bluuebunny/crossref_metadata_2025 huggingface dataset:
Discovering code smells in Javascript software using clustering techniques
Authors: Sales Luan , Macedo Charles , Valdivia-Delgado Karina
Published: March 2020

A presença de code smells em projetos de software têm consequências negativas no que diz respeito a coesão e manutenibilidade do código. Assim sendo, a análise de técnicas usadas para descoberta e detecção de code smells de maneira automática é um tópico cada vez mais explorado. Uma ferramenta semi-automática que permite descobrir padrões de defeitos e eventuais code smells em código JavaScript é a BugAID. O objetivo deste trabalho foi contribuir com a ferramenta BugAID na tarefa de descoberta de code smells comuns no desenvolvimento de software JavaScript através da melhoria na identificação de palavras associadas a código refatorado nas mensagens dos commits e com a implementação do módulo BE++. O módulo BE++ mostrou-se eficaz na identificação de code smells que envolvem pequenas alterações no código, descobrindo 5 code smells comuns dentro do grupo de refatorações. Esses code smells são candidatos à inclusão em ferramentas de detecção de code smells para prevenção de problemas no desenvolvimento de software JavaScript.
Classificação de Valores Humanos em Redes Sociais Usando Aprendizagem de Máquina
Authors: Correia Sergio , Malheiros Yuri , Nascimento Anderson , Gouveia Valdiney
Published: March 2020

O Twitter recebe milhões de mensagens diariamente de diferentes usuários e regiões do mundo. Estas mensagens contêm opiniões, avaliações e sentimentos, tornando o Twitter uma plataforma apropriada para diversos tipos de estudos. Assim, pode-se usar esta rede social para descobrir informações importantes sobre as pessoas, por exemplo, estado emocional, suas opiniões sobre produtos, preferência política, etc. Este trabalho tem como objetivo criar e avaliar modelos para classificação de valores humanos, um conceito da psicologia que define os princípios guia das pessoas. Foram testados três classificadores de aprendizagem de máquina, treinados usando mensagens do Twitter, para prever respostas de um questionário usado por psicólogos para determinar valores humanos. O melhor resultado alcançou uma acurácia de 60,08%.
Supervised Methods Applied to the Construction of a Vision System for the Classification of Cocoa Beans in the Cut-Test
Authors: Antunes Felipe , Canuto Anne , Bedregal Benjamin , Palmeira Eduardo , Silva Iaslan
Published: March 2020

Supervised machine learning methods, also known as classification algorithms, have been widely used in the literature for many classification tasks. In this context, some aspects of these algorithms, as the used attributes used and the form they were built, have a direct impact in the system performance. Therefore, in this paper, we evaluate the application of classification algorithms, along with attribute selection, to propose an improved version of a vision system that performs the classification of cocoa beans. The main aim of this investigation is to improve the performance of a cocoa classification system that aims at helping farmers to classify the different cocoa beans based on images of these beans.
Evaluating Ontology Development from the Extraction of Noun Phrases
Authors: Oliveira Alcione , Moreira Alexandra , Filho Jugurta
Published: March 2020

Existem vários métodos para construir uma ontologia. Entre o métodos automáticos, uma abordagem é a extração de termos de documentos de domínio e sua extração subsequente. Nesse caso, a primeira etapa do processo é a extração de sintagmas nominais que são possíveis candidatos a serem componentes da terminologia da área de interesse. Este artigo descreve uma ferramenta automática para o idioma português do Brasil que extrai sintagmas nominais que podem ser adotadas como termos para um determinado domínio. Além disso, o sistema associa os termos extraídos a uma ontologia de nível superior, o que resulta em uma ontologia inicial que pode ser refinada posteriormente. Para acoplar à ontologia, foi utilizado um termo âncora, sendo demonstrado estatisticamente que o uso do termo âncora leva a uma melhoria no desempenho do sistema. A ferramenta descrita neste artigo foi usada para selecionar termos a serem usados em uma ontologia para o domínio do setor eleétrico. Além disso, foi avaliada a precisão na criação da ontologia. A técnica conseguiu gerar a hierarquia correta para 70% dos termos
A GRASP Approach for The Minimum Spanning Tree Under Conflict Constraints
Authors: Barros Bruno , Pinheiro Rian , Ochi Luiz , Ramos Geymerson
Published: March 2020

Dados um grafo não direcionado com pesos nas arestas e um conjunto de pares de arestas conflitantes, a Árvore de Geradora Mı́nima com Restrições de Conflito (AGMRC) consiste em encontrar árvore geradora com no máximo uma aresta de cada par conflitante e custo mı́nimo. O problema é N P-difı́cil e foi introduzido recentemente na literatura. Este artigo propõe uma nova abordagem para a solução do AGMRC, o método é baseado na meta-heurı́stica GRASP com uso de uma memória adaptativa. A heurı́stica proposta foi avaliada nas instâncias da literatura com milhares de conflitos. Os resultados indicam que o algoritmo proposto foi capaz de encontrar todas as soluções ótimas conhecidas e superar as heurı́sticas da literatura para o AGMRC.
Detecting Suicidal Ideation on Tweets
Authors: Cardoso Vinícius , Sinoara Roberta , Rezende Solange , Calçada Dario , Silva Antonio Fhillipi
Published: March 2020

According to the World Health Organization, every 40s a person dies of suicide in the world. Among young people aged 15 to 29, suicide is the second largest cause of death. Yet such deaths can be prevented. In this scenario, social networks like Twitter can become sources of information in real time and help in suicide prevention. The present work makes an initial exploration of the problem of identifying individuals at risk of suicide in social networks in Portuguese Language. As a main result, a manually labeled dataset of tweets has been constructed that can be used in future research on the subject.
Single and Multiple Failures Diagnostics of Pneumatic Valves using Machine Learning
Authors: Sano Humberto , Malere Joao , Berton Lilian
Published: March 2020

Predictive maintenance of aeronautical systems is an important field of study to reduce airlines operational costs and non-scheduled events. Valves are important components of several aircraft systems. This fact motivates the need for health monitoring and prognosis. In this context, this work compares machine learning methods to predict pneumatic valves health conditions. A multilayer perceptron artificial neural network model was able to discriminate the three single failures modes with a mean accuracy of 99.9% and a support vector machine model was able to diagnose single and concurrent failure modes with an average accuracy of 94.3%. The results reveal an accuracy improvement compared to a previous pneumatic valves health assessment study.
On the Analysis of Machine Learning Classifiers to Detect Traffic Congestion in Vehicular Networks
Authors: Carvalho Lucas , Silva Maycon , Santos Edimilson , Guidoni Daniel
Published: March 2020

Problems related to traffic congestion and management have become common in many cities. Thus, vehicle re-routing methods have been proposed to minimize the congestion. Some of these methods have applied machine learning techniques, more specifically classifiers, to verify road conditions and detect congestion. However, better results may be obtained by applying a classifier more suitable to domain. In this sense, this paper presents an evaluation of different classifiers applied to the identification of the level of road congestion. Our main goal is to analyze the characteristics of each classifier in this task. The classifiers involved in the experiments here are: Multiple Layer Neural Network (MLP), K-Nearest Neighbors (KNN), Decision Trees (J48), Support Vector Machines (SVM), Naive Bayes and Tree Augment Naive Bayes.
Classificação de falhas de equipamentos de unidade de intervenção em construção de poços marítimos por meio de mineração textual
Authors: Cesar Marcus , Vellasco Marley , Figueiredo Karla
Published: March 2020

Este trabalho propõe o desenvolvimento de uma ferramenta para otimizar a classificação de registros textuais de falhas ocorridas em equipamentos de plataformas de perfuração de poços marítimos. Dado o alto custo de utilização destas plataformas e o elevado tempo dispendido para leitura e interpretação de dados textuais, tal ferramenta se traduz em uma forma prática e eficiente de tratamento deste tipo de dado. Após correções na base de dados, a ferramenta apresentou resultados acima dos obtidos em fase de avaliação.
Exploring centroids initialization within Deep Convolutional Embedded Clustering
Authors: Nogueira Leonardo , Serapião Adriane
Published: March 2020

Deep clustering uses a deep neural network to learn deep feature representation for performing clustering tasks. In this paper, we explored the Deep Convolutional Embedded Clustering (DCEC) method, which employs a stan- dart clustering method to get initial weight for the neural model training incor- porated to other clustering methods. The original DCEC uses K-Means with Euclidean distance for the clusters center initialization step. We have applied K-Means with Mahalanobis distance instead of Euclidean distance. In order to improve the DCEC performance, we have included the standart K-Harmonic Means clustering algorithm as well, which tries overcome the dependency of the K-Means performance on the clusters center initialization. The Kernel ba- sed K-Harmonic Means was also introduced in this study to reduce the effect of outliers and noise. We evaluated the performance of these clustering appro- aches within DCEC over benchmark image datasets and the results were better than the baseline.
Incorporação de Técnicas de Tratamento de Restrição Baseadas em Penalidade na Meta-heurística de Nuvem de Partículas no contexto do Problema do Escalonamento e Atribuição de Tarefas em Projetos de Software
Authors: Santos Werthen , Silva Leila , Britto André
Published: March 2020

O Problema do Escalonamento e Atribuição de Tarefas em Projetos de Software consiste na alocação de empregados a tarefas de forma a minimizar a duração e o custo do projeto. Para solucionar o problema algoritmos metaheurísticos têm sido aplicados, dentre eles a versão multiobjetivo do algoritmo Otimização por Nuvem de Partículas, SMPSO. No entanto, o algoritmo gera muitas soluções que violam alguma restrição, chamadas de soluções inválidas. Este trabalho investiga o impacto da incorporação ao SMPSO de técnicas de tratamento de restrição baseadas em penalidade, com objetivo de aumentar o número de soluções válidas geradas. Os resultados sugerem que a incorporação do tratamento de restrição melhora a qualidade das soluções geradas.
Algoritmos com Múltiplos Enxames no Problema de Escalonamento Dinâmico de Projetos de Software
Authors: Jesus Mikael De , Silva Leila , Britto André
Published: March 2020

O Problema de Escalonamento Dinâmico de Projetos de Software (DSPSP) e um problema ainda em aberto no ramo da Engenharia de Software Baseada em Busca. Na literatura, vários algoritmos foram utilizados e alguns deles se mostraram promissores. Entre estes estão os algoritmos de Otimização por Enxame de Partículas com Múltiplas Populações chamados de Multi-Swarm. O objetivo desse trabalho e explorar técnicas de otimização dinâmica para resolver o DSPSP. Para isso, novas estratégias baseadas em múltiplas populações são propostas. As abordagens propostas são comparadas com um algoritmo Multi-Swarm, utilizando-se uma instancia do DSPSP e fazendo-se uma analise com indicadores de qualidade e testes estatísticos.
Recognizing Power-law Graphs by Machine Learning Algorithms using a Reduced Set of Structural Features
Authors: Lima Alane , Vignatti André , Silva Murilo Da
Published: March 2020

The empirical study of large real world networks in the last 20 years showed that a variety of real-world graphs are power-law. There are evidence that optimization problems seem easier in these graphs; however, for a given graph, classifying it as power-law is a problem in itself. In this work, we propose using machine learning algorithms (KNN, SVM, Gradient Boosting and Random Forests) for this task. We suggest a graph representation based on [Canning et al. 2018], but using a much simplified set of structural properties of the graph. We compare the proposed representation with the one generated by the graph2vec framework. The experiments attained high accuracy, indicating that a reduced set of structural graph properties is enough for the presented problem.
Avaliando Algoritmos de Regressão para Sumarização Automática de Textos em Português do Brasil
Authors: Sodré Lucas , Oliveira Hilário De
Published: March 2020

A Sumarização Automática de Textos (SAT) é uma proeminente área de pesquisa, cujo objetivo é a criação automática de um resumo contendo as informações mais relevantes a partir de um ou mais documentos. Um dos principais desafios da SAT é identificar as informações mais relevantes que devem ser inseridas no resumo a ser gerado. Este trabalho tem por objetivo analisar a aplicação de algoritmos de regressão para estimar um escore de relevância das frases de uma coleção de artigos de notícias escritos em português do Brasil na tarefa de sumarização. Experimentos foram executados para avaliar diferentes métodos de estimação de relevância das frases, algoritmos de regressão, e comparar os resultados obtidos com outros trabalhos da literatura. Os resultados experimentais demonstraram que o algoritmo de regressão Bayesiana obteve os melhores resultados com base nas medidas de avaliação do ROUGE, atingindo uma taxa de 62,09% de cobertura.
Sport Analytics A Systematic Review
Authors: Bogo Jair , Oliveira Janine , Lima Elivelton , Mello Rafael , Furtado Ana
Published: March 2020

Ciência de Dados é uma das áreas da Tecnologia de Informação em maior desenvolvimento, sendo usada nos mais diversos ramos, impactando fortemente a competitividade das empresas e a forma como as pessoas interagem. O seu uso nos esportes é designado como Sport Analytics, sendo usado para entender padrões, definir táticas/treinamentos e prever resultados. Este artigo procura resumir as pesquisas que estão sendo realizadas neste campo, bem como entender o conhecimento gerado e como ele está sendo aplicado.
Assessing Regression-Based Sentiment Analysis Techniques in Financial Texts
Authors: Ferreira Taynan , Paiva Francisco , Silva Roberto Da , Paula Angel De , Costa Anna , Cugnasca Carlos
Published: March 2020

Sentiment analysis (SA) is increasing its importance due to the enormous amount of opinionated textual data available today. Most of the researches have investigated different models, feature representation and hyperparameters in SA classification tasks. However, few studies were conducted to evaluate the impact of these features on regression SA tasks. In this paper, we conduct such assessment on a financial domain data set by investigating different feature representations and hyperparameters in two important models -- Support Vector Regression (SVR) and Convolution Neural Networks (CNN). We conclude presenting the most relevant feature representations and hyperparameters and how they impact outcomes on a regression SA task.
A study on Anomaly Detection GAN-based methods on image data
Authors: Silva Emanuel , Lochter Johannes
Published: March 2020

The anomaly detection task is a well know problem being researched among a variety of areas, including machine learning. The task is to identify data patterns that have a non expected behaviour, that can be a malicious data sent by an attacker or a unexpected valid behaviour, in both cases the anomaly need to be identified. With the advance of deep learning based techniques showing that this class of algorithms can learn high-dimensional and complex data patterns, naturally it became an option to the anomaly detection task. Recent researches in literature are using a sub-field of deep learning algorithms named Generative Adversarial Networks for predicting anomalous samples, since the original method can learn the data distribution. These new techniques make some changes for the anomaly detection task, and this work provides a briefly review on these methods and provides a comparison with well known methods.
Algoritmo Genético Aplicado à Solução do Problema p-hub Centro Não Capacitado de Múltiplas Alocações
Authors: Silva Jardell Da , Martins Flavio , Silva Maria , Souza Sérgio De
Published: March 2020

Este trabalho estuda a solução de uma variante do problema p-Hub Centro (pHCP), denominada problema p-Hub Centro não capacitado de múltipla alocação (UMApHCP), usando algoritmo genético híbrido. O problema consiste em definir p hubs em um grafo completo, de forma que o custo máximo de transporte do grafo seja minimizado. Para a geração da população inicial, usa-se a fase de construção da metaheurística GRASP. Além disso, para cada configuração de hub gerada pelo AG, um algoritmo de tempo polinomial é aplicado para determinar a alocação ótima dos nós do grafo. Para avaliar esta implementação, utilizou-se de 2 conjuntos de instâncias, disponíveis na literatura, com até 300 nós e até 40 hubs. Testes computacionais são realizados para comprovar a eficiência da proposta.
Solução de Regressão Regularizada com Vetores Suporte através de Programação Linear
Authors: Teixeira Lucas , F. Neto Raul
Published: March 2020

Nesse trabalho foram introduzidos dois métodos de regressão baseados na teoria de vetor suporte que visam encontrar soluções esparsas. Esses métodos são solucionáveis por programação linear. Um deles só é aplicável a regressão linear entretanto o outro pode ser estendido para o caso não linear através de métodos kernel. Os métodos propostos obtiveram resultados numéricos próximos dos métodos considerados estado da arte.
Siting and sizing of distributed generators via NSGA-II and max-min composition
Authors: Ribeiro Andrei , Lemos Francisco , Barbosa Fábio
Published: March 2020

A Geração Distribuída (GD) pode proporcionar uma série de benefícios, sendo a redução das perdas o mais importante. Porém, mesmo com essa geração alcançando níveis crescentes de penetração, os custos associados ainda são elevados. Este trabalho apresenta um modelo de otimização multiobjetivo para o dimensionamento e posicionamento de geradores. Utilizou-se o NSGA-II como ferramenta de busca para minimizar as perdas de potência ativa e reduzir o custo anualizado. As simulações foram realizadas no MATPOWER em quatro versões do sistema de 69 barras. A composição max-min foi utilizada para trade-off e escolha final na fronteira de Pareto. As ferramentas utilizadas proporcionaram resultados superiores a outros trabalhos da literatura.
Protocolo de comunicaciones para control de la generación distribuida de flujo multimedia
Authors: Perez-Monte C. F. , Piccoli M. F. , Perez M. , Luciano C. , Rizzi S.
Published: March 2020

Aplicaciones de tiempo real como realidad virtual generan un flujo multimedia de tipo de máquina-humano que puede ser dividido tanto espacial como temporalmente para distribuir recursos de procesamiento, memoria o red. Este trabajo describe un protocolo para control de flujo de datos multimedia, donde su generación debe ser distribuida para incrementar el rendimiento. Este protocolo no describe la comunicación del flujo multimedia, sino solamente la comunicación de control para la generación de un único flujo multimedia entre múltiples nodos teniendo en cuenta un esquema de mejor esfuerzo. Para lograr estos objetivos se propone un protocolo de capa de aplicación, el cual utiliza UDP o UDP-lite en capa de transporte, IPv6 multicast en capa de red y Gigabit Ethernet con control de flujo en capa de enlace de datos.
Problema de Alocação de Controladores SDN: Uma Análise do Custo em Redes de Backbone
Authors: Santos Marcelo , Fernandes Stênio
Published: March 2020

O problema de alocação de controladores em Redes Definidas por Software (SDN) é um desafio em aberto por ser um problema de alocação NPCompleto análogo aos problemas clássicos de recobrimento de rede. Para solucionar esse problema, nós propomos um modelo matemático baseado em Programação Linear que realiza a distribuição de controladores SDN minimizando o custo de alocação de todos os controladores. Para validar nossa proposta foram estimados os custos de recobrimento de 112 redes de backbone. Em seguida foram analisadas quais características são determinantes no custo de implantação de controladores SDN de acordo com as características de cada rede.
Denkmal und Dynamit
Authors: Adriansen Inge
Published: March 2020

In jeder Stadt und jeder Landschaft gibt es eine Vielzahl von Denkmälern und Gedenksteinen. Viele von ihnen werden kaum bemerkt, andere hingegen stehen auch heute noch – oder wieder – im Brennpunkt des öffentlichen Interesses. Gerade das deutsch-dänische Grenzland ist übersät mit solchen Monumenten. Sie erzählen auf einzigartige Weise von den oft nicht einfachen deutsch-dänischen Beziehungen. Sowohl nach den Kriegen 1848–1851 und 1864 als auch im Gefolge der beiden Weltkriege entbrannte um diese Denkmäler heftiger Streit: einige wurden entfernt, andere gar mit Dynamit in die Luft gesprengt. Die Geschichte dieser Denkmalzerstörungen kann dazu beitragen, das heutige friedliche Zusammenleben der Menschen beiderseits der Grenze aus einer anderen Perspektive zu beleuchten. Inge Adriansen, Ph. D., dänische Kulturhistorikerin und stellvertretende Leiterin des Sonderburger Schlossmuseums berichtet detailliert und kenntnisreich über den beiderseitigen Umgang mit diesem gemeinsamen Kulturerbe. Gerade im Hinblick auf die im Herbst 2011 anstehende Rückführung des einst heftig umstrittenen Idstedt-Löwen nach Flensburg ist dies ein hochaktuelles Thema.
Correlation between HSAB Principle and Substitution Reactions in Bioinorganic Reactions
Authors: Soldatović Tanja
Published: March 2020

Substitution reactions are a type of reactions where one functional group or ligand is substituted by another. They could be electrophilic or nucleophilic, depending upon whether the reagent is involved. Complex compounds could be involved in a number of substitution reactions such as ligand exchange, solvent exchange, complexation or anation reactions, solvolysis, acid and base hydrolysis, inter- and intramolecular isomerization, racemization, and metal ion reaction. Hard-soft acid–base principle (HSAB) contributes to better understanding of the mechanism of nucleophilic substitution reactions of transition metal complexes. Metal–ligand bonds in transition metal compounds are closely related to the HSAB nature of metals and their preferred ligands. Also, the principle is qualitatively useful to predict the preference of the metal for the ligand in bioinorganic reactions.
El indigenismo en México como racismo de Estado: mestizaje asimilacionista y esterilización forzada
Authors: Karin Pedraza Ramos Alejandro
Published: March 2020

En este trabajo se exploran diferentes dimensiones del racismo, para construir una categoría de racismo de Estado que permita analizar el dispositivo indigenista con un objetivo doble: primero, exponer los esfuerzos por sistematizar las teorías y prácticas racistas que fundamentan la intervención organizada y regulada sobre la población indígena. Segundo, mostrar cómo, a pesar de que las políticas indigenistas se han modificado sustancialmente, el racismo de Estado subsiste, no tanto por sus formas –que en buena medida se ocultan–, sino por sus fundamentos y objetivos, es decir: la discriminación, subordinación, segregación, explotación, despojo y exterminio de las etnias culturalmente diferenciadas. Para ello se analizan dos dispositivos paradigmáticos de las políticas indigenistas: el mestizaje asimilacionista y la esterilización forzada.
La reflexión metalingüística en la prensa sefardí
Authors: Pawłowska Marta
Published: March 2020

El objetivo del artículo consiste en analizar las reflexiones metalingüísticas presentes en la prensa sefardí escrita en judeoespañol, con el fin de averiguar cuál es el estatus de dicho idioma entre sus hablantes. Como fuente de información, nos serviremos de los artículos publicados en la revista Aki Yerushalayim (Israel) y en el semanario Şalom (Turquía) en un periodo de tres años, de 2013 a 2015. Nos centraremos en cuestiones como las distintas denominaciones de la lengua y sus connotaciones, las actitudes frente al judeoespañol y, en general, frente al papel de la prensa sefardí, las posturas en relación al castellano y otras lenguas, etc., a fi n de determinar la importancia que tiene para la comunidad sefardí el idioma de sus ancestros expulsados de España.
NKCC1 involvement in the epithelial-to-mesenchymal transition is a prognostic biomarker in gliomas
Authors: Sun Huaiyu , Long Shengrong , Wu Bingbing , Liu Jia , Li Guangyu
Published: March 2020

Background

Gliomas are the most prevalent type of intracranial tumors. NKCC1 is an important regulator in tumor cell volume. We noticed that abnormally high NKCC1 expression resulted in changes in the shape and adhesion of glioma cells. However, little is known about the role of NKCC1 in the epithelial-mesenchymal transition (EMT) of gliomas. This study aims to clarify the biological function of NKCC1 in glioblastoma multiforme (GBM) progression.

Methods

Using data from The Cancer Genome Atlas (TCGA), we performed a Kaplan–Meier analysis on NKCC1 expression levels to estimate the rate of survival of mesenchymal GBM patients. The correlation between NKCC1 and EMT-related proteins was analyzed from the Gene Expression Profiling Interactive Analysis (GEPIA) server. We conducted Gene Set Enrichment Analysis (GSEA) to verify molecular signatures and pathways. We then studied the expression of NKCC1 in grade I–IV glioma tissue samples collected from patients using immunohistochemistry (IHC). Finally, we evaluated the effects of NKCC1 migration and invasion on the cellular behaviors of U251 cells using the transwell assay and western blots.

Results

High NKCC1 expression was associated with poor prognoses in mesenchymal GBM. Our results suggest a correlation between NKCC1 and EMT-protein markers: CDH2 and VIM. GSEA showed that gliomas, TGF-beta signaling and EMT were enriched in the NKCC1 high expression phenotype. Higher expression levels of NKCC1 in gliomas correlate with higher glioma grades. Transwell assay and western blot results demonstrated that the knockdown of NKCC1 led to a reduction in migration and invasion, while also inhibiting MMP-2 and MMP-9 expression in U251.

Conclusion

These results suggest that high expression of NKCC1 regulates EMT in gliomas, providing a new therapeutic strategy for addressing the spread of gliomas by inhibiting the spread of intracranial tumors.
Age-specific differences in gait domains and global cognitive function in older women: gait characteristics based on gait speed modification
Authors: Noh Byungjoo , Youm Changhong , Lee Myeounggon , Park Hwayoung
Published: March 2020

Background

Several studies have reported the association between gait and global cognitive function; however, there is no study explaining the age-specific gait characteristics of older women and association between those characteristics and global cognitive function by age-specific differences and gait speed modification. The aim of this study was to examine age-specific differences in gait characteristics and global cognitive function in older women as well as identify gait domains strongly associated with global cognitive function in older women based on gait speed modification.

Methods

One hundred sixty-four female participants aged 65–85 years were examined. Participants were assessed for global cognitive function through the mini-mental state examination. They also performed three trials of the overground walking test along a straight 20 m walkway. Inertial measurement unit sensors with shoe-type data loggers on both the left and right outsoles were used to measure gait characteristics.

Results

The pace at all speeds and the variability and phase at faster speeds were altered in women aged >75 years (all pace domain parameters, p < 0.05); variability and phase highly depended on age (all p < 0.05). Variability at slower speeds (β = −0.568 and p = 0.006) and the phase at the preferred (β = −0.471 and p = 0.005) and faster speeds (β = −0.494 and p = 0.005) were associated with global cognitive function in women aged >75 years.

Discussion

The variability and phase domains at faster speeds were considered to identify gait changes that accompany aging. In addition, the decreases in global cognitive function are associated with increased variability and phase domains caused by changes in gait speed in older women.

Conclusion

Our results are considered useful for understanding age-related gait characteristics with global cognitive function in old women.
Heavy Metal Bioaccumulation in Periwinkle (Tympanotonus fuscatus) and Tilapia Fish (Oreochromis niloticus) Samples Harvested from a Perturbed Tropical Creek in the Niger Delta, Nigeria
Authors: Abiaobo Nsikak O. , Asuquo Idopiseabasi E. , Akpabio Enobong P.
Published: March 2020

Different scientific studies with useful contributions in biomonitoring different environmental parameters and knowledge of their influences on aquatic ecosystem health and ultimately that of man have evolved through the years, however with scanty toxicological evidences. The present study was designed to investigate the concentrations of heavy metals in edible food of periwinkle and fish harvested from a perturbed creek in Niger Delta, Nigeria reported to constantly receive industrial effluent from two major oil and gas companies. Zn, Fe, Pb, Cu, Cr, Cd and Mn were assessed for 6 months from July – November, 2018. Higher concentrations of heavy metals were obtained with fish bio-accumulating more metals than periwinkle. The bio-availability sequence of metals in periwinkle was Fe>Cu>Mn>Cd>Zn>Cr>Pb and fish Fe>Cu> Zn>Mn>Cd>Cr>Pb. Mean values of Cd, Cr, Cu, Fe and Zn in some months in periwinkle and fish were above WHO/FEPA regulatory limits while Pb and Mn were lower. The study has provided some useful information on metal accumulation in the icthyofauna of the creek and call for more toxicological study and biomonitoring of anthropogenic sources on the creek. Results showed the dominance of Cd, Cr, Cu and Fe over other metals in both animals in all months. Cu level was relatively stable throughout the study. Fish bio-accumulated more metals than periwinkle with report of higher concentrations.
Monitoring of Surface Water Quality in Train Development Activities Plan between Makasar and Parepare, South Sulawesi Indonesia
Authors: Isworo Slamet , Oetari Poerna Sri , Alita Indah Nur , Adji Tosan
Published: March 2020

Background and Objectives: The plan for the construction of the Makassar - Parepare railway line is the priority for the development of the land transportation mode in South Sulawesi. The development plan has received an environmental permit which was then continued with a monitoring study.

Methodology: Descriptive analysis methods are then compared with quality standards based on South Sulawesi Governor Regulation No. 69 of 2010. Physical parameters with organoleptic and conductivity methods. Heavy metal parameters using the Atomic Absorption Spectrophotometry method. Aquatic biota parameters are based on the Shannon wiener diversity index.

The Results: The measurement results of the pre-construction stage addressing parameters that exceed the quality standard are turbidity. Measuring the monitoring period I, all parameters still meet quality standards, except Total Dissolved Solids and Cadmium, while other parameters are not required. Measurement. Period II, at all measurement locations the parameters of Total Dissolved Solids, Total Suspended Solid, Chemical Oxygen Demand and Dissolved Oxygen exceed the quality standards of the Diversity Index (H') results of the pre-construction period with the value            (H') = 1.92, (D) = 66, (E) = -, mild pollution waters category.  Period 1 (H') = 0.24, (D) = 0.88, (E) = 0.35, the category of moderately polluted.   Period II (H') = 0.78, (D) = 0.22, (E) = 0.49, the category of moderately polluted waters.

Conclusions: Monitoring results show an increase in surface water pollution from mild to moderate.
Interprofessional Undergraduate Analytical Study on Anger Management
Authors: Lwin Htay , Shen Sim Khye , Yunn Ch’ng Shi , Vasudevan Yasheera , Than Nan Nitra , Soe Htoo Htoo Kyaw , Abas Adinegara Lutfi , Htay Mila Nu Nu
Published: March 2020

Introduction: Anger has been defined in many ways from “a negative, phenomenological (or internal) feeling state” to “a basic emotion in which the function is to provide the organism with motivated capacities to overcome obstacles”. Anger has been the subject of many discourses and its vehemence in many religions and cultures. The study aimed to determine the ability of anger management among different gender and factors associated with anger management.

Methods: This is a cross-sectional prospective study. The validated ‘Quality of Life’ questionnaire from University of Washington, Seattle Washington, United Sates of America and Novaco Anger Scale from Mental Health America of Northern Kentucky & Southwest Ohio (WHOQOL-BREF) were used for students’ perception on anger management. Quantitative data were analyzed using Epi Info Version. 7 Software.

Results: The total of 358 students participated in this study. There is a significant association between anger management among different ethnicity.

Conclusion: Gender was not a significant factor in anger management, it was probably due to equal opportunity among male and female in acquiring education, application for scholarships and usage of education facilities. Gender equality had a big impact in enhancing the good anger management properties.
Bio-tower Application for Wastewater Treatment
Authors: Doelle Klaus , Qin Yue , Wang Qian
Published: March 2020

The study tested the performance of a batch-type recirculating laboratory scale bio-tower for the treatment of municipal wastewater. Performance tests were done with a HACH DR-1900 spectrophotometer include chemical oxygen demand, total phosphorus and nitrogen ammonia.

This study showed that the recirculated laboratory type bio-tower containing 0.276 ft3 (0.008 m3) of polypropylene growth media with a surface area of 6.624 ft2 (0.615 m2) can reduce the chemical oxygen demand between 70% to 87%. NH3-N reduction was found to be between 94% to 96%, and total phosphorus reduction was between 69% and 87% for flow rates of 0.6 l/min to 1.5 l/min.
Nonlinear unmanned aerial vehicle formation control via composite Laplacian quadratics
Authors: Jing Peng , Chen Fei
Published: March 2020

This article studies a leader‐following formation control problem, in which the agent model is governed by continuous‐time nonlinear differential equations. We are interested in designing a distributed control algorithm which is capable of handling the strong nonlinearities induced by the unmanned aerial vehicle model. Our primary objective is to investigate the convergence of the corresponding closed‐loop system, and to understand how the nonlinear dynamics and the network topologies may impose intrinsic barriers on formation control. The results show that an exponential convergence is guaranteed under the proposed algorithm via the composite Laplacian quadratics function as long as the network topology has a directed spanning
tree.
Biomaterials for Sequestration of Growth Factors and Modulation of Cell Behavior
Authors: Teixeira Simão P. B. , Domingues Rui M. A. , Shevchuk Mariya , Gomes Manuela E. , Peppas Nicholas A. , Reis Rui L.
Published: March 2020

Growth factors (GFs) are proteins secreted by cells that regulate a variety of biological processes. Although they have long been proposed as potent therapeutic agents, their administration in a soluble form has proven costly and ineffective due to their short half‐lives in biological environments. Biomaterial‐based approaches are increasingly sought as alternatives to improve the efficacy or, ideally, replace the need for exogenous administration of GFs in regenerative medicine strategies. The means by which these systems evolve from biomaterials for conventional controlled release of GFs to the recent extracellular matrix (ECM)–inspired approaches for sequestering these labile molecules and regulating their spatiotemporal activity and presentation are reviewed. Focus is placed on biomaterials functionalized either with ECM components, which show promiscuous GF binding, or with targeted GF ligands (antibodies, aptamers, or peptides). The potential of synthetic platforms with abiotic affinity as cost‐effective alternatives to the current biological ligands is also discussed. Overall, the various GF sequestering systems developed so far have remarkably improved the activity of GFs at reduced doses and, in some cases, completely avoided the need for their exogenous administration to guide cell fates. These bioinspired concepts thus enable the rational exploration of the full therapeutic potential of GFs in regenerative medicine.
Co‐Interlayer Engineering toward Efficient Green Quasi‐Two‐Dimensional Perovskite Light‐Emitting Diodes
Authors: Meng Fanyuan , Liu Xinyan , Chen Yuxuan , Cai Xinyi , Li Mengke , Shi Tingting , Chen Ziming , Chen Dongcheng , Yip Hin‐Lap , Ramanan Charusheela , Blom Paul W. M. , Su Shi‐Jian
Published: March 2020

With respect to three‐dimensional (3D) perovskites, quasi‐two‐dimensional (quasi‐2D) perovskites have unique advantages in light‐emitting devices (LEDs), such as strong exciton binding energy and good phase stability. Interlayer ligand engineering is a key issue to endow them with these properties. Rational design principles for interlayer materials and their processing techniques remain open to investigation. A co‐interlayer engineering strategy is developed to give efficient quasi‐2D perovskites by employing phenylbutylammonium bromide (PBABr) and propylammonium bromide (PABr) as the ligand materials. Preparation of these co‐interlayer quasi‐2D perovskite films is simple and highly controllable without using antisolvent treatment. Crystallization and morphology are readily manipulated by tuning the ratio of co‐interlayer components. Various optical techniques, including steady and ultrafast transient absorption and photoluminescence spectroscopies, are used to investigate their excitonic properties. Photoluminescence quantum yield (PLQY) of the perovskite film is dramatically improved to 89% due to the combined optimization of exciton binding energy and suppression of trap state formation. Accordingly, a high current efficiency of 66.1 cd A−1 and an external quantum efficiency of 15.1% are achieved for green co‐interlayer quasi‐2D perovskite LEDs without using any light out‐coupling techniques, indicating that co‐interlayer engineering is a simple and effective approach to develop high‐performance perovskite electroluminescence devices.
Function Follows Form: From Semiconducting to Metallic toward Superconducting PbS Nanowires by Faceting the Crystal
Authors: Ramin Moayed Mohammad Mehdi , Kull Sascha , Rieckmann Angelique , Beck Philip , Wagstaffe Michael , Noei Heshmat , Kornowski Andreas , Hungria Ana B. , Lesyuk Rostyslav , Stierle Andreas , Klinke Christian
Published: March 2020

In the realm of colloidal nanostructures, with their immense capacity for shape and dimensionality control, the form is undoubtedly a driving factor for the tunability of optical and electrical properties in semiconducting or metallic materials. However, influencing the fundamental properties is still challenging and requires sophisticated surface or dimensionality manipulation. Such a modification is presented for the example of colloidal lead‐sulfide nanowires. It is shown that the electrical properties of lead sulfide nanostructures can be altered from semiconducting to metallic with indications of superconductivity, by exploiting the flexibility of the colloidal synthesis to sculpt the crystal and to form different surface facets. A particular morphology of lead sulfide nanowires is prepared through the formation of {111} surface facets, which shows metallic and superconducting properties in contrast to other forms of this semiconducting crystal, which contain other surface facets ({100} and {110}). This effect, which is investigated with several experimental and theoretical approaches, is attributed to the presence of lead‐rich {111} facets. The insights promote new strategies for tuning the properties of crystals and new applications for lead sulfide nanostructures.
A Sieve‐Functional and Uniform‐Porous Kaolin Layer toward Stable Zinc Metal Anode
Authors: Deng Canbin , Xie Xuesong , Han Junwei , Tang Yan , Gao Jiawei , Liu Cunxin , Shi Xiaodong , Zhou Jiang , Liang Shuquan
Published: March 2020

Zinc metal is considered as one of the best anode choices for rechargeable aqueous Zn‐based batteries due to its high specific capacity, abundance, and safety. However, dendrite and corrosion issues remain a challenge for this system. Herein, sieve‐element function (selective channel of Zn2+) and uniform‐pore distribution (≈3.0 nm) of a kaolin‐coated Zn anode (KL‐Zn) is proposed to alleviate these problems. Based on the artificial Zn metal/electrolyte interface, the KL‐Zn anode not only ensures dendrite‐free deposition and long‐time stability (800 h at 1.1 mA h cm−2), but also retards side reactions. As a consequence, KL‐Zn/MnO2 batteries can deliver high specific capacity and good capacity retention as well as a reasonably well‐preserved morphology (KL‐Zn) after 600 cycles at 0.5 A g−1. This work provides a deep step toward high‐performance rechargeable Zn‐based battery system.
A Blue Photosensitizer Realizing Efficient and Stable Green Solar Cells via Color Tuning by the Electrolyte
Authors: Ren Yameng , Cao Yiming , Zhang Dan , Zakeeruddin Shaik Mohammed , Hagfeldt Anders , Wang Peng , Grätzel Michael
Published: March 2020

Semitransparent dye‐sensitized solar cells (DSCs) are appealing as aesthetically pleasing and colorful see‐through photovoltaics. Green semitransparent DSCs have been presented, but the best ones rely on green zinc porphyrin photosensitizers and high volatile electrolytes. For potential outdoor applications, the zinc porphyrin DSCs employing ionic liquid electrolytes merely reached a power conversion efficiency (PCE) of 6.3% even with opaque mesoporous TiO2 films. Herein, the new green DSC is realized by using a blue organic photosensitizer in conjunction with an orange ionic‐liquid‐based electrolyte, presenting a simple and an effective path for color tuning of photovoltaics. The new approach allows for broadly modulating the color from spring green to cyan by tuning the contributions of the light absorption by the dye‐sensitized TiO2 film and the electrolyte layer. The new semitransparent DSCs with spring green to cyan colors have PCEs ranging from 6.7% to 8.1% and show stability for 1000 h under accelerated ageing test at 80 °C, superior to the zinc porphyrin DSCs. The findings pave a new way to achieve efficient and stable colorful solar cells.
Anisotropic Optical and Frictional Properties of Langmuir–Blodgett Film Consisting of Uniaxially‐Aligned Rod‐Shaped Cellulose Nanocrystals
Authors: Chae Inseok , Ngo Dien , Chen Zhe , Kwansa Albert L. , Chen Xing , Meddeb Amira Barhoumi , Podraza Nikolas J. , Yingling Yaroslava G. , Ounaies Zoubeida , Kim Seong H.
Published: March 2020

Langmuir–Blodgett (LB) film deposition gives an opportunity to control the packing density and orientation of anisotropic nanoparticles at a monolayer level, allowing accurate characterization of their anisotropic material properties. The uniaxial deposition of rod‐shaped cellulose nanocrystals (CNCs) over a macroscopically large area is achieved by aligning the long axis of CNCs on the LB trough with the direction of the maximum drag force within the meniscus during the vertical pulling of the substrate from the LB trough. On the uniaxially‐aligned LB films, anisotropic linear and non‐linear optical properties of CNCs are obtained using Mueller matrix spectroscopy and sum frequency generation spectroscopy, respectively, and explained with time‐dependent density functional theory calculations. Also, the frictional anisotropy of the LB film is measured using atomic force microscopy and explained theoretically. The findings of this study will be valuable for preparation of anisotropic nanoparticle thin films with uniform arrangements and utilization of their anisotropic material properties.
Targeting Pyruvate Carboxylase by a Small Molecule Suppresses Breast Cancer Progression
Authors: Lin Qingxiang , He Yuan , Wang Xue , Zhang Yong , Hu Meichun , Guo Weikai , He Yundong , Zhang Tao , Lai Li , Sun Zhenliang , Yi Zhengfang , Liu Mingyao , Chen Yihua
Published: March 2020

Rapid metabolism differentiates cancer cells from normal cells and relies on anaplerotic pathways. However, the mechanisms of anaplerosis‐associated enzymes are rarely understood. The lack of potent and selective antimetabolism drugs restrains further clinical investigations. A small molecule ZY‐444 ((N4‐((5‐(4‐(benzyloxy)phenyl)‐2‐thiophenyl)methyl)‐N2‐isobutyl‐2,4‐pyrimidinediamine) is discovered to inhibit cancer cell proliferation specifically, having potent efficacies against tumor growth, metastasis, and recurrence. ZY‐444 binds to cellular pyruvate carboxylase (PC), a key anaplerotic enzyme of the tricarboxylic acid cycle, and inactivates its catalytic activity. PC inhibition suppresses breast cancer growth and metastasis through inhibiting the Wnt/β‐catenin/Snail signaling pathway. Lower PC expression in patient tumors is correlated with significant survival benefits. Comparative profiles of PC expression in cancer versus normal tissues implicate the tumor selectivity of ZY‐444. Overall, ZY‐444 holds promise therapeutically as an anti‐cancer metabolism agent.
Structured reporting of cardiovascular magnetic resonance based on expert consensuses and guidelines
Authors: Huang Yihua , Zhou Hui , Feng Yabo , Zhou Moling , Tang Haixiong , Zhou Gaofeng , Liu Jinkang , Liao Weihua
Published: March 2020

Background

There is a gap between China and developed countries in Europe and America as to the normalization of cardiac magnetic resonance (CMR) diagnostic reports. The aim of this study was to construct a structured CMR report template suitable for China's actual conditions.

Methods

Cardiac magnetic resonance standardized image interpretation and post‐processing guidelines and CMR report guidelines are the consensus and recommendations of the Society for Cardiovascular Magnetic Resonance (SCMR) experts whose goal is to ensure the consistent quality and repeatability of CMR reports. This structured CMR report template was constructed based on the guidelines for standardized image interpretation, post processing and reporting of CMR examinations, combined with the experiences learned in Germany and the practical experiences in China. It consisted of three parts: Device and Methods, Findings (Structure and function, Tissue Characterization), Summary and Conclusion. Detailed directions were provided section by section.

Results

This structured CMR report template underlined the comprehensive analysis of the results of morphological, functional and tissue characteristics to provide conclusive opinions and answer the corresponding important questions raised by the clinicians.

Conclusion

The standardization of qualitative and quantitative assessments of CMR results is the core of structured reporting of CMR.