bluuebunny/crossref_metadata_2025 huggingface dataset:
Intestinal Microbiota: Novel Personalized Cancer Immunotherapy in Colorectal Cancer
Authors: Azimi Maryam , Keshavarz Shahbaz Sanaz , Mansourabadi Amir Hossein , Mohamed Khosroshahi Leila , Pourkalhor Shahryar , Rezakhani Mehran , Masoumi Farimah
Published: August 2022

The human colon harbors a diverse array of microorganisms that play fundamental roles in colorectal cancer (CRC). Increasing evidence indicates that dysbiosis of the intestinal microbiome has been associated with the development of CRC. Interaction between host genetics, intestinal microbiota, and lifestyle is well-indicated in the influence, prevention, and treatment of CRC. Various microbiome compositions have reported anticancer and/or anti-inflammatory properties. The presence of our microbiota is integral to our development, but a change in its composition can often lead to adverse effects, increasing the propensity for serious diseases like cancers. Recently, molecular detection and metabolomic techniques have increased our knowledge of the role of microbiota in promoting tumorigenesis. Dietary interventions may be appropriate to regulate the growth of beneficial microbiota in the gut. Metagenomic approaches along with immunology and metabolomics will obvious a new path for the treatment of CRC. In this study, we summarized recent advances in understanding the mechanisms involved in microbiota-related colorectal carcinoma, based on evidence from immunotherapy studies.
COPD: Bei älteren Patienten an Sarkopenie denken und diese in ein therapeutisches Gesamtkonzept integrieren
Authors: Frohnhofen Helmut
Published: August 2022

Background: Chronic Obstructive Pulmonary Disease (COPD) is characterized by progressive and irreversible airflow limitation. Different factors that modify pulmonary function include age, sex, muscular strength, and a history of exposure to toxic agents. However, the impact of body composition compartments and sarcopenia on pulmonary function is not well-established. This study aimed to evaluate how body composition compartments and sarcopenia affect pulmonary function in COPD patients. Methods: In a cross-sectional study, patients with a confirmed diagnosis of COPD, > 40 years old, and forced expiratory volume in the first second/forced vital capacity ratio (FEV1/FVC) < 0.70 post-bronchodilator were included. Patients with cancer, HIV, and asthma were excluded. Body composition was measured with bioelectrical impedance. Sarcopenia was defined according to EWGSOP2, and pulmonary function was assessed by spirometry. Results: 185 patients were studied. The mean age was 72.20 ± 8.39 years; 55.14% were men. A linear regression adjusted model showed associations between body mass index, fat-free mass, skeletal muscle mass index, appendicular skeletal muscle mass index, and phase angle (PhA), and sarcopenia with FEV1 (%). As regards FVC (%), PhA and exercise tolerance had positive associations. Conclusion: Body composition, especially PhA, SMMI, ASMMI, and sarcopenia, has a significant impact on pulmonary function. Early detection of disturbances of these indexes enables the early application of such therapeutic strategies in COPD patients.
Statistical and machine learning approach for evaluation of control systems for automatic production lines
Authors: Tsenev Valentin , Ivanova Malinka
Published: August 2022

The manufacturing processes and the control systems for automatic production lines mainly are evaluated through usage of statistical methods as recently machine learning algorithms are also used. The aim of the paper is to present an approach for control measurement systems evaluation, based on a combination of statistical techniques like attribute repeatability and reproducibility analysis, measurement system analysis and supervised machine learning algorithms like random forest and KNN. The proposed method is verified in the production of the G8680x connector, which is used in the automotive industry. The control is performed 100% for all manufactured parts immediately after the “injection molding” process. It is proved that taking advantages of the statistics and machine learning, the manufacturing process and control measurement systems could be evaluated with very high accuracy. The exploration and analysis leads to the formulation of some recommendations in support of process engineers and managers.
Serious game self-regulation using human-like agents to visualize students engagement base on crowd
Authors: Umam Khothibul , Fachri Moch , Nugroho Fresy , Susiki Nugroho Supeno Mardi , Hariadi Mochamad
Published: August 2022

Nowadays, the emergence of artificial intelligent (AI) technology for games has been advancely developed. A serious game is a technology employing AI to create a virtual environment in a serious gamification strategy. This research describes AI based virtual classrooms to adopt proper strategies and focusing on maintaining and increasing student engagement by encouraging self-regulation behavior at the learning process. The self-regulation behavior describes student's ability to direct their own learning to achieve learning targets on a path full of obstacles. By employing a human-like agent to visualize student engagement, this visualization aims to provide human-like experiences for users to comprehend student behavior. A reciprocal velocity obstacles (RVO)-based crowd behavior is employed to visualize student engagement. RVO is an autonomous navigation approach for directing the achievement of agents target. The human-like agents behave in various ways to reach the goal points depending on the performances and the obstacles before them. We employ our method in an investigation of students' learning activities in a pedagogically-centered learning environment at Universitas Islam Negeri (UIN) Walisongo, Semarang, Indonesia. The results demonstrate the best scenario changes along with the performances and obstacles faced to reach the goal points as well as the learning target.
Design a mobile application to detect tomato plant diseases based on deep learning
Authors: Abdulla Marwa , Marhoon Ali
Published: August 2022

Plant diseases consider the most dominant matter for farmers' concerns becausethe operation of discovering and dealing with them requires accuracy, experience, and time. Therefore, this paper proposes an approach to classify seven varieties of tomato diseases using deep learning models. A dataset of 10448 images from PlantVillage and google utilize to train the deep learning (CNN models). The trained models proved their ability to classify with high accuracy, as the highest testing accuracy reached 95.71% for the proposed model for 50 epochs only. The resulted best model is published to a mobile application using the android studioplatform, this application enables the farmer to classify plant diseases accurately and easily. The proposed model and mobile application could be extended to classify as many plant diseases as possible.
Strong green-emission phosphor Ca2SiO4:Eu2+ to achieve the color constancy and high luminous efficiency for white LEDs
Authors: Liem Bui Van , Lee Hsiao-Yi , Cong Tran Thinh
Published: August 2022

The study uses the green phosphor of Ca2SiO4:Eu2+ to achieve the color constancy for the dual-film remote phosphor white-LED model at low as well as big CCTs. The utilized green phosphor Ca2SiO4:Eu2+ was prepared using the water-soluble-silicon liquid phase precursor method with the doped Eu2+ ion concentration of 3 mol%. The Ca2SiO4:Eu2+ phosphor emits strong green light with emission intensity focused at 502 nm wavelength, and a wide stimulation band of colors of 225 nm – 450 nm. After applying the Ca2SiO4:Eu2+ green phosphor and modifying its concentration, the modified color and luminous performances can be observed. The better color uniformity and higher luminescence efficiency can be obtained by increasing the percentage of Ca2SiO4:Eu2+ in the phosphor configuration. Meanwhile, the color rendering metrics tend to reduce slightly when the concentration of Ca2SiO4:Eu2+ is over 10% wt.
Prediction measuring local coffee production and marketing relationships coffee with big data analysis support
Authors: Sindar Ros Maryana Sinaga Anita , Eka Putra Ricky , Suganda Girsang Abba
Published: August 2022

Following the increasing enthusiasm of the coffee market in Indonesia, a machine learning model is developed to study the relationship between coffee producers, consumers, production, and the market. Machine learning work flow is constructed in various stages; explore, develop, and validate the models. In this research, the building model predicts the production and market of late departure coffee based on labeled and unlabeled variables. The best predictions from the trained type of model algorithms of machine learning like tree accuracy of 85.7%, support vector machine (SVM) accuracy of 82.9%, and k-nearest neighbors, the accuracy of 82.9%, which produce three categories, namely, high production of 2 provinces, medium production of 21 provinces, and low production of 11 provinces. The accuracy classification is supported by the AUC value obtained for a high class, a medium class, and a low class. In addition, local coffee marketing modeling used in logistic regression was found with an accuracy of 88.9%, aiming to classify coffee interests between Arabica coffee and Robusta coffee. We found that the AUC value logistic regression for arabica coffee is about 0.94, while for Robusta is 0.92. The analysis of the classification modeling results shows a high level of accuracy of 93.0%.
Effective monitoring of power system with phasor measurement unit and effective data storage system
Authors: Ponnala Ravi , Chakravarthy Muktevi , Lalitha Suraparaju Venkata Naga Lakshmi
Published: August 2022

In the recent years the monitoring and operation of the power system became complex, due to the more demand from the different linear and non-linear loads and generation from the different sources. For the effective monitoring and operation of the power system, existing power system monitoring methods need to improve or new technologies are required. For the effective monitoring and operation of the power system phasor measurement unit (PMU) based monitoring is suitable, because it provide the dynamic state monitoring system. In this paper PMU based monitoring is proposed with effective data storage system and protection. With this method phasor values of voltage and current signals are calculated at the location of PMU and with the help of software based program effective data storage also possible. With this proposed model the phasor values in the power system at different locations monitoring also possible and required phasor data only stored and total data is only monitored. The phasor values of signals are calculated with direct phasor measurement technique in LabVIEW and by adding time stamping to the each phasor value accurate measurement of power flow is possible.
An approach of anchor link prediction using graph attention mechanism
Authors: Le Van-Vang , Pham Phuong Nguyen Huy , Toai Tran Kim , Snasel Vaclav
Published: August 2022

Nowadays social networks such as Twitter, LinkedIn, and Facebook are a popular and necessary platform. It is considered a miniature of an actual social network because of its advantages in connecting and sharing information between users. The analysis of data on online social networks has become a field that has attracted a lot of attention from the research community and anchor link prediction is one of the main research directions in this field. Depending on demand, a user can simultaneously participate in many different online social networks, anchor link prediction is a kind of task that determines the identity of a user on many different social networks. In this article, we proposed an algorithm that determines missing/future anchor links between users from two different online social networks. Our algorithm utilizes the graph attention technique to represent the source and target network into the low-dimension embedding spaces, we then apply the canonical correlation analysis to recline their embeddings into same latent spaces for final prediction.
Detection of the patient with COVID-19 relying on ML technology and FAST algorithms to extract the features
Authors: Sahy Seba Aziz , Mahdi Sura Hammed , Gheni Hassan Muwafaq , Al-Barazanchi Israa
Published: August 2022

COVID-19 is unquestionably one of the most hazardous health issues of our century, and it is a significant cause of mortality for both men and women throughout the globe. Even with the most advanced pharmacological and technical innovations, cancer oncologists, and biologists still have a substantial problem treating COVID-19. For patients with COVID-19, it is critical to offer initial, precise, and effective indicative procedures to increase their survival and minimize morbidity and mortality, which is currently lacking. A COVID-19 detection method has been presented in this paper for the initial identification of COVID-19 hazard factors. Features from accelerated segment test (FAST), a robust feature was used to extract features in this suggested method. The experiments show that it is possible to identify FAST traits efficiently. A consequence was a high success rate (98%) for accuracy performance.
Gamifying education for classroom engagement in primary schools
Authors: Mee Rita Wong Mee , Rao Yugeshineey Subba , Pek Lim Seong , Ghani Khatipah Abd , Von Wong Yee , Ismail Md Rosli , Shahdan Tengku Shahrom Tengku
Published: August 2022

Gamification carries the element of fun and creativity into classroom teaching. It is not an unusual fact that playing games varied among learners and created an effective classroom environment. In the 21st-century teaching era, learners’ fun and creative learning environment are prioritized. Lessons filled with fun games are believed to produce a positive outcome during a lesson. Therefore, gamification prepares learners to be active and take responsibility for their learning. This study aimed to explore learners’ comprehension of the term ‘gamification’ and the effects of gamified elements implemented in the lesson on the targeted learners. A set of questionnaires was administered through an online survey to 100 respondents from local primary schools around Selangor who took part in a service-learning programmed. The data was then analyzed and presented in the form of tables. Results showed that respondents had prior knowledge of the term ‘gamification’ and the game culture’s overall context. The respondents agreed that their respective teachers had implemented several game elements when conducting a gamified lesson. Results also indicated that respondents were in preference to learn using gamified learning activities that helped them learn subconsciously. 
Implementation of education for sustainable development in geography subjects among trainee teachers
Authors: Pasang Benedic Sat Anak , Mohd Najib Sumayyah Aimi
Published: August 2022

Education for sustainable development (ESD) is a truly positive measure. This study was unique in that it made students aware of the positive qualities. Therefore, ESD is crucial to be inculcated among students. If the students are provided with in-depth knowledge related to sustainable development, hence it is not impossible for the sustainable development concept to come true. The study was conducted at Universiti Pendidikan Sultan Idris (UPSI), Perak, Malaysia. The respondents involved are geography students who have undergone teacher training in semester 7 and semester 8. This study also focused on the level of knowledge and the level of mastery among trainee teachers on ESD. In addition, this study was carried out for the trainee teachers to obtain the data the on the implementation of ESD values in teaching and learning (T&L) of geography subjects via a survey. Result showed that T&L of geography subjects shall be interesting and challenging so that students can enjoy fun learning. Teachers need to be smart in finding approaches to be tailored to the curriculum, especially in the geography subjects.
Enhancing pre-service teachers in learning management competency by TPACK framework study and professional requirement
Authors: Nithitakkharanon Piyaphat , Nuangchalerm Prasart
Published: August 2022

Increasing attention has been placed in recent years to the improvement of learning management competency of pre-service teachers, yet many institutions where the teacher education programs offered have not been provided the effective guidelines. The purposes of this study were to examine the ability of the teaching practice and to propose the enhancement approach on learning management competency of pre-service teacher based on technological pedagogical content knowledge (TPACK) framework. Sample of the study included 385 pre-service teachers studying the fifth-year program at Faculty of Education, Ubon Ratchathani Rajabhat University, Thailand. A learning management competency questionnaire and semi-structured interview were administered to inquire the ability on learning management competency of pre-service teachers during the teaching practice at school. Statistics used for data analysis included frequency distribution, average, standard deviation, and content analysis. Results indicated that pre-service teachers expressed their teaching practices considered each aspect of teaching quality, results ranged from the highest to lowest level were the ability on learner-centered management ( =3.00, S.D.=0.77), the knowledge on teaching design ( =2.96, S.D.=0.72), the assessment and evaluation methods ( =2.95, S.D.=0.74), and the integration of technology ( =2.70, S.D.=0.78), respectively. Recommendations and suggestions were further discussed regarding the enhancement approaches proposed on improving learning management competency of pre-service teachers.
A review of teachers’ assessment literacy proficiency measures
Authors: Juanjuan Geng , Mohd Yusoff Nurahimah
Published: August 2022

At present, there are several literature reviews on teachers’ assessment literacy (AL). However, little attention has been paid to a systematic analysis of AL measures. The review on AL measures helps to evaluate the available tools and provide recommendations for developing AL measures in further exploration. Hence, the purpose of the current literature review is to focus on analyzing the measures of teachers’ AL proficiency from 1991 to 2020. Across the contexts, 28 quantitative tools made up of questionnaires or tests were collected. Among them, 10 were designed to investigate overall AL proficiency and 18 were constructed to examine the sub-categories of AL proficiency among teachers. Each instrument was analyzed from the format, guiding framework, item characteristics, targeting population, and psychometric quality. Results showed that the current AL measures were derived more from instrumental than social-cultural conceptualization, examined more on sub-categories than the overall proficiency level, targeted more at in-service teachers than pre-service teachers, and focused more on elementary and middle education than pre- or higher education. Further studies are welcomed from four aspects: construct social-culturally, test generalizability, target at specific groups, and cover various types of AL.
Students’ satisfaction on learning calculus using open and distance learning method during COVID-19 pandemic
Authors: Ahmad Rusliza , Mohd Ghazali Zulkifli , Abd Halim Muhammad Syawal
Published: August 2022

In early 2020, due to the COVID-19 outbreak in Malaysia, all higher education institutions had to switch from face-to-face learning to open and distance learning (ODL) method. The main purpose was to prevent any further spread of the COVID-19 virus. This study aimed to identify factors carrying impacts on students’ satisfaction in learning calculus using ODL method. The sample consists of 224 students of Universiti Teknologi MARA (UiTM) Perak Branch, Tapah Campus who took calculus subjects using ODL method during the COVID-19 lockdown in Malaysia. Five factors are found to influence students’ satisfaction towards ODL method: student-lecturer interaction; lecturer performance; ODL course evaluation; design; and technical. By using partial least square (PLS)–SEM method, the results showed that lecturer performance has a large effect size on students’ satisfaction. Technical and design factors have medium effect sizes, while the ODL course evaluation and student-lecturer interaction have small effect sizes. This research provided useful insights for an effective planning of online calculus courses by considering all factors that influence students’ satisfaction.
Knowledge and attitudes about research ethics among social researchers in Vietnam: A cross-sectional study
Authors: Tran Kham Van , Pham Cuong Huy , Tran Nam Thanh , Nguyen Lan Thi Thai , Nguyen Nhung Thi Kim
Published: August 2022

Social research has attracted significant attention in Vietnam during recent years with more questions and discussions about how to promote the research outputs and publications in this area. However, there is limited information about the knowledge and attitudes of social researchers for research ethics in Vietnam. This paper aims to assess the knowledge and attitudes of social researchers about research ethics in Vietnam. A survey with 1200 questionnaires, through convenience sampling, was sent either printed copies or email to social researchers in the universities and research institutions in Vietnam. Our response rate was 65% (782), with mean age: 35.9 years (sd=.307). The results show that around one fifth had been trained with research ethics (23.5%), which led to significant responses to the "do not know" about the research ethics principles and research ethics committee with 14.3% and 55.3%, respectively. Despite such few experiences on the research ethics, the participants presented a positive understanding of the general principles of research ethics and positive attitudes to the importance of the related general ethics principles to social research in Vietnam. Such understandings and attitudes also led to the readiness to apply the research ethics values and principles while there are no formal ethical guidelines in Vietnam social research. These findings suggest that Vietnamese social researchers understood most critical ethics principles in social research and expect formal ethical guidelines.
The initial accountant competency of final year accounting students
Authors: Weli Weli , Marsudi Almatius Setya
Published: August 2022

The development of information technology towards the 4th industrial revolution era brought changes to business processes in various industries, which will eventually have an impact on jobs in the accounting field. Accountants must be adaptable and competent to work as accounting professionals. Therefore, this study aimed to analyze the perceptions of final-year accounting students regarding knowledge competence, soft skills, information technology capabilities, and perceptions of readiness to enter the workforce. It also analyzed whether these competencies affect students' readiness to enter the workforce. In this study, the soft skills competencies are dimensions of intellectual, personal, organizational, internal, and communication competencies, and ethics in accounting. The data was collected using a questionnaire based Google Form given to several universities in Indonesia that were willing to distribute the forms to their accounting students. A descriptive method was used for data and confirmatory factor analysis and data processing was performed with the help of statistical package for the social sciences (SPSS) and partial least squares (SmartPLS) programs. The results showed that soft skills competencies had a higher score compared to accounting and information technology competencies. Furthermore, there was a significant influence between competence and work readiness of accounting students. This study provides information in the preparation of the accounting curriculum to consider various competencies following industry needs.
Demotivating factors and coping strategies among Filipino EFL teachers in Thailand
Authors: Balintag Christopher Molingit , Saengsri Punyapa
Published: August 2022

Teaching demotivation may negatively affect teachers’ performance in English language teaching. This present study investigated the demotivating factors and coping strategies of seven Filipino English as a foreign language (EFL) teacher in Thailand.Using qualitative design, semi-structured interview was used to elicit the views of teachers. Findings have shown five demotivating factors: administration-demotivational factor, colleague-demotivational factor, student-demotivational factor, self-demotivational factor, and parent-demotivational factor. Moreover, self-regulation strategy and pedagogical strategy are useful for the teacher to cope with those factors. Implications were discussed to help foreign EFL teachers in Thailand become aware of teaching challenges in Thailand.
Career readiness among low-income Muslim students
Authors: Choirudin Choirudin , Degeng I Nyoman Sudana , Kuswandi Dedi , Purnomo Purnomo , Maba Aprezo Pardodi
Published: August 2022

This study investigated the context of career readiness for Muslim students from low-income families and its’ correlation among thinking styles and self-efficacy. There were 302 participants consisted of 85 males (28%) and 217 females (78%) with an average age of 20.03 years. The analysis results showed no significant correlation between students' thinking styles based on age and place of residence. However, the difference in age correlated to students thinking styles. There was also a correlation between gender and age toward students' self-efficacy with social persuasion. The analysis showed a significant positive correlation between career readiness and the legislative, liberal, hierarchical, global, executive, local, anarchic, oligarchic, and internal conservative, oligopoly, and internal. Furthermore, significant positive correlation between self-efficacy and career readiness. The higher the students’ career readiness will be the higher their self-efficacy mastery experience. The findings further confirmed the significance of different thinking styles, self-efficacy, and the context of career readiness for Muslim students from low-income families.
Needs assessment to promote the digital literacy among students in Thai community colleges
Authors: Ussarn Anyamanee , Pimdee Paitoon , Kantathanawat Thiyaporn
Published: August 2022

The objective of this research was to assess the need to promote digital literacy of the students under the supervision of Tak Community College. The population consisted of 152 students in Tak Community College, Tak Province, Thailand, registered for the second semester of the 2020 academic year. The research instrument was a digital literacy questionnaire, and the data were analyzed using percentage, mean, standard deviation, and the prioritization of the need. The findings revealed that the level of digital literacy skills of the students was moderate. The level of digital literacy that students expected, however, was very high. In concluding remarks, it was found that the highest average of the digital literacy skills of the Tak Community College students was the use of the spreadsheet program (PNIModified=0.30), followed by the use of presentation program (PNIModified=0.27), and the word processor program as the lowest average point of skills (PNIModified=0.23). The students of Tak Community College, therefore, are inevitability required the better digital literacy skills development from the lessons enlightened by the teachers.
Saúde Mascarada: tensionamentos e apropriações do personagem Zé Gotinha durante a pandemia brasileira
Authors: França Renné Oliveira
Published: August 2022

O presente trabalho dá continuidade à proposta de compreender personagens ficcionais como celebridades. Partindo do pressuposto de que estes seres imaginários possuem também poder de mobilização e reflexão de valores e anseios dentro de um determinado contexto, buscou-se aqui analisar três momentos em que o Zé Gotinha, figura símbolo da vacinação brasileira, atuou durante a pandemia de covid-19, entre final de 2020 e meados de 2021. Para tal, este artigo propôs pensar sua articulação em meio ao imaginário político atual a partir de uma breve recuperação de campanhas de vacinação anteriores, que construíram uma imagem do Zé Gotinha que foi tensionada nas disputas de sentido da esfera pública e ressignificada por usuários de redes sociais na disputa com a narrativa governamental.
Influenciadores, intelectuais, mediadores simbólicos
Authors: Ortiz Renato
Published: August 2022

Este ensaio tem como objeto de reflexão a figura do “influenciador”, personagem recente da esfera digital. Para apreender sua especificidade, o autor estabelece um contraste com outras figuras da literatura em ciências sociais: o intelectual, os mediadores simbólicos, as celebridades. É no contraponto entre essas categorias que a dimensão da “influência” se explicita.
Claudia Leitte e a indiferença na pandemia: jornalismo e celebridades na ambiência de um ciberacontecimento
Authors: Prado Denise Figueiredo Barros do , Tavares Frederico de Mello Brandão
Published: August 2022

A partir de uma fala insensível de Claudia Leitte com relação ao contexto brasileiro durante a pandemia de covid-19 no programa Altas Horas (Rede Globo), em maio de 2021, houve intensa reverberação nas redes sociais, seguida de retratação da artista e cobertura noticiosa. Estimulados por essa ocorrência, neste artigo, problematizamos como o cenário de reverberações e afetações do evento na cobertura noticiosa é capaz de revelar traços associados às formas de presença, ao posicionamento político dos célebres no contexto brasileiro e às relações entre jornalismo e ciberacontecimentos na contemporaneidade. Mapeamos e analisamos 19 publicações relacionadas ao tema, coletadas entre 22 de maio de 2021 e 29 de maio de 2021, período de emergência do caso, nas quais observamos como o processo interacional entre artista e público é estabelecido e se constitui como fenômeno no âmbito jornalístico.
Influenciadores digitais da fé: celebridades ou evangelizadores?
Authors: Medeiros Fernanda Faria , Souza Alzirinha Rocha de , Silva Aline Amaro da , Sbardelotto Moisés , Gomes Vinicius Borges
Published: August 2022

Este trabalho apresenta uma reflexão inicial sobre o conceito de influenciadores digitais, considerando as perspectivas anteriores dos estudos de celebridades, com objetivo de propor novas dimensões para a análise desse fenômeno circunscrito no ambiente da fé. Buscando apreender os fenômenos socioeclesiais gerados a partir dos processos interacionais em rede, pretende-se discorrer sobre métodos capazes de ajudar a compreender os elementos teológicos e comunicacionais que compõem o campo específico dos influenciadores digitais da fé.
Fotografia de bandidos: o enquadramento da celebridade criminosa
Authors: Susin Ivânia Valim
Published: August 2022

A celebridade atrelada à transgressão seria um dos efeitos da circulação de fotografias de bandidos nos jornais, a princípio, no formato mug shot e, depois, nas diversas variações produzidas pela atuação policial. Nesse sentido, o circuito de produção da fotografia policial e de imprensa e as transformações do olhar do espectador, entendidos como as pontas de um mesmo processo, são considerados agentes fundamentais na construção da celebridade de bandidos.
Enquadramentos de mulheres vaqueiras no Instagram: aspectos sobre enfrentamento e resistência de subcelebridades
Authors: Duarte Ricardo , Barroso Lívia Moreira
Published: August 2022

A vaquejada é uma manifestação cultural do sertão nordestino que sempre foi associada a elementos que enaltecem a masculinidade (virilidade, vigor e força), e o que era uma profissão – o ser vaqueiro – hoje também é tido como um esporte, uma brincadeira. Porém, as transformações sofridas pela antiga “pega do boi” permitiram aos poucos a presença das mulheres vaqueiras. Nesse sentido, analisamos os perfis no Instagram de duas vaqueiras que são consideradas celebridades no contexto da vaquejada, Dayane Pereira e Beterraba. Em um contexto contemporâneo em que os processos sociais se encontram midiatizados, procuramos compreender as diferentes inserções dos sujeitos no Instagram em suas situações, as alternâncias de quadros, os papéis estabelecidos e os conflitos evidenciados a partir das narrativas comunicativas produzidas. Neste sentido, observamos as narrativas da autoapresentação e da autorrevelação nos perfis selecionados.
Feminismos e vivências: uma análise das relações de gênero na China continental
Authors: Gonçalves Tuane Oliveira
Published: August 2022

A partir, principalmente, das ideias de Ya-chen Chen, o propósito deste artigo é trazer a debate o feminismo chinês e seu histórico de relevância nas pautas feministas e de gênero. Com o intuito de compreender como se consolidou o feminismo e quando começaram as discussões em torno do gênero na China continental, a análise vai desde um pouco antes da ascensão do Partido Comunista até problemas atuais. A ideia não é esgotar toda a discussão sobre o tema, mas introduzir a complexidade em torno das questões de gênero que estreitam as relações sociais no país asiático.
Editorial Zi Yue 2022
Authors: Chia Ho Yeh
Published: August 2022

Apresentação Editorial Zi Yue 2022.
Conhecimento e estratégia geopolítica em "A arte da guerra" de Sunzi
Authors: Souza Neto João Alves de
Published: August 2022

O presente artigo objetiva interpretar a elaboração do problema do conhecimento do conflito geopolítico da obra A arte da guerra de Sunzi. Essa abordagem procura avançar as interpretações correntes acerca dessa obra. O problema histórico elaborado nesse livro diz respeito a um problema geopolítico que possui a guerra como condição de sua existência, marca do Período de Estados Combatentes (sécs. V–III aec.). A realização da guerra implica um conhecimento estratégico bastante elaborado. Apresentamos nossa interpretação a partir do exame dos capítulos um, dois, três e treze, que dizem respeito ao caminho e às fontes do conhecimento e sua necessidade.
Lexicase Selection for Multi-Task Evolutionary Robotics
Authors: Stanton Adam , Moore Jared M.
Published: August 2022

In Evolutionary Robotics, Lexicase selection has proven effective when a single task is broken down into many individual parameterizations. Evolved individuals have generalized across unique configurations of an overarching task. Here, we investigate the ability of Lexicase selection to generalize across multiple tasks, with each task again broken down into many instances. There are three objectives: to determine the feasibility of introducing additional tasks to the existing platform; to investigate any consequential effects of introducing these additional tasks during evolutionary adaptation; and to explore whether the schedule of presentation of the additional tasks over evolutionary time affects the final outcome. To address these aims we use a quadruped animat controlled by a feed-forward neural network with joint-angle, bearing-to-target, and spontaneous sinusoidal inputs. Weights in this network are trained using evolution with Lexicase-based parent selection. Simultaneous adaptation in a wall crossing task (labelled wall-cross) is explored when one of two different alternative tasks is also present: turn-and-seek or cargo-carry. Each task is parameterized into 100 distinct variants, and these variants are used as environments for evaluation and selection with Lexicase. We use performance in a single-task wall-cross environment as a baseline against which to examine the multi-task configurations. In addition, the objective sampling strategy (the manner in which tasks are presented over evolutionary time) is varied, and so data for treatments implementing uniform sampling, even sampling, or degrees of generational sampling are also presented. The Lexicase mechanism successfully integrates evolution of both turn-and-seek and cargo-carry with wall-cross, though there is a performance penalty compared to single task evolution. The size of the penalty depends on the similarity of the tasks. Complementary tasks (wallcross/turn-and-seek) show better performance than antagonistic tasks (wall-cross/cargo-carry). In complementary tasks performance is not affected by the sampling strategy. Where tasks are antagonistic, uniform and even sampling strategies yield significantly better performance than generational sampling. In all cases the generational sampling requires more evaluations and consequently more computational resources. The results indicate that Lexicase is a viable mechanism for multitask evolution of animat neurocontrollers, though the degree of interference between tasks is a key consideration. The results also support the conclusion that the naive, uniform random sampling strategy is the best choice when considering final task performance, simplicity of implementation, and computational efficiency.
Intrinsic Evolution of Analog Circuits Using Field Programmable Gate Arrays
Authors: Whitley Derek , Yoder Jason , Carpenter Nicklas
Published: August 2022

Evolvable hardware is a field of study exploring the application of evolutionary algorithms to hardware systems during design, operation, or both. The work presented here focuses on the use of field programmable gate arrays (FPGAs), a type of dynamically reconfigurable hardware device typically used for electronic prototyping in conjunction with a newly created open-source platform for performing intrinsic analog evolvable hardware experiments. This work targets the reproduction of seminal field experiments that generated complex analog dynamics of unclocked FPGAs evolved through genetic manipulation of their binary circuit representation: the bitstream. Further, it demonstrates the intrinsic evolution of two nontrivial analog circuits with intriguing properties, amplitude maximization and pulse oscillation, as well as the robustness of evolved circuits to temperature variation and across-chip circuit translation.
Nonhuman Cinema and the Logistical Sublime
Authors: Stine Kyle
Published: August 2022

Erika Magnusson and Daniel Andersson's Logistics (2012) is the longest film ever made, at over thirty-five days in duration. The film endeavors to make the world-spanning network of global logistics perceptible through an experience of the slow journey of the Dutch container-ship Elly Maersk from Gothenburg, Sweden, to Shenzhen, China. Following this document of an oceanic passage that coincided with—and was at one point halted by—the events of the Arab Spring, this article explores how extreme durational cinema raises questions about the position of the spectator and the limits of representation in an era of digitally networked media. It suggests that there exists, beyond the immediate relationship between spectator and image, a correspondence between the magnitude of filmic address and the logistical conditions of art's creation.
Sporoxeia vietnamensis (Melastomataceae), a new species from northern Vietnam
Authors: THU THUY NGUYEN , ZENG SIJIN , HAI DO VAN , THI HOAN DUONG , LIN ZHELI , DENG YUNFEI
Published: August 2022

A new species of Sporoxeia (Melastomataceae), S. vietnamensis, is described from northern Vietnam. It is morphologically similar to S. blastifolia in having obtusely quadrangular stems, slightly unequal leaf blades with cuneate bases, and two secondary veins on each side of midvein, but differs by having stiffly papery leaf blades, larger and densely horned hypanthia, larger calyx lobes with concave adaxial surface and convex abaxial surface forming a ridge, and larger petals. Photos and illustration are provided together with information of habitat, ecology and preliminary conservation assessment following IUCN criteria. An identification key to the Sporoxeia species is also provided.
Physical mapping of 45S and 5S rDNA and telomeric repeat loci in eight diploid hyacinth cultivars
Authors: HE YUAN-HAO , SU XIAO-QIAN , XU ZI-HAN , HU FENG-RONG
Published: August 2022

Hyacinth, one of the five best-selling bulbous flowers in the world, is a favored flower of garden landscapes in the spring. Hyacinth has a single origin, but there are many horticultural varieties. Physical mapping of ribosomal DNA (rDNA) and telomeric repeat loci by fluorescence in situ hybridization (FISH) is helpful to understand the genetic relationship and chromosome inheritance in hyacinth breeding. In this study, 45S rDNA, 5S rDNA and telomeric repeats were used as probes, the mitotic metaphase chromosomes of 8 diploid hyacinth cultivars were analyzed by FISH location, and their karyotype parameters were analyzed by Q-type cluster analysis. The results showed that two 45S rDNA loci were detected in all eight hyacinth cultivars, four 5S rDNA loci were detected in ‘Gypsy Queen’, and three were detected in other cultivars. In addition to the presence of telomere loci at both ends of chromosomes, seven telomere loci were detected in ‘Gypsy Princess’ and ‘Yellow Stone’, and eight telomere loci were detected in other cultivars. At the same time, when the euclidean distance between groups was 20, the eight hyacinth cultivars were clustered into three groups (‘Yellow Stone’, ‘Red Pearl’ and ‘Pink Pearl’), and ‘Gypsy Prince’ was a single group; the other four cultivars were in one group. The distribution of 45S rDNA loci in diploid hyacinth cultivars was relatively conservative, while the locus number and distribution of 5S rDNA and telomeric repeats were highly polymorphic. The FISH physical mapping in this study provides a basic understanding of the karyotype evolution of hyacinth species, which could increase the understanding of the evolutionary history and phylogenetic relationships of hyacinths.
Determination of oil pollutants by three-dimensional fluorescence spectroscopy combined with improved pattern recognition algorithm
Authors: Cheng Pengfei , Zhu Yanping , Cui Chuanjin , Wang Fubin , Pan Jinyan
Published: August 2022

Petroleum refineries are one of the main sources of hazardous air pollutants, so the accurate determination of petroleum pollutants is of great significance to maintain ecological balance. In this study, three-dimensional (3D) fluorescence spectroscopy combined with pattern recognition algorithm is adopted to distinguish the composition and content of oil pollutants efficiently and accurately. Three hundred samples of kerosene, diesel, and gasoline mixed solutions with different concentrations are prepared. The principal component analysis is used to extract the optimal feature variables, and the correlation coefficient method is used to obtain eight groups of principal component features in the spectra. The dimension is selected as 8, and the principal component score is calculated, which is used as the input data of the extension neural network. Next, the pattern recognition method is improved, and the designed neural network has functions of both resolution and measurement. The results of neural network pattern recognition are used as the input of the concentration network. The first 270 samples are used as the training samples to train the network model, and the remaining 30 samples are used as test samples, which are applied to the input layer of the trained neural network. The relative fluorescence intensity, relative slope, and comprehensive background parameters are used as the input parameters, and the extension neural network is used for pattern recognition and evaluation of oil pollutants. The experimental results show that the average recognition rate of the improved pattern recognition algorithm for oil pollutants is 98.43%, and the average recovery rate of concentration is 98.67%. Further, the average time for pattern recognition is 1.53 s, while the parallel factor analysis algorithm takes 2.89 s. This suggests that the improved extension neural network is an effective and reliable pattern recognition method for the identification of mixed oil pollutants.
Ncor1 Deficiency Promotes Osteoclastogenesis and Exacerbates Periodontitis
Authors: Ma X.X. , Meng X.Q. , Wang Y.L. , Liu Y. , Shi X.R. , Shao S. , Duan S.Z. , Lu H.X.
Published: August 2022

Nuclear receptor corepressor 1 ( Ncor1) has been reported to regulate different transcription factors in different biological processes, including metabolism, inflammation, and circadian rhythms. However, the role of Ncor1 in periodontitis has not been elucidated. The aims of the present study were to investigate the role of Ncor1 in experimental periodontitis and to explore the underlying mechanisms through an experimental periodontitis model in myeloid cell–specific Ncor1-deficient mice. Myeloid cell–specific Ncor1 knockout (MNKO) mice were generated, and experimental periodontitis induced by ligation using 5-0 silk sutures was established. Ncor1 flox/flox mice were used as littermate controls (LC). Histological staining and micro–computed tomography scanning were used to evaluate osteoclastogenesis and alveolar bone resorption. Flow cytometry was conducted to observe the effect of Ncor1 on myeloid cells. RNA sequencing was used to explore the differentially targeted genes in osteoclastogenesis in the absence of Ncor1. Coimmunoprecipitation (Co-IP), chromatin immunoprecipitation (ChIP) experiments, and dual luciferase assays were performed to explore the relationship between NCoR1 and the targeted gene. Alveolar bone resorption in the MNKO mice was significantly greater than that in the LC mice after periodontitis induction and osteoclastogenesis in vitro. The percentage of CD11b+ cells, particularly CD11b+ Ly6G+ neutrophils, was substantially higher in gingival tissues in the MNKO mice than in the LC mice. Results of RNA sequencing demonstrated that CCAAT enhancer binding protein α ( Cebpα) was one of the most differentially expressed genes between the MNKO and LC groups. Mechanistically, Co-IP assays, ChIP experiments, and dual luciferase assays revealed that NCOR1 interacted with peroxisome proliferator-activated receptor gamma (PPARγ) and cooperated with HDAC3 to control the transcription of Cebpα. In conclusion, Ncor1 deficiency promoted osteoclast and neutrophil formation in mice with experimental periodontitis. It regulated the transcription of Cebpα via PPARγ to promote osteoclast differentiation.
A mesoscale tensile model for woven fabrics based on Timoshenko beam theory
Authors: Wang Jichong , Zhou Helezi , Ouyang Zeyu , Peng Xiongqi , Zhou Huamin
Published: August 2022

The yarn weave architectures highly influence the mechanical response of woven fabrics. To provide an accurate prediction of the mechanical behaviors of woven fabrics under tension, a mesoscale model is developed. The model takes into account yarn properties, yarn weaving pattern, and interactions between yarns. The yarn properties such as tensile modulus and yarn strength of yarns are considered as random variables. Each yarn in fabric is modeled as a Timoshenko beam with a weaving shape modeled by a parabolic function. The yarn shape evolution and mechanical response of undulated yarn under tension are computed based on Castigliano’s second theorem. The damage initiation and propagation of a yarn in fabric is introduced through a damage variable. The model is demonstrated on woven jute fabrics. Analytical and numerical analyses are carried out and show good prediction on the macroscopic tensile response of woven jute fabric. The model provides a quantitative understanding between yarn geometrical parameters and the expected material response, and makes it helpful for designing woven structural composites with high performance.