Ursidae. Herein, we include published and unpublished data on native terrestrial Neotropical carnivores (Canidae; Felidae; Mephitidae; Mustelidae; Procyonidae; and Ursidae). NEOTROPICAL CARNIVORES is a publicly available data set that includes 99,605 data entries from 35,511 unique georeferenced coordinates. Detection/non-detection and quantitative data were obtained from 1818 to 2018 by researchers, governmental agencies, non-governmental organizations, and private consultants. Data were collected using several methods including camera trapping, museum collections, roadkill, line transect, and opportunistic records. Literature (peer-reviewed and grey literature) from Portuguese, Spanish and English were incorporated in this compilation. Most of the data set consists of detection data entries (n = 79,343; 79.7%) but also includes non-detection data (n = 20,262; 20.3%). Of those, 43.3% also include count data (n = 43,151). The information available in NEOTROPICAL CARNIVORES will contribute to macroecological, ecological, and conservation questions in multiple spatio-temporal perspectives. As carnivores play key roles in trophic interactions, a better understanding of their distribution and habitat requirements are essential to establish conservation management plans and safeguard the future ecological health of Neotropical ecosystems. Our data paper, combined with other large-scale data sets, has great potential to clarify species distribution and related ecological processes within the Neotropics. There are no copyright restrictions and no restriction for using data from this data paper, as long as the data paper is cited as the source of the information used. We also request that users inform us of how they intend to use the data

Characterisation of microbial attack on archaeological bone

As part of an EU funded project to investigate the factors influencing bone preservation in the archaeological record, more than 250 bones from 41 archaeological sites in five countries spanning four climatic regions were studied for diagenetic alteration. Sites were selected to cover a range of environmental conditions and archaeological contexts. Microscopic and physical (mercury intrusion porosimetry) analyses of these bones revealed that the majority (68%) had suffered microbial attack. Furthermore, significant differences were found between animal and human bone in both the state of preservation and the type of microbial attack present. These differences in preservation might result from differences in early taphonomy of the bones. © 2003 Elsevier Science Ltd. All rights reserved

A randomized trial of planned cesarean or vaginal delivery for twin pregnancy

Background: Twin birth is associated with a higher risk of adverse perinatal outcomes than singleton birth. It is unclear whether planned cesarean section results in a lower risk of adverse outcomes than planned vaginal delivery in twin pregnancy.\ud \ud Methods: We randomly assigned women between 32 weeks 0 days and 38 weeks 6 days of gestation with twin pregnancy and with the first twin in the cephalic presentation to planned cesarean section or planned vaginal delivery with cesarean only if indicated. Elective delivery was planned between 37 weeks 5 days and 38 weeks 6 days of gestation. The primary outcome was a composite of fetal or neonatal death or serious neonatal morbidity, with the fetus or infant as the unit of analysis for the statistical comparison.\ud \ud Results: A total of 1398 women (2795 fetuses) were randomly assigned to planned cesarean delivery and 1406 women (2812 fetuses) to planned vaginal delivery. The rate of cesarean delivery was 90.7% in the planned-cesarean-delivery group and 43.8% in the planned-vaginal-delivery group. Women in the planned-cesarean-delivery group delivered earlier than did those in the planned-vaginal-delivery group (mean number of days from randomization to delivery, 12.4 vs. 13.3; P = 0.04). There was no significant difference in the composite primary outcome between the planned-cesarean-delivery group and the planned-vaginal-delivery group (2.2% and 1.9%, respectively; odds ratio with planned cesarean delivery, 1.16; 95% confidence interval, 0.77 to 1.74; P = 0.49).\ud \ud Conclusion: In twin pregnancy between 32 weeks 0 days and 38 weeks 6 days of gestation, with the first twin in the cephalic presentation, planned cesarean delivery did not significantly decrease or increase the risk of fetal or neonatal death or serious neonatal morbidity, as compared with planned vaginal delivery