Incidence of Argas miniatus Koch in Matosinhos, Minas Gerais

Na sede do Município de Matosinhos, latitude sul 19° 33' 30" e longitude W.G. 40° 04' 45", Estado de Minas Gerais, Brasil, fêz-se um inquérito cujo escopo foi verificar a presença e a intensidade de infestação de Argas miniatus Koch (Acarina, Argosidae). Foram visitadas 41 propriedades, com criação de aves sem finalidades comerciais. Destas 46,3% apresentavam o ixodídeo. Apenas três proprietárias o conheciam e somente um o combateu, queimando o galinheiro. Esta é a primeira vez que se faz menção da presença desse argasídeo em Matosinhos.A survey was made in Matosinhos town, State of Minas Gerais, Brazil, to study the intensity of infestation of Argas miniatus Koch, Acarina, Argasidae. Fourty properties, in which chickens were raised on a non-commercial basis were found to be infested by this parasite at the range of 46.3%. Only three owners knew the parasite while only one knew to control it

Skills in Reading and Mathematics: Perceptions of Teachers about the Possible Impacts of Remote Teaching on Students of the Elementary School, from a Neuropsychopedagogical Perspective

This study analyzed impacts caused by the emergency implementation of distance education, during the COVID 19 Pandemic, through the perceptions of 6th grade teachers in public schools located in Baixada Fluminense, State of Rio de Janeiro. Teachers participated, among the subjects of Portuguese Language and Mathematics, through Google Forms, which made it possible to collect data from those who are on the front line, working directly with our students. Our data proved that the pedagogical losses that occurred during the implementation period of remote teaching are significant. Therefore, we point out paths that are already yielding excellent results through evidence shown in schools, in loco, with the inclusion of Neuropsychopedagogy protocols, the science of learning. The notes and study shown here about the impacts of remote teaching on the learning of our students in basic skills in the curricular components of reading and Mathematics, suggest a great need to intensify studies on the subject and propose a dialogue with the theoretical and methodological contributions of Neuropsychopedagogy

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

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

Characterization of interference thin films grown on stainless steel surface by alternate pulse current in a sulphochromic solution

The aim of this work was to characterize thin interference films grown on the surface of AISI 304 stainless steel for decorative purposes. Films were grown in a sulphochromic solution at room temperature by an alternating pulse current method. The morphology and chemical state of the elements in the films were investigated by field emission scanning electron microscopy (FESEM), atomic force microscopy (AFM), glow discharge optical emission spectrometry (GDOES), and infrared Fourier transform spectroscopy (FTIR). Depth-sensing indentation (DSI) experiments and wear abrasion tests were employed to assess the mechanical resistance of the films. The coloration process resulted in porous thin films which increased the surface roughness of the substrate. The interference films mainly consisted of hydrated chromium oxide containing iron. Increasing film thickness produced different colors and affected the mechanical properties of the coating-substrate system. Thicker films, such as those producing gold and green colors, were softer but more abrasion resistant

Coagulation-flocculation of anaerobically treated sugarcane stillage

Anaerobic digestion applied to stillage usually results in treatment performances. However, effluents from anaerobic reactors still present a residual polluting load due to the presence of organic recalcitrant compounds. Additional treatment methods, such as coagulation-flocculation, may be utilized to improve the final effluent quality. In this study, we assessed the processes of coagulation and flocculation for sugarcane stillage samples previously submitted to anaerobic digestion, aiming to obtain optimal conditions for the physicochemical treatment. Natural corn starch and ferric chloride were tested as coagulants. While starch was considered as not suitable for the treatment for the tested conditions, ferric chloride assays presented satisfactory results. The investigated parameters included coagulant solution dose, rapid mixing gradient and time, flocculation gradient and time, and sedimentation time. Their adjusted values at which better performances obtained were, respectively, 1.6 g L-1, 325 rpm, 10 s, 65 rpm, 20 and 20 min. The best color, turbidity, and chemical oxygen demand removal efficiencies were 95, 97, and 65%, respectively. Stillage pH variation to alkaline conditions did not result in improved removal efficiencies. Although relatively high removal efficiencies of constituents were obtained, the final effluent characteristics did not fit regulations of water reuse in the agriculture through fertigation. However, stillage can definitely become more easily managed if better final effluent quality control parameters are achieved, enabling for example effluents discharge in water bodies. © 2013 Copyright Balaban Desalination Publications