44 10 20655 https://www.socictopen.socict.org/files/original/9738183adc1deec5731f61e59ceeaf65.pdf 0dae89014b2f823f67c530508791538b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Agricultura sostenible Description An account of the resource Dominio científico: Agricultura sostenible Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A CULTURA DO AÇAFRÃO (Curcuma longa L.) EM GOIÁS - CONTRIBUIÇÕES PARA A SUSTENTABILIDADE THE TURMERIC CULTURE (Curcuma longa L.) IN GOIÁS - CONTRIBUTIONS TO SUSTAINABILITY Creator An entity primarily responsible for making the resource Alzirene de Vasconcelos Milhomem, Sônia Milagres Teixeira Description An account of the resource  O açafrão (Curcuma longa L.), amplamente utilizado como corante natural e condimento, além de agente terapêutico, é cultivado por pequenos produtores familiares, em Goiás, no município de Mara Rosa. Visando a oferecer subsídios à pesquisa sobre a cultura, o processamento e a qualidade do produto final, este trabalho foi realizado com o objetivo de promover a sustentabilidade e pluriatividade da agricultura familiar no estado. O estudo atesta a importância de se viabilizarem processos alternativos para o manejo da cultura, beneficiamento com qualidade, além de descrever aspectos socio-econômicos da atividade, em uma região caracterizada pela concentração de pobreza. PALAVRAS-CHAVE: Agricultura familiar; tecnologias; processamento; custos de produção. Turmeric (Curcuma longa L.), widely used as a natural colorific and spice, besides as a therapeutic agent, is cultivated by important group of small family farmers, in Mara Rosa, Goiás, Brazil. In an attempt to offer subsidies to a research project with the crop and product processing, with quality, this research was developed, among the objectives to promote sustainability and pluriactivity of family farms in the Goiás State. The study confirms the importance of alternatives for crop management and processing with quality, besides describing socio-economic aspects of the activity, in a region characterized by concentration of poverty. KEY-WORDS: Family farm; technology; processing; production; costs. Date A point or period of time associated with an event in the lifecycle of the resource 2007 Subject The topic of the resource Agricultura Familiar, Custos de Produção, Tecnologias, processamento Identifier An unambiguous reference to the resource within a given context 10.5216/pat.v29i2.2855 Source A related resource from which the described resource is derived Pesquisa Agropecuária Tropical Publisher An entity responsible for making the resource available Universidade Federal de Goiás Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Agriculture (General) Relation A related resource <a href="http://www.revistas.ufg.br/index.php/pat/article/view/2855" target="_blank" rel="noreferrer noopener">http://www.revistas.ufg.br/index.php/pat/article/view/2855</a> https://www.socictopen.socict.org/files/original/abd8c1f5225aebc1d39fa76d5586bc3b.pdf e8bef52b6589d74b8c44edce1f9c3c8d Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Data Driven Approach for Prioritizing COVID-19 Vaccinations in the Midwestern United States. Creator An entity primarily responsible for making the resource Matthew Blaser, Michael D Cailas, John R Canar, Brian Cooper, Peter J Geraci, Kristin M Osiecki, Apostolis Sambanis, Greg Arling, Joel Flax-Hatch Description An account of the resource Considering the potential for widespread adoption of social vulnerability indices (SVI) to prioritize COVID-19 vaccinations, there is a need to carefully assess them, particularly for correspondence with outcomes (such as loss of life) in the context of the COVID-19 pandemic. The University of Illinois at Chicago School of Public Health Public Health GIS team developed a methodology for assessing and deriving vulnerability indices based on the premise that these indices are, in the final analysis, classifiers. Application of this methodology to several Midwestern states with a commonly used SVI indicates that by using only the SVI rankings there is a risk of assigning a high priority to locations with the lowest mortality rates and low priority to locations with the highest mortality rates. Based on the findings, we propose using a two-dimensional approach to rationalize the distribution of vaccinations. This approach has the potential to account for areas with high vulnerability characteristics as well as to incorporate the areas that were hard hit by the pandemic. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Identifier An unambiguous reference to the resource within a given context 10.5210/ojphi.v13i1.11621 Source A related resource from which the described resource is derived Online journal of public health informatics https://www.socictopen.socict.org/files/original/30bf3827f19aa38f056b1e0f33223c06.pdf 7c29ec12d38ee8c6d6c59422ab9e0329 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Data-Driven Framework for Coding the Intent and Extent of Political Tweeting, Disinformation, and Extremism Creator An entity primarily responsible for making the resource Mahdi Hashemi Description An account of the resource Disinformation campaigns on online social networks (OSNs) in recent years have underscored democracy’s vulnerability to such operations and the importance of identifying such operations and dissecting their methods, intents, and source. This paper is another milestone in a line of research on political disinformation, propaganda, and extremism on OSNs. A total of 40,000 original Tweets (not re-Tweets or Replies) related to the U.S. 2020 presidential election are collected. The intent, focus, and political affiliation of these political Tweets are determined through multiple discussions and revisions. There are three political affiliations: rightist, leftist, and neutral. A total of 171 different classes of intent or focus are defined for Tweets. A total of 25% of Tweets were left out while defining these classes of intent. The purpose is to assure that the defined classes would be able to cover the intent and focus of unseen Tweets (Tweets that were not used to determine and define these classes) and no new classes would be required. This paper provides these classes, their definition and size, and example Tweets from them. If any information is included in a Tweet, its factuality is verified through valid news sources and articles. If any opinion is included in a Tweet, it is determined that whether or not it is extreme, through multiple discussions and revisions. This paper provides analytics with regard to the political affiliation and intent of Tweets. The results show that disinformation and extreme opinions are more common among rightists Tweets than leftist Tweets. Additionally, Coronavirus pandemic is the topic of almost half of the Tweets, where 25.43% of Tweets express their unhappiness with how Republicans have handled this pandemic. Date A point or period of time associated with an event in the lifecycle of the resource 2021 Subject The topic of the resource misinformation, social media, twitter, politics, Elections, Extremism Identifier An unambiguous reference to the resource within a given context 10.3390/info12040148 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Information technology https://www.socictopen.socict.org/files/original/327e439c4aa45889a9c8d511c06874cd.pdf e9c2543055c3354ddc9d322f5c610b07 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A dataset for the perceived vulnerability to disease scale in Japan before the spread of COVID-19 [version 2; peer review: 2 approved] Creator An entity primarily responsible for making the resource Yuki Yamada, Haoqin Xu, Kyoshiro Sasaki Description An account of the resource The COVID-19 outbreak is a worldwide medical and epidemiological catastrophe, and the number of psychological studies concerning COVID-19 is growing daily. Such studies need baseline data from before the COVID-19 outbreak for comparison, but such datasets have not yet been accumulated and shared. Here, we provide a dataset on the perceived vulnerability to disease scale for 1382 Japanese participants obtained through an online survey conducted in 2018 that will be useful for comparison with current or post-COVID-19 perceived vulnerability to disease data. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Identifier An unambiguous reference to the resource within a given context 10.12688/f1000research.23713.2 Source A related resource from which the described resource is derived Biotemas Publisher An entity responsible for making the resource available Universidade Federal de Santa Catarina Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science, Medicine https://www.socictopen.socict.org/files/original/c0293e815cb0f3b0e72534086668d6fe.pdf 2ca8923224ed82e0b3ef037673eb2e40 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Agricultura sostenible Description An account of the resource Dominio científico: Agricultura sostenible Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A década da nutrição, a política de segurança alimentar e nutricional e as compras públicas da agricultura familiar no Brasil Creator An entity primarily responsible for making the resource Carmem Priscila Bocchi, Élcio de Souza Magalhães, Lilian Rahal, Patrícia Gentil, Rafaela de Sá Gonçalves Description An account of the resource A aprovação da Década da Nutrição (2016 a 2025) pelas Nações Unidas partiu da constatação de que as causas que levam à má nutrição são complexas e multidimensionais – a exemplo da situação de pobreza e extrema pobreza e da falta de acesso a uma dieta diversificada e de qualidade, que respeite os hábitos e as culturas alimentares dos diversos povos e países. No Brasil, a agenda da segurança alimentar e nutricional sempre foi conduzida por uma visão integrada do sistema alimentar, expressa no conceito de “segurança alimentar e nutricional”. O objetivo do presente artigo é descrever como a experiência brasileira na estruturação de uma agenda pública nacional de segurança alimentar e nutricional nas duas últimas décadas dialoga e converge com a concepção de nutrição e sistemas alimentares abordada nos documentos que instituem a Década. Para tanto, são abordados aspectos relativos à governança da segurança alimentar e nutricional no Brasil e o papel dos programas de compras públicas da agricultura familiar, com objetivo de incentivar a produção, a comercialização e o acesso a uma alimentação saudável em nível local e propiciar um sistema alimentar mais saudável. Date A point or period of time associated with an event in the lifecycle of the resource 2019 Subject The topic of the resource Alimentação escolar, Alimentação saudável, Brasil, Colaboração Intersetorial, Segurança alimentar e nutricional Identifier An unambiguous reference to the resource within a given context 10.26633/RPSP.2019.84 Source A related resource from which the described resource is derived Revista Panamericana de Salud Pública Publisher An entity responsible for making the resource available Pan American Health Organization Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine, Public aspects of medicine, Arctic medicine. Tropical medicine Relation A related resource <a href="http://iris.paho.org/xmlui/handle/123456789/51645" target="_blank" rel="noreferrer noopener">http://iris.paho.org/xmlui/handle/123456789/51645</a> https://www.socictopen.socict.org/files/original/204ea92f0d13fd31f2fe48361a1c666f.pdf 66443a445961a1123e73f0dad719822e Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Decision Aide for the Risk Stratification of GU Cancer Patients at Risk of SARS-CoV-2 Infection, COVID-19 Related Hospitalization, Intubation, and Mortality Creator An entity primarily responsible for making the resource Dara J. Lundon, Brian D. Kelly, Devki Shukla, Damien M. Bolton, Peter Wiklund, Ash Tewari Description An account of the resource Treatment decisions for both early and advanced genitourinary (GU) malignancies take into account the risk of dying from the malignancy as well as the risk of death due to other causes such as other co-morbidities. COVID-19 is a new additional and immediate risk to a patient’s morbidity and mortality and there is a need for an accurate assessment as to the potential impact on of this syndrome on GU cancer patients. The aim of this work was to develop a risk tool to identify GU cancer patients at risk of diagnosis, hospitalization, intubation, and mortality from COVID-19. A retrospective case showed a series of GU cancer patients screened for COVID-19 across the Mount Sinai Health System (MSHS). Four hundred eighty-four had a GU malignancy and 149 tested positive for SARS-CoV-2. Demographic and clinical variables of >38,000 patients were available in the institutional database and were utilized to develop decision aides to predict a positive SARS-CoV-2 test, as well as COVID-19-related hospitalization, intubation, and death. A risk tool was developed using a combination of machine learning methods and utilized BMI, temperature, heart rate, respiratory rate, blood pressure, and oxygen saturation. The risk tool for predicting a diagnosis of SARS-CoV-2 had an AUC of 0.83, predicting hospitalization for management of COVID-19 had an AUC of 0.95, predicting patients requiring intubation had an AUC of 0.97, and for predicting COVID-19-related death, the risk tool had an AUC of 0.79. The models had an acceptable calibration and provided a superior net benefit over other common strategies across the entire range of threshold probabilities. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource mortality, covid-19, Decision curve analysis, Risk calculator, genitourinary cancer, urologic oncology Identifier An unambiguous reference to the resource within a given context 10.3390/jcm9092799 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine https://www.socictopen.socict.org/files/original/0cd0ecea2c8231c86173adbd913b4516.pdf f256efeaea0a1cdd99b9e124b97c086b Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Deep Convolutional Neural Network for Oil Spill Detection from Spaceborne SAR Images Creator An entity primarily responsible for making the resource Kan Zeng, Yixiao Wang Description An account of the resource Classification algorithms for automatically detecting sea surface oil spills from spaceborne Synthetic Aperture Radars (SARs) can usually be regarded as part of a three-step processing framework, which briefly includes image segmentation, feature extraction, and target classification. A Deep Convolutional Neural Network (DCNN), named the Oil Spill Convolutional Network (OSCNet), is proposed in this paper for SAR oil spill detection, which can do the latter two steps of the three-step processing framework. Based on VGG-16, the OSCNet is obtained by designing the architecture and adjusting hyperparameters with the data set of SAR dark patches. With the help of the big data set containing more than 20,000 SAR dark patches and data augmentation, the OSCNet can have as many as 12 weight layers. It is a relatively deep Deep Learning (DL) network for SAR oil spill detection. It is shown by the experiments based on the same data set that the classification performance of OSCNet has been significantly improved compared to that of traditional machine learning (ML). The accuracy, recall, and precision are improved from 92.50%, 81.40%, and 80.95% to 94.01%, 83.51%, and 85.70%, respectively. An important reason for this improvement is that the distinguishability of the features learned by OSCNet itself from the data set is significantly higher than that of the hand-crafted features needed by traditional ML algorithms. In addition, experiments show that data augmentation plays an important role in avoiding over-fitting and hence improves the classification performance. OSCNet has also been compared with other DL classifiers for SAR oil spill detection. Due to the huge differences in the data sets, only their similarities and differences are discussed at the principle level. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Synthetic Aperture Radar (SAR), deep convolutional neural network (DCNN), oil spill detection, oil spills, lookalikes, dark patch Identifier An unambiguous reference to the resource within a given context DOI: 10.3390/rs12061015 Source A related resource from which the described resource is derived Remote Sensing Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Science Language A language of the resource EN https://www.socictopen.socict.org/files/original/0383eea47515a0bd7b33713a4b1e8d51.pdf 3e857597dc6a074114363335fb597f96 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Deep-Learning-Based Framework for Automated Diagnosis of COVID-19 Using X-ray Images Creator An entity primarily responsible for making the resource Irfan Ullah Khan, Nida Aslam Description An account of the resource The emergence and outbreak of the novel coronavirus (COVID-19) had a devasting effect on global health, the economy, and individuals’ daily lives. Timely diagnosis of COVID-19 is a crucial task, as it reduces the risk of pandemic spread, and early treatment will save patients’ life. Due to the time-consuming, complex nature, and high false-negative rate of the gold-standard RT-PCR test used for the diagnosis of COVID-19, the need for an additional diagnosis method has increased. Studies have proved the significance of X-ray images for the diagnosis of COVID-19. The dissemination of deep-learning techniques on X-ray images can automate the diagnosis process and serve as an assistive tool for radiologists. In this study, we used four deep-learning models—DenseNet121, ResNet50, VGG16, and VGG19—using the transfer-learning concept for the diagnosis of X-ray images as COVID-19 or normal. In the proposed study, VGG16 and VGG19 outperformed the other two deep-learning models. The study achieved an overall classification accuracy of 99.3%. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource coronavirus, covid-19, Pandemic, deep learning, Transfer learning Identifier An unambiguous reference to the resource within a given context 10.3390/info11090419 Source A related resource from which the described resource is derived Epidemiology and Health Publisher An entity responsible for making the resource available Korean Society of Epidemiology Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Information technology https://www.socictopen.socict.org/files/original/f0788c28ea55d6e4f5dcbbfdec97da35.pdf bc9d55cc624c56e7b46a3b67c9269296 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Agricultura sostenible Description An account of the resource Dominio científico: Agricultura sostenible Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A Deeper Microscopic Study of the Interaction between Gum Rosin Derivatives and a Mater-Bi Type Bioplastic Creator An entity primarily responsible for making the resource Miguel Aldas, Emilio Rayón, Juan López-Martínez, Marina P. Arrieta Description An account of the resource The interaction between gum rosin and gum rosin derivatives with Mater-Bi type bioplastic, a biodegradable and compostable commercial bioplastic, were studied. Gum rosin and two pentaerythritol esters of gum rosin (Lurefor 125 resin and Unik Tack P100 resin) were assessed as sustainable compatibilizers for the components of Mater-Bi® NF 866 polymeric matrix. To study the influence of each additive in the polymeric matrix, each gum rosin-based additive was compounded in 15 wt % by melt-extrusion and further injection molding process. Then, the mechanical properties were assessed, and the tensile properties and impact resistance were determined. Microscopic analyses were carried out by field emission scanning electron microscopy (FE-SEM), atomic force microscopy (AFM) and atomic force microscopy with nanomechanical assessment (AFM-QNM). The oxygen barrier and wettability properties were also assayed. The study revealed that the commercial thermoplastic starch is mainly composed of three phases: A polybutylene adipate-co-terephthalate (PBAT) phase, an amorphous phase of thermoplastic starch (TPSa), and a semi-crystalline phase of thermoplastic starch (TPSc). The poor miscibility among the components of the Mater-Bi type bioplastic was confirmed. Finally, the formulations with the gum rosin and its derivatives showed an improvement of the miscibility and the solubility of the components depending on the additive used. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource Biodegradable Polymers, gum rosin, gum rosin esters, thermoplastic starch Identifier An unambiguous reference to the resource within a given context 10.3390/polym12010226 Source A related resource from which the described resource is derived Polymers Publisher An entity responsible for making the resource available MDPI AG Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Organic chemistry Relation A related resource <a href="https://www.mdpi.com/2073-4360/12/1/226" target="_blank" rel="noreferrer noopener">https://www.mdpi.com/2073-4360/12/1/226</a> https://www.socictopen.socict.org/files/original/45f32aa2959dd5434196648a5693aafd.pdf 061503095885488ff672f6a71fbf29bd Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Agricultura sostenible Description An account of the resource Dominio científico: Agricultura sostenible Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource A descentralização da Política Nacional de ATER: uma experiência nos assentamentos de reforma agrária no noroeste mineiro – Brasil / Decentralization of the National Politics of ATER: an experience in the agrarian reform settlements in northwest mineiro – Brazil Creator An entity primarily responsible for making the resource José Humberto Valadares Xavier, Suenia Cibeli Ramos Almeida, ,, Marcelo Nascimento Oliveira Description An account of the resource descentralização de políticas públicas no país permitiu a participação da sociedade civil organizada em diferentes âmbitos de sua formulação, execução e fiscalização. Desde a década de 1990, a universalização desse processo vem se consolidando no meio rural por meio da operacionalização de serviços de assistência técnica e extensão rural realizada por organizações não governamentais. Com a regulamentação da Política Nacional de Assistência Técnica e extensão Rural houve uma ampliação na participação das organizações sociais ligadas aos movimentos sociais de agricultores familiares. O presente texto aborda uma experiência vivenciada por agentes de desenvolvimento em assentamentos de reforma agrária do município de Unai, Minas Gerais. Date A point or period of time associated with an event in the lifecycle of the resource 2010 Subject The topic of the resource Agricultura Familiar, Descentralização, Desenvolvimento Local, Extensão rural, Reforma agrária, assistência técnica Source A related resource from which the described resource is derived Revista Sociedade & Natureza Publisher An entity responsible for making the resource available Editora da Universidade Federal de Uberlândia Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Environmental sciences, Social sciences (General) Relation A related resource <a href="http://www.seer.ufu.br/index.php/sociedadenatureza/article/view/9959/pdf_18" target="_blank" rel="noreferrer noopener">http://www.seer.ufu.br/index.php/sociedadenatureza/article/view/9959/pdf_18</a>