bluuebunny/crossref_metadata_2025 huggingface dataset:
PRODUCTION POTENTIAL OF HOLDINGS SPECIALIZING IN COW MILK PRODUCTION IN MACROREGIONS OF THE EUROPEAN UNION – A TYPOLOGICAL ANALYSIS
Authors: Baer-Nawrocka Agnieszka , Barczak Wioleta
Published: March 2020

The purpose of this paper was to classify FADN macroregions in the European Union into types by production potential of farms specializing in cow milk production in 2008 and 2017. The production of cow milk is one of the most important branches of animal production both in Poland and other European Union countries, therefore it is the subject of numerous publications. Most often, cow milk production is the subject of research in global terms, European Union countries or regional diversity in Poland. Relatively rarely does the subject of milk production cover a regional approach throughout the European Union. Due to dynamic changes in factors affecting milk production and, in particular, the abolition of the cow milk production quota system in EU countries in 2015, it is important to continue to monitor changes in the milk market, especially on the supply side. Hellwig’s method was employed in the calculation of the synthetic indicator of production potential for each macroregion in order to determine types. The study demonstrated that the most advantageous characteristics of the production potential of milk farms, in both years covered, were mostly reported by EU-15 macroregions located in western and northern Europe. Macroregions of new member countries, except Slovakia, were less competitive in terms of their potential. As demonstrated by this analysis, development disparities persist between milk farms located in different EU macroregions.
INTERNET IN THE PROMOTION AND SALE OF FOOD INDUSTRY PRODUCTS
Authors: Werenowska Agnieszka
Published: March 2020

The purpose of the article was to present the possibilities of using new media as an opportunity to promote food products. The study analyzed the literature on the subject and available reports. A strategic approach to promotion in every industry is one of the basic elements of creating a competitive advantage. This statement also applies to the broadly understood food industry. Its diversity requires deep analysis and adaptation to the specificity of individual food markets. The Internet presents a huge field of activity in the promotion of food industry products and contact with customers. The customers of the 21st century are aware recipients, who use modern media to obtain information and make shopping decisions. As the results of research show (E-grocery report), in Poland, already 16% of Internet users declare that they regularly buy food products via the Internet. Taking into consideration the fact that the generation determining demand in the near future will be representatives of the Z generation, i.e. those born after 1996, manufacturers must adapt their form of communication to the lifestyle and needs of such clients. It is estimated that, by 2020, they may constitute up to 40% of consumers. Due to the fact that the main communication channel with the X and Z generation are new media, it is becoming necessary to use this communication channel, while adapting in form to the manner of communication of representatives of this generation.
ASPECTS OF FARMLAND LEASE IN THE CONTEXT OF HOMESTEAD FUNCTIONING IN WARMIAN-MASURIAN VOIVODSHIP
Authors: Mioduszewski Jarosław
Published: March 2020

The aim of this research was to identify and assess the impact of chosen aspects of farmland lease on the functioning of homesteads in the Warmian-Masurian Voivodship. It was achieved through an opinion poll carried out with the use of questionnaires among 101 leaseholders and purchasers from the region of Warmia and Masuria. By the end of 2017, over 4.74 mln ha of land was purchased by the Agricultural Property Stock of the State Treasury (APAoST). The lands of the State Treasury were spatially diverse but the majority was located in north-west Poland. Firstly, they underwent a process of management privatization (administration and lease), and later proprietorial privatization (sale). At the end of 2017, 3,4m ha of purchased lands were permanently managed, the majority of which (80.4%) were sold. The Treasury still owns 1.4 mln ha of lands and leases 1.03 mln ha of it, 11.8% of which is located in the Warmia and Masuria Province. The decision on the form of cultivating the farmlands (lease/purchase) was determined financially (mostly mortgages and private funds), whereas their development and functioning were mostly determined by resources (area and quality of farmland, machinery park), price of farmland, profitability of production, and demand for farm produce. The possible development of homesteads was strongly impacted by a financial barrier, which resulted from the availability of funds needed, liabilities, legal-formal regulations regarding the purchase/lease of agricultural properties, lease rent, and instalments for purchased land.
Forecasting the demand for transport services on the example of a selected logistic operator
Authors: Grzelak Małgorzata , Borucka Anna , Buczyński Zbigniew
Published: March 2020

The number of shipments is growing every year, and as a result, new transport companies arise. The increase in competition requires from entrepreneurs to apply solutions increasing the level of services provided in order to best satisfy the needs of the customers. In this aspect, minimizing the time of deliveries is extremely important, and it can be achieved, for example, by implementing the cross-docking method. It consists in consolidation of cargo from different shipment locations that is delivered in the same direction. The main feature of the above method is to keep the labor intensity of operations and the interference in the cargo to the minimum.
The purpose of this article is to present a research on a logistic operator working based on a cross-docking warehouse with a capacity significantly lower than the average daily quantity of shipments handled. This requires both effective management of the available space and minimizing the time spent on manipulation activities. Therefore, it is important to know the expected number of parcels that are planned to be received and shipped on a given day in order to coordinate the work in the warehouse. It is possible to estimate it by using mathematical methods of forecasting. One of them - the multiple regression - is presented in this article. The calculations were made on the basis of collected empirical observations concerning orders for pallet spaces placed by customers. Such a forecast allows for improvement of the processes of planning and management of the possessed resources. It allows to adjust the number of warehouse workers or vehicles necessary for internal transport to the expected needs. Ultimately, it may translate into more efficient functioning not only of the surveyed branch, but also of the whole network.
Insight into the genetic architecture of back pain and its risk factors from a study of 509.000 individuals
Authors: Freidin Maxim B. , Freidin Maxim B. , Tsepilov Yakov A. , Tsepilov Yakov A. , Palmere Melody , Palmere Melody , Karssen Lennart C. , Karssen Lennart C. , Suri Pradeep , Suri Pradeep , Aulchenko Yurii S. , Aulchenko Yurii S. , Williams Frances M.K. , Williams Frances M.K.
Published: March 2020

Back pain (BP) is a common condition of major social importance and poorly understood pathogenesis. Combining data from the UK Biobank and CHARGE consortium cohorts allowed us to perform a very large genome-wide association study (total N = 5 509.070) and examine the genetic correlation and pleiotropy between BP and its clinical and psychosocial risk factors. We identified and replicated 3 BP-associated loci, including one novel region implicating SPOCK2/CHST3 genes. We provide evidence for pleiotropic effects of genetic factors underlying BP, height, and intervertebral disk problems. We also identified independent genetic correlations between BP and depression symptoms, neuroticism, sleep disturbance, overweight, and smoking. A significant enrichment for genes involved in the central nervous system and skeletal tissue development was observed. The study of pleiotropy and genetic correlations, supported by the pathway analysis, suggests at least 2 strong molecular axes of BP genesis, one related to structural/anatomical factors such as intervertebral disk problems and anthropometrics, and another related to the psychological component of pain perception and pain processing. These findings corroborate with the current biopsychosocialmodel as a paradigm for BP. Overall, the results demonstrateBP to have an extremely complex genetic architecture that overlapswith the genetic predisposition to its biopsychosocial risk factors. The work sheds light on pathways of relevance in the prevention and management of low BP.
Challenges and tensions in collaborative planning of a student-led course on sustainability education
Authors: Herranen Jaana , Tolppanen Sakari , Vesterinen Veli-Matti , Aksela Maija
Published: March 2020

AbstractStudent-led courses have been described as a promising approach to improve sustainability education. However, there is a lack of systematic studies about the benefits and challenges of such courses. This qualitative case study examines the challenges and tensions that arose in the planning of a student-led higher education course on sustainability education. The challenges were identified from the student course designers’ conversations and interviews using discourse analysis, focusing on their disagreements during planning. The identified challenges concerned sustainability and sustainability education, the course designers’ roles, and collaborative decision-making. To relate the challenges to wider discourses on these topics, five underlying tensions were recognized. These include the tension between participatory action and critical discussion approaches for sustainability education, and the tension between drive towards unanimity and agreeing to disagree in collaborative educational planning. Finally, it is discussed how, and to what degree, the challenges and tensions can and should be mitigated.
Rede Neo-Fuzzy-Neuron com Programação Genética Aplicada em Problemas de Previsão e Identificação de Sistemas Não-Lineares
Authors: Brás Glender , Silva Alisson
Published: March 2020

Este artigo propõe dois algoritmos baseados em Programação Genética (PG) para aprendizado em redes Neo-Fuzzy Neuron (NFN). As abordagens utilizam a PG para gerar as regras associadas a cada entrada, criando e ajustando as funções de pertinência, e um método baseado no Gradiente para ajuste de pesos. Os modelos propostos são avaliados e comparados com modelos alternativos em problemas de previsão e identificação de sistemas não lineares. Os resultados obtidos mostram que os modelos propostos são promissores e competitivos com modelos alternativos do estado da arte.
Improving distributed vector representation of short and noisy texts in the context of online classification
Authors: Silva Renato , Lochter Johannes , Almeida Tiago
Published: March 2020

The classification of messages generated by users on social networks and other Internet platforms is challenging because they are often short and full of slang, abbreviations, and idioms, which hinders the feature extraction. To address this problem, this study proposes a data augmentation technique to increase the number of data in order to improve the quality of the textual representation model and, consequently, the performance in the classification. The proposed technique is evaluated in the online classification of sentiments in Twitter messages. The experiments were carefully performed and a statistical analysis of the results indicated that the data augmentation is effective in online classification of short and noisy text messages.
Adoção da seleção de características como mecanismo antiphishing: aplicabilidade e impactos
Authors: Barros Mateus , Silva Carlo , Miranda Péricles
Published: March 2020

Phishing websites são páginas falsas que enganam as vítimas, passando-se por sites legítimos de bancos ou empresas para obterem informações pessoais sem o consentimento delas. Embora algoritmos de aprendizagem tenham sido largamente utilizados para a detecção de phishing, não existe um consenso sobre que atributos são relevantes para uma melhor descrição de uma página maliciosa. Este artigo apresenta um estudo experimental que investiga e analisa o grau de relevância de atributos em diferentes bases de dados de phishing. Os resultados mostraram que uma metodologia adequada para a seleção de atributos é capaz de reduzir o custo computacional do processo de classificação, e ainda alcançar resultados satisfatórios de acurácia e F1 Score.
Genetic algorithms and multiprocessor task scheduling: A systematic literature review
Authors: Silva Eduardo , Gabriel Paulo
Published: March 2020

This paper reports a systematic review of the literature about genetic algorithms applied to the multiprocessor task scheduling problem. After defining a protocol with the main rules of this review, the research was performed considering journal papers published between 1990 and 2018. At the end of this process, 37 works were recovered and analyzed. By performing a meta-analysis, a variety of information was extracted and summarized, including impact factor, Eigenfactor score, scenarios considered, optimization metrics, volume of citations, and others.
Evaluating Vector Representations from User's Reviews in a Recommendation Task
Authors: Tonon Vitor , Silva Tiago , Silva Vínicius , Pereira Gean , Rezende Solange
Published: March 2020

The recommendation task is a prominent and challenging area of study in Machine Learning. It aims to recommend items such as products, movies, and services to users according to what they have liked in the past. In general, most of the recommendation systems only consider structured information. For instance, in recommending movies to users they might use features such as genre, actors, and directors. However, unstructured data such as users' reviews may also be considered, since they can aggregate important information to the recommendation process, improving the performance of recommendation systems. Thus, in this work, we evaluate the use of text mining methods to extract and represent relevant information about user reviews, which were used alongside with rating data, as input of a content-based recommendation algorithm. We considered three different strategies for this purpose, which were: Topics, Embeddings and Relevant Embeddings. We hypothesized that using the considered strategies, it is possible to create more meaningful and concise representations than the traditional bag-of-words model, and yet, increase the performance of recommendation systems. In our experimental evaluation, we confirmed such a hypothesis, showing that the considered representations strategies are indeed very promising for representing user reviews in the recommendation process.
Prediction of Hospital Admissions from Air Pollutant Data
Authors: Jr. Marcelo , Pozza Simone , Coelho Guilherme
Published: March 2020

Diversos trabalho na literatura indicam que poluentes atmosféricos são nocivos à saúde. Sendo assim, neste trabalho buscou-se verificar a possibilidade de prever, a partir de dados de concentração de poluentes atmosféricos e com 24 h de antecedência, o número de internações hospitalares associadas a doenças respiratórias. Para isso, foram utilizados Extreme Learning Machines (ELMs) como preditores e experimentos foram realizados com dados referentes à cidade de Campinas (SP). Os resultados mostraram que, apesar do uso de dados de alguns poluentes específicos levarem a menores erros de previsão, os melhores resultados ainda foram obtidos utilizando-se apenas a série histórica de internações hospitalares como entrada para as ELMs.
Relevant Traffic Light Localization via Deep Regression
Authors: Freitas Rafael De , Paixão Thiago , Berriel Rodrigo , Souza Alberto De , Badue Claudine , Oliveira-Santos Thiago
Published: March 2020

Artificial intelligence advances have an important role on self-driving cars development, such as assisting the recognition of traffic lights. However, when relying on images of the scene alone, little progress was observed on selecting the traffic lights defining guidance to the car. Common detection approaches rely on additional high-level decision-making process to select a relevant traffic light. This work address the problem by proposing a deep regression system with an outliers resilient loss to predict the coordinates of a relevant traffic light in the image plane. The prediction can be used as a high-level decision-maker or as an assistant to a cheaper classifier to work on a region of interest. Results for European scenes show success in about 88% of the cases.
Identificação Automática de Postagens Relacionadas ao Uso Através de Modelos de Aprendizagem Profunda
Authors: Oliveira Hismael De , Arruda Alexandre , Mendes Marilia
Published: March 2020

Algumas postagens em Sistemas Sociais (SS) podem trazer informações significativas sobre o uso daquele SS, estas chamamos de Postagens Relacionadas ao Uso (PRU). PRU é um conceito importante para a avaliação de sistemas. Existem ferramentas capazes de identificar as PRUs, porém possuem menor precisão quanto as classificações manuais. Tendo em vista este problema, o presente trabalho busca investigar essa deficiência utilizando modelos de aprendizagem profunda para a identificação automática de PRUs nos SS, neste caso a rede social Twitter. Nos testes realizados nosso modelo possuiu alta precisão de classificação quando comparado com outros utilizados para esta tarefa.
Will I Remain Popular? A Study Case on Spotify
Authors: Araujo Carlos , Cristo Marco , Giusti Rafael
Published: March 2020

Atualmente, as plataformas de streaming on-line são a forma mais importante de consumo de música. Neste artigo, apresentamos um modelo para prever se uma música popular no Spotify permanecerá popular após um determinado peróodo de tempo.  O Spotify é o segundo maior serviço global de streaming. Se  uma  música  for  popular  nessa  plataforma,  ela  garantirá  um bom retorno financeiro para o artista e sua gravadora. Abordamos o problema como uma tarefa de classificação e empregamos classificadores baseados em informações  prévias  do  ranking  Top  50  Global  da  plataforma.  O classificador de Máquina de Vetores de Suporte (SVM) com kernel linear alcançou os melhores resultados. Também verificamos se informações acústicas podem fornecer  recursos úteis  para  esse  problema.  Fizemos uma série de rodadas  declassificação, onde os resultados de uma rodada eram utilizados como entradada rodada posterior. Nossos resultados mostram que os dados prévios são suficientes para prever se uma música permanecerá no Top 50 Global com dois meses de antecedência, alcançando precisão, valor preditivo negativo, revocação, especificidade e valor-F1 acima de 70% para essa tarefa. Ademais,  resultados  até  6,60%  superiores  puderam  ser  obtidos  ao  utilizar  as  características acústicas das faixas.
A Multi-document Summarization System for News Articles in Portuguese using Integer Linear Programming
Authors: Gomes Laerth , Oliveira Hilário De
Published: March 2020

Automatic Text Summarization (ATS) has been demanding intense research in recent years. Its importance is given the fact that ATS systems can aid in the processing of large amounts of textual documents. The ATS task aims to create a summary of one or more documents by extracting their most relevant information. Despite the existence of several works, researches involving the development of ATS systems for documents written in Brazilian Portuguese are still a few. In this paper, we propose a multi-document summarization system following a concept-based approach using Integer Linear Programming for the generation of summaries from news articles written in Portuguese. Experiments using the CSTNews corpus were performed to evaluate different aspects of the proposed system. The experimental results obtained regarding the ROUGE measures demonstrate that the developed system presents encourage results, outperforming other works of the literature.
A solution for the Elevators Group Dispatch by Multiagent Reinforcement Learning
Authors: Memória Jordão , Maia José
Published: March 2020

In this work, a modeling and algorithm based on multiagent reinforcement learning is developed for the problem of elevator group dispatch. The main advantage is that, along with the function approximation, this multi-agent solution leads to reduction of the state space, allowing complex states to be addressed with a synthesizing evaluation function. Each elevator is considered an agent that have to decide about two actions: answer or ignore the new call. With some iterations, the agents learn the weights of an evaluation function which approximate the state-action value function. The performance of solution (average waiting time - AWT), shown varying the traffic pattern, flow of people, number of elevators and number of floors, is comparable to other current proposals reported in the literature.
Modelos de deep learning para classificação de gases detectados por matrizes de sensores nariz artificial
Authors: Araujo Ismael , Gamboa Juan , Silva Adenilton
Published: March 2020

O uso de técnicas como Deep Learning tem se mostrado promissor para problemas de classificação, principalmente em relação a classificação de imagens. Classificação de gases detectados por um nariz artificial é mais uma das áreas em que técnicas de Deep Learning podem ser utilizadas para aprimoramento de classificação. O sucesso na tarefa de classificação de gases pode ser vantajoso tanto para controle de qualidade, quanto para prevenção de acidentes. Neste trabalho são apresentados modelos de Deep Learning voltados especificamente à tarefa de classificação de gases.
Fatiamento em Reconhecimento Facial: Uma Investigação Baseada em Unidades de Ação para possíveis melhorias através da seleção de fatias da face em Nuvens de Pontos 3D
Authors: Martins Patricia , Soares José , Thé George
Published: March 2020

Neste artigo e proposta uma investigação para fatiamento de nuvens de pontos 3D, que representam rostos, dentro do problema de reconhecimento de faces. Para isso, e feita uma comparação entre os resultados de classificação com e sem fatiamento das faces, utilizando características geométricas no processo de extração de informação. Também foram comparados dois tipos de segmentação em subnuvens, o fatiamento Triaxial e o fatiamento em Pizza com Superposição - aqui proposto. O objetivo das comparações é investigar se a seleção de regiões específicas da face 3D pode aprimorar os resultados da classificação. Os resultados mostram-se promissores, indicando que um refinamento da técnica pode gerar uma classificação de indivíduos robusta a variações da face.
Uma abordagem baseada em letras para a descoberta de conhecimento da música brasileira: o sertanejo como um estudo de caso
Authors: Silva Junior Jorge , Rossi Rafael , Lobato Fabio
Published: March 2020

Técnicas computacionais podem ser usadas para identificar tendências e padrões musicais, ajudando as pessoas a filtrar e selecionar músicas de acordo com suas preferências. Nesse cenário, pesquisas afirmam que o futuro da música permeia a inteligência artificial, que desempenhará o papel de compor músicas que melhor atendam aos gostos dos consumidores. Portanto, extrair padrões desses dados é fundamental e pode contribuir para o ecossistema da indústria da música. Essas técnicas são bem conhecidas no campo da recuperação de informações musicais. Eles consistem na extração das características de áudio (conteúdo) ou letra (contexto), sendo o último preferível por exigir menor custo computacional e apresentar melhores resultados. No entanto, ao observar o estado da arte, verificou-se a falta de antecedentes que investiguem a extração de padrões musicais brasileiros por meio de letras. Nesse sentido, o objetivo principal deste trabalho é preencher essa lacuna por meio de técnicas de mineração de texto, analisando a classificação das músicas nos subgêneros do sertanejo. Essa análise é baseada em letras e extração de conhecimento para explicar como os subgêneros diferem.
Um Sistema Automático de Classificação de Folhas Baseado em Características da Forma
Authors: Britto Larissa , Pacífico Luciano , Ludermir Teresa
Published: March 2020

As plantas são peças indispensáveis para nossos ecossistemas, provendo recursos insubistituíveis para os animais. Porém, a identificação de espécies de plantas é uma tarefa difícil, e a maioria das pessoas não esté apta ao reconhecimento correto de muitas espécies de plantas. Neste trabalho, uma abordagem para o reconhecimento de espécies de plantas é desenvolvida, baseada na extração de características de forma das imagens de suas folhas. Uma base de dados de plantas medicinais é proposta, e quatro classificadores são testados como módulo de reconhecimento do sistema automático proposto. Os resultados experimentais mostram que os melhores classificadores são capazes de obter uma acurácia média acima de 98% na base de dados proposta.
Self-Organizing Fuzzy Rule-Based Approach for Dealing with the Classification of Indoor Environments for IoT Applications
Authors: Dias Ualison , Hell Michel , Medeiros Álvaro , Silveira Daniel , Aguiar Eduardo De
Published: March 2020

Atualmente, grande parte dos sensores utilizados em Internet das Coisas adota tecnologia sem fio, a fim de facilitar a construção de redes de sensoriamento. Neste sentido, a classificação do tipo de ambiente no qual estes sensores estão localizados exerce um importante papel no desempenho de tais redes de sensoriamento, uma vez que pode ser utilizada na determinação de níveis mais eficientes de consumo de energia dos sensores que as compõe. Assim, neste trabalho é apresentada uma abordagem baseada em Classificadores Fuzzy Auto-organizáveis para a classificação de ambientes internos a partir de medições em tempo real do sinal de radiofrequência de uma rede de sensoriamento sem fio em um ambiente real. Os resultados experimentais apresentados mostram que a abordagem proposta obteve alto desempenho com baixo custo computacional na solução do problema apresentado.
Análise de Sentimentos para Revisões de Aplicativos Mobile em Português Brasileiro
Authors: Britto Larissa , Pacífico Luciano
Published: March 2020

Mesmo com a crescente popularidade da Análise de Sentimentos (AS), a quantidade de recursos e ferramentas disponíveis para o português brasileiro ainda é limitada. Neste trabalho serão descritas as etapas para o desenvolvimento de uma base de dados em português no domínio de aplicativos móveis, para aplicações em AS. Além disso, a base proposta será utilizada para a comparação dos principais métodos utilizados na literatura de AS, como as Redes Neurais Recorrentes.
Análise de Performance do PUSH em Conexões HTTP/2 no Carregamento de Páginas Web
Authors: de Oliveira Igor Nogueira , Davison Wesley , Sadok Djamel , Endo Patricia Takako
Published: March 2020

Recentemente, o protocolo HTTP foi atualizado e recebeu diversas modificações, direcionadas principalmente a melhorias na utilização dos recursos da rede. Dentre estas melhorias, pode-se citar a adição do recurso push, que permite que o servidor responda a uma solicitação com mais de um recurso simultaneamente. Este trabalho apresenta uma análise de desempenho do recurso push no transporte de páginas web em conexões HTTP/2. Para tanto, foram realizados experimentos em um cenário real, utilizando TDT (Total Download Time) como métrica de análise, e requisições de páginas web com diferentes quantidades e tamanhos de objetos.
Management of Tourism Crisis in the Middle East
Authors: Jawabreh Omar
Published: March 2020

This study looks for to recognize the realism of management of tourism crisis in Jordan (Amman Hotels’ Bombing case study). In order to show the role of the management and its effects in facing the tourism crisis in Jordan, the researcher will try to handle a group of points: finding a special concept for tourism crisis, crisis generative environment, management of tourism crisis, and studying Jordan management of the Hotel bombing in Amman. To clarify and achieve the objectives of the research, the researcher adopted the descriptive analytical approach to what is stated in the most important books and references Arab and foreign periodicals, statistics, and official reports relating to the ethics of the research. It is recommended, in this study, to provide training opportunities for all people who have a role in the management of tourism crisis especially in the communication sector, the massive presence of police in the tourism site, hotels, and all the tourism places under the condition of not being seen, and to provide the qualified policemen with modern defensive weapons.
Vulnerabilidade natural à contaminação do aquífero Alter do Chão na área urbana de Manaus, Amazonas, Brasil
Authors: Duarte Miqueias Lima , Costa Heron Salazar , Silva Tatiana Acácio da , Santos Mariano Vieira dos
Published: March 2020

A utilização dos recursos hídricos subterrâneos cresce em função do crescimento populacional e da atividade produtiva, aumentando a demanda por água de qualidade, ao mesmo tempo em que crescem os riscos de sua contaminação. O presente estudo avaliou a vulnerabilidade à contaminação do aquífero Alter do Chão na área urbana do município de Manaus, com a aplicação do método GOD (Groundwater occurrence Overall Lithology of the unsaturated zone, Depth of the water table). O emprego do método possibilitou o mapeamento de áreas diferenciadas nas três classes de vulnerabilidade. A baixa vulnerabilidade à contaminação foi predominante (0,41%), seguida pela média vulnerabilidade (0,35%) e alta vulnerabilidade à contaminação (0,24%). A distribuição das classes de alta vulnerabilidade na área de estudo é motivo de preocupação, pelo potencial de contaminação associado o atual uso e ocupação do solo, também em função da direção do fluxo subterrâneo.
Alimento para los dioses, alimento para los hombres”. Ritos y modos de cocción en el México nahua de hoy
Authors: Hémond Aline
Published: March 2020

Se estudiarán algunas comidas rituales elaboradas durante los ritos del ciclo agrícola de una localidad de la región nahua del sur-oeste mexicano del estado de Guerrero. Se analizarán en particular dos métodos de cocción privilegiados de los platillos de la comida sacrificial a base de masa de maíz y de carne: en caldo y al vapor. Se quiere desarrollar la idea de que el modo de cocción, en particular la distinción entre lo cocido-humedo (p.ej., el caldo) y lo cocido-seco (p.ej., tostado), descansa sobre modalidades simbólicas y semánticas que permiten asegurar una buena comunicación de la súplica de los hombres hacia las potencias no-humanas. Por otra parte, dentro de los alimentos rituales preparados en caldo, existen diferencias de preparación de la carne del guajolote, alimento sacrificial por excelencia. Estos procedimientos disímiles perfilan una línea divisoria en el sistema simbólico: por un lado, quedan las ofrendas destinadas a las entidades no-humanas geoclimáticas, responsables de las buenas cosechas y de la protección del pueblo; por otro lado, tenemos las ofrendas que permiten la comensalidad, la colaboración de los humanos vivos asociados en torno a la repartición de las comidas. En conclusión, veremos que el modo de cocción que privilegia lo líquido, lo muy caliente y los alimentos de color verde se concibe en analogía con el ciclo del agua y el ciclo de evapotranspiración solar/terrestre. Asimismo, seleccionar los ingredientes según su procedencia (criolla o forastera) permite la construcción de la autoctonía y el control de los terrenos por los grupos rituales locales (mayordomías).
Antagonistic regulation by insulin-like peptide and activin ensures the elaboration of appropriate dendritic field sizes of amacrine neurons
Authors: Luo Jiangnan , Ting Chun-Yuan , Li Yan , McQueen Philip , Lin Tzu-Yang , Hsu Chao-Ping , Lee Chi-Hon
Published: March 2020

Establishing appropriate sizes and shapes of dendritic arbors is critical for proper wiring of the central nervous system. Here we report that Insulin-like Peptide 2 (DILP2) locally activates transiently expressed insulin receptors in the central dendrites of Drosophila Dm8 amacrine neurons to positively regulate dendritic field elaboration. We found DILP2 was expressed in L5 lamina neurons, which have axonal terminals abutting Dm8 dendrites. Proper Dm8 dendrite morphogenesis and synapse formation required insulin signaling through TOR (target of rapamycin) and SREBP (sterol regulatory element-binding protein), acting in parallel with previously identified negative regulation by Activin signaling to provide robust control of Dm8 dendrite elaboration. A simulation of dendritic growth revealed trade-offs between dendritic field size and robustness when branching and terminating kinetic parameters were constant, but dynamic modulation of the parameters could mitigate these trade-offs. We suggest that antagonistic DILP2 and Activin signals from different afferents appropriately size Dm8 dendritic fields.
An abundant quiescent stem cell population in Drosophila Malpighian tubules protects principal cells from kidney stones
Authors: Wang Chenhui , Spradling Allan C
Published: March 2020

Adult Drosophila Malpighian tubules have low rates of cell turnover but are vulnerable to damage caused by stones, like their mammalian counterparts, kidneys. We show that Drosophilarenal stem cells (RSCs) in the ureter and lower tubules comprise a unique, unipotent regenerative compartment. RSCs respond only to loss of nearby principal cells (PCs), cells critical for maintaining ionic balance. Large polyploid PCs are outnumbered by RSCs, which replace each lost cell with multiple PCs of lower ploidy. Notably, RSCs do not replenish principal cells or stellate cells in the upper tubules. RSCs generate daughters by asymmetric Notch signaling, yet RSCs remain quiescent (cell cycle-arrested) without damage. Nevertheless, the capacity for RSC-mediated repair extends the lifespan of flies carrying kidney stones. We propose that abundant, RSC-like stem cells exist in other tissues with low rates of turnover where they may have been mistaken for differentiated tissue cells.
Self-concept in poor readers: a systematic review and meta-analysis
Authors: McArthur Genevieve M. , Filardi Nicola , Francis Deanna A. , Boyes Mark E. , Badcock Nicholas A.
Published: March 2020

Background

The aims of this systematic review and meta-analyses were to determine if there is a statistically reliable association between poor reading and poor self-concept, and if such an association is moderated by domain of self-concept, type of reading impairment, or contextual factors including age, gender, reading instruction, and school environment.

Methodology

We searched 10 key databases for published and unpublished studies, as well as reference lists of included studies, and studies that cited included studies. We calculated standardised mean differences (SMDs) and 95% confidence intervals for one primary outcome (average self-concept) and 10 secondary outcomes (10 domains of self-concept). We assessed the data for risk of bias, heterogeneity, sensitivity, reporting bias, and quality of evidence.

Results

Thirteen studies with 3,348 participants met our selection criteria. Meta-analyses revealed statistically significant SMDs for average self-concept (−0.57) and five domains of self-concept (reading/writing/spelling: −1.03; academic: −0.67; math: −0.64; behaviour: −0.32; physical appearance: −0.28). The quality of evidence for the primary outcome was moderate, and for secondary outcomes was low, due to lack of data.

Conclusions

These outcomes suggest a probable moderate association between poor reading and average self-concept; a possible strong association between poor reading and reading-writing-spelling self-concept; and possible moderate associations between poor reading and self-concept in the self-concept domains of academia, mathematics, behaviour, and physical appearance.
The complete mitochondrial genome of Dysgonia stuposa (Lepidoptera: Erebidae) and phylogenetic relationships within Noctuoidea
Authors: Sun Yuxuan , Zhu Yeshu , Chen Chen , Zhu Qunshan , Zhu Qianqian , Zhou Yanyue , Zhou Xiaojun , Zhu Peijun , Li Jun , Zhang Haijun
Published: March 2020

To determine the Dysgonia stuposa mitochondrial genome (mitogenome) structure and to clarify its phylogenetic position, the entire mitogenome of D. stuposa was sequenced and annotated. The D. stuposa mitogenome is 15,721 bp in size and contains 37 genes (protein-coding genes, transfer RNA genes, ribosomal RNA genes) usually found in lepidopteran mitogenomes. The newly sequenced mitogenome contained some common features reported in other Erebidae species, e.g., an A+T biased nucleotide composition and a non-canonical start codon for cox1 (CGA). Like other insect mitogenomes, the D. stuposa mitogenome had a conserved sequence ‘ATACTAA’ in an intergenic spacer between trnS2 and nad1, and a motif ‘ATAGA’ followed by a 20 bp poly-T stretch in the A+T rich region. Phylogenetic analyses supported D. stuposa as part of the Erebidae family and reconfirmed the monophyly of the subfamilies Arctiinae, Catocalinae and Lymantriinae within Erebidae.
The Attitude of Vegetable Growers towards Mitigating the Adverse Effects of Agricultural Chemicals
Authors: Manunayaka G. , Ganesamoorthi S. , Patil N. D. Chethan , Bellagi Rahul D.
Published: March 2020

India is the world's second-largest producer of vegetables next to China, but the annual loss of fresh vegetables on an average is about 12 per cent in India which is significantly affecting the agricultural economy. Thus, crop protection is very much essential to prevent losses and feed the growing population. Chemical crop protection in India began in the year 1947-48 with the introduction of Benzene Hexa Chloride (BHC). Today India is the fourth largest producer of pesticide in the world. But over the years pesticides are being used more indiscriminately and unscientifically which has led to a negative impact on humans, soil, water and the environment as a whole. Due to the unscientific pesticide application, the pests gradually develop resistance to the poison that normally kills them. Even with all these ill-effects, it is inevitable to use pesticides to grow the crops and therefore they can be called as a necessary evil. The present study was conducted in Kolar district of Karnataka state in India during 2018-19 to ascertain the attitude of vegetable growers towards mitigating the ill-effects of agricultural chemicals. The data was collected from 120 vegetable growers using a pretested interview schedule. It was found that more than half of the vegetable growers (52.50%) had highly favourable attitude towards mitigating the ill-effects of agricultural chemicals; sixty per cent of the vegetable growers were undecided whether to spray pesticides in the opposite direction of the wind or along the direction of the wind. The study facilitates the agriculture and horticulture departments to train farmers enabling them to safely use, handle and store the agricultural chemicals.
Diagnosis and Risk Factors of Latent Tuberculosis Infection among Healthcare Workers Using Whole Blood Human Interferon-gamma Release Assay and Tuberculin Skin Testing
Authors: Umo A. N. , Akinjogunla O. J. , Umoh N. O. , Uzono G. E.
Published: March 2020

This study established the diagnosis and risk factors of latent tuberculosis infection (LTBI) among health-care workers in an endemic population using Tuberculin skin test (TST) and Quantiferon TB-gold. A total of 609 Healthcare workers from tuberculosis treatment facilities in Akwa Ibom State, Nigeria were studied. The Interferon-gamma release assay was performed using 3ml of whole blood by ELISA according to the manufacturer’s instruction (Cellestis Ltd., Carnegie, Australia) after which 0.1 ml of 5 tuberculin units of Purified Protein Derivative (PPD) was administered intra-dermally to each subject. TST results were read after 72 hours by measuring the size of indurations in millimetres. Data were analysed using SPSS version 17 (SPSS Inc., Chicago, Illinois). At the threshold of 10 mm, the prevalence of LTBI by TST was 45.8% and 24.8% at the IGRA diagnostic value of ≥ 0.351 IU. Laboratory staff and ward orderlies as well as being in service for >10 years, were more significantly associated with LTBI. A moderate agreement of 76.7%, k = 0.51 was obtained between TST at 10 mm, and QFT. Neither previous exposure to TST nor BCG vaccination affected the prevalence of LTBI in the study population. The difference of 54% prevalence of LTBI between TST and QFT may be due to non-tuberculous mycobacterium (NTM) since TST is non-specific. This may have grave implications of drug toxicity and development of resistance to anti-TB drug among individuals harbouring NTM, but receiving anti-TB medication. The 76.7% agreement between the two tests is an indication that the 10 mm cut-off induration for TST is still relevant in the diagnosis of LTBI.
Pharmacotherapeutic Activity of Allium sativum (Garlic) Bulb against Gram-positive and Gram-negative Bacteria
Authors: Airaodion Augustine I. , Ngwogu Ada C. , Ngwogu Kenneth O. , Ekenjoku John A. , Megwas Anthony U.
Published: March 2020

Background: Emergence of methicillin drug resistance is evident and has become a global challenge. Seeking for alternative antibiotics that are new, natural, plant based, cost eﬀective and less toxic is the recent task for global health.

Aim: This study is aimed at assessing the pharmacotherapeutic activity of Allium sativum (Garlic) bulb against gram-positive and gram-negative bacteria.

Materials and Methods: Fresh A. sativum bulbs were purchased from a local market in Ibadan, Nigeria and were identified by a botanist. They were cut into small pieces and mashed in a laboratory with a mortar and pestle and the fluid squeezed out of the resultant slurry. The antibacterial activity of the juice was determined by diffusion method. Nutrient agar medium was prepared using standard method. Pure cultures of Coliform bacillus, Staphylococcus epidermidis, Streptococcus viridians, Salmonella typhi and Escherichia coli were obtained from the Department of Veterinary Microbiology and Parasitology, Federal University of Agriculture, Abeokuta, Nigeria. The juices were serially diluted to obtain 1.0%, 0.5%, 0.25% and 0.125% solutions in sterile test tubes. Sterilized 9 mm filter paper disc soaked in the diluted juice were placed on the plate and incubated for 24 hours at room temperature. The plates were examined for clear zones of inhibition. Presence of zones of inhibition indicated activity.

Results: The results showed that A. sativum bulb has antibacterial potential against all the bacteria used in this study and also exhibited inhibitory activity against them.

Conclusion: The result of this present study showed that A. sativum juice has high range of antibacterial potential against both gram positive (S. epidemidis and S. viridans) and gram negative bacteria (C. bacillus, E. coli and S. typhi). However, the extract has a greater inhibitory activity against gram positive bacteria than gram negative bacteria.
New Modified Adomin Decomp osition Metho d for Boundary Value Problems of Higher-order Ordinary Differential Equation
Authors: Al-Rabahi Zainab Ali Ab du , Hasan Yahya Qaid
Published: March 2020

This study will present a new modified differential operator for solving third-order boundary value problems into higher-order ordinary differential equation. We found the differential operator for new three inverse operator which can be applied for solving equations at more than one type in different conditions. We put a detailed plan for five non-linear examples from a high-order, we get dynamic and quickly to the exact solution.
A Study on Heavy Metal Ion Adsorption, Antibacterial and Anticancer Activities of Sawdust Chitosan Activated Carbon
Authors: Kayalvizhi K. , Alhaji N. M. I. , Saravanakkumar D. , Ayeshamariam A.
Published: March 2020

Sawdust-Chitosan Composite beads (SDCCB), a low-cost non-conventional surface modified activated carbon, has been used for the efficient removal of Cu(II) ions from aqueous solutions. Surface morphology of the sample has been characterized by XRD, SEM, EDAX and FTIR analyses. Batch experiments have been conducted spectrophotometrically in order to determine the maximum adsorption capacity and influence of physicochemical parameters. The experimental data has been fitted with various isotherm and kinetic models to predict the conditions for maximum adsorption. The activation parameters evaluated for this adsorption process propose the adsorption mechanism as feasible, spontaneous, endothermic and increased randomness. Also, the antimicrobial and anticancer activities of SDCCB have been screened by disk diffusion method and MTT assay, respectively.
Isolation, Characterization and Antimicrobial Activity of Quercetin-3-O-(2”-α-Methyl-p-Coumaryl)-Rutinoside from Delonix elata Flowers
Authors: Rajeshkanna A. , Senthamilselvi M. M. , Prabhakaran D.
Published: March 2020

Aims: To investigate the isolated flavonoid compound, characterization and antimicrobial activity of Quercetin-3-O-(2”-α-methyl-p-Coumaryl)-rutinoside from Delonix elata flowers.

Place and Duration of Study: The research work was carried out at Research laboratory, Department of chemistry, Periyar E.V.R College, Trichy-23, between May 2016 to January 2018.

Methodology: Extraction and fractionation was carried out from the solvents of ethanol, benzene, petroleum ether, diethyl ether and ethyl acetate. The structure of the isolated compound (Quercetin-3-O-(2”-α-methyl-p-Coumaryl)-rutinoside) was elucidated through their physical and chemical methods. The isolated compound was characterized by using various spectral data such as UV, 1H NMR, 13C NMR, MS. Four bacterial strains Salmonella typhi, Escherichia coli, Enterococcus faecalis, Bacillus cereus and two fungal strains Curvularia lunata and Candida albicans were tested by using disc diffusion method.

Conclusion: The present study was concluded that the dry sample of ethyl acetate fraction of Delonix elata flowers was Quercetin-3-O-(2”-α-methyl-p-Coumaryl)-rutinoside and it possesses effective antimicrobial activity against bacteria and fungi.