bluuebunny/crossref_metadata_2025 huggingface dataset:
Analysis of residual gases of internal combustion engines at working on biogas and their effects on the environment
Authors: Dykun T. V. , Artym V. I. , Demianchuk Ya. M. , Kozak F. V. , Haieva L. I.
Published: March 2021

Given the limited resources of Ukraine in petroleum fuels for internal combustion engines, the use of alternative fuels is quite relevant. One of their sources is biogas from livestock by-products and garbage dump. Ukraine has significant volumes of these renewable sources, the potential of which reaches more than 100 million tons of conventional fuel. Unfortunately, this resource is rarely used. In developed countries, biogas is widely used for electricity generation in power plants with internal combustion engines. Today in the United States the volume of biogas production is about 500 million m3 / year, in France – 40 million m3 / year. In the Czech Republic, Austria, Denmark, Finland and other countries, biogas is used as a motor fuel. Business Concerns Volvo, Scania produce buses running on biogas. In Ukraine, gas from landfills and livestock by-products is mostly released into the atmosphere or burned by flares, polluting the surrounding air. This causes additional greenhouse gas emissions. It is known that the main source of air pollution is vehicles. Exhaust, i.e. residual gases are considered toxic. The World Motor Vehicle Park annually emits up to 260 million tons of carbon monoxide, 40 million tons of volatile hydrocarbons, nitrogen oxides and others. The composition of the residual gases of the internal combustion en-gine depends on the component composition of the sources of fuel and, of course, on the mode of operation of the internal combustion engine In the given article the structure of residual gases of internal combustion engines at work on biogas is analyzed and their influence on environment is generalized. Based on analytical calculations, it is determined how the amount of residual gas components changes depending on the excess air ratio and the per-centage of methane in biogas. Recommendations for improving the performance of internal combustion engines on biogas by using it in mixtures with natural gas are given. According to the research results, the corresponding graphical dependences are constructed.
Peculiarities of using Future Continuous in the modern English language
Authors: Selezneva Olga Nikolaevna
Published: March 2021

The article raises the question of the ambiguous grammatical status of the means expressing the future tense. The author of the article analyzes the Future Continuous form, its grammatical status and expressed lexical meaning. The article assumes that unlike other continual forms of the English verb tenses system, the main meaning of which is the expression of an action’s duration or a process, the main function of Future Continuous is to designate neutral future actions.
RELAÇÃO ENTRE ATIVIDADE FÍSICA, ÍNDICE DE MASSA CORPORAL E ESTRESSE EM ACADÊMICOS DE MEDICINA DE UMA UNIVERSIDADE DO SUL DE SANTA CATARINA
Authors: Castelini Mendes Rafaela , Guedes Correia Manoela , De Souza Kock Kelser
Published: March 2021

O presente estudo tem como objetivo investigar a relação da atividade física no índice de massa corporal e estresse em acadêmicos de medicina. Foi realizado um estudo observacional transversal. A população foi composta por acadêmicos de medicina da Universidade do Sul de Santa Catarina, Campus Tubarão, SC. Foram avaliados sexo, massa, estatura, índice de massa corporal (IMC), quantidade de horas sentadas ao dia e horas de sono por noite, nível de atividade física por meio da versão curta e validada do IPAQ (Questionário Internacional de Atividade Física) e a Escala de Estresse Percebido (PSS14 - Perceived Stress Scale). Foram analisados 402 acadêmicos, com maioria do sexo feminino (62,2%), mediana de idade de 22 anos, IMC normal em 74,1% dos participantes e 41,0% na faixa de baixo nível de atividade física. Na comparação entre os sexos foram observadas diferenças significativas no IMC (homens=24,09±3,99; mulheres=21,32±3,01 kg/m2) com p
INFLUÊNCIA DO NÍVEL DE ATIVIDADE FÍSICA NA QUALIDADE DE VIDA E ESTADOS DE HUMOR DE PROFESSORES UNIVERSITÁRIOS
Authors: Neves Rodrigo Vanerson Passos , Castro Henrique De Oliveira , Rosa Thiago Santos , Silva Renata Chavier da , Fonseca Richard Xavier , Clemente Filipe Manuel , Lima Ricardo Franco , Moraes Milton Rocha , Corrêia Hugo De Luca , Aguiar Samuel Da Silva
Published: March 2021

O excesso de tarefas diárias, bem como a rotina estressante, faz parte da rotina de algumas atividades ocupacionais, principalmente em professores universitários. Além disso, essas tarefas influenciam diretamente na falta de atividades físicas dessa população. Assim, estudos surgiram com a preocupação de entender a relação entre atividade física, qualidade de vida e fatores psicológicos, sendo que um conjunto de evidências pertencentes à relação entre humor e atividade física ainda permanecem confusas na literatura científica. Objetiva-se analisar a influência do nível de atividade física na qualidade de vida e estados de humor de professores de universidades particulares. Participaram 47 professores de universidades particulares do Distrito Federal. Utilizou-se o IPAQ_versão curta para análise do nível de atividade física e divisão dos grupos ativo, pouco ativo e inativo e os questionários WHOQOL_Bref e POMS, com o objetivo de avaliação da qualidade de vida e estados de humor, respectivamente. Os resultados apresentados apontam uma associação entre o nível de atividade física com os domínios psicológico, meio ambiente e qualidade de vida geral em professores universitários. Embora não houve associação com os estados de humor. Em nossa amostra avaliada houve associação entre o nível de atividade física com a qualidade de vida. Evidências científicas prévias indicam que a qualidade de vida e o estado psicológico estão diretamente associados com o nível de atividade física, em algumas populações. Conclui-se que houve associação entre o nível de atividade física com a qualidade de vida geral, e com os domínios psicológico e meio ambiente, mas não ocorreu associação com os estados de humor em professores universitários do Distrito Federal.
PERFIL DOS PROPRIETÁRIOS DAS ACADEMIAS DE GINÁSTICA DE PELOTAS: UM ESTUDO CENSITÁRIO
Authors: Caputo Eduardo Lucia , Vilela Guilherme Da Fonseca , Rombaldi Airton José , Da Silva Marcelo Cozzensa , Reichert Felipe Fossati
Published: March 2021

O objetivo do estudo foi descrever o perfil dos proprietários de academias de ginásticas da cidade de Pelotas/RS. Estudo descritivo parte do censo de academias de Pelotas realizado em 2012. Para mapear as academias de ginástica da zona urbana da cidade, dividiu-se o município em 19 setores, foram encontradas 170 academias e 183 proprietários. Os dados foram coletados através de entrevista estruturada, contendo questões econômicas (renda mensal em reais), sociodemográficas (sexo, cor da pele, idade, escolaridade), comportamentais (hábito de fumo, consumo de álcool, atividade física), laborais (número de estabelecimentos em que é proprietário, carga horário semanal), e de conhecimento sobre legislação trabalhista (CLT) e conselho fiscalizador (CREF). Foi realizada uma análise descritiva com cálculo de médias e desvios-padrão para as variáveis numéricas e proporções para as variáveis categóricas. Ao todo, 161 proprietários participaram do estudo. Em sua maioria, os proprietários eram do sexo masculino (64,4%), de cor de pele branca (42,8%), pertencentes à faixa etária de 30 a 39 anos (42,8%), não fumavam (75,8%) e eram ativos fisicamente (82,0%). Quanto à formação, mais da metade (54,0%) era graduado em Educação Física e possuía algum curso de pós-graduação (52,2%). Com relação à experiência de trabalho em academias e conhecimento, 71,6% trabalhavam há mais de cinco anos nas academias e 41,6% tinham pouco/nenhum conhecimento sobre leis trabalhistas. Concluiu-se que, apesar do tempo de atuação como gestores, é evidente a carência de formação adequada e conhecimento sobre legislação, indicando que os gestores ainda atuavam apenas com o conhecimento empírico adquirido ao longo dos anos.
EFEITOS DE UM PROGRAMA DE INTERVENÇÃO INTERDISCIPLINAR SOBRE O AGRUPAMENTO DE VARIÁVEIS CARDIOMETABÓLICAS EM ADOLESCENTES COM EXCESSO DE PESO
Authors: Tornquist Debora , Tornquist Luciana , Reuter Cézane Priscila , Renner Jane Dagmar Pollo , Burgos Miria Suzana
Published: March 2021

O estudo tem por objetivo investigar alterações nas características de agrupamento de variáveis cardiometabólicas relacionados a resistência à insulina em resposta à um programa de intervenção interdisciplinar em adolescentes com excesso de peso. Estudo realizado em adolescentes com excesso de peso, composto por grupo controle (n=19) e grupo intervenção (n=20), o qual participou de programa interdisciplinar de seis meses. Foi avaliado o índice de massa corporal, a circunferência da cintura, pressão arterial sistólica e diastólica; realizada coleta sanguínea para avaliação da glicose, insulina e ácido úrico e calculado o índice HOMA-IR, antes e após o programa. Foi realizada análise fatorial exploratória por meio de análise de componentes principais, tendo sido consideradas cargas fatoriais associadas os valores ? 0,50. No período pré intervenção, três componentes fatoriais explicavam a variabilidade das variáveis em ambos os grupos, sendo a composição dos componentes igual entre estes, em que variáveis antropométricas e de pressão arterial compunham o fator 1; o segundo componente dizia respeito as variáveis relacionadas à resistência à insulina, insulina e HOMA-IR; e o terceiro componente era composto da glicemia e ácido úrico. Pós intervenção, dois componentes explicavam em ambos grupos e a composição era distinta, sendo que no grupo intervenção insulina e HOMA-IR passaram a fazer parte do fator 1; já no grupo controle, a glicemia correlacionou-se negativamente com os indicadores antropométricos e de pressão arterial no componente 1; e glicemia, insulina, HOMA-IR e ácido úrico associaram-se no fator 2. Conclui-se que o programa de intervenção promoveu modificação no agrupamento das variáveis cardiometabólicas de adolescentes obesos, em que as variáveis insulina e HOMA-IR passaram a pertencer ao fator 1. Não foi encontrado nenhum fator central que explicasse o agrupamento das variáveis em nenhuma das análises, confirmando assim, a complexa relação entre as variáveis analisadas.
TRANSTORNOS INVASIVOS DE DESENVOLVIMENTO NO AUTISMO E SÍNDROME DE ASPERGER: UMA REVISÃO SISTEMÁTICA
Authors: Haas Patrícia , Paiva Karina Mary , Corrêa Vanessa Pereira , Gonzales Ana Inês , Besen Eduarda , Moreira Emanuelle , Cunha Josiane Da
Published: March 2021

Introdução: O autismo e a síndrome de Asperger são descritos como transtornos invasivos do desenvolvimento e suas características clínicas centrais incluem déficits qualitativos na interação social e na comunicação, padrões de comportamento repetitivos e estereotipados e um repertório limitado de interesses e atividades. Esse transtorno geralmente está associado à comorbidades como o Transtorno do Desenvolvimento da Coordenação (TDC). Objetivo: Verificar evidências científicas da a importância do exercício físico no tratamento do indivíduo autista e com Síndrome de Asperger, além de observar as modalidades de intervenção utilizadas e seus benefícios concomitantes na coordenação motora e desenvolvimento cognitivo destes pacientes. Métodos: Realizadas buscas nas bases de dados PUBMED, LILACS, SciELO e PEDro sem restrição de idiomas ou localização e tempo até maio de 2019. Utilizando os termos [(Autistic Disorder) AND (Asperger Syndrome) AND (Exercise) AND (Cognition)]. Tendo como critérios de inclusão estudos com intervenções com uso de exercício físico. Resultados: Após busca nas bases, foram identificados 655 artigos, ao final, somente 7 cumpriram os critérios de inclusão estabelecidos respondendo a pergunta norteadora, sendo considerados elegíveis. Ambos os estudos retrataram diversas abordagens diferentes dos exercícios físicos, sendo aeróbicos, de força, aquáticos, com uso de tecnologias. A quantidade e duração das sessões dos exercícios variaram de estudo para estudo. Conclusão: Pode-se concluir que os exercícios físicos trazem um importante impacto em diversos aspectos da vida do paciente TEA, e diante das abordagens investigadas o exercício aquático se mostrou mais eficaz. Abre-se, assim, uma lacuna na literatura para novos estudos que busquem explicações para esses resultados, além da busca por tratamentos mais eficazes.
The Formation of Responsive Regional Regulations in Supporting Regional Autonomy in Pekanbaru City
Authors: Hakim Amri , Marisa Hizra
Published: March 2021

This article aims to produce regional laws that are responsive in supporting the implementation of regional autonomy so that the implementation of regional autonomy does not create new problems that can hinder or damage economic development and growth in a region. In this study, several legal approaches used include the main approach of Law number 32 of 2004 concerning regional autonomy and Law number 12 of 2011 concerning the law on the establishment of legislation. Another approach approached in one case is a historical approach, a comparative approach, and a conceptual approach. Results illuminate how the drafting of Perda constitutes based on certain principals (i.e. clarity of objectives, appropriate institutional or organ formation, compatibility between types and material content) can accommodate local wisdom for the community and avoid potentially problematic regulations in the regions.
Knowledge, Attitudes, and Barriers to Breastfeeding in Adolescent Mothers: a Review
Authors: Kullmann Kimberly , Leader Amy , Frasso Rosemary
Published: March 2021

Introduction: Despite the proven benefits of breastfeeding, there are a variety of reasons why many women do not, or cannot, breastfeed their children. Adolescent mothers are even less likely to breastfeed than non-adolescent mothers. The aim of this review was to synthesize the current literature on breastfeeding practices in adolescent mothers and explore the factors influencing their breastfeeding decisions.

Methods: A literature search was conducted in January 2018 using PubMed. Studies were included in the review if they discussed adolescent mothers’ views and experiences of breastfeeding or if they reporting breastfeeding rates among adolescent mothers. For this review, adolescence was defined as the ages between 13 and 21.

Results: Of the 19 studies selected, each study was summarized and analyzed to determine that the proportion of adolescent mothers who breastfeed is lower than non-adolescent mothers: 31-100% initiated breastfeeding, 17-64% breastfed exclusively, and more than half stopped within the first month. Intention to breastfeed, social support and maternity care support were positive predictors of breastfeeding behaviors. Although significant effects of the interventions aimed at improving breastfeeding rates was revealed by this review, findings also indicated analytical themes related to adolescents’ breastfeeding knowledge, attitudes, and barriers that are unique to their age group.

Conclusions: This review highlights that adolescents have limited breastfeeding knowledge, unique attitudes, and face a variety of barriers to breastfeeding, including returning to school, social stigma, the physical demands of breastfeeding and unease with the act of breastfeeding. These findings indicate that developmentally sensitive education and support is fundamental to effective interventions aimed to increase breastfeeding rates among adolescent mothers.
Süd-Süd-Beziehungen und Bioökonomie. Die chinesisch-brasilianische Handelsachse
Authors: Rodríguez Fabricio
Published: March 2021

Inwiefern prägen bioökonomische Agenden den Übergang weg von der fossilen Abhängigkeit im Kontext der Süd-Süd-Beziehungen? Wie stellen sich Akteure aus dem Globalen Süden das Konzept und die Umsetzung der Bioökonomie vor? Besitzt die Bioökonomie das Potential, die Landschaft globaler Ungleichheiten durch die aktive Beteiligung von Akteuren aus dem globalen Süden umzustrukturieren? Der Artikel behandelt diese Fragen anhand einer kritischen Analyse der Handelsbeziehungen zwischen China und Brasilien im Zeitraum 2000-2018. Der chinesisch-brasilianische Fall wird als eine wichtige Achse der Süd-Süd-Beziehungen im Kontext der entstehenden Bioökonomie interpretiert. Dabei zeigt sich, dass sich die Handelsbeziehungen zwischen beiden Ländern trotz grüner Politiken keineswegs in Richtung einer kohlenstoffarmen Transition entwickeln. Obwohl die chinesisch-brasilianischen Handelsströme einen Ausdruck der Süd-Süd-Kooperation darstellen, geht mit ihnen kein Abbau der klassischen Produktionshierarchien zwischen Zentrum und Peripherie einher. Dagegen entstehen neue Ungleichheiten mit hoher Relevanz für die Bioökonomie.
A new perspective of exponential stability for Timoshenko systems under history and thermal effects
Authors: Jorge Silva Marcio A. , Pinheiro Sandro B.
Published: March 2021

We address a Timoshenko system with memory in the history context and thermoelasticity of type III for heat conduction. Our main goal is to prove its uniform (exponential) stability by illustrating carefully the sensitivity of the heat and history couplings on the Timoshenko system. This investigation contrasts previous insights on the subject and promotes a new perspective with respect to the stability of the thermo-viscoelastic problem carried out, by combining the whole strength of history and thermal effects.
Systematic Review of the Role of BCG in the Treatment of Urothelial Carcinoma of the Prostatic Urethra
Authors: Patschan Oliver , Spiess Philippe E. , Thalmann George N. , Redorta Joan Palou , Gakis Georgios
Published: March 2021

BACKGROUND:

In patients with non-invasive urothelial carcinoma of the prostatic urethra (PUC), treatment with Bacillus Calmette-Guérin (BCG) could be beneficial.

OBJECTIVE:

To assess the response rates to BCG in the different tumor stages, to describe the clinical impact of transurethral resection of the prostate (TURP) before BCG treatment, and to review the side effects of BCG treatment for PUC.

METHODS:

A systematic search was conducted using the PubMed database to identify original studies between 1977 and 2019 reporting on PUC and BCG.

RESULTS:

Of a total of 865 studies, ten were considered for evidence synthesis. An indication for BCG treatment was found in non-stromal invasive stages (Tis pu, Tis pd) and in stromal infiltrating cases (T1) of primary and secondary PUC when transitional cell carcinoma was the histology of origin. Studies including patients treated with TURP before BCG showed a better local response in the prostatic urethra with a higher disease free survival (DFS) (80–100% vs. 63–89%) and progression free survival (PFS) (90–100% vs. 75–94%) than patients in studies in which no TURP was performed. However, this difference in recurrence and progression in the prostate neither affected the total PFS (57–75% vs. 58–93%), nor the disease specific survival (70–100% vs. 66–100%).

CONCLUSIONS:

The use of resection loop biopsies of the prostatic urethra in appropriate cases during the primary work-up for suspected PUC, as well as the use of the current TNM classification for PUC, need to be improved. BCG therapy for non-stromal invasive stages of PUC show a good local response. Local response is further improved by a TURP before BCG therapy, although the overall prognosis does not seem to be affected. Further evidence for BCG treatment in the rare cases of stromal invasive PUC is needed. Specific side effects of BCG treatment for PUC are not reported.
Applicability of pain neuroscience education: Where are we now?
Authors: Barbari Valerio , Storari Lorenzo , Maselli Filippo , Testa Marco
Published: March 2021

BACKGROUND: Explaining pain to patients through pain neuroscience education (PNE) is currently a widespread treatment studied in the musculoskeletal context. Presently, there is sufficient evidence supporting the effectiveness of PNE in patients with chronic musculoskeletal disorders. However, clinicians must pay attention to the actual possibility to transfer research findings in their specific clinical context. OBJECTIVE: We analysed the applicability of results of studies focused on PNE, which has not been done previously. METHODS: A detailed discussion on PNE applicability is provided, starting from published randomized controlled trials that investigated the effectiveness of PNE. RESULTS: This paper markedly points out the awareness of clinicians on the need for an accurate contextualization when choosing PNE as an intervention in clinical practice.
FAM196B promotes proliferation and migration via regulating epithelial-mesenchymal transition in esophageal cancer
Authors: Xia Haifeng , Hu Fang , Pan Liangbin , Xu Chengcheng , Huang Haitao , Chen Shaomu , Ma Haitao
Published: March 2021

This article has been retracted, and the online PDF replaced with this retraction notice. DOI: 10.3233/CBM-229004
miR-125b enhances metastasis and progression of cancer via the TXNIP and HIF1α pathway in pancreatic cancer
Authors: Wang Pengli , Zheng Dan , Qi Hongyang , Gao Qi
Published: March 2021

BACKGROUND: MicroRNAs (miRNAs) play potential role in the development of various types of cancer conditions including pancreatic cancer (PC) targeting several cellular processes. Present study was aimed to evaluate function of miR-125b and the mechanism involved in PC. METHODS: Cell migration, MTT and BrdU study was done to establish the migration capability, cell viability and cell proliferation respectively. Binding sites for miR-125b were recognized by luciferase assay, expression of protein by western blot and immunofluorescence assay. In vivo study was done by BALB/c nude xenograft mice for evaluating the function of miR-125b. RESULTS: The study showed that expression of miR-125b was elevated in PC cells and tissues, and was correlated to proliferation and migration of cells. Also, over-expression of miR-125b encouraged migration, metastasis and proliferation of BxPC-3 cells, the suppression reversed it. We also noticed that thioredoxin-interacting protein (TXNIP) was the potential target of miR-125b. The outcomes also suggested that miR-125b governed the expression of TXNIP inversely via directly attaching to the 3′-UTR activating hypoxia-inducible factor 1α (HIF1α). Looking into the relation between HIF1α and TXNIP, we discovered that TXNIP caused the degradation and export of HIF1α by making a complex with it. CONCLUSION: The miR-125b-TXNIP-HIF1α pathway may serve useful strategy for diagnosing and treating PC.
Evolution of e-participation in Greek local government
Authors: Costopoulou Constantina , Ntaliani Maria , Ntalianis Filotheos
Published: March 2021

Local governments are increasingly developing electronic participation (e-participation) initiatives, expecting citizen involvement in local community affairs. Our objective was to assess e-participation and the extent of its change in local government in Greece. Using content analysis for 325 Greek municipal websites, we assessed e-participation status in 2017 and 2018 and examined the impact of change between these years. The assessment regards two consecutive years, since the adoption of digital technologies by municipalities has been rapid. The main findings show that Greek local governments have made significant small- to medium-scale changes, in order to engage citizens and local societies electronically. We conclude that the integration of advanced digital technologies in municipalities remains underdeveloped. We propose that Greek municipalities need to consider incorporating new technologies, such as mobile apps, social media and big data, as well as e-decision making processes, in order to eliminate those obstacles that hinder citizen engagement in local government. Moreover, the COVID-19 outbreak has highlighted the need for enhancing e-participation and policymakers’ coordination through advanced digital technologies.
Polyphenol-Peptide Interactions in Mitigation of Alzheimer’s Disease: Role of Biosurface-Induced Aggregation
Authors: Gaudreault Roger , Hervé Vincent , van de Ven Theo G.M. , Mousseau Normand , Ramassamy Charles
Published: March 2021

Alzheimer’s disease (AD) is the most common age-related neurodegenerative disorder, responsible for nearly two-thirds of all dementia cases. In this review, we report the potential AD treatment strategies focusing on natural polyphenol molecules (green chemistry) and more specifically on the inhibition of polyphenol-induced amyloid aggregation/disaggregation pathways: in bulk and on biosurfaces. We discuss how these pathways can potentially alter the structure at the early stages of AD, hence delaying the aggregation of amyloid-β (Aβ) and tau. We also discuss multidisciplinary approaches, combining experimental and modelling methods, that can better characterize the biochemical and biophysical interactions between proteins and phenolic ligands. In addition to the surface-induced aggregation, which can occur on surfaces where protein can interact with other proteins and polyphenols, we suggest a new concept referred as “confinement stability”. Here, on the contrary, the adsorption of Aβ and tau on biosurfaces other than Aβ- and tau-fibrils, e.g., red blood cells, can lead to confinement stability that minimizes the aggregation of Aβ and tau. Overall, these mechanisms may participate directly or indirectly in mitigating neurodegenerative diseases, by preventing protein self-association, slowing down the aggregation processes, and delaying the progression of AD.
Stability and control of fuzzy time delay systems with unmatched preconditions
Authors: Hou Yubao , Gao Jinding
Published: March 2021

The stability and control of nonlinear time-delay systems of Takagi-Sugeno (T-S) fuzzy model are studied in this paper. The integral inequality of a free weight matrix is chosen to give a less conservative delay-dependent stability criterion in the form of linear matrix inequalities (LMIs). The premise mismatch strategy is applied, it is combined with Finsler lemma, a more flexible design method of fuzzy state feedback controller is proposed. This method does not require the controller and system to share the common premise membership function and the number of rules. The controller design strategy proposed in this paper can effectively solve the control problem of fuzzy systems when the number of state variables is not equal to the number of input variables (r≠c), or mi⁢(x⁢(t))≠hi⁢(x⁢(t)),i=1,2,…,r. Finally, two simulation examples are given to prove the advancement and effectiveness of the proposed theory.
A wireless real-time monitoring system on intelligent underwater pollution cleaning robot
Authors: Wu Xiaoyan , Wang Shu , Wang Xinnan , He Guogeng
Published: March 2021

Intelligent underwater pollution cleaning robot is used to release microbial solution which can dissolve into water slowly into polluted river, so that the solution can react fully with pollutants, so as to achieve the purpose of river pollution control. The research of robot wireless monitoring system is based on the comprehensive application of wireless communication technology and intelligent control technology, in order to achieve real-time monitoring and centralized remote control of underwater pollution removal. Through the three-dimensional structure modeling of the intelligent underwater pollution cleaning robot, the overall scheme design and debugging test of the wireless monitoring system, it is proved that the intelligent underwater pollution cleaning robot is feasible in the intelligent and efficient underwater cleaning operation, and it is a research method worthy of reference and promotion.
Parallel FCM clustering algorithm of fuzzy number based on cut set
Authors: Huang Dakun , Wang Jing , Wen Zhicheng
Published: March 2021

Aiming at the problem of complex method and low efficiency of fuzzy numbers in classification processing, a parallel Fuzzy CMeans (FCM) clustering method based on cut set is proposed. Firstly, according to the decomposition theorem, the fuzzy numbers are divided horizontally into the form of the union of interval numbers, and then the interval numbers are transformed into the determined “real” data, and the parallel FCM clustering algorithm is used to classify the fuzzy numbers. The theoretical analysis and application show that the method has good classification accuracy and efficiency for fuzzy data clustering.
The depth utilization method of condensate system’s energy-storage to improve large turbine generator units’ load response characteristic
Authors: Shi Jiakui , Yao Kun , Sun Jianguo , Wang Wei , Wan Jie , Gu Weifei , Tong Xiaozhong , Qin Ganghua
Published: March 2021

Load response characteristics of high thermal power units are critical to a safe and efficient grid-connected utilization of large-scale renewable energy with strong randomness. A condensate throttling regulation was reported to improve the units variable load rate. However, it is not verified by tests in different types of units. In the paper, the influence of the storage capacity of the steam generator’s condensate system on the load response characteristics is studied for four subcritical 330 MW heating units by simulation and an experimental test. The result shows the feasibility of the condensate throttling regulation, which is of great value to the practical engineering application in the future. In addition, this paper obtains the condensate regulation potential of units under different power generation load conditions through simulation and actual tests. These real data will help other units of the same type to carry out similar modifications or tests.
Influence of structure parameters of optical current sensor with iron core on temperature distribution
Authors: Shi Zhengang , Fu Wenjie , Sun Chong , Zhang Linhao , Li Han , Wu Chaofei
Published: March 2021

The accuracy of optical current sensors in power systems will be affected by the interference of the external environment. Among them, temperature has a significant influence on the accuracy of optical current sensors, which is one of the main factors that restrict the practicality of optical current sensors. In this paper, the temperature field distribution of the optical current sensor with iron core is calculated by simulation. The influence of its structural parameters on the temperature field distribution is studied. It is compared with the temperature field distribution of the optical current sensor of the commonly used magnetic ring structure. It is found that under the same current, the temperature of the magneto-optical material with the core optical current sensor is much lower than the optical current mutual inductance of the common magnetic ring structure. The geometric structure parameters of the optical current sensor with iron core have a great influence on its temperature field distribution. The temperature field distribution can be improved by optimizing the structure parameters, thereby improving the measurement accuracy. This article can provide a basis for the design optimization of optical current sensors.
Deep learning and signal processing based algorithm for autorecognition of harmonic loads
Authors: Srikanth Pullabhatla , Koley Chiranjib
Published: March 2021

A convolution neural network (CNN) based deep learning method has been proposed for automatic classification and localization of nonlinear loads present in an interconnected power system. The identification of nonlinear loads has been previously dealt with the use of Nonlinear Auto Regression neural network with eXogenous inputs (NARX), Backpropagation Neural Network (BPNN), Probabilistic Neural Network (PNN), Artificial Neural Networks (ANN) and Fuzzy Logic (FL). However, these techniques had not explored the area of classification of industrial and domestic nonlinear loads in an interconnected power system. Also, a Deep learning-based solution for identification of the type of nonlinear load has not been reported in the literature to date. Hence, to address these shortcomings, an IEEE-9 Bus system with industrial nonlinear loads has been used to obtain various current waveforms with distortions. The recorded current waveforms are transformed into a time-frequency (TF) domain plane, and the obtained images are then fed to the deep learning algorithm. The colored images of the TF plots of each type of nonlinear load in Red-Green-Blue (RGB) index provide the best visual features for extraction. The TF domain signatures of individual events are scaled to a standard size before feeding to the algorithm. Through these TF signatures, unique features were extracted with the deep learning algorithm, and then passed on to different stages of convolution and max-pooling with fully connected layers. The softmax classifier at the end classifies the input data into the type of nonlinear present in the power system. The algorithm, when run at different buses, also identifies the location of the nonlinear load. The proposed methodology avoids the usage of any additional fusion layer for obtaining unique features, reduces the training time and maintains the highest accuracy of 100%.
Distributed probability density based multi-objective routing for Opp-IoT networks enabled by machine learning
Authors: Ajith Kumar S.P. , Banyal Siddhant , Bhardwaj Kartik Krishna , Thakur Hardeo Kumar , Sharma Deepak Kumar
Published: March 2021

Opportunistic IoT networks operate in an intermittent, mobile communication topology, employing peer-to-peer transmission hops on a store-carry-forward basis. Such a network suffers from intermittent connectivity, lack of end-to-end route definition, resource constraints and uncertainties arising from a dynamic topology, given the mobility of participating nodes. Machine learning is an instrumental tool for learning and many histories-based machine learning paradigms like MLPROPH, KNNR and GMMR have been proposed for digital transformations in the field with varying degrees of success. This paper explores the dynamic topology with a plethora of characteristics guiding the node interactions, and consequently, the routing decisions. Further, the study ascertains the need for better representation of the versatility of node characteristics that guide their behavior. The proposed scheme Opportunistic Fuzzy Clustering Routing (OFCR) protocol employs a three-tiered intelligent fuzzy clustering-based paradigm that allows representation of multiple properties of a single entity and the degree of association of the entity with each property group that it is represented by. Such quantification of the extent of association allows OFCR a proper representation of multiple node characteristics, allowing a better judgement for message routing decisions based on these characteristics. OFCR performed 33.77%, 6.07%, 3.69%, 6.88% and 78.14% better than KNNR, GMMR, CAML, MLPRoPH and HBPR respectively across Message Delivery probability. OFCR, not only shows improved performance from the compared protocols but also shows relatively more consistency across the change in simulation time, message TTL and message generation interval across performance metrics.
Optimization of multi-task nodes in wireless sensor networks based on discrete particle swarm algorithm
Authors: Zhu Xiuying
Published: March 2021

Aiming at the competition conflict problem of task allocation of sensor node in wireless sensor network multi-target tracking, a discrete particle swarm optimization tracking task allocation optimization algorithm based on nearest neighbor is proposed. By constructing the mathematical model and objective function of the multi-objective multi-sensor node alliance cooperative tracking task allocation problem, the nearest neighbor method is used to initialize the particle group node task allocation, the objective function is used as the fitness function to guide the particle flight, and the optimal node allocation can be quickly realized. Experiments show that in the case of sparse node coverage, the particle swarm optimization node task allocation method has greatly reduced energy consumption compared with the nearest neighbor method, and can effectively solve the problem of multi-target tracking node task allocation conflict and multiple monitoring alliances on sensor resources the problem of increased system energy consumption during competition conflicts. Discrete particle swarm optimization has superiority for wireless sensor network multi-target tracking in actual environment.
Research on the university intelligent learning analysis system based on AI
Authors: Huang Meng , Liu Shuai , Zhang Yahao , Cui Kewei , Wen Yana
Published: March 2021

The integration of Artificial Intelligence technology and school education had become a future trend, and became an important driving force for the development of education. With the advent of the era of big data, although the relationship between students’ learning status data was closer to nonlinear relationship, combined with the application analysis of artificial intelligence technology, it could be found that students’ living habits were closely related to their academic performance. In this paper, through the investigation and analysis of the living habits and learning conditions of more than 2000 students in the past 10 grades in Information College of Institute of Disaster Prevention, we used the hierarchical clustering algorithm to classify the nearly 180000 records collected, and used the big data visualization technology of Echarts + iView + GIS and the JavaScript development method to dynamically display the students’ life track and learning information based on the map, then apply Three Dimensional ArcGIS for JS API technology showed the network infrastructure of the campus. Finally, a training model was established based on the historical learning achievements, life trajectory, graduates’ salary, school infrastructure and other information combined with the artificial intelligence Back Propagation neural network algorithm. Through the analysis of the training resulted, it was found that the students’ academic performance was related to the reasonable laboratory study time, dormitory stay time, physical exercise time and social entertainment time. Finally, the system could intelligently predict students’ academic performance and give reasonable suggestions according to the established prediction model. The realization of this project could provide technical support for university educators.
Signal processing algorithms for SSVEP-based brain computer interface: State-of-the-art and recent developments
Authors: Hong Jie , Qin Xiansheng
Published: March 2021

Over past two decades, steady-state evoked potentials (SSVEP)-based brain computer interface (BCI) systems have been extensively developed. As we all know, signal processing algorithms play an important role in this BCI. However, there is no comprehensive review of the latest development of signal processing algorithms for SSVEP-based BCI. By analyzing the papers published in authoritative journals in nearly five years, signal processing algorithms of preprocessing, feature extraction and classification modules are discussed in detail. In addition, other aspects existed in this BCI are mentioned. The following key problems are solved. (1) In recent years, which signal processing algorithms are frequently used in each module? (2) Which signal processing algorithms attract more attention in recent years? (3) Which modules are the key to signal processing in BCI field? This information is very important for choosing the appropriate algorithms, and can also be considered as a reference for further research. Simultaneously, we hope that this work can provide relevant BCI researchers with valuable information about the latest trends of signal processing algorithms for SSVEP-based BCI systems.
Stance detection using diverse feature sets based on machine learning techniques
Authors: Ayyub Kashif , Iqbal Saqib , Nisar Muhammad Wasif , Ahmad Saima Gulzar , Munir Ehsan Ullah
Published: March 2021

Sentiment analysis is the field that analyzes sentiments, and opinions of people about entities such as products, businesses, and events. As opinions influence the people’s behaviors, it has numerous applications in real life such as marketing, politics, social media etc. Stance detection is the sub-field of sentiment analysis. The stance classification aims to automatically identify from the source text, whether the source is in favor, neutral, or opposed to the target. This research study proposed a framework to explore the performance of the conventional (NB, DT, SVM), ensemble learning (RF, AdaBoost) and deep learning-based (DBN, CNN-LSTM, and RNN) machine learning techniques. The proposed method is feature centric and extracted the (sentiment, content, tweet specific and part-of-speech) features from both datasets of SemEval2016 and SemEval2017. The proposed study has also explored the role of deep features such as GloVe and Word2Vec for stance classification which has not received attention yet for stance detection. Some base line features such as Bag of words, N-gram, TF-IDF are also extracted from both datasets to compare the proposed features along with deep features. The proposed features are ranked using feature ranking methods such as (information gain, gain ration and relief-f). Further, the results are evaluated using standard performance evaluation measures for stance classification with existing studies. The calculated results show that the proposed feature sets including sentiment, (part-of-speech, content, and tweet specific) are helpful for stance classification when applied with SVM and GloVe a deep feature has given the best results when applied with deep learning method RNN.
MGFPN: Enhancing multi-scale feature for object detection
Authors: He Weiming , Wu You , Xiao Jing , Cao Yang
Published: March 2021

Feature pyramids are commonly applied to solve the scale variation problem for object detection. One of the most representative works of feature pyramid is Feature Pyramid Network (FPN), which is simple and efficient. However, the fully power of multi-scale features might not be completely exploited in FPN due to its design defects. In this paper, we first analyze the structure problems of FPN which prevent the multi-scale feature from being fully exploited, then propose a new feature pyramid structure named Mixed Group FPN (MGFPN), to mitigate these design defects of FPN. Concretely, MGFPN strengthens the feature utilization by two modules named Mixed Group Convolution(MGConv) and Contextual Attention(CA). MGConv reduces the spatial information loss of FPN in feature generation stage. And CA narrows the semantic gaps between features of different receptive field before lateral summation. By replacing FPN with MGFPN in FCOS, our method can improve the performance of detectors in many major backbones by 0.7 to 1.2 Average Precision(AP) on MS-COCO benchmark without adding too much parameters and it is easy to be extended to other FPN-based models. The proposed MGFPN can serve as a simple and strong alternative for many other FPN based models.
Forecasting the spread and total size of confirmed and discharged cases of COVID-19 in Nigeria using an ARIMA model
Authors: Agboola S. , Niyang P. , Olawepo O. , Ukponu W. , Niyang S. , Ujata I. , Ihueze A. , Ibrahim R. , Shallangwa J. , Adamu H. , Ogbeh S. , Madubuko E. , Eze A. , Njoku K. , Gobir B.
Published: March 2021

Coronavirus disease 2019 (COVID-19) has been considered a global threat spreading to Nigeria and posing major public health threats and concerns. This led to the introduction of internationally acceptable non-pharmaceutical interventions (NPI) such as lockdowns, social distancing, and mandatory use of face masks by the Nigerian government to curtail the disease. This study aims to develop an Autoregressive Integrated Moving Average (ARIMA) model to predict COVID-19 cases vis Total Confirmed Cases (TCC) and Total Discharged Cases (TDC) in Nigeria based on the daily data obtained from the Nigeria Centre for Diseases Control (NCDC) from 27th February 2020 to 6th June 2020. The autocorrelation function (ACF), and partial autocorrelation function (PACF) were used to determine the constructed model. An ARIMA model was developed to predict the trend of TCC and TDC for the next 200 days. Forecasting was done using the constructed models. The finding shown that TCC increased to 50,225 with a CI between 29,425 to 100,450 and TDC to 20,186 with CI between 11,106 to 40,366 approximately. The result shows a significant increase in both TCC and TDC from COVID-19 which should guide the government roll out and management of the different NPI and policies to contain the virus.
Influence of heart rate and coronary artery calcification on image quality and diagnostic performance of coronary CT angiography: comparison between 96-row detector dual source CT and 256-row multidetector CT
Authors: Qian Wen , Liu Wangyan , Zhu Yinsu , Wang Jun , Chen Yang , Meng Haoyu , Chen Leilei , Xu Yi , Zhu Xiaomei
Published: March 2021

BACKGROUND:

CT-derived fractional flow reserve (FFRCT) and diagnostic accuracy rely on good image quality during coronary CT angiography (CCTA).

OBJECTIVE:

To investigate whether heart rate (HR) and coronary artery calcium (CAC) score decrease image quality and diagnostic performance of two advanced CT scanners including 96-row detector dual source CT (DSCT) and 256-row multidetector CT (MDCT).

METHODS:

First, 79 patients who underwent CCTA (42 with DSCT and 37 with MDCT) and invasive coronary angiography (ICA) are enrolled. Next, coronary segments with excellent image quality are evaluated and the percentage is calculated. Then, diagnostic accuracy in detecting significant diameter stenosis is presented with ICA as the reference standard.

RESULTS:

Compared with the DSCT, the percentage of coronary segments with excellent image quality is lower (P = 0.010) while diagnostic accuracy on per-segment level is improved (P = 0.037) using MDCT. CAC score≥400 is the only independent factor influencing the percentage of coronary segments with excellent image quality [odds ratio (OR): DSCT, 3.096 and MDCT, 1.982] and segmental diagnostic accuracy (OR: DSCT, 2.630 and MDCT, 2.336) for both scanners. HR≥70 bpm (OR: 5.506) is the independent factor influencing the percentage of coronary segments with excellent image quality with MDCT.

CONCLULSION:

During CCTA, CAC score≥400 still decreases the proportion of coronary segments with excellent image quality and diagnostic accuracy with advanced CT scanners. HR≥70 bpm is another factor causing image quality decreasing with MDCT.
PHYTOCHEMICAL EVALUATION OF INDIGOFERA ASTRAGALINA
Authors: Tailor B. , Singh Y.
Published: March 2021

The word diabetes is Greek for a draw off, referring to the ejection of a more quantity of urine; and mellitus is Latin used for sugar. Consequently diabetes mellitus means the passage of huge amounts of sweet urine. This is derived from the information that excess glucose in the blood spills over into the urine, absorbing fluids with it. Based on the exhaustive literature survey, the objective of the present work focussed on the search of herb to be proved as more suitable among the reported herbs/ herbal preparations/claimed herbs, towards the control of blood glucose level in hyperglycemic condition. In the present investigation herbs; Indigofera astragalina were considered based on their literature information. In general, there is very little biological knowledge on the specific modes of action in the treatment of diabetes, but most of the plants have been found to contain substances like phenols, glycosides, alkaloids, terpenoids, flavonoids etc., that are normally concerned as having antidiabetic effect.

Keywords: Keywords: Antidiabetic activity, alkaloids, Flavonoid, Phenol and Indigofera Astragalina.