Os negócios jurídicos processuais à luz da Lei n. 13.105/2015

- Este trabalho acadêmico faz parte do Programa de Concessão de Bolsas de Pós-graduação Lato sensu e Stricto Sensu no Superior Tribunal de Justiça.Superior Tribunal de Justiça (STJ)

Modelos para localização e conexão de facilidades baseados em fluxos

Mestrado em Matemática e AplicaçõesCom o presente trabalho apresentamos alguns modelos para o problema de localização e conexão de facilidades. O problema de localização de facilidades consiste em encontrar os melhores locais de instalação de determinados serviços de modo a satisfazer o pedido de determinados clientes. O problema da conexão das facilidades determina a melhor forma de ligar as facilidades entre si. Neste trabalho consideramos os dois problemas em simultâneo. Utilizamos vários modelos, os modelos de fluxo multiproduto com uma mercadoria por cliente, fluxo multiproduto com uma mercadoria por facilidade e ainda modelos com base nas restrições de eliminação de sub-ciclos de Miller-Tucker-Zemlin. Testamos computacionalmente programas desenvolvidos para cada um dos modelos referidos usando o software Xpress e, finalmente, apresentamos as nossas conclusões relativamente aos resultados obtidos nos vários modelos utilizados tendo em conta o tempo computacional e a qualidade da solução obtida através das relaxações lineares dos modelos apresentados.In this work we present models for the facility location problem and the facility connection problem. The facility location problem is to find the best places to install specific services to meet the request of certain customers. The problem of connecting the facilities is to determine the best way to connect the facilities between them. In this work we consider both problems simultaneously. We use several models, multicommodity flow models with a commodity per customer, multicommodity flow models with a commodity per facility and also models based on the well know Miller-Tucker-Zemlin subtour elimination constraints. We tested computationally programs developed for each of these models using the software Xpress and finally, we present our findings regarding the results obtained in the various models used considering the computation time used by the programs and the quality of the linear relaxation solutions of the models

Comparison between devices for homogenization and reduction of soybean grain samples

In the grain market the most diverse equipment is used for homogenization and reduction of the working samples. Thus, this paper aims to analyze the performance of devices used for sample homogenization and reduction for soybean classification. A sample composed of 8% of damaged soybeans with yellow and black coat was previously prepared. Samples were homogenized and reduced in bucket, crate, Boerner, 16:1 multichannel splitter and 4:1 multichannel splitter. The design used was completely randomized with five treatments (homogenizers) and one percentage of damaged grains (8%). Evaluations were subjected to analysis of variance and treatment means were compared to one another by Tukey test (p 0.5) and to the mean of the original sample (8%) by Student s t-test. The devices Boerner, 16:1 multichannel splitter and 4:1 multichannel splitter were similar in the homogenization and reduction of the soybean sample. The crate and bucket showed the worst performance in the grain homogenization because they compromise the result of the product’s qualitative analysis

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

ATLANTIC EPIPHYTES: a data set of vascular and non-vascular epiphyte plants and lichens from the Atlantic Forest

Epiphytes are hyper-diverse and one of the frequently undervalued life forms in plant surveys and biodiversity inventories. Epiphytes of the Atlantic Forest, one of the most endangered ecosystems in the world, have high endemism and radiated recently in the Pliocene. We aimed to (1) compile an extensive Atlantic Forest data set on vascular, non-vascular plants (including hemiepiphytes), and lichen epiphyte species occurrence and abundance; (2) describe the epiphyte distribution in the Atlantic Forest, in order to indicate future sampling efforts. Our work presents the first epiphyte data set with information on abundance and occurrence of epiphyte phorophyte species. All data compiled here come from three main sources provided by the authors: published sources (comprising peer-reviewed articles, books, and theses), unpublished data, and herbarium data. We compiled a data set composed of 2,095 species, from 89,270 holo/hemiepiphyte records, in the Atlantic Forest of Brazil, Argentina, Paraguay, and Uruguay, recorded from 1824 to early 2018. Most of the records were from qualitative data (occurrence only, 88%), well distributed throughout the Atlantic Forest. For quantitative records, the most common sampling method was individual trees (71%), followed by plot sampling (19%), and transect sampling (10%). Angiosperms (81%) were the most frequently registered group, and Bromeliaceae and Orchidaceae were the families with the greatest number of records (27,272 and 21,945, respectively). Ferns and Lycophytes presented fewer records than Angiosperms, and Polypodiaceae were the most recorded family, and more concentrated in the Southern and Southeastern regions. Data on non-vascular plants and lichens were scarce, with a few disjunct records concentrated in the Northeastern region of the Atlantic Forest. For all non-vascular plant records, Lejeuneaceae, a family of liverworts, was the most recorded family. We hope that our effort to organize scattered epiphyte data help advance the knowledge of epiphyte ecology, as well as our understanding of macroecological and biogeographical patterns in the Atlantic Forest. No copyright restrictions are associated with the data set. Please cite this Ecology Data Paper if the data are used in publication and teaching events. © 2019 The Authors. Ecology © 2019 The Ecological Society of Americ

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

Use of Next-Generation Sequencing to Support the Diagnosis of Familial Interstitial Pneumonia

Familial interstitial pneumonia (FIP) is defined as idiopathic interstitial lung disease (ILD) in two or more relatives. Genetic studies on familial ILD discovered variants in several genes or associations with genetic polymorphisms. The aim of this study was to describe the clinical features of patients with suspected FIP and to analyze the genetic variants detected through next-generation sequencing (NGS) genetic testing. A retrospective analysis was conducted in patients followed in an ILD outpatient clinic who had ILD and a family history of ILD in at least one first- or second-degree relative and who underwent NGS between 2017 and 2021. Only patients with at least one genetic variant were included. Genetic testing was performed on 20 patients; of these, 13 patients had a variant in at least one gene with a known association with familial ILD. Variants in genes implicated in telomere and surfactant homeostasis and MUC5B variants were detected. Most variants were classified with uncertain clinical significance. Probable usual interstitial pneumonia radiological and histological patterns were the most frequently identified. The most prevalent phenotype was idiopathic pulmonary fibrosis. Pulmonologists should be aware of familial forms of ILD and genetic diagnosis

Use of Next-Generation Sequencing to Support the Diagnosis of Familial Interstitial Pneumonia

Familial interstitial pneumonia (FIP) is defined as idiopathic interstitial lung disease (ILD) in two or more relatives. Genetic studies on familial ILD discovered variants in several genes or associations with genetic polymorphisms. The aim of this study was to describe the clinical features of patients with suspected FIP and to analyze the genetic variants detected through next-generation sequencing (NGS) genetic testing. A retrospective analysis was conducted in patients followed in an ILD outpatient clinic who had ILD and a family history of ILD in at least one first- or second-degree relative and who underwent NGS between 2017 and 2021. Only patients with at least one genetic variant were included. Genetic testing was performed on 20 patients; of these, 13 patients had a variant in at least one gene with a known association with familial ILD. Variants in genes implicated in telomere and surfactant homeostasis and MUC5B variants were detected. Most variants were classified with uncertain clinical significance. Probable usual interstitial pneumonia radiological and histological patterns were the most frequently identified. The most prevalent phenotype was idiopathic pulmonary fibrosis. Pulmonologists should be aware of familial forms of ILD and genetic diagnosis